Biomechanical Modeling of Bone-Needle Interaction for Haptic Rendering in Needle Insertion Simulation
Medical simulators are increasingly being used for surgical training. For interactive surgical simulation involving haptic rendering, the force at the needle tip has to be computed very fast. We are developing biomechanical models for bone needle insertion. The cortical bone can be regarded as a dense form of cancellous bone that can be modeled using a linear elastic material. The porosity of the bone determines the resistance felt as the user inserts the needle into the bone. The bar element method that represents each trabecular bone as a FE beam is most computationally efficient. With 1000 FE elements, the computed force feedback were close to the insertion force measured during experiments. However, the extended bar element method may be the more appropriate choice for taking into consideration the trabecular distribution and hence, inhomogeneous of bone. The simulation studies on bone-needle interaction also showed that a diamond bevel needle may penetrate the bone with less force

title: A component-oriented software toolkit for patient-specific finite element model generation
abstract: A component-oriented software system, i.BioMech (image-based biomechanical modeling) is proposed for generation of patient-specific finite element model. It applies a systematic software engineering approach to patient/subject-specific meshing and assignment of material properties. The prototype program is based on the component object model (COM), which enables ease of combination of existing mesh generation algorithms and material property assignment schemes, and incorporation of new ones. It also facilitates utilization by other programming languages or platforms. Data input comprises a series of medical images captured from the patient. The output is a patient-specific finite element model for computational analysis using commercially available finite element software. The prototype software system provides a framework to compare the different finite element mesh generation methods as well as schemes for material property assignment. Our focus is on patient/subject-specific modeling of the human vertebrae.

title: Advances in Fuzzy Method for Natural Computing
abstract: Both natural computing and fuzzy method exhibit human-like mental processing. Natural computing is the field of research that works with computational techniques inspired in part by natural systems. Fuzzy method is an alternative to traditional notions of set membership and logic, and it occurs in many applications of engineering, science and medicine. This paper presents a survey of recent advances in fuzzy method for natural computing, such as fuzzy artificial neural networks, fuzzy genetic algorithms, fuzzy ant colony optimization, fuzzy artificial immune systems, etc. We utilize uncertainty handling capacity of fuzzy method for modeling ambiguity, and the learning ability of natural computing for efficiently traversing large search spaces.

title: Automatic detection of signs with affine transformation
abstract: In this paper, we propose an approach for detecting signs from natural scenes. The approach efficiently embeds multiresolution, adaptive search, and affine rectification algorithms in a hierarchical framework, with different emphases at each layer. We combine in multi-resolution and multi-scale edge detection techniques to effectively detect text in different sizes. By using the cites from text inside the image, we introduce affine rectification transformation to recover deformation of the text region caused by air inappropriate camera view angle. This procedure can significantly improve text detection rate and OCR (Optical Character Recognition) accuracy. Experimental results have demonstrated feasibility of the proposed algorithms. We have applied the proposed approach to a Chinese sign translation system, which can automatically detect Chinese text input from a camera, recognize the text, and translate the recognized text into English or voice stream.

title: Flexible Feature Processing Mechanism of Radar Target Signal
abstract: Extracting effective and reliable features is fundamental and critical for constructing target recognition systems. Flexible Feature Processing Mechanism emphasizes the integration of feature extraction arithmetic and the self-adaptation of feature selection. On one hand, it would try to dig up the valuable information on as many as possible aspects, so as to construct the feature extraction method sets. On the other hand, it emphasizes to select the distinct features and eliminate the redundant features. The series of feature processing methods have been applied in multiple radar recognition projects successfully. According to the observation and analysis on a large number of real-life data, and taking the thinking process and the description methods of radar operators for reference, a set of feature extraction and selection methods basing on visual effects for dynamic radar target echo series have been introduced. The effectiveness, robustness and extendibility have been proved by large amount of tests and applications.

title: Spectral Decomposition Approach for Transient Analysis of Multi-Server Discrete-Time Queues
abstract: Discrete time queueing systems are extensively used in modeling the ATM environment at the cell level. This paper examines the transient behavior of a discrete time FCFS multiple server queue. For the arrival process we assume a general discrete time Markovian batch arrival process, where the batch size distribution of the arrivals in successive slots is governed by a finite state discrete time Markov chain. We show that once the spectral decomposition of the “probability generating matrix” of the arrival process is obtained, the complete solution in the transform domain may be given. Using the complex analysis technique and Cauchy's integral formula, we present an efficient numerical method for the numerical calculation of a few performance measures of interest, namely transient probability of queue being empty, and the mean of the queue length distribution. We also generalize our numerical method in the situations where the superposition of a number of independent arrival sources are fed to the queue. It is shown that the numerical complexity of obtaining the transient solution in this case can be substantially reduced by using the approach based on the Kronecker product. The finite buffer case is also analyzed.

title: Model-driven generative techniques for scalable performability analysis of distributed systems
abstract: The ever increasing societal demand for the timely availability of newer and feature-rich but highly dependable network-centric applications imposes the need for these applications to be constructed by the composition, assembly and deployment of off-the-shelf infrastructure and domain-specific services building blocks. Service oriented architecture (SOA) is an emerging paradigm to build applications in this manner by defining a choreography of loosely coupled building blocks. However, current research in SOA does not yet address the per for mobility (i.e., performance and dependability) challenges of these modern applications. Our research is developing novel mechanisms to address these challenges. We initially focus on the composition and configuration of the infrastructure hosting the individual services. We illustrate the use of domain-specific modeling languages and model weavers to model infrastructure composition using middleware building blocks, and to enhance these models with the desired performability attributes. We also demonstrate the use of generative tools that synthesize metadata from these models for performability validation using analytical, simulation and empirical benchmarking tools.