Stability of Local On‐Ramp Metering Control Laws

A framework for stability analysis of local on‐ramp metering control strategies based on the cell transmission model is presented. Within this framework, it is possible to formulate Lyapunov and input‐state stability results for on‐ramp metering control strategies in an open section of highway with on‐ramps. Using this analysis, recommendations for the design of on‐ramp metering control laws set points are derived. Two examples on the use of such analysis are presented. One deals with the stability analysis of a local on‐ramp metering control law and the other with the design of a disturbance observer that, used in combination with the local on‐ramp metering control law, provides a more robust response to traffic regulation. Simulation results are included that confirm the possibility of using this framework to test the impact of local on‐ramp metering control strategies.     

Spiral-shaped inertial stem cell device for high-throughput enrichment of iPSC-derived neural stem cells

Stem cell enrichment plays a critical role in both research and clinical applications. The typical method for stem cell enrichment may use invasive processes and takes a long period of time. Spiral-shaped microfluidic devices, which combine lift and Dean drag forces to direct cells of different sizes into separate trajectories, can be used to noninvasively process samples at a rate of milliliters per minute. This paper presents a simple 2-loop spiral-shaped inertial microfluidic devices with the aid of sheath flow to enrich neural stem cells (NSCs), derived from induced pluripotent stem cells. NSCs and spontaneously differentiated non-neural cells were mixed and flowed through the spiral-shaped devices. Samples collected at the outlets were analyzed for purity and recovery. It was found that the device focused the NSCs into a narrow trajectory, which could then be collected in two out of the eight outlets. The device was tested at different flow rates and found that the most highly enriched fractions (2.1×) with NSCs recovery 93% were achieved at the flow rate (3 ml/min). Next, we extended our investigation from 2-loop design to 10-loop design to eliminate the use of sheath flow. NSCs were enriched to 2.5×, but only 38% of the NSCs were recovered from the most enriched fractions. Spiral-shaped microfluidic devices are capable of rapid, label-free enrichment of target stem cells, and have great potential in point-of-care tissue preparation.     

Incorporating technology in service-oriented i* business models: a case study

In recent years, considerable attention has been paid to enterprise information systems. This interest is motivated by the need for achieving better integration of new technologies (hardware and software) with the business processes of an organization. Business processes have become more and more dependent on technologies because technology has a direct impact on business processes, changing the way they are performed and thus also affecting the way analysts design the software system. However, at the present time, there are still some gaps between the definition of business processes and the technologies used in the organization. In practice, organizations have carried out their business processes using different technologies; however, it is sometimes not possible to determine how technologies are useful in achieving current business goals. This is because business models do not explicitly consider the technologies in the organizational requirements. The goal of this paper is to present a systematic process for integrating business processes and technologies at the conceptual level. To validate our approach, we present a case study that describes the processes of the inventory management department of a public research center.     

Standard process monitoring and traceability programming in collaborative CAD/CAM/CNC manufacturing scenarios

The paper focuses on collaborative STEP-based CAD/CAM/CNC supply chains to program and automate machining process data monitoring and traceability activities. A traceability interface (traceability nc_functions) is defined for the new CNC programming standard ISO STEP-NC. CAM systems will be able to program monitoring and data access activities by inserting traceability nc_function calls in CNC programs. On the shop floor, controllers will automatically interpret these nc_functions to access process data while machining and will relate data records with the corresponding machining operations in a STEP-NC part program. With both types of information—process data and standard machining program (STEP-NC part program)—spread and technologically heterogeneous engineering systems will have full knowledge about what has happened in production. Traceability data access automation will assure data reliability. The paper describes a traceability scenario where standards such as MTConnect and ISA-95 support, rather than interfere with, the STEP-NC traceability proposal.     

A Faà di Bruno Hopf algebra for a group of Fliess operators with applications to feedback

A Faà di Bruno type Hopf algebra is developed for a group of integral operators known as Fliess operators, where operator composition is the group product. Such operators are normally written in terms of generating series over a noncommutative alphabet. Using a general series expansion for the antipode, an explicit formula for the generating series of the compositional inverse operator is derived. The result is applied to analytic nonlinear feedback systems to produce an explicit formula for the feedback product, that is, the generating series for the Fliess operator representation of the closed-loop system written in terms of the generating series of the Fliess operator component systems. This formula is employed to provide a proof that local convergence is preserved under feedback.     

Admission control for a responsive distributed middleware using decision trees to model run-time parameters

The software in modern systems has become too complex to make accurate predictions about their performance under different configurations. Real-time or even responsiveness requirements cannot be met because it is not possible to perform admission control for new or changing tasks if we cannot tell how their execution affects the other tasks already running. Previously, we proposed a resource-allocation middleware that manages the execution of tasks in a complex distributed system with real-time requirements. The middleware behavior can be modeled depending on the configuration of the tasks running, so that the performance of any given configuration can be calculated. This makes it possible to have admission control in such a system, but the model requires knowledge of run-time parameters. We propose the utilization of machine-learning algorithms to obtain the model parameters, and be able to predict the system performance under any configuration, so that we can provide a full admission control mechanism for complex software systems. In this paper, we present such an admission control mechanism, we measure its accuracy in estimating the parameters of the model, and we evaluate its performance to determine its suitability for a real-time or responsive system.     

Proof Pearl: a Formal Proof of Higman��s Lemma in ACL2

Higman??s lemma is an important result in infinitary combinatorics, which has been formalized in several theorem provers. In this paper we present a formalization and proof of Higman??s Lemma in the ACL2 theorem prover. Our formalization is based on a proof by Murthy and Russell, where the key termination argument is justified by the multiset relation induced by a well-founded relation. To our knowledge, this is the first mechanization of this proof.     

A model of cerebral cortex formation during fetal development using reaction-diffusion-convection equations with Turing space parameters

The cerebral cortex is a gray lamina formed by bodies of neurons covering the cerebral hemispheres, varying in thickness from 1.25 mm in the occipital lobe to 4 mm in the anterior lobe. The brain's surface is about 30 times greater that of the skull because of its many folds; such folds form the gyri, sulci and fissures and mark out areas having specific functions, divided into five lobes. Convolution formation may vary between individuals and is an important feature of brain formation; such patterns can be mathematically represented as Turing patterns. This article describes how a phenomenological model was developed by describing the formation pattern for the gyri occurring in the cerebral cortex by reaction diffusion equations with Turing space parameters. Numerical examples for simplified geometries of a brain were solved to study pattern formation. The finite element method was used for the numerical solution, in conjunction with the Newton–Raphson method. The numerical examples showed that the model can represent cerebral cortex fold formation and reproduce pathologies related to gyri formation, such as polymicrogyria and lissencephaly.     

Face tracking with automatic model construction

This paper describes an active model with a robust texture model built on-line. The model uses one camera and it is able to operate without active illumination. The texture model is defined by a series of clusters, which are built in a video sequence using previously encountered samples. This model is used to search for the corresponding element in the following frames. An on-line clustering method, named leaderP is described and evaluated on an application of face tracking. A 20-point shape model is used. This model is built offline, and a robust fitting function is used to restrict the position of the points. Our proposal is to serve as one of the stages in a driver monitoring system. To test it, a new set of sequences of drivers recorded outdoors and in a realistic simulator has been compiled. Experimental results for typical outdoor driving scenarios, with frequent head movement, turns and occlusions are presented. Our approach is tested and compared with the Simultaneous Modeling and Tracking (SMAT) [1], and the recently presented Stacked Trimmed Active Shape Model (STASM) [2], and shows better results than SMAT and similar fitting error levels to STASM, with much faster execution times and improved robustness.