Aristides A. G. Requicha

Bio: Aristides A. G. Requicha is an academic researcher from University of Southern California. The author has contributed to research in topics: Constructive solid geometry & Solid modeling. The author has an hindex of 46, co-authored 100 publications receiving 7923 citations. Previous affiliations of Aristides A. G. Requicha include Applied Science Private University & University of Rochester.

Representations for Rigid Solids: Theory, Methods, and Systems

Abstract: Computer-based systems for modehng the geometry of rigid solid objects are becoming increasingly important in mechanical and civil engineering, architecture, computer graphics, computer vision, and other fields that deal with spatial phenomena. At the heart of such systems are symbol structures (representations) designating "abstract solids" (subsets of Euclidean space) that model physical solids. Representations are the sources of data for procedures which compute useful properties of objects. The variety and uses of systems embodying representations of solids are growing rapidly, but so are the difficulties in assessing current designs, specifying the characteristics that future systems should exhibit, and designing systems t9 meet such specifications. This paper resolves many of these difficulties by providing a coherent view, based on sound theoretical principles, of what is presently known about the representation of solids. The paper is divided into three parts. The first introduces a simple mathematical framework for characterizing certain important aspects of representations, for example, their semantic (geometric) integrity. The second part uses the framework to describe and compare all of the major knownschemes fo~ representing solids. The third part briefly surveys extant geometric modeling systems and then applies the concepts developed in the paper to the high-level design of a multiple*representation geometric modeling system which exhibits a level of reliability and versatility supermr to that of systems currently used in industrial computer-aided design and manufacturing.

Toward a Theory of Geometric Tolerancing

Abstract: Manual drafting is rapidly being replaced by modern, computerized systems for defining the geometry of mechanical parts and assemblies, and a new generation of powerful systems, called geometric (solid) modeling systems (GMSs), is entering industrial use. Solid models are beginning to play an important role in off-line robot programming, model- driven vision, and other industrial robotic applications.A major deficiency of current GMSs is their lack of facilities for specifying tolerancing information, which is essential for design analysis, process planning, assembly planning for tightly toleranced components, and other applications of solid modeling. This paper proposes a mathe matical theory of tolerancing that formalizes and generalizes current practices and is a suitable basis for incorporating tolerances into GMSs.A tolerance specification in the proposed theory is a collection ofgeometric constraints on an object's surface features, which are two-dimensional subsets of the object's boundary. An obje...

Spatial reasoning for the automatic recognition of machinable features in solid models

Abstract: Discusses an automatic feature recognizer that decomposes the total volume to be machined into volumetric features that satisfy stringent conditions for manufacturability, and correspond to operations typically performed in 3-axis machining centers. Unlike most of the previous research, the approach is based on general techniques for dealing with features with intersecting volumes. Feature interactions are represented explicitly in the recognizer's output, to facilitate spatial reasoning in subsequent planning stages. A generate-and-test strategy is used. OPS-5 production rules generate hints or clues for the existence of features, and post them on a blackboard. The clues are assessed, and those judged promising are processed to ensure that they correspond to actual features, and to gather information for process planning. Computational geometry techniques are used to produce the largest volumetric feature compatible with the available data. The feature's accessibility, and its interactions with others are analyzed. The validity tests ensure that the proposed features are accessible, do not intrude into the desired part, and satisfy other machinability conditions. The process continues until it produces a complete decomposition of the volume to be machined into fully-specified features. >

Boolean operations in solid modeling: Boundary evaluation and merging algorithms

Abstract: Solid modeling plays a key role in electromechanical CAD/CAM, three-dimensional computer graphics, computer vision, robotics, and other disciplines and activities that deal with spatial phenomena. Almost all contemporary solid modeling systems support Boolean operations akin to set intersection, union, and difference on solids. Boundary representations (face/edge/vertex structures) for solids defined through Boolean operations are generated in these modelers by using so-called boundary evaluation and boundary merging procedures. These are the most complex and delicate software modules in a solid modeler. This paper describes boundary evaluation algorithms used by the PADL solid modeling systems developed at the University of Rochester, and discusses other known approaches in terms of concepts that emerged from the PADL work, notably set membership classification and neighborhood manipulation.

Solid modeling: current status and research directions

Abstract: The March 1982 issue of IEEE Computer Graphics and Applications was devoted to solid modeling. The lead article in that issuel summarized the history of the field and its status as of late 1981; this article is an update to the 1982 article. Here, we shall note the proliferation of commercial systems over the past two years, discuss changes in system organization, and summarize applications support. We shall also survey work aimed at enhancing the geometric coverage, the applications coverage, and the performance of solid modeling systems. Research is progressing swiftly on several fronts, and it is virtually certain that late-1980s solid modelers will be markedly more powerful than those available now.

Gold nanoparticles: assembly, supramolecular chemistry, quantum-size-related properties, and applications toward biology, catalysis, and nanotechnology.

Abstract: Although gold is the subject of one of the most ancient themes of investigation in science, its renaissance now leads to an exponentially increasing number of publications, especially in the context of emerging nanoscience and nanotechnology with nanoparticles and self-assembled monolayers (SAMs). We will limit the present review to gold nanoparticles (AuNPs), also called gold colloids. AuNPs are the most stable metal nanoparticles, and they present fascinating aspects such as their assembly of multiple types involving materials science, the behavior of the individual particles, size-related electronic, magnetic and optical properties (quantum size effect), and their applications to catalysis and biology. Their promises are in these fields as well as in the bottom-up approach of nanotechnology, and they will be key materials and building block in the 21st century. Whereas the extraction of gold started in the 5th millennium B.C. near Varna (Bulgaria) and reached 10 tons per year in Egypt around 1200-1300 B.C. when the marvelous statue of Touthankamon was constructed, it is probable that “soluble” gold appeared around the 5th or 4th century B.C. in Egypt and China. In antiquity, materials were used in an ecological sense for both aesthetic and curative purposes. Colloidal gold was used to make ruby glass 293 Chem. Rev. 2004, 104, 293−346

Gold nanoparticles in chemical and biological sensing.

Abstract: Detection of chemical and biological agents plays a fundamental role in biomedical, forensic and environmental sciences1–4 as well as in anti bioterrorism applications.5–7 The development of highly sensitive, cost effective, miniature sensors is therefore in high demand which requires advanced technology coupled with fundamental knowledge in chemistry, biology and material sciences.8–13 In general, sensors feature two functional components: a recognition element to provide selective/specific binding with the target analytes and a transducer component for signaling the binding event. An efficient sensor relies heavily on these two essential components for the recognition process in terms of response time, signal to noise (S/N) ratio, selectivity and limits of detection (LOD).14,15 Therefore, designing sensors with higher efficacy depends on the development of novel materials to improve both the recognition and transduction processes. Nanomaterials feature unique physicochemical properties that can be of great utility in creating new recognition and transduction processes for chemical and biological sensors15–27 as well as improving the S/N ratio by miniaturization of the sensor elements.28 Gold nanoparticles (AuNPs) possess distinct physical and chemical attributes that make them excellent scaffolds for the fabrication of novel chemical and biological sensors (Figure 1).29–36 First, AuNPs can be synthesized in a straightforward manner and can be made highly stable. Second, they possess unique optoelectronic properties. Third, they provide high surface-to-volume ratio with excellent biocompatibility using appropriate ligands.30 Fourth, these properties of AuNPs can be readily tuned varying their size, shape and the surrounding chemical environment. For example, the binding event between recognition element and the analyte can alter physicochemical properties of transducer AuNPs, such as plasmon resonance absorption, conductivity, redox behavior, etc. that in turn can generate a detectable response signal. Finally, AuNPs offer a suitable platform for multi-functionalization with a wide range of organic or biological ligands for the selective binding and detection of small molecules and biological targets.30–32,36 Each of these attributes of AuNPs has allowed researchers to develop novel sensing strategies with improved sensitivity, stability and selectivity. In the last decade of research, the advent of AuNP as a sensory element provided us a broad spectrum of innovative approaches for the detection of metal ions, small molecules, proteins, nucleic acids, malignant cells, etc. in a rapid and efficient manner.37 Figure 1 Physical properties of AuNPs and schematic illustration of an AuNP-based detection system. In this current review, we have highlighted the several synthetic routes and properties of AuNPs that make them excellent probes for different sensing strategies. Furthermore, we will discuss various sensing strategies and major advances in the last two decades of research utilizing AuNPs in the detection of variety of target analytes including metal ions, organic molecules, proteins, nucleic acids, and microorganisms.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Abstract: From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Underwater acoustic sensor networks: research challenges

Abstract: Underwater sensor nodes will find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications. Moreover, unmanned or autonomous underwater vehicles (UUVs, AUVs), equipped with sensors, will enable the exploration of natural undersea resources and gathering of scientific data in collaborative monitoring missions. Underwater acoustic networking is the enabling technology for these applications. Underwater networks consist of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area. In this paper, several fundamental key aspects of underwater acoustic communications are investigated. Different architectures for two-dimensional and three-dimensional underwater sensor networks are discussed, and the characteristics of the underwater channel are detailed. The main challenges for the development of efficient networking solutions posed by the underwater environment are detailed and a cross-layer approach to the integration of all communication functionalities is suggested. Furthermore, open research issues are discussed and possible solution approaches are outlined. � 2005 Published by Elsevier B.V.

Topology matching for fully automatic similarity estimation of 3D shapes

Abstract: There is a growing need to be able to accurately and efficiently search visual data sets, and in particular, 3D shape data sets. This paper proposes a novel technique, called Topology Matching, in which similarity between polyhedral models is quickly, accurately, and automatically calculated by comparing Multiresolutional Reeb Graphs (MRGs). The MRG thus operates well as a search key for 3D shape data sets. In particular, the MRG represents the skeletal and topological structure of a 3D shape at various levels of resolution. The MRG is constructed using a continuous function on the 3D shape, which may preferably be a function of geodesic distance because this function is invariant to translation and rotation and is also robust against changes in connectivities caused by a mesh simplification or subdivision. The similarity calculation between 3D shapes is processed using a coarse-to-fine strategy while preserving the consistency of the graph structures, which results in establishing a correspondence between the parts of objects. The similarity calculation is fast and efficient because it is not necessary to determine the particular pose of a 3D shape, such as a rotation, in advance. Topology Matching is particularly useful for interactively searching for a 3D object because the results of the search fit human intuition well.