Showing papers in "IEEE Transactions on Automation Science and Engineering in 2009"

An Accurate Tag Estimate Method for Improving the Performance of an RFID Anticollision Algorithm Based on Dynamic Frame Length ALOHA

Abstract: In a radio-frequency identification (RFID) system, the dynamic frame length ALOHA protocol is widely adopted to solve the anticollision problem. Analysis for the anticollision problem can be divided into two primary parts. The concern of the first part is how to precisely estimate the number of tags. The other part involves determination of dynamic frame length to achieve maximum throughput or channel usage efficiency. In this paper, we present an accurate method for estimating tag quantity. This method is based on the maximum a posteriori probability decision. We also derive the optimal frame length using radio channel efficiency. Simulation results indicate the tag estimate error of the proposed method is less than 4%. Use of our proposed tag estimate method together with optimal frame length can achieve close to the theoretical maximum throughput of the framed ALOHA algorithm.

A Petri Net-Based Method for Compatibility Analysis and Composition of Web Services in Business Process Execution Language

Abstract: Automatic Web service composition is gaining momentum as the potential silver bullet in service oriented architecture. The need for interservice compatibility analysis and indirect composition has gone beyond what the existing service composition/verification technologies can handle. Given two services whose interface invocation constraints are described by a Web services-business process execution language (WS-BPEL or BPEL), we analyze their compatibility and adopt mediation as a lightweight approach to make them compatible without changing their internal logic. We first transform a BPEL description into a service workflow net, which is a kind of colored Petri net (CPN). Based on this formalism, we analyze the compatibility of two services, and then devise an approach to check whether there exists any message mediator so that their composition does not violate the constraints imposed by either side. The method for mediator generation is finally proposed to assist the automatic composition of partially compatible services. Our approach is validated through a real-life case and further research directions are pointed out.

Robust Location-Aware Activity Recognition Using Wireless Sensor Network in an Attentive Home

Abstract: This paper presents a robust location-aware activity recognition approach for establishing ambient intelligence applications in a smart home. With observations from a variety of multimodal and unobtrusive wireless sensors seamlessly integrated into ambient-intelligence compliant objects (AICOs), the approach infers a single resident's interleaved activities by utilizing a generalized and enhanced Bayesian Network fusion engine with inputs from a set of the most informative features. These features are collected by ranking their usefulness in estimating activities of interest. Additionally, each feature reckons its corresponding reliability to control its contribution in cases of possible device failure, therefore making the system more tolerant to inevitable device failure or interference commonly encountered in a wireless sensor network, and thus improving overall robustness. This work is part of an interdisciplinary Attentive Home pilot project with the goal of fulfilling real human needs by utilizing context-aware attentive services. We have also created a novel application called ldquoActivity Maprdquo to graphically display ambient-intelligence-related contextual information gathered from both humans and the environment in a more convenient and user-accessible way. All experiments were conducted in an instrumented living lab and their results demonstrate the effectiveness of the system.

Environmental-Adaptive RSSI-Based Indoor Localization

Abstract: This paper addresses a novel method for localizing a stationary object in an indoor office environment. The proposed method utilizes the received-signal-strength index (RSSI) of radio signals radiating from fixed reference nodes and reference tags placed at known positions to generate a precise signal propagation model. Signal attenuation parameters are updated online according to environmental variation; thus, the proposed method has environmental-adaptation capabilities. Subsequent experiments were conducted to demonstrate the superiority of the proposed technique over a commercial location-based service (LBS) chipset.

Detecting Human Behavior Models From Multimodal Observation in a Smart Home

Abstract: This paper addresses learning and recognition of human behavior models from multimodal observation in a smart home environment. The proposed approach is part of a framework for acquiring a high-level contextual model for human behavior in an augmented environment. A 3-D video tracking system creates and tracks entities (persons) in the scene. Further, a speech activity detector analyzes audio streams coming from head set microphones and determines for each entity, whether the entity speaks or not. An ambient sound detector detects noises in the environment. An individual role detector derives basic activity like ldquowalkingrdquo or ldquointeracting with tablerdquo from the extracted entity properties of the 3-D tracker. From the derived multimodal observations, different situations like ldquoaperitifrdquo or ldquopresentationrdquo are learned and detected using statistical models (HMMs). The objective of the proposed general framework is two-fold: the automatic offline analysis of human behavior recordings and the online detection of learned human behavior models. To evaluate the proposed approach, several multimodal recordings showing different situations have been conducted. The obtained results, in particular for offline analysis, are very good, showing that multimodality as well as multiperson observation generation are beneficial for situation recognition.

Regularity Analysis for Patterned Texture Inspection

Abstract: This paper considers regularity analysis for patterned texture material inspection. Patterned texture-like fabric is built on a repetitive unit of a pattern. Regularity is one of the most important features in many textures. In this paper, a new patterned texture inspection approach called the regular bands (RB) method is described. First, the properties of textures and the meaning of regularity measurements are presented. Next, traditional regularity analysis for patterned textures is introduced. Many traditional approaches such as co-occurrence matrices, autocorrelation, traditional image subtraction and hash function are based on the concept of periodicity. These approaches have been applied for image retrieval, image synthesis, and defect detection of patterned textures. In this paper, a new measure of periodicity for patterned textures is described. The Regular Bands method is based on the idea of periodicity. A detailed description of the RB method with definitions, procedures, and explanations is given. There is also a detailed evaluation using the Regular Bands of some patterned textures. Three kinds of patterned fabric samples are used in the evaluation and a high detection success rate is achieved. Finally, there is a discussion of the method and some conclusions.

Visual-Based Impedance Control of Out-of-Plane Cell Injection Systems

Abstract: In this paper, a vision-based impedance control algorithm is proposed to regulate the cell injection force, based on dynamic modeling conducted on a laboratory test-bed cell injection system. The injection force is initially calibrated to derive the relationship between the force and the cell deformation utilizing a cell membrane point-load model. To increase the success rate of injection, the injector is positioned out of the focal plane of the camera, used to obtain visual feedback for the injection process. In this out-of-plane injection process, the total cell membrane deformation is estimated, based on the X-Y coordinate frame deformation of the cell, as measured with a microscope, and the known angle between the injector and the X-Y plane. Further, a relationship between the injection force and the injector displacement of the cell membrane, as observed with the camera, is derived. Based on this visual force estimation scheme, an impedance control algorithm is developed. Experimental results of the proposed injection method are given which validate the approach.

A Scale Stretch Method Based on ICP for 3D Data Registration

Abstract: In this paper, we are concerned with the registration of two 3D data sets with large-scale stretches and noises. First, by incorporating a scale factor into the standard iterative closest point (ICP) algorithm, we formulate the registration into a constraint optimization problem over a 7D nonlinear space. Then, we apply the singular value decomposition (SVD) approach to iteratively solving such optimization problem. Finally, we establish a new ICP algorithm, named Scale-ICP algorithm, for registration of the data sets with isotropic stretches. In order to achieve global convergence for the proposed algorithm, we propose a way to select the initial registrations. To demonstrate the performance and efficiency of the proposed algorithm, we give several comparative experiments between Scale-ICP algorithm and the standard ICP algorithm.

Intelligent Optimal-Setting Control for Grinding Circuits of Mineral Processing Process

Abstract: During the operation of a grinding circuit (GC) in mineral processing plant the main purpose of control and optimal operation is to control the product quality index, namely the product particle size, into its technically desired ranges. Moreover, the grinding production rate needs to be maximized. However, due to the complex dynamic characteristics between the above two indices and the control loops, such control objectives are difficult to achieve using existing control methods. The complexity is reflected by the existence of process heavy nonlinearities, strong coupling and large time variations. As a result, the lower level loop control with human supervision is still widely used in practice. However, since the setpoints to the involved control loops cannot be accurately adjusted under the variations of the boundary conditions, the manual setpoints control cannot ensure that the actual production indices meet with technical requirements all the time. In this paper, an intelligent optimal-setting control (IOSC) approach is developed for a typical two-stage GC so as to optimize the production indices by auto-adjusting on line the setpoints of the control loops in response to the changes in boundary conditions. This IOSC approach integrates case-based reasoning (CBR) pre-setting controlling, neural network (NN)-based soft-sensor and fuzzy adjusting into one efficient control model. Although each control element is well known, their innovative combination can generate better and more reliable performance. Both industrial experiments and applications show the validity and effectiveness of the proposed IOSC approach and its bright application foreground in industrial processes with similar features.

An Optimal Q-Algorithm for the ISO 18000-6C RFID Protocol

Abstract: Passive radio-frequency identification (RFID) systems based on the ISO/IEC 18000-6C (aka EPC Gen2) protocol have typical read rates of up to 1200 unique 96-bit tags per second. This performance is achieved in part through the use of a medium access control algorithm, christened the Q-algorithm, that is a variant of the Slotted Aloha multiuser channel access algorithm. We analyze the medium access control algorithm employed by the ISO/IEC 18000-6C RFID air interface protocol and provide a procedure to achieve optimal read rates. We also show that theoretical performance can be exceeded in many practical use cases and provide a model to incorporate real-world data in read-rate estimation.

High-Throughput Automated Injection of Individual Biological Cells

Abstract: The ability of efficiently delivering soluable/insoluable drug compounds or biomolecules into individual biological cells and quantifying their cellular responses is important for genetics, proteomics, and drug discovery. This paper presents a fully automated system for zebrafish embryo injection, which overcomes the problems inherent in manual injection, such as human fatigue and large variations in success rates due to poor reproducibility. Based on ldquolooking-then-movingrdquo control, the microrobotic system performs injection at a speed of 15 zebrafish embryos (chorion unremoved) per minute. Besides a high injection speed that compares favorably with that of a highly proficient injection technician, a vacuum-based embryo holding device enables fast immobilization of a large number of zebrafish embryos, shortening the embryo patterning process from minutes to seconds. The recognition of embryo structures from image processing identifies a desired destination inside the embryo for material deposition, together with precise motion control resulting in a success rate of 100%. Carefully tuning suction pressure levels as well as injection and retraction speeds produced a high survival rate of 98%. The quantitative performance evaluation of the automated system was based on the continuous injection of 250 zebrafish embryos. The technologies can be extended to other biological injection applications such as the injection of mouse embryos, Drosophila embryos, and C. elegans to enable high-throughput biological and pharmaceutical research.

Web Service Configuration Under Multiple Quality-of-Service Attributes

Abstract: With the popularity of Internet technology, Web services are becoming the most promising paradigm for distributed computing. However, when a single Web service fails to meet service requestor's multiple function needs, web services need to be dynamically configured together to form a web service composition. Since there may be many configurations providing identical functionality with different quality-of-service (QoS), a choice needs to be made according to users' functional and nonfunctional requirements. In this paper, we formulate a Web service functional configuration problem by using Petri nets. The graph structure and algebraic properties of the model are analyzed in detail to show that a basis solution of a state-shift equation of the Petri net model corresponds to a realizable configuration process. This result is later used to formulate the multiple attribute QoS optimization problem to a linear programming problem. Finally, a case study is performed to show that the proposed analysis result can be effectively applied in practice.

Direction Sensing RFID Reader for Mobile Robot Navigation

Abstract: A self-contained direction sensing radio frequency identification (RFID) reader is developed employing a dual-directional antenna for automated target acquisition and docking of a mobile robot in indoor environments. The dual-directional antenna estimates the direction of arrival (DOA) of signals from a transponder by using the ratio of the received signal strengths between two adjacent antennas. This enables the robot to continuously monitor the changes in transponder directions and ensures reliable docking guidance to the target transponder. One of the technical challenges associated with this RFID direction finding is to sustain the accuracy of the estimated DOA that varies according to environmental conditions. It is often the case that the robot loses its way to the target in a cluttered environment. To cope with this problem, the direction correction algorithm is proposed to triangulate the location of the transponder with the most recent three DOA estimates. Theoretical simulation results verify the reliability of the proposed algorithm that quantifies the potential error in the DOA estimation. Using the algorithm, we validate mobile robot docking to an RFID transponder in an office environment occupied by obstacles.

Game-Theoretic Modeling of Joint Topology Control and Power Scheduling for Wireless Heterogeneous Sensor Networks

Abstract: Wireless Heterogeneous Sensor Network (WHSN) facilitates ubiquitous information acquisition for Ambient Intelligence (AmI) systems. It is of great importance of power management and topology control for WHSN to achieve desirable network performances, such as clustering properties, connectivity and power efficiency. This paper proposes a game theoretic model of topology control to analyze the decentralized interactions among heterogeneous sensors. We study the utility function for nodes to achieve desirable frame success rate and node degree, while minimizing the power consumption. Specifically, we propose a static complete-information game formulation for power scheduling and then prove the existence of the Nash equilibrium with simultaneous move. Because the heterogeneous sensors typically react to neighboring environment based on local information and the states of sensors are evolving over time, the power-scheduling problem in WHSN is further formulated into a more realistic incomplete-information dynamic game model with sequential move. We then analyze the separating equilibrium, one of the perfect Bayesian equilibriums resulted from the dynamic game, with the sensors revealing their operational states from their actions. The sufficient and necessary conditions for the existence of separating equilibrium are derived for the dynamic Bayesian game, which provide theoretical basis to the proposed power scheduling algorithms, NEPow and BEPow. The primary contributions of this paper include applying game theory to analyze the distributed decision-making process of individual sensor nodes and to analyze the desirable utilities of heterogeneous sensor nodes. Simulations are presented to validate the proposed algorithms and the results show their ability of maintaining reliable connectivity, reducing power consumption, while achieving desirable network performances.

Contrast Enhancement and Intensity Preservation for Gray-Level Images Using Multiobjective Particle Swarm Optimization

Abstract: The contrast enhancement of gray-level digital images is considered in this paper. In particular, the mean image intensity is preserved while the contrast is enhanced. This provides better viewing consistence and effectiveness. The contrast enhancement is achieved by maximizing the information content carried in the image via a continuous intensity transform function. The preservation of image intensity is obtained by applying gamma-correction on the images. Since there is always a trade-off between the requirements for the enhancement of contrast and preservation of intensity, an improved multiobjective particle swarm optimization procedure is proposed to resolve this contradiction, making use of its flexible algorithmic structure. The effectiveness of the proposed approach is illustrated by a number of images including the benchmarks and an image sequence captured from a mobile robot in an indoor environment.

RFIDSim—A Physical and Logical Layer Simulation Engine for Passive RFID

Abstract: Radio-frequency identification (RFID) poses a number of research challenges, such as interference mitigation, throughput optimization and security over the RF channel. A number of new approaches to address these issues have been proposed recently, but due to the highly integrated nature of passive RFID tags, it is difficult to evaluate them in real-world scenarios. In this paper, we present an RFID simulation engine, RFIDSim, which implements the ISO 18000-6C communication protocol and supports pathloss, fading, backscatter, capture, and tag mobility models. This paper also shows that our implementation of RFIDSim that relies on a discrete event simulator can be used to simulate large populations featuring thousands of RFID tags. RFIDSim also simulates the deep fades that lead to frequent power losses of the battery-less RFID tags by modeling the multipath effects statistically.

Passive UHF RFID in Paper Industry: Challenges, Benefits and the Application Environment

Abstract: Radio frequency identification (RFID) systems for the paper industry is an emerging research topic due to the need for an automated identification system for the paper industry which would carry on the identification codes of paper and board reels throughout their life cycle. This paper discusses the application of passive ultra-high frequency (UHF) RFID systems to the paper industry. Challenges, benefits, and the application environment of using passive UHF RFID systems in the paper industry are presented and discussed. The major challenges are development of globally operable tag antenna designs and integration of reader units and reader antennas to paper handling machinery. To confront and solve these challenges, this paper presents novel tag antenna designs for paper and board reel identification and proposes solutions for reader and reader antenna integration to paper handling machinery. In addition, the identification locations within the paper reel supply chain and the effects of RFID systems to supply chain visibility are presented and discussed. In addition, test results of using passive UHF RFID systems in the paper industry environment are presented.

Designing Distributed Diagnosers for Complex Continuous Systems

Abstract: Wear and tear from sustained operations cause systems to degrade and develop faults. Online fault diagnosis schemes are necessary to ensure safe operation and avoid catastrophic situations, but centralized diagnosis approaches have large memory and communication requirements, scale poorly, and create single points of failure. To overcome these problems, we propose an online, distributed, model-based diagnosis scheme for isolating abrupt faults in large continuous systems. This paper presents two algorithms for designing the local diagnosers and analyzes their time and space complexity. The first algorithm assumes the subsystem structure is known and constructs a local diagnoser for each subsystem. The second algorithm creates the partition structure and local diagnosers simultaneously. We demonstrate the effectiveness of our approach by applying it to the Advanced Water Recovery System developed at the NASA Johnson Space Center.

Inference-Based Ambiguity Management in Decentralized Decision-Making: Decentralized Diagnosis of Discrete-Event Systems

Abstract: The task of decentralized decision-making involves interaction of a set of local decision-makers, each of which operates under limited sensing capabilities and is thus subjected to ambiguity during the process of decision-making. In our prior work, we made a key observation that such ambiguities are of differing gradations and presented a framework for inferencing over varying ambiguity levels to arrive at local and global control decisions. We develop a similar framework for performing diagnosis in a decentralized setting. For each event-trace executed by a system being monitored, each local diagnoser issues its own diagnosis decision (failure or nonfailure or unsure), tagged with a certain ambiguity level (zero being the minimum). A global diagnosis decision is taken to be a ldquowinningrdquo local diagnosis decision, i.e., one with a minimum ambiguity level. The computation of an ambiguity level for a local decision requires an assessment of the self-ambiguity as well as the ambiguities of the others, and an inference based up on such knowledge. In order to characterize the class of systems for which any fault can be detected within a uniformly bounded number of steps (or ldquodelayrdquo), we introduce the notion of N -inference-diagnosability for Failures (also called N-inference F-diagnosability), where the index N represents the maximum ambiguity level of any winning local decision. We show that the codiagnosability introduced in is the same as 0-inference F-diagnosability; the conditional F-codiagnosability introduced in , is a type of 1-inference F-diagnosability; the class of higher-index inference F-diagnosable systems strictly subsumes the class of lower-index ones; and the class of inference F-diagnosable systems is strictly subsumed by the class of systems that are centrally F-diagnosable.

Experimental Case Study of a BACnet-Based Lighting Control System

Abstract: Lighting control systems provide various benefits in building management, and building automation and control network (BACnet) is an international standard data communication protocol for building automation and control networks. We introduce a reference model for BACnet-based lighting control systems and evaluate its performance using an experimental model. The experimental results show that the system can reduce the energy consumption for lighting loads by 40%. Stable operation of the control system is guaranteed below a certain threshold of network traffic.

Design, Fabrication, and Visual Servo Control of an XY Parallel Micromanipulator With Piezo-Actuation

Abstract: This paper presents a complete design and development procedure of a new XY micromanipulator for two-dimensional (2-D) micromanipulation applications. The manipulator possesses both a nearly decoupled motion and a simple structure, which is featured with parallel-kinematic architecture, flexure hinge-based joints, and piezoelectric actuation. Based on pseudo-rigid-body (PRB) simplification approach, the mathematical models predicting kinematics, statics, and dynamics of the XY stage have been obtained, which are verified by the finite-element analysis (FEA) and then integrated into dimension optimization via the particle swarm optimization (PSO) method. Moreover, a prototype of the micromanipulator is fabricated and calibrated using a microscope vision system, and visual servo control employing a modified PD controller is implemented for the accuracy improvement. The experiments discover that a workspace size of 260 mum times 260 mum with a 2-D positioning accuracy and repeatability around 0.73 and 1.02 mum, respectively, can be achieved by the micromanipulator.

Reachability Graph of Finite and Deterministic DEVS Networks

Abstract: This paper shows how to generate a finite-vertex graph, called a reachability graph for discrete-event system specification (DEVS) network. The reachability graph is isomorphic to a given original DEVS network in terms of behavior but the number of vertices as well as the number of edges of the reachability graph are finite.

An Open CNC System Based on Component Technology

Abstract: In a conventional CNC system, communications between the motion controller and the analogue servo driver usually take place in a unidirectional manner, i.e., from the controller to the driver. In order to increase the interoperability level between the motion controller and the driver, Fieldbus is used in this research. The digital servo in a Fieldbus-based system enables applications with all servo loops closed. Functions that have been traditionally executed by the motion controller can now be shifted to the driver. In this research, the traditional CNC system has been redesigned based on the component technology. Following the analysis of the architecture of a traditional CNC and the features of a Fieldbus, component models have been developed for the motion controller and the driver. This Fieldbus-based CNC system gives the much-needed interoperability between the motion controller and the driver. A comparative experiment based on a four-axis CNC system has been carried out to showcase the component model-based system.

A First-Order Hybrid Petri Net Model for Supply Chain Management

Abstract: A supply chain (SC) is a network of independent manufacturing and logistics companies that perform the critical functions in the order fulfillment process. This paper proposes an effective and modular model to describe material, financial and information flow of SCs at the operational level based on first-order hybrid Petri nets (PNs), i.e., PNs that make use of first-order fluid approximation. The proposed formalism enables the SC designer to choose suitable production rates of facilities in order to optimize the chosen objective function. The optimal mode of operation is performed based on the state knowledge of the obtained linear discrete-time, time-varying state variable model in order to react to unpredictable events such as the blocking of a supply or an accident in a transportation facility. A case study is modeled in the proposed framework and is simulated under three different closed-loop control strategies.

Automatic Reconfiguration of Petri Net Controllers for Reconfigurable Manufacturing Systems With an Improved Net Rewriting System-Based Approach

Abstract: The advent of reconfigurable manufacturing systems (RMSs) has given rise to a challenging problem, i.e., how to reconfigure rapidly and validly a RMS supervisory controller in response to frequent changes in the manufacturing system configuration driven by fluctuating market. This paper presents an improved net rewriting system (INRS)-based method for automatic reconfiguration of Petri net (PN) supervisory controllers for RMS. We begin with presenting the INRS which overcomes the limitations of the net rewriting system and can dynamically change the structure of a PN without damaging its important behavioral properties. Based on INRS, a method for design reconfigurable PN controllers of RMS is introduced. Subsequently, we presented an INRS-based method for rapidly automatic reconfiguration of this class of PN controllers. In the reconfiguration method, changes in a RMS configuration can be formalized and act on an existing controller to make it reconfigure rapidly into a new one. Noticeably, no matter the design or reconfiguration, the expected behavioral properties of the resultant PN controllers are guaranteed. Thus, efforts for verification of the results can be avoided naturally. We also illustrate the reconfiguration of a PN controller for a reconfigurable manufacturing cell.

Robust Supervisory Control for Product Routings With Multiple Unreliable Resources

Abstract: Manufacturing systems are often subject to resource failure. In past work, we developed ldquorobustrdquo supervisory controllers for the single-unit resource allocation model. These guarantee that if any subset of resources fail, parts in the system requiring failed resources do not block the production of parts not requiring failed resources. To establish supervisor correctness, we assumed that each part type required at most one unreliable resource in its route. We now relax this assumption using a central buffer and present supervisors that guarantee robust operation without assumptions on route structure.

Dynamics Modeling and Analysis of a Swimming Microrobot for Controlled Drug Delivery

Abstract: Dynamics modeling and analysis of a tiny swimming robot, which is composed of a helix type head and an elastic tail, is presented in this paper. The microrobot is designed for controlled drug delivery. It is at the micrometer scale and suitable for a swimming environment under low Reynolds number (Re). The head of the swimming robot is driven by an external rotating magnetic field, which enables it to be operated wirelessly. The spiral-type head accommodates communication and control units and serves as the base for the elastic tail. When a rotating magnetic field is applied, the head rotates synchronously with the field, generating and propagating driving torque to the straight elastic tail. When the driving torque reaches a threshold, dramatic deformation takes place on the elastic tail. The tail then transforms into a helix and generates propulsive thrust. The entire tail also serves as a drug reservoir. This paper focuses on analyzing the dynamics of the microrobot using resistive force theory (RFT), and comparing the propulsion performance with other rigid-body microrobots.

A Synchronization Approach for the Minimization of Contouring Errors of CNC Machine Tools

Abstract: This paper presents a synchronization control approach for the minimization of contouring errors of multi-axis CNC machine tools. The contouring errors are presented by the position synchronization errors that are defined as differential position errors between each axis and its adjacent ones. Using cross-coupling concept, a decentralized tracking controller is developed with feedback of both position and synchronization errors, formed with a combination of feedforward, feedback and a saturation control. It is proven that this controller can asymptotically stabilize both position and synchronization errors to zero. The proposed controller does not require significant use of the system dynamic models. Experiments performed on a multi-axis machine tool demonstrate improved performance especially in the contouring error minimization.

Meshless Harmonic Volumetric Mapping Using Fundamental Solution Methods

Abstract: Harmonic volumetric mapping aims to establish a smooth bijective correspondence between two solid shapes with the same topology. In this paper, we develop an automatic meshless method for creating such a mapping between two given objects. With the shell surface mapping as the boundary condition, we first solve a linear system constructed by a boundary method called the method of fundamental solution, and then represent the mapping using a set of points with different weights in the vicinity of the shell of the given model. Our algorithm is a true meshless method (without the need of any specific meshing structure within the solid interior) and the behavior of the interior region is directly determined by the boundary, which can improve the computational efficiency and robustness significantly. Therefore, our algorithm can be applied to massive volume data sets with various geometric primitives and topological types. We demonstrate the utility and efficacy of our algorithm in information transfer, shape registration, deformation sequence analysis, tetrahedral remeshing, and solid texture synthesis.

Weighting Restriction for Intravenous Insulin Delivery on T1DM Patient via $H_{\infty}$ Control

Abstract: A weighting restriction with frequency components is proposed for the insulin delivery on Type 1 Diabetics Mellitus (T1DM) towards the control of the blood glucose level. The weighting restriction is stated from a model of healthy subjects which includes a rate for insulin delivery. The frequency components are incorporated via a transfer function from the plasma glucose to the free-plasma insulin such that a H infin-based controller is designed. In this way, the control synthesis involves the frequency components on which a healthy pancreas delivers insulin for the glucose homeostasis. In order to test controller performance, a dynamical model of an actuator is also included in the closed-loop system to add its effects in the closed-loop evaluation of the H infin -based controller. The actuator is a pump to deliver of an insulin infusion according with the rate computed by the controller. Note that the contribution is particularly focused on T1DM; however, the inclusion of weighting restriction can be used also onto critical care conditions.