Simulation of Assembly Tolerance and Characteristics of High Pressure Common Rail Injector Fuel injector is the key part of a high-pressure common rail fuel injection system. Its manufacturing precision and assembly quality affect system's property and performance. According to the characteristics and demands of assembly of the fuel injector, an intelligent optimization algorithm is proposed to resolve the problem of assembly sequence planning. Based on geometric modeling, assembly dimension chain of the injector control chamber is established, and the relationship between assembly tolerance and volume change of control chamber is analyzed. The optimization model of the assembly is established. The impact of assembly tolerance on injector's performance is simulated according to the optimization algorithm. The simulation result shows that quantity of injection fuel changes correspondingly with the change of assembly tolerance, while injection rate and pressure do not change significantly, and the response rate of needle considerably slow. Similarly, the leakage rate of fuel in control chamber is calculated, indicating that the assembly tolerance has obvious impact on fuel leakage and its rate. The study illuminates that injector's assembly tolerance has prominent effect on injection. The rigorous exhaust emission legislation and increasingly development of diesel engine electronic control technology make high-pressure common-rail fuel injection system come into the world. It initiates the new era of diesel engine fuel injection technology. As a high flexible fuel injection system, the high-pressure common-rail injection system has become a trend of the diesel engine technology for its remarkable characteristics. Acting as the execution unit, Fuel injector is the key part of a high-pressure common rail fuel injection system. Its structural parameters, manufacturing precision, assembly quality have an important impact on the injecting of the fuel system [1] [2] . Based on the structural analysis of the fuel injector, a study on assembly dimension chain of the injector control chamber is conducted. And the impact of assembly tolerance on injector's performance is simulated with Hydsim software. On this basis, the principle of selective assembly for injector assembly is put forward. Based on the theoretical calculation and simulation analysis, the following conclusions can be drawn: 1) When the assembly design tolerance of the control chamber T0 is 0.08mm, in the case of ensuring the assembly tolerance T 0 , the smaller tolerance of control piston on axial direction is, and the greater tolerance of control chamber on axis direction is, the better the characteristic of the injection system is.. 2) For the gap between the control piston and chamber, the tolerance must be strictly controlled in the design value. The simulation results show that if the gap tolerance were increased 0.001mm, the amount of fuel leaked and leakage rate would be doubly increased.

B O B I O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O


Osteoclasts and Integrins ABSTRACT: The osteoclast is the unique bone resorptive cell that accomplishes its mission by forming an isolated acidified microenvironment between itself and the bone surface. Creation of this compartment is the first step in bone degradation and establishes that an intimate physical relationship must exist between the osteoclast and bone. Thus, identification of the mechanisms by which the osteoclast attaches to bone is essential to understanding how the cell degrades skeletal tissue. Our studies have investigated whether absence of the ␣v␤3 integrin modifies the ability of c-Fms to induce Rho GTPases, and the implications for formation of the osteoclast cytoskeleton.The osteoclast is the unique bone resorptive cell that accomplishes its mission by forming an isolated acidified microenvironment between itself and the bone surface. Creation of this compartment is the first step in bone degradation and establishes that an intimate physical relationship must exist between the osteoclast and bone.1 Thus, identification of the mechanisms by which the osteoclast attaches to bone is essential to understanding how the cell degrades skeletal tissue.Integrins are transmembrane ␣␤ heterodimers that mediate cell/cell and cell/matrix recognition.2 In the case of integrins mediating matrix attachment, their extracellular domains are liganded by extracellular proteins, while their intracellular tails interact with signaling molecules and the cytoskeleton.A series of in vitro experiments established that ␣v␤3 is the principal osteoclast integrin. ␣v␤3, like all members of the ␣v family of integrins, recognizes the arginine-glycine-aspartic acid (RGD) motif. This ligand is present in a number of bone-residing proteins, such as osteopontin and bone sialoprotein. To determine if the ␣v␤3 integrin, identified in vitro, has physiological significance, we deleted the ␤3 integrin gene in mice.

O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O


Developing the Agile IS Development Practices in Large-Scale IT Projects: The Trust-Mediated Organizational Controls and IT Project Team Capabilities Perspectives Abstract Many practitioners and researchers in today's dynamic business environment find difficulty in achieving success in their IT project implementations. Despite years of research on IT project management and despite the wide availability of practical knowledge on project management, many IT projects still fail (The Standish Group International, 2009 ). According to the CHAOS Summary Report, which has tracked IT project failure rates since 1994, only 32 percent of the IT projects investigated was successful in 2009 (The Standish Group International, 2009 ). The same report also presented a worrying trend since 2002 of an increased IT project failure rate: from 15 percent to 24 percent. With increasing time-to-market pressure and an unprecedented rate of change in the user requirements during the system development in recent times (Lee, Venkatraman, Tanriverdi, & Iyer, 2010; Pacheco-de-Almeida, 2010) , implementing IT projects successfully is becoming increasingly challenging even for a highly experienced software team (Geneca, 2011; Schmidt, Lyytinen, Keil, & Cule, 2001) . This is apparent to the extent that more than 75 percent of the IT professionals surveyed deemed their IT projects as "doomed" right from the start (Geneca, 2011) . As a result, the practitioner and research communities largely agree that the current state of IS development practices needs to be improved (Dingsøyr, Nerur, Balijepally, & Moe, 2012) .. Since 2001, many scholars and practitioners have regarded agile IS development as the solution to the high rate of IT project failures (Abrahamsson, Conboy, & Wang, 2009) . Advocating a close developer-user collaboration, agile IS development practices allow any development team to constantly adapt its developmental efforts toward ever-changing business requirements (Lee & Xia, 2010) . Many scholars have deemed a close developer-user partnering process as the critical success factor in the increasingly volatile IT project development environment (Hsu, Liang, Wu, Klein, & Jiang, 2011; Jiang, Klein, & Chen, 2006; Wang, Shih, Jiang, & Klein, 2006) . Not surprisingly, popular agile IS development practices that embrace such collaboration processes between developers and users have often enjoyed higher chances of project success (Stephens & Rosenberg, 2003) . Many organizations regard these practices as a better collective solution to improve the quality of user interaction, user satisfaction, and project management processes (Ceschi, Sillit, Giancario, & De Panfil, 2005) compared to traditional IS development practices. As a result, many organizations have adopted agile IS development practices into their mainstream application development processes over the last decade (Finley, Wilson, & van Huizen, 2012) . Unfortunately, extant research on the agile IS development has not been able to catch up with this increased demand for knowledge on the adoption of these practices. The emergence of several IS journals' special issues that have covered agile IS development practices supports this conclusion (e.g., Abrahamsson et al., 2009; Ågerfalk, Fitzgerald, & Slaughter, 2009; Dingsøyr et al., 2012; Erickson, Lyytinen, & Siau, 2005) .. Despite the large number of empirical studies that investigate agile IS development practices in realistic contexts (e.g. Fitzgerald, Hartnett, & Conboy, 2006; Grenning, 2001; Mangalaraj, Mahapatra, & Nerur, 2009; Murru, Deias, & Mugheddu, 2003) , we identify two gaps in the literature of these practices. The first gap concerns whether agile IS development practices can be developed in largescale IT projects (Dingsøyr et al., 2012; Freudenberg & Sharp, 2010) . Based on a survey conducted during the 11th International Conference on Agile Software Development in 2010, 300 practitioners identified the most-desirable research topic as "the adoption of agile IS development practices in large-scale IT projects" (Freudenberg & Sharp, 2010) ; and, in the same survey conducted in 2011, academics identified the same topic (Dingsøyr et al., 2012) . Although scholars have researched the application of agile IS development practices in large IT projects to some extent (e.g., Elshamy & Elssamadisy, 2006) , our current understanding of them is still very limited (Abrahamsson et al., 2009; Dingsøyr et al., 2012) .. The second gap, according to several comprehensive reviews of the agile IS development literature (e.g., Abrahamsson et al., 2009; Dingsøyr et al., 2012; Dybå & Dingsøyr, 2008) , is that "not enough attention [has been] paid to establishing theoretical underpinnings when investigating agile development and its various practices". Because agile IS development is a research area that is primarily practitioner driven, and because of the lack of sound theoretical ground to explain agile IS development's essential methodology-independent concepts (Abrahamsson et al., 2009; Jacobson & Spence, 2009) , accumulating knowledge on the adoption and application of agile IS development practices has been a challenging process (Abrahamsson et al., 2009; Erickson et al., 2005) . This lack of theoretical foundation has led to much confusion for those who practice and research these practices (Conboy, 2009) . As a result, many researchers have realized the importance of establishing a robust theoretical basis to guide ongoing research (Abrahamsson et al., 2009; Ågerfalk et al., 2009; Dingsøyr et al., 2012) .. In this study, we address these two gaps in the extant agile IS development literature. By conducting a case study based on four large-scale IT projects used to construct Beijing Capital International Airport (BCIA) Terminal 3, we address the knowledge gap of the agile IS development practices in large-scale IT projects, and leverage the literature of trust-mediated organizational control and IT project team capabilities to develop the theoretical underpinnings that outline the essential ingredients of an agile IS development practice in a large-scale IT project. In so doing, we provide the essential methodology-independent concepts that can serve as powerful theoretical glue to bind all future agile IS development research on large-scale IT projects (Jacobson & Spence, 2009; Whetten, 1989) . Our research question is: How are agile IS development practices developed in a large-scale IT project?. Since the publication of the Agile manifesto in 2001 (Beck et al., 2001) , agile IS development practices have received significant interest from many practitioners. Various forms of agile IS development practices (such as eXtreme Programming and Scrum) that are, based on the principles developed in the Agile Manifesto, have emerged. Practitioner-initiated research, inspired by many of those practices, has also created significant interest in the research community, (Dingsøyr et al., 2012; Dybå & Dingsøyr, 2008) . Notwithstanding the efforts of pioneer research, we have subsequently identified two gaps in the research on agile IS development; namely, whether agile practices can be extended to large-scale IT projects, and the lack of theoretical underpinnings in research on agile IS development. By presenting models detailing the four distinct types of agile IS development practices that can be developed in a large-scale IT project, this study makes several important theoretical and practical contributions. First, this study sheds light on the ways that the underlying process of agile IS development practices can be developed in large-scale IT projects. This answers the call by many researchers and practitioners to extend agile IS development research onto large-scale IT projects (Ågerfalk et al., 2009; Dingsøyr et al., 2012; Freudenberg & Sharp, 2010) . Second, we have developed our models built on a strong theoretical basis found in the literature. We have built our models from the insight that has been drawn from the research on trust-mediated organizational control, BCIA's IT project team's capabilities, and agile IS development. To the best of our knowledge, we also conclude that our models are the first theoretically driven models on the study of agile IS development practices in the context of large-scale IT projects. Our theoretically driven models help to complement the existing practitioner-driven agile methods, such as XP or Scrum. We are confident that our models will increase the success rate of extending the agile IS development to large-scale IT project in organizations. These contributions are of significant value to both the practitioners and researchers. While prior studies have advocated a contingency view that defines the success of an agile IS development practice in the small-scale projects (e.g., Cao et al., 2009) , it is unclear what these contingency factors are for the agile IS development in a large-scale IT project. Our study has also identified two of such contingency factors (viz., (1) project uncertainty, and (2) project completion urgency) drawn from the insight cited in the extant literature. Through our theoretical models, we present ways that the varying types of project uncertainty and project completion urgency can be effectively addressed through the interplay of an IT project team's capabilities and trust-mediated organizational control mechanisms. Finally, in so doing, we provide a trustworthy roadmap for practitioners who are keen to explore agile IS development practices in large-scale IT projects. In addition, our theoretical models provide the necessary foundation for future research on agile IS development practices, especially in the area of large-scale IT projects. We contend that two contingent factors play crucial roles in developing agile IS development practices for large-scale IT projects; namely, (1) project uncertainty, and (2) project completion urgency. When an IT project is large, uncertainty is an especially salient factor that often troubles even the most experienced project manager (Meyer et al., 2002) . This is largely due to many managers' regarding uncertainty as a single type. Thus, they fail to realize that different types of project uncertainty require different management approaches in planning, monitoring, and controlling (Meyer et al., 2002) . Very often, these managers assume that most of a project's uncertainties can be identified right from the onset of the project and can planned for (Meredith & Mantel, 1995) . Hence, we analyze our data by first matching the profiles of the four project uncertainties that have been identified in the literature to the large-scale IT projects of our study (see Table 6 ).. In order for an IT project team to devise an effective IT project management approach to handle project uncertainty, it needs to develop a set of unique capabilities (Fink & Neumann, 2007; Sambamurthy, Anandhi, & Varun, 2003) . Hence, we focus on identifying the dominant IT project team capabilities developed specially to address the type of "project uncertainty" identified in each of the four large-scale IT projects in our study.. The other contingent factor crucial to the development of the agile IS development practices is project completion urgency. We postulate that an IT project team needs to develop a set of effective organizational control mechanisms to manage vendors and users in order to adhere to the required project timeline. For instance, organizational control mechanisms are important factors that affect the software team's ability to respond to changing requirements (Maruping et al., 2009) . Hence, our case analysis focuses on identifying the dominant organizational control mechanisms used in each of the four large-scale IT projects. Although business process of passenger check-in has remained similar for decades, the main requirement of the system is to perform small customizations tailored for airlines, which vary from one airline to another. This makes the project outcome vary randomly but within a predictable range.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


A CONSTRAINT SOLVER AND ITS APPLICATION TO PATH FEASIBILITY ANALYSIS Many testing methods are based on program paths. A well-known problem with them is that some paths are infeasible. To decide the feasibility of paths, we may solve a set of constraints. In this paper, we describe constraint-based tools that can be used for this purpose. They accept constraints expressed in a natural form, which may involve variables of different types such as integers, Booleans, reals and fixed-size arrays. The constraint solver is an extension of a Boolean satisfiability checker and it makes use of a linear programming package. The solving algorithm is described, and examples are given to illustrate the use of the tools. For many paths in the testing literature, their feasibility can be decided in a reasonable amount of time. Program testing methods can be roughly divided into two categories: black-box and white-box. The former is based on the functional specification, while the latter uses the source code of the program.. Many white-box testing methods can be viewed as path-oriented. We select a set of paths of the program, such that some criteria are met. A commonly used criterion is statement coverage, which means that all statements should be included in the chosen set of paths. There are also other criteria such as branch coverage and path coverage.. To execute each path, we need to find appropriate values for the input variables. This problem is called test data generation. If no values of the variables can cause the program to be executed along a path, we say that the path is infeasible or non-executable. A well-known problem in program testing is that many paths are infeasible [1, 2] . In this paper, we shall describe constraint-based tools and their application to the analysis of path feasibility. This paper is organized as follows. In the next section, we recall some basic concepts of path-oriented testing and analysis. Then in Sec. 3, we briefly show how to derive a set of constraints from a path automatically. The path is executable if these constraints are satisfiable. In Sec. 4, we describe a constraint solver and its use in the analysis of path feasibility. Finally, our work is compared with other related approaches, and some further research topics are discussed. A major difficulty with path-oriented testing methods is that many paths turn out to be non-executable or infeasible. This also occurs frequently in the assertion-based analysis approach, where a postcondition is negated. (Unless the program contains many bugs, the negated postcondition is usually not satisfiable.). To determine the feasibility of program paths, we may generate a set of constraints and then decide their satisfiability. This can be done by hand or with the help of various tools (such as theorem provers, decision procedures and constraint solvers). We believe that the constraint solving approach is better in terms of efficiency and degree of automation. However, many existing constraint solvers are not so easy to use for the purpose of program testing. Our experiences indicate that the constraints are generally not too difficult to solve, but they may be complicated syntactically. There can be variables of different types and many Boolean operators.. In this paper, we describe constraint-based tools for determining the feasibility of paths. The tool PAT extracts path conditions, while BoNuS is used to solve them. They can be combined to generate test data and to detect infeasible paths. The tools are highly automatic, and they allow the user to specify constraints and paths in a very natural way. Common data types such as integers, Booleans, and arrays are accepted. PAT can also be used as a front-end to constraint solvers like BoNuS, since a "path" can contain logical expressions only (without assignment statements). The tools may also be combined with other path selection methods and tools (e.g., that of [4] ), to generate executable test cases.. One problem with our approach is that LP packages like lp solve suffer from rounding errors when dealing with real numbers. This is not too serious, since in many cases, there is not much numerical computation, and the constraints are either unsatisfiable or easily satisfiable. The main drawback of our approach is the complexity of the underlying algorithms. We do not expect that it works on large programs. However, bad theoretical results do not necessarily imply that a particular problem instance cannot be solved quickly. Moreover, the performance of computer hardware has been improved rapidly. In the future, we will make improvements to the search algorithm and find better ways to deal with arrays. We also plan to study other data types such as pointers and character strings. We believe that our tools are useful in the evaluation of algorithms and in the unit testing phase of software development. There has been a large amount of work on test data generation, some of which use constraint-based techniques. For example, a set of tools for test data generation, called Godzilla, was described in [8] . It includes a path analyzer, a constraint generator and a constraint satisfier. Godzilla keeps all constraints in the Disjunctive Normal Form (DNF). The constraint solving method used in Godzilla is incomplete. It may not be able to find a solution even when the constraints are satisfiable. Similarly, optimization methods like simulated annealing [17] and genetic algorithms [19] have been used to generate test data. They are automatic, and effective in many cases. But they cannot be used to prove that a path is infeasible.. Some heuristic rules for identifying infeasible constraints are given in [20] . Most of the rules are very simple. An example is the following:. For any two constants k 1 and k 2 , if (k 1 > k 2 ), then the two constraints (x > k 1 ) and (x < k 2 ) conflict.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Informational analysis: a Shannon theoretic approach to measure the performance of a diagnostic test mammography are higher (0.201 and 0.229, respectively), but IR corresponds to a cutoff with higher sensitivity but lower specificity, thus suggesting that larger information provided by digital mammography carries the risk of more false-positive cases. Standard analysis of accuracy, for a dichotomous diagnostic test, is currently based on the calculation of sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV), as well as SE-and SP-derived measures, such as likelihood ratios [10, 24] . Even though there may be preference for either specificity or sensitivity (in which case a single measure would hide the required detailed information about different aspects of accuracy), nevertheless a single statistical measure, that can summarize the global quality of a dichotomous diagnostic test, is of interest in many clinical situations and is still lacking [18] . In the case of continuous test results, standard analysis includes receiver operating characteristic (ROC) curve analysis as the most popular method to assess a test or to compare it with a different one [4, 8, 15, 16] . Different summary measures have been proposed to describe the accuracy with a single, objective index, e.g., the area under the curve (AUC) provided by ROC analysis, and each of them shows well-known advantages and drawbacks [3, 24] . Another important problem is which decision cutoff should be used to classify continuous test results, and how the choice of a decision threshold affects comparisons between Abstract Diagnostic test accuracy, based on sensitivity, specificity, positive/negative predictive values (dichotomous case), and on ROC analysis (continuous case), should be expressed with a single, coherent index. We propose to modelize the diagnostic test as a flow of information between the disease, that is, a hidden state of the patient, and the physicians. We assume that (1) sensitivity, specificity, and false-positive/false-negative rates are the probabilities of a binary asymmetric channel; (2) the diagnostic channel information is measured by mutual information. We introduce two summary measures of accuracy, namely the information ratio (IR) for the dichotomous case, and the global information ratio (GIR) for the continuous case. We apply our model to a study by Pisano et al. (N Engl J Med 353 (17) : [1773] [1774] [1775] [1776] [1777] [1778] [1779] [1780] [1781] [1782] [1783] 2005) , who compared digital versus film mammography, in diagnosing breast cancer in a screening population of 42,760 women. In film mammography, the maximum IR (0.178) corresponds to the standard cutoff of sensitivity and specificity provided by the ROC analysis (GIR 0.200). Maximum IR and GIR for digital two diagnostic tests or between two raters [15] . Even these are critical questions when computing sensitivity and specificity, yet the choice for the decision threshold is often arbitrary [15] .. Regardless of the method chosen for the summary measure or for the cutoff, standard analysis is based on the comparison between a standard of reference (SR) and test results, that is, on probabilities that a test result really represents the presence or absence of a certain medical condition. Even assuming that SR always provides a correct representation of the patient status, which is not the case [24] , standard analysis does not rigorously objectify which is the maximum information on the disease we can achieve depending on that specific test. One might argue this is a potential limitation, since it might be difficult to understand (1) whether a disappointing test performance has been conditioned by definite characteristics of a clinical setting (low prevalence, selection bias, and so on) or rather by intrinsic limits on the amount of diagnostic information the test can "physically" vehicle; (2) whether, for a certain clinical scenario, it could be convenient to improve further an already good test performance, or not. Furthermore, one might expect that quantifying information underlying test results might complement the standard dichotomous or ROC analysis.. To our knowledge, no definite methods to measure test accuracy in informational terms are currently available. We hypothesize that Information Theory [21] is the proper framework to define such a method, since it is the mathematical apparatus underlying current telecommunication systems, based on a rigorous, quantifiable notion of information and information-derived measures [23] . As detailed below, we show that a diagnostic test can be modeled using Information Theory, and consequently, that diagnostic test accuracy can be expressed coherently, with a single index, in the form of a summary information measure; it can be used also to select the best cutoff in the continuous case.. On this basis, the aim of this paper was manyfold: (1) to present the above model of Shannon informational analysis of diagnostic accuracy; (2) to illustrate how informational analysis can be considered as a useful complement to standard ROC analysis, (3) to show that informational analysis is able to overtake some weakness of the ROC/AUC approach, and (4) to illustrate the applicability of the informational model using a dataset from the medical literature. We proposed a conceptual framework based on Information Theory, in which (1) the diagnostic test is equivalent to an asymmetric binary transmission channel; (2) the diagnostic process can be modeled using MI, which is a well-established measurement of the information exchanged through the channel between a transmission source (assumed to be represented by the disease) and a receiver (assumed to be represented by the physician). On this basis, the accuracy of a diagnostic test can be expressed, in informational terms, through two summary measures, namely the IR and GIR, which apply to tests providing dichotomous and continuous results, respectively. Potential advantages of using informational indexes are related to the independency from pretest probability and the capability to refine conventional analysis of accuracy (e.g., ROC analysis) by assessing the type and limits of diagnostic information that a certain test can vehicle, that is, by objectifying how much diagnostic information of a certain type (e.g., breast cancer) is transmitted given test properties (e.g., being a film or digital image obtained using X-rays). Using data from a previous study, we showed that informational analysis is applicable to a real clinical scenario and can represent an informational counterpart of standard analysis of accuracy based on ROC curves. of any good diagnostic system. Since we have only one coherent measure of information (remember the unicity theorem of Khinchin [12] ), this method is the only "objective" one in the case we assign the same cost to FP and FN.. Fallacy of the undistributed middle ROC curves, even if widely used, have at least one significant pitfall, that is, the so-called fallacy of the undistributed middle [8] : all random models score an AUC of 0.5, but not every model that scores an AUC of 0.5 is random; in other words, AUC = 0.5 does not necessarily imply that the classifier is no better than random guessing. An interesting example of this situation is given in figure 4a of [3] , where the "two-threshold classifier" assumes that a certain quantity q, being below a threshold t 1 or exceeding a threshold t 2 > t 1 , indicates disease, while q ∈ [t 1 , t 2 ] means normal. Systolic blood pressure or expression of a gene could be an example of such a situation. If we use ROC analysis, the AUC equals 0.5 (figure 4b of [3] ), and so the AUC approach is not able to discriminate this good classifier from a random one. On the contrary, if one uses the IRC approach, one can clearly discriminate this classifier, characterized by GIR = 0.342, from the random one (GIR = 0).. IRC analysis gives us a global evaluation of the diagnostic test performance (GIR) and a choice for the best threshold of specificity. As a consequence, it could be considered, at least in principle, as a competitor of ROC curves. Unfortunately, up to this moment, the IRC tool is not yet complete, since it lacks a strategy to fit properly the empiric GIR curve and a statistical rule to compare different GIRs, that is, to attest whether different values of GIRs are statistically significant.. Nevertheless, we can appreciate the fact that IRC analysis is able to strengthen ROC analysis, taking it to a deeper level. We suggest here two issues in this perspective:. Informational chart The iso-informational curves of Fig. 4 that are drawn on the ROC plane could be used as a sort of graph paper (informational chart) over which one can draw a ROC curve; this allows to directly visualize the information associated with each point of the ROC curve, integrating the ROC and the IRC approaches together.. The worst ROC curves are good Always from Fig. 4 , we can note that each iso-level curve of the upper left side of the diagram has a same-level correspondence in the lower right side of the same diagram. Even if this is not usual in clinical practice, this means that, in an informational sense, a bad diagnostic test, whose ROC curve stands entirely below the diagonal, performs as a good one, whose ROC curve stands entirely above the diagonal. This is not surprising, since the complement of a systematically incorrect test result is systematically correct. This would suggest that a more correct measure of the diagnostic test performance using the ROC approach, with a ROC curve entirely standing above or below the diagonal, should be the AUC * between the ROC curve and the diagonal, that is, AUC * = |AUC − 0.5|. The American mathematician and engineer C. Shannon (1916 Shannon ( -2001 built the foundations of Information Theory in 1948 [21] ; it formalizes the mathematical rules underlying telecommunications and defines the general properties that communications systems should have in order to transmit information reliably and affordably [23] . Since the theory provides objective measures of information, it is a pillar in telecommunication technologies and has been used to model a variety of phenomena in different fields, including physics [11] , neuroscience [22] , molecular biology [7] , and others.. We propose an information theoretic model in which SE, SP, FPR, and FNR are interpreted as the probabilities of correct and incorrect signal transmission through an asymmetric binary diagnostic channel; here, a certain quantity of average information (namely, the Mutual Information) flows from the "hidden" status of the disease to the reader, e.g., a radiologist interpreting mammograms. The higher the MI, the higher the diagnostic information available to the physician interpreting the test. Not surprisingly, this measure has already been hypothesized as a possible tool to compare different classifiers [13] . However, the use of Information Theory-derived indexes is quite limited in the medical statistics literature; an example is given by the Akaike information criterion [20] , based on entropy, which is a measure of the relative quality of a statistical model for a given set of data; nevertheless, it is not useful to assess the information associated with a diagnostic test [6] .. In our model, IRC analysis provides two different informational measures of test accuracy, namely the IR and the GIR. IR expresses, within the interval 0 . . . 1, how much information on the disease a dichotomous test carries on compared to the SR, that is, compared to the ideal channel operating without the "noise" associated with incorrect diagnoses. Of note, IR results from a MI-Curve representing the MI values at all possible pretest probabilities of disease. Consequently, this measure is not only independent from this probability in a given clinical experiment, but also shows the additional advantage of expressing the maximum information for all clinical scenarios at one time (e.g., screening or high-pretest probability populations). The typical MI-Curve behavior of Fig. 3 derives from a mathematical structure of the corresponding formula, which is similar to that of the binary entropy (13) [5] ; so the curve tends to zero when the prevalence approaches 0 or 1, as it should be from the intuitive point of view: a diagnostic test applied to a population where all the members are ill (or healthy) carries no information. On the contrary, the maximum amount of diagnostic information is associated with the situation where the prevalence is close to 1/2.. Even though there may be preference for either specificity or sensitivity, due to the kind of diagnostic test (screening or not) or to the costs for FPs and FNs, nevertheless a single statistical measure that can summarize the global quality of a dichotomous diagnostic test is still lacking [18] (p. 340). IR gives such a measure. While the IR is applicable to tests providing a dichotomous result, the GIR applies to tests yielding continuous values (e.g., prostate PSA) or ordered categories (e.g., 7-point scale in breast imaging), corresponding to multiple cutoffs of specificity. Indeed, the GIR is the ratio between the areas under the IRC of the test and the LIC, i.e., the reference curve representing the maximum amount of information we can gain by varying 1 − SP on the abscissa when SE is fixed to 100 %. In this setting, the GIR plays the role of an informational summary measure [16] that expresses the accuracy by using a single number and facilitates the comparison between diagnostic tests. ROC analysis, which is the state-of-the-art method for describing the diagnostic accuracy of a test, is universally used and shows well-known advantages [4, 8, 15] . Which are the potential, additional benefits of using the informational analysis? In the "Appendix," we briefly summarize some technical points and show how it is possible to overcome some weakness of the classical ROC/AUC approach.. On this basis, we believe that, as usual for a newborn instrument, both theoretical refinements and concrete Table 1 IR values calculated on data extracted from Table 3 of the study [19] Highest IRs are highlighted in bold. Asterisks indicate the values of SE/1 − SP 7-points scale threshold used in the ROC analysis of the original study clinical applications will probably clarify in which scenarios our method can support or even outperform ROC analysis; however, whether this potential is realizable will be assessed by clinicians. At present, we suggest the use of IRC analysis as a complement to strengthen ROC analysis results with a formally consistent and independent method. Why? In IRC analysis, accuracy is calculated directly from the amount of information flowing through a diagnostic channel, which in turn depends on the channel properties.. In standard analysis, information related to test properties can be inferred only indirectly: we suppose something on diagnostic information based on the count of the expected outcomes, but we do not have a direct access inside the "black box" of the test, in particular to quantify the information made available by the test to obtain the sensitivity and specificity measured by ROC analysis under certain clinical conditions. Informational indexes do provide such a quantification. Three potential consequences may occur in this respect. The first one is exemplified by the coincidence between highest IR and the cutoff of 1 − SP/SE of ROC analysis we observed for FM in the paper of Pisano et al. [19] . In this situation, best-coupled sensitivity/specificity corresponds to the maximum information provided by the test, i.e., IRC analysis shows the upper limit of test capabilities. One might assume that if they correspond to suboptimal test accuracy, no further improvement is permitted unless changing the diagnostic channel (e.g., by incorporating a technological development such as DM) or supplying it with additional diagnostic tools (change in diagnostic workup). The second scenario also emerges from our clinical example [19] : the IR cutoff for DM "moved" to the right of the ROC analysis cutoff, leading to an increase in SE (49 cancers) at the expense of a significant increase in FPs (2175 cases). Our explanation for this finding is that higher information provided by DM translated in better visibility of subtler anatomical details mimicking malignancy (e.g., spiculated margins or microcalcifications) that might have acted as confounders, thus increasing sensitivity and decreasing specificity. In a third, theoretical scenario, the IR cutoff moves "to the left" of the ROC analysis cutoff, suggesting that information provided by a certain test tends to decrease sensitivity and increase specificity. This might occur, e.g., if the higher information carried by this test is used to enlighten the signs that tend to exclude the disease. The last two scenarios suggest that, regardless of a rigorous quantification of information, the comparison between ROC analysis and IRC analysis has the potential to indicate the "direction" (sensitivity or specificity) toward which information associated with a new technology moves when interacting with the reader. Again, one can suppose that such a knowledge is of help in refining diagnostic tools (e.g., by guiding the technological upgrade) and/or diagnostic strategies. Whether this is clinically acceptable/relevant or not depends on the specific setting, the type of diagnostic test, and the decision rules used to establish the proper cutoff. We hypothesize that such a capability is of potential relevance at least for all those tests providing the diagnosis with inherently different technologies, i.e., channels with different informational properties. The IRC analysis suffers, however, some limitations. First, similarly to ROC analysis [15] , our method is based on the weak assumption that, when human readers Table 1 derived from [19] . a Film mammography: the threshold corresponds to the point associated with the maximum information. b Digital mammography: the threshold does not correspond to the point associated with the maximum information participate into the diagnostic process (as occurs for radiologists), they always interpret information provided by the test correctly, so that FN and FP cases depend on the test only. In other words, IRC analysis, in its present form, probably overestimates diagnostic accuracy and does not account for intra-and inter-reader variability. How to overcome these limitations? We suggest that informational indexes might be obtained for each of the readers of a "multireader factorial" study design, which is currently recommended for conventional analysis of accuracy [17] . In this multireader/multicase model, the same patients undergo all of the diagnostic tests under study, and an adequate number of readers interpret the results from all the diagnostic tests. One can assume that the comparison of IR or GIR values measured on the same clinical setting is per se indicative of reader-related variability. On the other hand, similarly to conventional analysis, IRC analysis might be complemented by calculation from raw data of classical indexes of intra-and/or inter-rater agreement for different number of raters and types of variable, such as Cohen's kappa or intraclass correlation coefficient (ICC). Lines of future improvement of IRC analysis include the development of methods (1) to adjust α and β errors of the transition matrix for reader-related variability; (2) to adjust for variability in the specific setting of multireader/multicase approach, possibly in accordance with the "random effects" model, that is, by treating the variation in readers performance as an independent source of variability [17] . Second, our model does not yet include (1) a strategy to fit properly the empiric GIR curve; and (2) the statistical rules to compare different GIRs, that is, to attest whether different values of GIRs are statistically significant. On the other hand, both points (1) and (2) constitute by themselves an entire field of research [15] , as it happened at the very beginning for ROC analysis. We believe all the above points can be faced confidently in future works, and their current lack does not influence qualitatively our results. Maximum IR for film mammography is found in the point corresponding to the main threshold used in original ROC analysis (column 4). On the contrary, maximum IR for DM corresponds to a higher cutoff compared to that used with ROC analysis (column 3), with an increase in SE (49 cancers) and in FPs (2175 cases).

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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O 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EAR: An Energy and Activity-Aware Routing Protocol for Wireless Sensor Networks in Smart Environments Sensor network, unlike traditional communication network, is deeply embedded in physical environments and its operation is mainly driven by the event activities in the environment. In long-term operations, the event activities usually show certain patterns which can be learned and exploited to optimize network design. However, this has been underexplored in the literature. One work related to this is using AT P G for radio duty cycling ([1]). In this paper we present a novel Energy and Activity aware Routing (EAR) protocol for sensor networks. As a case study, we have evaluated EAR with the data trace of real Smart Environments. In EAR an Activity Transition Probability Graph (AT P G) is learned and built from the event activity patterns. EAR is an online routing protocol, which chooses the next-hop relay node by utilizing: activity pattern information in the AT P G graph and a novel index of energy balance in the network. EAR extends network lifetime by maintaining an energy balance across the nodes in the network, while meeting application performance with desired throughput and low data delivery latency. We theoretically prove that: (a) the network throughput with EAR achieves a competitive ratio (i.e., the ratio of the performance of any offline algorithm that has knowledge of all past and future packet arrivals to the performance of our online algorithm) which is asymptotically optimal, and (b) EAR achieves a lower bound in network lifetime. Extensive experimental results from: (a) 82 node Motelab sensor network testbed [2] and (b) varying size network (20-100) in sensor network simulator TOSSIM, validate that EAR outperforms the existing methods both in terms of network performance (network lifetime, network energy consumption) and application performance (low latency, desired throughput) for an energy-constrained sensor network. Unlike traditional communication networks, sensor networks are deeply embedded in physical environments to provide high degree of visibility into environmental physical processes. Its data generation operation is mainly driven by the physical event activities in the environments. Here, by activity we mean the events those are sensed and reported by the sensor nodes to base station (sink) node. For example, in a smart home environment, the detected motion events of the residents constitute activities. Figure 1 shows the event activities detected and reported by a node (in a 30 node smart workplace sensor network deployed across a floor) with motion sensor and corresponding node energy consumption. Through observation, it is clear that node energy consumption (thus node operations) is strongly correlated to the event activities.. In long-term operations, these activities usually show certain periodic patterns (e.g. Figure 2 ), which can be learned and exploited to optimize network design. However, this has been underexplored in the literature. In this paper we present a novel Energy and Activity aware online Routing (EAR) protocol for sensor networks. EAR can adapt its network operations based on learned activity FIGURE 1. Event activity detected and reported by node with motion sensor in smart workplace, and corresponding energy consumption pattern of sensor node patterns and an index of balance in node remaining energy in the network. Unlike traditional networks, the operation of sensor networks is driven by activities in the embedded environment. These activities show certain patterns in long-term operation. But the existing sensor network design seldom learns and exploits the activity patterns to optimize network operations. In this paper we have proposed EAR for activity-aware and energy-balanced routing. As a case study EAR is evaluated with Smart Environment data trace. The experimental results have demonstrated its efficiency both with respect to application and network performance, as well as its scalability. The possible future work includes adaptive joint radio scheduling and routing, with delay control. To best of our knowledge, activity-aware routing is almost an unexplored area in the literature. Some relevant works on energy-balanced or lifetimemaximized routing design issues include [5] , [6] , [7] . The work in [5] has formulated the lifetime maximization problem as a linear program and has solved it using distributed heuristics technique. But this work assumes that the message generation rate at nodes are fixed and known. In [6] the observation has been made that the linear program is equivalent to that of a maximum concurrent flow problem. The algorithms proposed in [5] and [6] are able to determine how the traffic (generated at a constant rate) should be split among the different routes in order to maximize the network lifetime. Since the traffic generation rates are assumed to be constant and known in these works, the network can solve the energy aware routing problem off-line. The work in [8] converts the maximum network lifetime problem into a utility-based nonlinear optimization problem and proposes a distributed routing algorithm to solve the problem. But this work also assumes that the data generation rate at each node is fixed and known in advance. But sensor networks are majorly driven by activities. Therefore the data generation rates at nodes are usually non-uniform and not known exactly in advance. Our proposed protocol EAR uses this more realistic view.. For many practical applications (for example smart environment activity detection sensor networks) the message generation rate at different nodes are nonuniform and also dynamic.. Therefore there is no complete advance knowledge of future message generation process. This problem needs to be solved with online routing protocol which does not need to know the message generation rates. Our proposed EAR is an online routing protocol. An online routing algorithm max-min zP min is proposed in [7] for network lifetime maximization and it provides a competitive analysis. CM AX [9] proposes an algorithm that tries to maximize the network capacity using shortest path computation with routing metric based on node remaining energy. The work in [10] proposes E −W M E online routing algorithm for the scenario of energy harvesting sensor nodes. Most of these energy aware online routing algorithms are based on remaining energy of relaying nodes. Unlike our proposed online routing protocol EAR, these works don't try to maintain energy balance in the network as a whole, and don't learn from activity patterns. In this paper we have considered the issue of energy balance across the network. An energy-welfare index (using Atkinson Inequality Index) is utilized in [11] to keep energy balance in network. But the forwarder selection procedure is complex and expensive (computing the index for each forwarder for each packet). Also there is no theoretical analysis of its proposed routing. The energy balance index in EAR is localized and simple to compute. We have also provided theoretical performance analysis of EAR. Also to note that, for the goal of maximizing network lifetime one possible solution may be to route the messages along the path with the maximal minimal fraction of remaining energy (the max-min routing). The performance of max-min path can degrade in situations (as described with some example in [7] ). Another issue with the maxmin routing is that following route with max-min energy node may be expensive compared to other possible paths. For large number of data streams there can be significant energy consumption for common nodes on max-min routing paths. This creates bottleneck nodes with high energy consumption and thus degrades the network lifetime quickly.. There are some works on activity-aware or contextaware networking. The work of ActSee ( [1] ) proposes an activity-aware radio duty cycling protocol that utilizes the learned event activity pattern information to intelligently adjust radio duty cycles in wireless residual energy of node i before routing message k s k , d k , l k Source, destination and size of message k cij energy required by node i to send unit size data to j ptr(x, y) probability of activity transition from node x to y ttr(x, y) predicted activity transition delay from node x to y CL(i) activity cluster of node i sensor networks. The work in [12] presents a proactive communication algorithm for context aware sensor network. A framework for integrated unicast and multicast routing in context-aware ordered meshes is presented in [13] . But utilizing activity awareness for energy efficient and resource optimizing networking is not explored in these works, while EAR attempts these issues in depth.

O O O O B B O O B I I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Access control and key management for mobile agents Security is a fundamental precondition for the acceptance of mobile agent systems. In this paper we present a mobile agent structure which supports authentication, security management and access control for mobile agents. Above we presented a flexible and extensible structure for the representation of mobile agents which supports hierarchical access control, and proposed an initial interpretation of this structure with respect to the roles in a general mobile agent model. The structure maps well on existing and widely distributed technology. Furthermore the interpretation is an initial step to define a security policy for mobile agents and agent servers as well; it also facilitates security management and the implementation of security services for both while supporting basic agent tasks and operations -the management of data.. The structure as well as the interpretation should undergo a refinement process while being explored within a security centered mobile agent framework. Complemented by a discussion of advisable and suitable extensions and modifications, the results should probably be input to a standardization process with the intention to establish a portable and interoperable agent structure which is acceptable to all major agent facilities.

B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


LOCALIZED STRUCTURES IN NONEQUILIBRIUM SYSTEMS We study numerically a prototype equation which arises generically as an envelope equation for a weakly inverted bifurcation associated to traveling waves: The complex quintic Ginzburg-Landau equation. We show six different stable localized structures including stationary pulses, moving pulses, stationary holes and moving holes, starting from localized initial conditions with periodic and Neumann boundary conditions. In the last decade experimental evidence of localized structures in dissipative systems far from equilibrium has been reported. In a quasi one-dimensional system, an annulus filled with a mixture of ethanol and water and heated from below, localized structures of convection surrounded by non-convecting fluid has been studied. 1 More recently, the formation of clusters of localized structures via the self-completion scenario in a quasi two-dimensional gas discharge system, 2 and the interaction of dissipative localized structures in an optical pattern-forming system have been observed. 3 Experiments on vertically vibrated granular layers in evacuated containers reveal a variety of patterns including particle-like localized excitations (oscillons). 4 In chemical systems, catalytic oxidation of CO on Pt(110) exhibits oscillatory kinetics giving rise to solitary waves, 5 and experiments on a ferrocyanide-iodate-sulfite reaction diffusion system show spot patterns that undergo a continuous process of growth through replication and death through overcrowding.. The wide range of qualitatively different localized structures cannot be understood with a single mechanism. Coexistence between two stable states (not necessarily homogeneous 7 ) or excitability are common features of the dynamics of nonequilibrium media that facilitates the formation of localized patterns.. Reaction-diffusion models have been successfully showing a rich variety of behaviors, such as self-replication, 8, 9 elastic behavior upon collision, 10,11 or soliton behavior. 12 Localized solutions have been observed in monostable and bistable systems with two stable fixed points and one unstable fixed point 13 or one stable fixed point, a stable limit cycle and an unstable limit cycle. We studied the quintic complex Ginzburg-Landau equation numerically, with only one non-variational parameter. We have shown that this prototype equation, with periodic boundary conditions, admits six different stable localized structures: Stationary pulses, moving pulses, three kinds of stationary holes, and moving holes. So far, the existence (and even coexistence) of stationary pulses, stationary 2π-holes and π-holes of the first kind was known only for a simple reaction-diffusion model. 24 We obtained two different sequences of localized solutions starting from the different classes of localized initial conditions, namely, initial conditions in phase and initial conditions in antiphase. Finally we addressed the question whether a change in the boundary conditions (from periodic to Neumann) leads to qualitative changes in the localized solutions created with periodic boundary conditions.

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A STABLE DIRECT SOLUTION OF PERSPECTIVE-THREE-POINT PROBLEM The perspective-three-point problem (P3P) is a classical problem in computer vision. The existing direct solutions of P3P have at least 3 limitations: (1) the numerical instability when using different vertex permutations, (2) the degeneration in the geometric singularity case, and (3) the dependence on particular equation solvers. A new direct solution of P3P is presented to deal with these limitations. The main idea is to reduce the number of unknown parameter by using a geometric constraint we called "perspective similar triangle" (PST). The PST method achieves high stability in the permutation problem and in presence of image noise, and does not rely on particular equation solvers. Furthermore, reliable results can be retrieved even in "danger cylinder", a typical kind of geometric singularity of P3P, where all existing direct solutions degenerate significantly. The term "perspective-three-point problem" (P3P) is coined by Fischler and Bolles 1 for the problem of determining the pose of a calibrated camera from 3 correspondences between 3D target points and their 2D projections. The P3P problem has a long history since 1841 2 and has many applications in computer vision 3,4,5 , photogrammetry 6, 7 , robotics 8, 9 , etc. P3P attracts many researchers, because it is the smallest subset of perspective-npoint problem (PnP) 5, 4 and yields multiple solutions 10, 11 . Haralick et al. 3 reviewed many old and new variants of the basic three-point methods and carefully examined their numerical stability. Gao et al. 10 obtained a complete solution classification using Wu-Ritt's zero decomposition method. DeMenthon and Davis 12 showed that the camera pose can be estimated efficiently by using approximations of the perspective. The direct solution of P3P has a long history since 1841 but it still remains some important limitations, which are permutation problem, singularity problem, and the dependence on particular equation solvers. Our work can be seen as an useful supplement to this classic subject because the above limitations are overcome by using PST geometrical constraint. The PST method is stable in the permutation problem, and it does not rely on particular equation solvers. Robust results can be retrieved by PST in presence of noise. To the best of our know, there is no existing direct solution can retrieve stable result in geometric singularity case until our approach came out. The experimental results show that reliable results can be retrieved in "danger cylinder" which is a typical kind of geometric singularity.

O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I