Phase-based and time-of-flight laser scanners can capture dense point-clouds of indoor and outdoor environment. However, such point-clouds usually lack the backsides of objects and the portions occluded by other ones. In this paper, we propose a new modeling methodology which converts a point-cloud to a Mercator image and a mesh model, and enables reconstructing the missing portions interactively by using image-based techniques. The grid mesh format is proposed for quick access to largescale mesh models. A prototype system is implemented to show the efficiency of our method.
The crucial issue in Knowledge-Based Engineering is representation of expert knowledge in a readable way for both a computer agent and human. Properly prepared knowledge (captured, assessed, formalized and structured) plays an important role for success of every knowledge based system; particularly in the discipline of machinery design. Many knowledge model properties are of great significance, in addition to formal structure and consistency, reusability, flexibility, interoperability of knowledge model are also becoming increasingly essential for the knowledge-based systems research community. This paper presents a hybrid knowledge representation for solving deductive engineering tasks in Knowledge Based Machinery Design. We propose two different methods for storing engineering knowledge; as a repository for declarative knowledge, an ontological knowledge based was applied; for procedural knowledge storage as a formal representation, a geometrical model was used. Apart from theoretical foundations the work is also concerned with presenting and discussing an industrial application of the above-mentioned knowledge representation. As a practical part an application for engineer supporting in design process of dies with non-cutting shape forming in automotive field is indicated. This part deals with problems, challenges and bottlenecks coming up during developing process that application and shows advantages and disadvantages of this knowledge representation. For carrying out the effort CATIA V5 as Computer Aided Design system was applied. To fulfill the knowledge model requirements, especially reusability, flexibility and inter-operability, Protégé as an ontology editor and knowledge-based framework with OKBC (Open Knowledge Base Connectivity) protocol was used.
Recent reports have described several cases of double muscle transfers to restore natural, symmetrical smiles in patients with long-standing facial paralysis. However, these complex procedures sometimes result in cheek bulkiness owing to the double muscle transfer. We present the case of a 67-year-old woman with long-standing facial paralysis, who underwent two-stage facial reanimation using two superficial subslips of the serratus anterior muscle innervated by the masseteric and contralateral facial nerves via a sural nerve graft. Each muscle subslip was transferred to the upper lip and oral commissures, which were oriented in different directions. Furthermore, a horizontal fascia lata graft was added at the lower lip to prevent deformities such as lower lip elongation and deviation. Voluntary contraction was noted at roughly 4 months, and a spontaneous smile without biting was noted 8 months postoperatively. At 18 months after surgery, the patient demonstrated a spontaneous symmetrical smile with adequate excursion of the lower lip, upper lip, and oral commissure, without cheek bulkiness. Dual-innervated muscle transfer using two multivector superficial subslips of the serratus anterior muscle may be a good option for long-standing facial paralysis, as it can achieve a symmetrical smile that can be performed voluntarily and spontaneously.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.