Interference checking approach with tolerance based on assembly dimension chain

CAD model with nominal dimension is implemented in interference checking of assembly simulation of aircraft complex parts at present,which causes inadequate availability.In order to address this challenging issue,interference checking method with tolerance based on assembly dimension chain was proposed.Worst case and maximum error probability of tolerance of composing loop were used,and CAD models were respectively re-constructed and inserted into simulation system.Before dynamic interference checking,engineering semantic interference condition was set to assembly requirements.Finally,the interface checking result was a basis for reasonability of assembly process and tolerance.A prototype system was developed based on the above research.     

A multi-front eikonal model of cardiac electrophysiology for interactive simulation of radio-frequency ablation

Virtual reality-based therapy simulation meets a growing interest from the medical community due to its potential impact for the training of medical residents and the planning of therapies. However, computer models of the human anatomy are often very computationally demanding, thus incompatible with the constraints of such interactive simulations.In this paper, we propose a fast model of the cardiac electrophysiology based on an eikonal formulation implemented with an anisotropic fast marching method. We demonstrate the use of this model in the context of a simulator of radio-frequency ablation of cardiac arrhythmia from patient-specific medical imaging data. Indeed, this therapy can be very effective for patients but still suffers from a rather low success rate. Being able to test different ablation strategies on a patient-specific model can have a great clinical impact.In our setting, thanks to a haptic 3D user interface, the user can interactively measure the local extracellular potential, pace locally the myocardium or simulate the burning of cardiac tissue as done in radio-frequency ablation interventions.     

基于模型检查的VHDL到FSM的转换

随着计算机软硬件系统规模的日益复杂,如何保证系统的正确和可靠,逐渐成为当前理论界和产业界共同关心的重要问题.为此提出的诸多理论和方法中,模型检查以其简洁明了和自动化程度高而引人注目.提出了一个针时时序电路VHDL设计的模型检查的解决方案.讨论了该方案的系统结构,将VHDL设计转化为有限状态机模型的算法,以及针对同步时序电路设计的模型化简,可有效减少FSM的状态空间,继而可以采用符号模型检查算法对需要检查的性质进行验证.     

A psychophysical study to determine acceptable limits for repetitive hand impact severity during automotive trim installation

The purpose of the current study was to use a psychophysical methodology to establish acceptable impact severity levels for this automotive trim installation. Two studies were conducted. In the first study, 17 male and 12 female subjects (6 assembly line workers and 23 students) performed 5 hand impacts/min on a device that simulated the process of seating push pins during door trim panel installation. In both studies, subjects were asked to impact the simulation device as hard as they found acceptable without causing injury, numbness or pain. Subjects were trained for 11 h. Force and hand acceleration time-histories were recorded from the simulation device and a hand-mounted accelerometer, respectively. The magnitude of each impact was quantified with eight dependent measures: peak, time-to-peak, load rate and impulse, from both the force and acceleration transducers. Statistics were used to determine the effects of gender, skill level and impact location on acceptable impact severity. In the second study, 8 male and 8 female subjects performed repeated hand impacts on a wall-mounted force plate at three different frequencies (2, 5 and 8 impacts/min) over three separate sessions. Force measures and statistics were the same as in Study 1. In the first study, impact location did not appear to have a consistent effect on the acceptable impact severities and there was no significant differences observed between male and female values. For both force and acceleration, impulse was the most reliable variable followed by the peak. In the second study an increase in impact frequency was observed to result in a significant decrease in the acceptable levels of peak force and force impulse. This effect was largest when going from 2 to 5 impacts/min and was less pronounced when going from 5 to 8 impacts/min (especially for force impulse). Male subjects demonstrated significantly higher acceptable impulse levels. Based on the combined results from both studies, acceptable limits were recommended for peak force and impulse that would be acceptable to 75% of the population for a range of frequencies. These limits were observed to range from 181 (8/min) to 259 N (2/min) for peak force and 2.53 (8/min) to 3.52 N s (2/min) for force impulse. It was concluded that force impulse and peak force were the variables most likely being controlled by the subjects.

Relevance to industry

Automotive assembly includes a number of tasks that involve hand impacts within the manufacturing process. One such task is the door trim panel installation process where the base of the hand is used to impact the door trim panel and drive fastening push pins through holes in the metal door frames. The current study provides tolerance limits so that industrial tasks involving hand impacts can be evaluated for their injury risk.     

A symbolic model checking approach to verifying satellite onboard software

This paper discusses the use of symbolic model checking technology to verify the design of an embedded satellite software control system called the attitude and orbit control system (AOCS). This system is mission critical because it is responsible for maintaining the attitude of the satellite and for performing fault detection, isolation, and recovery decisions. An executable AOCS implementation by Space Systems Finland has been provided in Ada source code form, and we use the input language of the symbolic model checker NuSMV 2 to model the implementation at a detailed level. We describe the modeling techniques and abstractions used to alleviate the state space explosion due to the handling of timers and the large number of system components controlled by the AOCS. The required behavior has been specified as extended state machine diagrams and translated to temporal logic properties. Besides well-known LTL and CTL model checking algorithms, we adapt a previously unexplored form of the liveness-to-safety approach to the problem. The latter new technique turns out to successfully prove all desired properties of the system, outperforming both the LTL and CTL implementations of NuSMV 2.     

时间序列模型在入侵检测中的应用研究

入侵检测是计算机系统安全技术的重要组成部分,是计算机领域当前研究热点之一。提出了一种用于入侵检测的时间序列模型。对于计算机系统运行的某一时段,用前K次审计时事件发生次数的均值作为第K 1次的期望值,然后求期望值和第K 1次的实际次数的相对误差。当相对误差超过某一阈值时,则认为在第K 1次发生了入侵。通过仿真揭示了阈值的选择规律。仿真结果证明,在突然发生较多的入侵事件时,模型工作良好。     

A distributed and interactive system to integrated design and simulation for collaborative product development

The goal of applying collaborative product development in industry has raised the need to develop software tools supporting system integration and group collaboration. Current methods and tools mainly focus on the collaborative creation of design components and assemblies. However, few of them support the collaborative work in developing simulation models so that proposed design concepts and solutions can be evaluated by integrating expertise from several disciplines. The purpose of this research is to develop a distributed and interactive system on which designers and experts can work together to create, integrate and run simulations for engineering design. To develop such a system, a number of issues, e.g. effectiveness and efficiency of modeling work, the re-use of models, interaction and cooperation, accuracy of simulation, collaborative operation on models, etc., need to be addressed. This paper describes an open architecture to developing simulations for engineering design in a distributed and collaborative environment, identifies a set of key issues raised in this architecture, and presents the techniques employed in our solution.     

A fault-tolerant approach to robot teams

As the applications of mobile robotics evolve it has become increasingly less practical for researchers to design custom hardware and control systems for each problem. This paper presents a new approach to control system design in order to look beyond end-of-lifecycle performance, and consider control system structure, flexibility, and extensibility. Towards these ends the Control ad libitum philosophy was proposed, stating that to make significant progress in the real-world application of mobile robot teams the control system must be structured such that teams can be formed in real-time from diverse components. The Control ad libitum philosophy was applied to the design of the HAA (Host, Avatar, Agent) architecture: a modular hierarchical framework built with provably correct distributed algorithms. A control system for mapping, exploration, and foraging was developed using the HAA architecture and evaluated in three experiments. First, the basic functionality of the HAA architecture was studied, specifically the ability to: (a) dynamically form the control system, (b) dynamically form the robot team, (c) dynamically form the processing network, and (d) handle heterogeneous teams and allocate robots between tasks based on their capabilities. Secondly, the control system was tested with different rates of software failure and was able to successfully complete its tasks even when each module was set to fail every 0.5–1.5 min. Thirdly, the control system was subjected to concurrent software and hardware failures, and was still able to complete a foraging task in a 216 m² environment.     

Learning to make errors: evidence from a driving task simulation

Human errors represent a mismatch between the demands of an operational system and what the operator does. If they cannot be reversed, their consequences may be severe. Errors are frequently classified as design-or operator-induced. A third class of errors may also be identified, namely process-induced errors. Such errors arise out of on-going processes which typically extend over time. One such process is that of learning. In relation to the acquisition of skills, for example, learning frequently involves a trial-and-error component. Accidents by inexperienced drivers may represent a severe consequence of such errors. Errors may also arise out of particular learning experiences which provide a distorted underestimate of objective risk and/or motivate high risk behaviour. These phenomena are investigated in a computer simulation of the driving task. The relationship is discussed between various kinds of learning experience and the development of situations in which the possibility of error recovery declines. Some suggestions for reducing the frequency of irreversible errors and for increasing the data base for human error in vehicle driving are made.     

A workflow model based on parallelism for distributed organizations

Distribution has become an increasingly common characteristic for modern service and production companies. Enterprises nowadays rely on distribution of their operations for provision of their supplies, labor, and for selling their products in dynamic global markets. Much of today enterprises efforts to cope with global markets are being directed towards the finding of effective collaboration means among their operations and partners. This research proposes a model for assisting distributed enterprises in modeling their operations by optimizing and integrating their workflow to accomplish the collaborative objective. The method developed, called the distributed parallel integration evaluation model (DPIEM) models the workflow in the distributed enterprise based on three integration scenarios. DPIEM minimizes the integrated tasks total cost by adding as many parallel servers per task as possible. The method was tested for a case of distributed assembly of two part-types. A total of eight scenarios for the case were analyzed, yielding the recommended number of parallel servers per integrated task. For comparison, each scenario was also simulated with the TIE parallel-computer environment. The TIE simulation results corroborate the DPIEM recommendation based on the lowest total cost for the case analyzed.     

A Bayesian solution to the multivariate Behrens-Fisher problem

One of the most common problems in applied statistics is to compare two normal population means when the ratio of variances is unknown and not equal to 1. This is the known Behrens-Fisher problem. There are many approaches to the distribution to the t-statistic in the univariate circumstance under the Behrens-Fisher problem. In the multivariate case, most solutions are based on adjusting the degrees of freedom to obtain better approximations to the chi-squared or Hotelling’s T² distributions. In both circumstances there are Bayesian solutions proposed by some authors. This work aimed to propose a computational Bayesian solution to the multivariate Behrens-Fisher problem based on the complex analytical solution of Johnson and Weerahandi (1988), to evaluate its performance through Monte Carlo simulation computing the type I error rates and power and to compare it with the modified Nel and Van der Merwe test, that is considered the best frequentist solution. The inferences were made to the population difference of the mean vectors. It was used as a conjugate prior distribution to the population mean vector and covariance matrix obtaining a posterior multivariate t distribution to , for i=1, 2. In general, the Bayesian test was conservative for samples of different sizes and liberal in some circumstances of equal and small sample sizes and its power was equal to or greater than that of its competitor in large samples and/or in balanced circumstances. The new solution has competitive advantages and in some circumstances surpasses its main competitor, therefore its use in real cases should be recommended.     

Contributions of 3'-overhang to the dissociation of small interfering RNAs from the PAZ domain: molecular dynamics simulation study

RNA interference (RNAi) is a ‘knock-down’ reaction to reduce expression of a specific gene through highly regulated, enzyme-mediated processes. Small interfering RNAs (siRNAs) are RNA molecules that play an effector role in RNAi and can bind the PAZ domains present in Dicer and RISC. We investigated the interaction between the PAZ domain and the siRNA-like duplexes through dissociation molecular dynamics (DMD) simulations. Specifically, we focused on the response of the PAZ domain to various 3′-overhang structures of the siRNA-like duplexes. We found that the siRNA-like duplex with the 3′ UU-overhang made relatively more stable complex with the PAZ domain compared to those with 3′ CC-, AA-, and GG-overhangs. The siRNA-like duplex with UU-overhang was easily dissociated from the PAZ domain once the structural stability of the complex is impaired. Interestingly, the 3′ UU-overhang spent the least time at the periphery region of the binding pocket during the dissociation process, which can be mainly attributable to UU-overhang's smallest number of hydrogen bonds.     

A simulation model for eliciting scheduling knowledge: an application to the precast manufacturing process

This paper discusses the process of eliciting scheduling knowledge from a simulation model and the development of a dynamic modelling approach to the scheduling process in the precast concrete industry. Due to the problems associated with eliciting scheduling knowledge from an ‘expert’ in the precast industry or perhaps in most of the manufacturing industries, simulation is used to complement human knowledge in this paper. Such knowledge will be used for online support to advise production schedulers and for further development of the simulation model by incorporating the knowledge in the model and making it more dynamic. The paper suggests that dynamic selection of scheduling rules during real-time operation has been recognised as a promising approach to the scheduling process in the precast industry. For this strategy to work effectively, sufficient knowledge is required to enable the model to predict the most effective scheduling rule to meet current factory status. The paper concludes that if the knowledge rules are used effectively, they could be a considerable managerial tool for exploring and improving managerial practices. Recommendations have been made regarding the development of a more realistic and practical scheduling system.     

A dynamic integration algorithm to model surfaces from multiple range views

This paper presents a dynamic integration algorithm to triangulate a surface from multiple range views. This integration technique is based on the reparameterization of the canonic subsets of the Venn diagram of the set of range views. We compute a model based onN views from a model based onN–1 views by processing only the surface segments visible in theN ^th view. An experimental result shows that the proposed integration algorithm can process complex multipart objects containing holes.     

A quantum-confinement model for surrounding-gate MOSFETS from subthreshold to strong-inversion regions

A new analytical model is developed for quantum-confinement effects of short channel surroundinggate MOSFETs.The eigenenergies and wavefunctions are obtained by solving Schrdinger’s equation with an accurate potential energy distribution.The potential energy distribution is derived from the solution of Poisson’s equation,which contains both depletion charge and free charge.The eigenenergies obtained from our model are compared with other two quantum-confinement models,which use flat-well approximation and parabola-well approximation as the potential energy distributions,respectively.And we point out the relationship between the eigenenergies and the potential energy distribution for the first time.Based on this model,the electron density with quantum confinement effects are derived,and threshold voltage is defined based on average electron density.After considering quantum confinement effects,the electron density becomes smaller while the threshold voltage becomes larger.The results show that this model is applicable from the subthreshold region to the stronginversion region in different channel doping conditions.     

A computational model of time for stiff hybrid systems applied to control synthesis

Computation has quickly become of paramount importance in the design of engineered systems, both to support their features as well as their design. Tool support for high-level modeling formalisms has endowed design specifications with executable semantics. Such specifications typically include not only discrete-time and discrete-event behavior, but also continuous-time behavior that is stiff from a numerical integration perspective. The resulting stiff hybrid dynamic systems necessitate variable-step solvers to simulate the continuous-time behavior as well as solver algorithms for the simulation of discrete-time and discrete-event behavior. The combined solvers rely on complex computer code which makes it difficult to directly solve design tasks with the executable specifications. To further leverage the executable specifications in design, this work aims to formalize the semantics of stiff hybrid dynamic systems at a declarative level by removing implementation detail and only retaining ‘what’ the computer code does and not ‘how’ it does it. A stream-based approach is adopted to formalize variable-step solver semantics and to establish a computational model of time that supports discrete-time and discrete-event behavior. The corresponding declarative formalization is amenable to computational methods and it is shown how model checking can automatically generate, or synthesize, a feedforward control strategy for a stiff hybrid dynamic system. Specifically, a stamper in a surface mount device is controlled to maintain a low acceleration of the stamped component for a prescribed minimum duration of time.     

A vision-based regression model to evaluate Parkinsonian gait from monocular image sequences

Parkinson’s Disease (PD) is a common neurodegenerative disorder with progressive loss of dopaminergic and other sub-cortical neurons. Among various approaches, gait analysis is commonly used to help identify the biometric features of PD. There have been some studies to date on both the classification of PD and estimation of gait parameters. However, it is also important to construct a regression system that can evaluate the degree of abnormality in PD patients. In this paper, we intended to develop a PD gait regression model that is capable of predicting the severity of motor dysfunction from given gait image sequences. We used a model-free strategy and thus avoided the critical demands of segmentation and parameter estimation. Furthermore, we used linear discriminant analysis (LDA) to increase the feature efficiency by maximizing and minimizing the between- and within-group variations. Regression was also achieved by assessing the spatial and temporal information through classification and finally by using these two new indices for linear regression. According to the experiments, the outcomes significantly correlated with the sum of sub-scores from the Unified Parkinson’s Disease Rating Scale (UPDRS): motor examination section with r = 0.92 and 0.85 for training and testing, respectively, with p < 0.0001. Compared with conventional methods, our system provided a better evaluation of PD abnormality.     

On the model granularity to simulate protein dynamics: A biological physics view on biomolecular computing

What granularity is needed to carry out computer simulations of biomolecular reactions/motions? This is one of the central issues of the in silico biomolecular computing. In this paper, we addressed this issue by studying model granularity dependence of the native structure dynamics of protein molecules. We conducted molecular dynamics simulations employing three different protein models: the model with full atomic details and two coarse-grained models in which only C_α atoms interacting with each other through simple potentials are considered. In addition to the observed agreement among the three models in terms of isotropic thermal fluctuation, principal component analysis showed that the coarse-grained models can also reproduce the anisotropy (or directionality) of the fluctuation, particularly of collective modes having relevance to molecular function. This indicates that the dependence of the essential dynamics of a protein molecule on the model granularity is weak, although it was also shown that incorporation of the Lennard–Jones-type potential into the harmonic-potential-based coarse-grained model improves the reproducibility to some degree, and that a plastic nature of structural dynamics observed in the full atomic model transforms into an elastic one in the coarse-grained models. The coarse-grained model can be applied to a molecular motor system, which may lead to a new view of biomolecular computing in the context of biological physics.     

A multi-objective decision-making model with fuzzy rough coefficients and its application to the inventory problem

In this paper, we concentrate on developing a fuzzy rough multi-objective decision-making model according to uncertainty theory. We present some equivalent models and a traditional algorithm based on an interactive fuzzy satisfying method, which is similar to the interactive fuzzy rough satisfying method, in order to obtain a satisfying solution for the decision maker. In addition, the technique of fuzzy rough simulation is applied to deal with general fuzzy rough objective functions and fuzzy rough constraints which are usually difficult to convert into their equivalents. Furthermore, combined with the techniques of fuzzy rough simulation, a genetic algorithm using the compromise approach is designed for solving a fuzzy rough multi-objective programming problem. Finally, a model is applied to an inventory problem to illustrate the usefulness of the proposed model and algorithm, and then a sensitivity analysis is made.