Sticker DNA computer model ——PartⅡ: Application

Sticker model is one of the basic models in the DNA computer models. This model is coded with sin-gle-double stranded DNA molecules. It has the following advantages that the operations require no strands extension and use no enzymes; What抯 more, the materials are reusable. Therefore, it arouses attention and interest of scientists in many fields. In this paper, we extend and improve the sticker model, which will be definitely beneficial to the construction of DNA computer. This paper is the second part of our series paper, which mainly focuses on the application of sticker model. It mainly consists of the following three sections: the matrix representation of sticker model is first presented; then a brief review of the past research on graph and com-binatorial optimization, such as the minimal set covering problem, the vertex covering problem, Hamiltonian path or cycle problem, the maximal clique problem, the maximal independent problem and the Steiner spanning tree problem, is described; Finally a DNA algorithm for the graph iso-morphic problem based on the sticker model is given.     

Multiscale computation from a chemical engineering perspective

This paper mainly discusses the multiscale computation from a chemical engineering perspective. From the application designer＇ s perspective, we propose a new approach to investigate and develop both flexible and efficient computer architectures. Based on the requirements of applications within one category, we first induce and extract some inherent computing patterns or core computing kernels from the applications. Some computing models and innovative computing architectures will then be developed for these patterns or kernels, as well as the software mapping techniques. Finally those applications which can share and utilize those computing patterns or kernels can be executed very efficiently on those novel computing architectures. We think that the proposed approach may not be achievable within the existing technology. However, we believe that it will be available in the near future. Hence, we will describe this approach from the following four aspects： multiscale environment in the world, mesoscale as a key scale, energy minimization multiscale （EMMS） paradigm and our perspective.     

The rise of granular computing

This paper has two purposes. One is to present a critical examination of the rise of granular computing and the other is to suggest a triarchic theory of granular computing. By examining the reasons, justifications, and motivations for the rise of granular computing, we may be able to fully appreciate its scope, goal and potential values. The results enable us to formulate a triarchic theory in the light of research results from many disciplines. The three components of the theory are labeled as the philosophy, the methodology, and the computation. The integration of the three offers a unified view of granular computing as a way of structured thinking, a method of structured problem solving, and a paradigm of structured information processing, focusing on hierarchical granular structures. The triarchic theory is an important effort in synthesizing the various theories and models of granular computing.     

Characteristics of a Two-Class Polling System Model

Polling system models have a wide range of important applications including time-sharing computer systems, industrial control, communications, and computer networks. In this paper, we propose a two-class priority- based polling system that uses gated and exhaustive services to achieve the priority-based scheme. This model is set up according to the method of the imbedded Markov chain theory and the generation function and explicitly analyzes key system performance characteristics including mean queue length, cyclic time, and throughput. Theoretical and simulation results are identical and demonstrate the efficiency of the model.     

基于神经网络扩展内容寻址的"彩色磨粒智能识别机"研究与实现

Wear particle′s automatic recognition and analysis is one of the most important but difficult technical key to realize the automatic,intelligent and systematic wear monitoring and fault diagnosis of machine equipment.This paper will introduce our ANN-based on ANN′s Extended Content Address(ECA).Due to its complicated content,in this paper we′ll detail more on the idea and experiment results than on models and theory in CWPIR.Our idea and models here can also be used in other fields of micro particle image′s auto-analysis.     

Car-following models of vehicular traffic

The Car-following model is a kind of microscopic simulation model for vehicular traffic, which describe the one-by-one following behaviors of vehides in the same traffic lane. As a common traffic phenomenon, following behavior is of great importance in the micro-study of intelligent traffic control.Compared with other traffic-flow models, car-following model embodies the human factors and feflects the real traffic sit-uation in a better way. This paper gives a systematic review of the development and actuality of car-following models by introducing and analyzing in detail the advantages and disavantages of GHR model, OV model,CA model and fuzzy-logic model. In addition, local stability and asymptotic stability of car-following models are discussed in this paper.     

Plausible cloth animation using dynamic bending model

Simulating the mechanical behavior of a cloth is a very challenging and important problem in computer animation. The models of bending in most existing cloth simulation approaches are taking the assumption that the cloth is little deformed from a plate shape. Therefore, based on the thin-plate theory, these bending models do not consider the condition that the current shape of the cloth under large deformations cannot be regarded as the approximation to that before deformation, which leads to an unreal static bending. [This paper introduces a dynamic bending model which is appropriate to describe large out-plane deformations such as cloth buckling and bending, and develops a compact implementation of the new model on spring-mass systems. Experimental results show that wrinkles and folds generated using this technique in cloth simulation, can appear and vanish in a more natural way than other approaches.]     

Integrated research of parallel computing: Status and future

In the past twenty years, the research group in University of Science and Technology of China has developed an integrated research method for parallel computing, which is a combination of ＂Architecture- Algorithm-Programming-Application＂. This method is also called the ecological environment of parallel computing research. In this paper, we survey the current status of integrated research method for parallel computing and by combining the impact of multi-core systems, cloud computing and personal high performance computer, we present our outlook on the future development of parallel computing.     

An Energy-Saving Task Scheduling Strategy Based on Vacation Queuing Theory in Cloud Computing

High energy consumption is one of the key issues of cloud computing systems. Incoming jobs in cloud computing environments have the nature of randomness, and compute nodes have to be powered on all the time to await incoming tasks. This results in a great waste of energy. An energy-saving task scheduling algorithm based on the vacation queuing model for cloud computing systems is proposed in this paper. First, we use the vacation queuing model with exhaustive service to model the task schedule of a heterogeneous cloud computing system.Next, based on the busy period and busy cycle under steady state, we analyze the expectations of task sojourn time and energy consumption of compute nodes in the heterogeneous cloud computing system. Subsequently, we propose a task scheduling algorithm based on similar tasks to reduce the energy consumption. Simulation results show that the proposed algorithm can reduce the energy consumption of the cloud computing system effectively while meeting the task performance.     

A New Segmentation Model—Combined Mumford-Shah Model with Narrow Band

A segmentation model that combines the Mumford-Shah (M-S) model and narrow band scheme of level set is presented. The M-S model is a desirable model for image segmentation, but computationally time-consuming. This paper introduces a fast segmentation model, which combines the M-S model and narrow band scheme using new initialization method. The new initialization method is based on fastmarching method, and the computing time is O (n). In each iteration step, the new segmentation model only deals with the data in narrow band instead of the whole image. Comparing M-S model and new narrow band M-S, experiments show that the two models can obtain almost the same segmentation result, but the computing time of new narrow band M-S model is much less than M-S model.     

Genetic algorithm in DNA computing： A solution to the maximal clique problem

Genetic algorithm is one of the possible ways tobreak the limit of brute-force method in DNA computing.Using the idea of Darwinian evolution, we introduce a geneticDNA computing algorithm to solve the maximal clique prob-lem. All the operations in the algorithm are accessible withtoday‘s molecular biotechnoiogy. Our computer simulationsshow that with this new computing algorithm, it is possible toget a solution from a very small initial data pool, avoidingenumerating all candidate solutions. For randomly generatedproblems, genetic algorithm can give correct solution withina few cycles at high probability. Although the current speedof a DNA computer is slow compared with silicon computers,our simulation indicates that the number of cycles needed inthis genetic algorithm is approximately a linear function ofthe number of vertices in the network. This may make DNAcomputers more powerfully attacking some hard computa-tional problems.     

Analysis and Application for Integrity Model on Trusted Platform

To build a trusted platform based on Trusted Computing Platform Alliance (TCPA)‘s recommendation, we analyze the integrity mechanism for such a PC platform in this paper. By combinning access control model with information flow model, we put forward a combined process-based lattice model to enforce security. This model creates a trust chain by which we can manage a series of processes from a core root of trust module to some other application modules. In the model,once the trust chain is created and managed correctly,the integrity of the computer‘s hardware and sofware has been mainfained, so does the confidentiality and authenticity. Moreover, a relevant implementation of the model is explained.     

The Extended Linear-Drift Model of Memristor and Its Piecewise Linear Approximation

Memristor is introduced as the fourth basic circuit element.Memristor exhibits great potential for numerous applications,such as emulating synapse,while the mathematical model of the memristor is still an open subject.In the linear-drift model,the boundary condition of the device is not considered.This paper proposes an extended linear-drift model of the memristor.The extended linear-drift model keeps the linear characteristic and simplicity of the linear-drift model and considers the boundary condition of the device.A piecewise linear approximation model of the extended linear-drift model is given.Both models are suitable for describing the memristor.     

Proposed Methodology for Generation of Building Information Model with Laserscanning

For refurbishment and state review of an existing old building, a new model reflecting the current state is often required especially when the original plans are no longer accessible. Laser scanners are used more and more as surveying instruments for various applications because of their high-precision scanning abilities. For buildings, the most notable and widely accepted product data model is the IFC product data model. It is designed to cover the whole lifecycle and supported by various software vendors and enables applications to efficiently share and exchange project information. The models obtained with the laser scanner, normally sets of points ("point cloud"), have to be transferred to an IFC compatible building information model to serve the needs of different planning states. This paper presents an approach designed by the German Research Center in Karlsruhe (Forschungszentrum Karlsruhe) to create an IFC compatible building information model from laser range images. The methodology through the entire process from data acquisition to the IFC compatible product model was proposed in this paper. In addition, IFC-Models with different level of detail (LoDs) were introduced and discussed within the work.     

Applied Approaches of Rough Set Theory to Web Mining

Rough set theory is a new soft computing tool, and has received much attention of researchers around the world. It can deal with incomplete and uncertain information. Now, it has been applied in many areas successfully. This paper introduces the basic concepts of rough set and discusses its applications in Web mining. In particular, some applications of rough set theory to intelligent information processing are emphasized.     

Fault-Tolerant Technique in the Cluster Computation of the Digital Watershed Model

This paper describes a parallel computing platform using the existing facilities for the digital watershed model. In this paper, distributed multi-layered structure is applied to the computer cluster system, and the MPI-2 is adopted as a mature parallel programming standard. An agent is introduced which makes it possible to be multi-level fault-tolerant in software development. The communication protocol based on checkpointing and rollback recovery mechanism can realize the transaction reprocessing. Compared with conventional platform, the new system is able to make better use of the computing resource. Experimental results show the speedup ratio of the platform is almost 4 times as that of the conventional one, which demonstrates the high efficiency and good performance of the new approach.     

URMG: Enhanced CBMG-Based Method for Automatically Testing Web Applications in the Cloud简

To satisfy the rapid growth of cloud technologies, a large number of web applications have been developed and deployed, and these applications are being run in clouds. Due to the scalability provided by clouds, a single web application may be concurrently visited by several millions or billions of users. Thus, the testing and performance evaluations of these applications are increasingly important. User model based evaluations can significantly reduce the manual work required, and can enable us to determine the performance of applications under real runtime environments. Hence, it has become one of the most popular evaluation methods in both industry and academia. Significant efforts have focused on building different kinds of models using mining web access logs, such as Markov models and Customer Behavior Model Graph （CBMG）. This paper proposes a new kind of model, named the User Representation Model Graph （URMG）, which is built based on CBMG. It uses an algorithm to refine CBMG and optimizes the evaluations execution process. Based on this model, an automatic testing and evaluation system for web applications is designed, implemented, and deployed in our test cloud, which is able to execute all of the analysis and testing operations using only web access logs. In our system, the error rate caused by random access to applications in the execution phase is also reduced, and the results show that the error rate of the evaluation that depends on URMG is 50% less than that which depends on CBMG.     

Testing and Evaluation for Web Usability Based on Extended Markov Chain Model

As the increasing popularity and complexity of Web applications and the emergence of their new characteristics. the testing and maintenance of large, complex Web applications are becoming more complex and difficult. Web applications generally contain lots of pages and are used by enormous users. Statistical testing is an effective way of ensuring their quality. Web usage can be accurately described by Markov chain which has been proved to be an ideal model for software statistical testing. The results of unit testing can b eutilized in the latter stages, wbich is an important strategy for bottom-to-top integration testing, and the other improvement of extended Markov chain model (FMM) is to present the error type vector which is treated as a part of page node. This paper also proposes the algorithm for generating test cases of usage paths. Finally, optional usage reliability evaluation methods and an incremental usability regression testing model for testing and evaluation are presented.     

Solve the partitioning problem by sticker model in DNA computing

The aim of this work is to solve the partitioning problem, the most canonical NP-complete problem containing numerical parameters, within the sticker model of DNA computing. We firstly design a parallel program for addition, and then give a program to calculate the subset sums of a set. At last, a program for partitioning is given, which contains the former programs. Furthermore, the correctness of each program is proved in this paper.     

Parallel scheduling strategy of web-based spatial computing tasks in multi-core environment

In order to improve the concurrent access performance of the web-based spatial computing system in cluster,a parallel scheduling strategy based on the multi-core environment is proposed,which includes two levels of parallel processing mechanisms.One is that it can evenly allocate tasks to each server node in the cluster and the other is that it can implement the load balancing inside a server node.Based on the strategy,a new web-based spatial computing model is designed in this paper,in which,a task response ratio calculation method,a request queue buffer mechanism and a thread scheduling strategy are focused on.Experimental results show that the new model can fully use the multi-core computing advantage of each server node in the concurrent access environment and improve the average hits per second,average I/O Hits,CPU utilization and throughput.Using speed-up ratio to analyze the traditional model and the new one,the result shows that the new model has the best performance.The performance of the multi-core server nodes in the cluster is optimized; the resource utilization and the parallel processing capabilities are enhanced.The more CPU cores you have,the higher parallel processing capabilities will be obtained.