A probabilistic approach to quantum Bayesian games of incomplete information A Bayesian game is a game of incomplete information in which the rules of the game are not fully known to all players. We consider the Bayesian game of Battle of Sexes that has several Bayesian Nash equilibria and investigate its outcome when the underlying probability set is obtained from generalized Einstein-Podolsky-Rosen experiments. We find that this probability set, which may become non-factorizable, results in a unique Bayesian Nash equilibrium of the game. The standard approach to constructing quantum games naturally uses the formalism of quantum mechanics in Hilbert space [57] . In recent years, however, a probabilistic approach to this research area [27, 38, [47] [48] [49] [51] [52] [53] has been proposed that uses sets of non-factorizable quantum mechanical probabilities, i.e. without using the quantum mechanical concepts of state vectors, self-adjoint operators, and quantum measurement etc. This is with a view of making the area of quantum games more accessible to wider mathematical application, as the methods and range of solution concepts of game theory [58] [59] [60] [61] are used and exploited, without any real need for invoking the Hilbert space formalism of quantum mechanics.. The probabilistic approach for a two-player two-strategy game directly uses sets of quantum probabilities corresponding to the measurement outcomes on a two qubit quantum system. As is known, the setting of generalized Einstein-Podolsky-Rosen (EPR) experiments [62] [63] [64] [65] [66] [67] [68] [69] [70] performed on this system leads to the consideration of a set of 16 quantum probabilities. Properties of this probability set have been investigated by Cereceda [70] and it has been pointed out that the CHSH form of Bell's inequality [69] can be re-expressed in terms of constraints on the elements from this set. It is observed that only a non-factorizable probability set, as is defined later, can lead to the violation of Bell's inequality and that not every non-factorizable probability set violates Bell's inequality.. A Bayesian game is a game of incomplete information in which the rules of the game are not fully known to all players. In this paper, we study a Bayesian game that is a variant of the well known Battle of Sexes game, also studied [11, 35] in the quantum game literature. In an earlier study [35] , using the quantization protocol based on Schmidt decomposition [57] , a Bayesian game of incomplete information [61] has been investigated in relation to the violation of Bell's inequality [57, [64] [65] [66] [67] . The present paper, however, adopts a different approach in that, without referring to the Hilbert space formalism, it finds the outcome of a Bayesian game when the considered probability set can be non-factorizable-this can arise, in an experimental situation, from a set up involving quantum entanglement, such as an EPR-type experiment, where the CHSH form of Bell's inequality is violated.. In its normal form representation, the game matrix of the Bayesian game has the same number of entries as the 16 elements ε i in the probability set that corresponds to the generalized EPR experiments [70] . We find that the richer structure of the Bayesian game permits a natural embedding of the classical factorizable game within the quantum game. We show that, whereas the classical factorizable Bayesian game of imperfect information has several Nash equilibria, its non-factorizable quantum version obtained from a set of quantum probabilities corresponding to generalized EPR experiments has a unique Nash equilibrium.. The suggested probabilistic approach to obtaining quantum games thus re-expresses players' payoff relations in terms of a set of probabilities that can also arise in a quantum mechanical experiment. As the approach is based on probabilities only, it does not refer to the formalism of quantum mechanics using state vectors, unitary transformations, and quantum measurements etc. As game theory is a broad area, with applications ranging from trade, politics, sociology, biology, engineering etc., most researchers in this area are naturally not familiar with the mathematical formalism of quantum mechanics. This paper thus fills in that gap and demonstrates how an unusual game-theoretic outcome for a Bayesian game results when probability sets that are obtained in quantum mechanical experiments are the underlying probabilities of a Bayesian game. In this approach, the quantum game reduces itself to the classical game when the considered probability set becomes factorizable.. The rest of this paper is organized as follows. Sections 2-3 present a review of the classical theory of a Bayesian game that is a variant of the game of Battle of Sexes. Section 4 describes quantum probabilities in generalized EPR experiments, their constraints, and how within the quantum game the players' payoff relations are defined in terms of these probabilities. Section 5 analyses the outcome of the Bayesian game of Battle of Sexes with EPR probabilities and Section 6 discusses the results. As is well known, Bell's inequality presents stark difference between the classical and quantum world. The CHSH form of Bell's inequality can be expressed as a constraint on probabilities without referring to the formalism and mathematical machinery of quantum mechanics. Game theory is based on the theory of probability and this suggests that the quantum contents of quantum games can be given an expression that only employ probabilities without referring to the formalism of quantum mechanics. A probabilistic approach to quantum games is only a matter of perspective as the quantum Bayesian game discussed in this paper can be physically implemented using EPR type experiments that result in non-factorizable probabilities. Essentially, this paper discusses a physical implementation of a quantum Bayesian game using EPR experiments. We find that these experiments provide a natural setting for analyzing a quantum Bayesian game. Our analysis uses only probabilities as they facilitate wider access to the area of quantum games. The physical realization of our game is provided by actual EPR experiments where quantum mechanics makes the difference and which can also be expressed in terms of probabilities only.. We study the game of Battle of Sexes with incomplete information that has both pure and mixed Bayesian Nash equilibria. We investigate the situation when the underlying probabilities of this game can become non-factorizable. As is known, the probabilities in generalized EPR experiments can become non-factorizable and in certain cases can maximally violate the corresponding CHSH version of Bell's inequality. When the quantum mechanical probabilities are factorizable the game attains a classical interpretation. However, when the probabilities are allowed to become non-factorizable, we find that the solution of the game turns out to be entirely different and, in contrast to the classical game that has both pure and mixed Bayesian Nash equilibria, the quantum game has a unique Bayesian Nash equilibrium.. A natural question to ask here is whether any set of probabilities that satisfies the constraints (18, 19) is physically realizable? Quantum mechanics is known to impose further constraints and one such constraint is given by the CHSH version of Bell's inequality [57, 69, 70] . This constraint states that the quantity ∆ defined by ∆ = 2(ε 1 + ε 4 + ε 5 + ε 8 + ε 9 + ε 12 + ε 14 + ε 15 − 2). is restricted in the range |∆ QM | ≤ 2 √ 2 by the laws of quantum mechanics and the CHSH version of Bell's inequality is violated in quantum mechanical experiments when 2 < |∆|. These constraints are imposed by physical realizations and a maximum value of ∆ = 4 emerges when only nonnegative probabilities are considered. It is known that this value is not physically realizable.. Our analysis for a Bayesian game of Battle of Sexes shows that when the underlying probabilities are obtained from generalized EPR experiments, and thus can be non-factorizable, a unique Bayesian Nash equilibrium of the game emerges. This equilibrium corresponds to ε * 2 = ε * 6 = ε * 10 = ε * 14 = 1 with the remaining ε * j being zeros. Substituting these values in Eq. (32) gives ∆ = −2 i.e. the unique Bayesian Nash equilibrium is obtained without violating the CHSH version of Bell's inequality.. A particularly interesting situation would be when the violation of CHSH version of Bell's inequality leads to a new outcome of the game. Quantum mechanics is known to put its own constraints on the allowed ranges of the variables (ε 1 + ε 2 + ε 5 + ε 6 ), (ε 9 + ε 10 + ε 13 + ε 14 ), (ε 1 + ε 3 + ε 9 + ε 11 ), and (ε 5 + ε 7 + ε 13 + ε 15 ), as described in Eqs. (23) , and they are different from those imposed by just not permitting probabilities to have negative values. An important question would then be to ask whether this would change or affect the outcome of the game. A consideration of Eqs. (29, 30) shows that the conditions yielding the Bayesian Nash equilibrium are simply too strong to be affected by extra constraints that quantum mechanics can impose on the allowed ranges of the variables (ε 1 + ε 2 + ε 5 + ε 6 ), (ε 9 + ε 10 + ε 13 + ε 14 ), (ε 1 + ε 3 + ε 9 + ε 11 ), and (ε 5 + ε 7 + ε 13 + ε 15 ). However, it is possible that for other Bayesian games the conditions giving the outcome are not so strong and it then would be worthwhile to investigate this question further.

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


Fault monitoring and fault recovery control for position-moored vessels This paper addresses fault-tolerant control for position mooring of a shuttle or floating production storage and offloading vessels. A complete framework for fault diagnosis is presented. A loss of a sub-sea mooring line buoyancy element and line breakage are given particular attention, since such failures might cause high-risk abortion of an oil-loading operation. With significant drift forces from waves, non-Gaussian elements dominate forces and the residuals designed for fault diagnosis. Hypothesis testing is designed using dedicated change detection for the type of distribution encountered. A new position recovery algorithm is proposed as a means of fault accommodation in order to keep the mooring system in a safe state, despite faults. The position control is shown to be capable of accommodating serious failures and preventing breakage of a mooring line, or a loss of a buoyancy element, from causing subsequent failures. Properties of the detection and fault-tolerant control algorithms are demonstrated by high fidelity simulations. With oil and gas exploration going into deeper waters and harsher environments, Position-Mooring (PM) systems are encountering more challenges with regard to mechanical reliability, automatic control and associated safety aspects. For thruster-assisted position mooring, the main objective is to maintain the vessel's position within a limited region and keep the vessel on the desired heading such that the external environmental load is minimised (Strand et al., 1998; Aamo and Fossen, 2001) . In extreme weather, the main objective changes to that of ensuring that mooring lines avoid breakage Berntsen et al., 2008a) .. The safety of dynamic positioning is a prime concern in the marine industry, and regulations are made to prevent that faults in equipment cause accidents at the system level (DNV, 2008b) . In position mooring, accident consequences need be analysed for line breakage and the loss of one or more Mooring Line Buoyancy Elements (MLBEs). Such analysis has traditionally been based solely on the reliability analysis of mechanical structures, with studies of risk of fatigue damage or line breakage under extreme conditions as the essential means of analysis (Gao and Moan, 2007) .. Since thrusters are also available on the types of vessels considered, the automatic control part has been receiving increased attention for reasons of potential contributions to safety. A non-linear controller was proposed by Berntsen et al. (2006) , who formulated a structural reliability index and a controller to prevent a mooring line from getting into a zone of low reliability. A switching controller was used by Nguyen and Sørensen (2009) for thruster-assisted position mooring. Mooring line breakage was prevented by detecting a change in the environment and switching between dedicated controllers. Systematic fault-tolerant control was studied for station keeping of a marine vessel by Blanke (2005) , who validated a structure-graph approach to fault diagnosis and control reconfiguration by sea tests. extended this study to position mooring and suggested offline fault-accommodation design of a bank of controllers.. Failure of mooring line buoyancy elements was not considered in these previous studies.. The purpose of this paper is to widen fault-tolerant control design for position-mooring systems to include a loss of mooring line buoyancy elements and to enhance the fault-tolerant control strategy in the case of mooring line breakage. Investigating control-system topology by structure-graph analysis, diagnosis system design is extended to include buoyancy elements on mooring lines. Residuals are shown to be non-Gaussian, due to the nature of drift forces from waves, and a dedicated changedetection and hypothesis test is designed for the particular distributions at hand. A novel algorithm is suggested for fault accommodation that is capable of avoiding breakage of further mooring lines, even if one line is broken or a buoyancy element has been lost. Simulations illustrate how the new position algorithm prevents mooring line tension from exceeding a critical level after either of these two failures.. The remainder of this paper is organised as follows. Section 2 addresses the modelling of the position-moored vessel. Section 3 presents fault diagnosis and change detection. The optimal position algorithm in fault accommodation is presented in Section 4. The proposed algorithm is validated by simulations in Section 5, and conclusions are drawn in Section 6. Fault-tolerant control for position mooring was analysed in this paper with specific emphasis on the cases of loss of a mooring line buoyancy element and line breakage. Position-mooring control was analysed with the dynamics of mooring line buoys attached. Structural analysis was employed to get residuals to detect changes that could indicate faults in the system. A new fault-accommodating position algorithm was suggested that could prevent critical safety levels of mooring line tension from being exceeded. The proposed algorithm monitored the influence of the external environment directly from tensions of the mooring lines, and the control algorithm was able to simultaneously control the tension of more than one mooring line, even when it was close to critical levels, provided sufficient thruster forces were available.

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


Social networks and context-aware spam Social networks are popular for online communities. This paper evaluates the risk of sophisticated context-aware spam that could result from information sharing on social networks and discusses potential mitigation strategies. Unlike normal spam, context-aware spam would likely have a high click-through rate due to exploitation of authentic social connections. Context-aware spam could lead to more insidious attacks that try to install malware or steal passwords. In this paper, we analyzed Facebook, a popular social networking website. Our goal was to determine how many users were vulnerable to context-aware attack email and understand aspects of Facebook's design that make such attacks possible. We also classified different kinds of email attacks based on certain pieces of data such as birthdays, lists of friends, wall posts, and user news feeds. We analyzed Facebook starting from a single university e-mail address to calculate the number of users who would be vulnerable to each type of attack. We found that a hacker could send sophisticated context-aware email to approximately 85% of users. Furthermore, our analysis shows that people with private profiles are almost equally vulnerable to a subset of attacks. Finally, we discuss defense strategies. Some strategies would require users to coordinate their privacy policies with each other. We also suggest design improvements for social networks that may help reduce exposure to context-aware attack email. Social networks, such as Facebook, MySpace, LinkedIn, Friendster [3] , and Tickle have millions of members who use them for both social and business networking. In this paper, we analyze the extent to which the current usage of such systems also poses significant risks for its users to cleverly targeted, context-aware email spam. We then use the analysis to suggest risk mitigation strategies for both users of social networks as well their designers.. Email is one of the most common delivery mechanisms for network-based attacks such as phishing [4, 5] , computer viruses, Trojan horses, bots, worms, browser exploits, key loggers, spyware, adware, and others. MessageLabs, which scans millions of emails per day as part of its managed email security service, previously reported that on average every one in 12 emails contains malware [8] . Some studies indicate that users are increasingly comfortable with email [7] , including spam-filtering functions. Thus, the success of delivered attacks is dependent almost entirely upon the click-through rate of the email; if the target does not click on the malicious link presented in the email, then the attack usually fails.. To improve click-through rates, many techniques of varying complexity exist that mask the malicious nature of the email: hiding the destination of hyperlinks, falsifying header information, and creative use of images are a few of these methods [21, 14] . Simple social engineering techniques can also help disguise malicious emails, such as by mimicking notification emails from popular financial websites (e.g. bankofamerica.com, chase.com), or by mimicking notification emails from popular commercial websites like amazon.com and ebay.com. However, these social engineering techniques are relatively crude; they blindly send messages claiming to be from large websites to people who may or may not have accounts on those sites.. The attacks we analyze in this paper involve the use of email messages that take advantage of some shared context among friends on a social network such as birthday celebrations, living in the same home town, or participating in a common event. This shared context dramatically increase email authenticity, more easily bypassing spam filters and increasing the click-through rate for spam that contains advertisements, installs malicious software, or solicits sensitive personal information. This paper examines users' privacy policies within a large University Facebook network and looks at the extent of vulnerability to contextaware email attacks.. We analyzed over 7000 profiles on the University of Michigan Facebook network. Many social networks, including Facebook, do not, by default, make email addresses visible on public profiles. However, we found that there was sufficient information available on public profiles to look up emails in another public database for approximately 90% of the Facebook users in our dataset. We also found that almost two-thirds of users have privacy policies for their profiles that permit access to non-friends. On most publicly-accessible profiles, contextual information exists that can be used to generate contextaware attack email. Overall data from out test network indicates that a spammer could target 85% of users who have visible profiles with context-aware attack email. Perhaps somewhat surprisingly, our findings also indicate that almost an equal percentage of users with closed (private) profiles may be vulnerable to attacks.. To help mitigate the risk of context-aware spam, our findings indicate that privacy controls must be viewed from a community perspective -users must collaborate to stop attacks. We also suggest possible changes at the interface of social networking systems that would make it harder for an attacker to reconstruct the relationships in social networks that are a basis for these attacks.. The rest of the paper is organized as follows. We first discuss our methodology as well as the threat model. Next, we classify various types of context-aware email attacks. Then, we present a vulnerability analysis of users in a test university network to different types of context-aware email attacks. Next, we discuss potential defense strategies for both users and designers of social networks. Finally, we conclude. In this paper, we analyzed Facebook, a popular social network among high school and university students, for its degree of vulnerability to different kinds of context-aware attack email. Our goal was to understand aspects of Facebook's policies and usage that may make its users vulnerable to sophisticated attacks via context-aware email. We classified attacks into three types: relationship-based attacks, unshared-attribute attacks, and shared-attribute attacks. We analyzed over 7000 randomly-accessed profiles on one university social network. By combining data from public profiles at Facebook with data from publicly accessible university directory services, we estimated that close to 85% of users could be accurately targeted with sophisticated context-aware attack email. Furthermore, even users with strict privacy policies on their profiles are almost equally vulnerable. We presented a detailed analysis of the potential risks for different types of attacks. We then discussed some potential defenses, along with trade-offs, which could help to reduce the risks. Our findings indicate that systematic defenses, which require changes at Facebook, are more likely to work than individual defenses. Security companies have pointed out that social networks are likely to become a target for attackers [20] . Traditional attacks have been to corrupt data at sites so as to induce users to click on malicious links. This paper examines the possibility of email-based attacks on users of social networking sites.. Earlier studies have shown that email attacks using contextual information have a higher click-through rate than normal email attacks. For example, Jagatic et al. harvested publicly available information from Facebook and used it for email-based attacks [13] . By simply pretending to be a friend of the sender, a phishing attack email had a 72% click-through rate versus 15% for email from non-friends.. There is also evidence that email-based attacks using Outlook address books as an attack vector are very effective. For example, the study in [19] analyzed the graph of relationships implied by address books at a university system and the potential for email worms to spread via the address books. One of the findings in that study was that random vaccination of computers using antivirus software is likely to be ineffective because the outbreak drops very slowly as vertices corresponding to the users are removed from the connectivity graph. This paper builds on the above prior work. It gives insights into aspects of the design of social network systems that contribute significantly to the potential of context-aware spam. Furthermore, based on the analysis, it suggests design strategies for social networks that would help to mitigate the risks of attacks outlined in this paper. In our work, we used a five-step approach to characterizing the risk of context-aware spam and establishing countermeasures:. 1. Sample data from one popular group on a social networking site.. 2. Study the available attributes on public profiles within that social network and determine how they may be exploited to generate context-aware spam 3. Create sample attack emails to provide evidence that it would be trivial to automate the generation of contextaware spam using a database of profile information.. 4. Analyze the social network to determine the fraction of users that could be targeted by various attacks, along with characteristics in their profiles that contribute to their vulnerability.. 5. Based on the anatomy of attacks, recommend defense strategies to mitigate the risk of context-aware spam.. As in any vulnerability analysis work, we are aware that the results of this paper could incite potential spammers, especially if defenses are not deployed. However, we believe that spammers may already aware of how contextual information can improve click-through rate. It is important to quantify the risks and suggest possible solutions before this type of attack becomes widespread.

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


Fast Practical Multi-Pattern Matching The main result of the paper is the construction of a very fast multi-pattern matching algorithm, called DAWG-MATCH. The algorithm is of Boyer-Moore type. Previous algorithm of this type is the Commentz-Walter algorithm. The DAWG-MATCH algorithm behaves better than Commentz-Walter algorithm. We combine the ideas of two algorithms: the Aho-Corasick algorithm, and the Reverse Factor algorithm from Crochemore et alii. The new algorithm performs at most 2jtextj inspections of text characters, and is very fast on the average. We give some experimental evidence of its good behavior for random words, against the Commentz-Walter algorithm. The algorithm is especially simple for a single pattern: in this case the Aho-Corasick algorithm can be replaced by the strategy of the Knuth-Morris-Pratt algorithm. The basic tool in the algorithm DAWG-MATCH is the directed acyclic word graph. This graph is usually used as representation of the text to be scanned, but, in our case we use it to represent the set of reverse patterns. We consider the multiple string matching problem: nding all occurrences of a nite set P of string patterns in a text t of length n. Finding all occurrences of elements of P is a problem that appears in bibliographic search and in information retrieval. The rst algorithm to solve this problem in O(n) was the Aho-Corasick (AC algorithm, for short) AC 75], which can be viewed as a generalization of the Knuth-Morris-Pratt algorithm (KMP algorithm) KMP 77], designed for a single pattern. As for one pattern, the Boyer-Moore algorithm (BM algorithm) BM 77] has a better behavior in practice than the KMP algorithm, CommentzWalter developed an algorithm combining the ideas of AC and BM algorithms ( Co 79a,Co 79b]). A complete version can be found in Ah 90]. Later, Uratani Ur 88], and Baeza-Yates and R egnier BR 90] developed similar algorithms. In this paper, we show how to use the power of directed acyclic word graphs (DAWG's) for nding a nite set of patterns. Such graphs are used to represent all factors (subwords) of a given word. We recently presented a family of algorithms for nding one pattern using the DAWG of the reverse pattern C-R 94]. Direct extension of this algorithm to solve the multi-pattern matching problem gives an algorithm running in quadratic time in the worst case. However, the algorithm has a good behavior in practice. Combining this idea with the AC algorithm, we present a new algorithm which performs at most 2n inspections of text characters, and which is simultaneously very fast on the average. In the case of one pattern, the same technique applies. It gives a new algorithm combining the strategies of the KMP algorithm and the Reverse Factor algorithm ( Le 92,C-R 94]). This new algorithm performs at most 2n inspections of text characters, and it is more simple than the Turbo Reverse Factor algorithm presented in C-R 94]. Like the Reverse Factor type algorithms, the new algorithm is optimal on the average, with O((n log m)=m) inspections of text characters (m is the length of the pattern).

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Effects of facial similarity on user responses to embodied agents We investigated the effects of facial similarity between users and embodied agents under different experimental conditions. Sixty-four undergraduates interacted with two different embodied agents: in one case the agent was designed to look somewhat similar to the user, and in the other case the agent was designed to look dissimilar. We varied between subjects how helpful the agent was for a given task. Results showed that the facial similarity manipulation sometimes affected participants' responses, even though they did not consciously detect the similarity. Specifically, when the agent was helpful, facial similarity increased participantsi ratings of involvement. However, when exposed to unhelpful agents, male participants had negative responses to the similar-looking agent compared to the dissimilar one. These results suggest that using facially similar embodied agents has a potential large downside if that embodied agent is perceived to be unhelpful. A decade ago, Nass et al. [1998] suggested that videoconferencing systems and virtual environments would facilitate the use of the user's own face as part of the interface. These authors showed that users who interacted with their own faces took the application more seriously, trusted the computer more, believed the computer was fairer, and took more responsibility for negative feedback [Nass et al. 1998 ]. In using photographs as embodied agents in a game context, De Bruine [2002] found that participants trusted agents that were facially similar to them more than agents that were not facially similar. Facial similarity also facilitates persuasion, especially when the embodied agent also mimics the user's nonverbal gestures [Ratan and Bailenson 2007] . Al-Natour et al. [2005] confirmed that personality and behavioral similarity positively affected customers' evaluations of automated shopping assistants. Similarly, Li et al. [2007] demonstrated that participants rated that agents were more influential when the agents' faces were facially similar to their own, compared to when the faces were dissimilar.. The findings from these studies are relatively intuitive. After all, physical appearance is an accessible and salient dimension along which people judge others (e.g., [Sangrador and Yela 2000]) , and the face is considered one of the most important dimensions involved in social interactions [Sergent and Signoret 1992] . Facial characteristics may affect people at a glance. For example, people can be instantly and unconsciously affected by facial attractiveness [Langlois et al. 1991; Olson and Marshuetz 2005] . The similarity-attraction hypothesis posits that people resemblance in personality and appearance causes social influence [Byrne 1971 ]. For example, Hinsz [1989] showed participants photographs of real or randomly generated couples and asked them to rate the similarity between the faces. Actual couples showed higher facial similarities than the ad-hoc couples. Payne and Jaffe [2005] showed that in human-pet pairs sampled in pet beauty contests, a significant proportion of the partners showed higher facial resemblances than could be expected by random pair formation. Facial similarity even affects people's voting behavior during elections [Bailenson et al. 2008] .. Nevertheless, the similarity-attraction hypothesis sometimes produces mixed results. Moreno and Flowerday [2006] tested the effects on learning and affect in students by using a multimedia program with or without an animated pedagogical agent for science education. They found that same gender yielded insignificant effects, and that the same ethnicity was preferred only by students with dark skin. Only in a few cases, however, this increased the learning and affect scores.. The current hypothesis is that participants might be less uncomfortable interacting with a facially dissimilar agent if that agent is unhelpful. We isolated these effects by measuring user involvement, distance, and use intentions. While previous literature has often treated these three factors as related or even identical, we examine them as unique constructs, and demonstrate that agent features and affordances differently affect user outcomes on each of the three measurements. In the next section, we discuss social comparison theory and emphasize that in the agent domain, affordances play an important role. We develop two hypotheses on how similarity in combination with agent affordances are expected to affect user responses-in particular, involvement with, distance towards, and intentions to use the agent. These hypotheses are further developed by relating them to the two emotion variables, relevancei and valence. Our aim was to study the effects of facial similarity between agent and user under different conditions. More specifically, the agent had either aiding or obstructing affordances for the user-the agent was helpful or unhelpful. We predicted that facial similarity would cause positive effects on user responses in case of an aiding agent but negative effects in case of an obstructing agent. We also predicted that the effects of facial similarity and affordances on user responses would be indirect, via perceptions of relevance and valence. Independent variables were psychological involvement and distance (measures related to user affect) and use intentions (a measure related to user behavior).. Results demonstrated that participants were more willing to use an aiding agent than an obstructing agent. This result fits previous findings [Van Vugt et al. 2006] . For females, regardless of affordance condition self-similarity resulted in higher use intentions than self-dissimilarity (see Table II ). Male users had higher intentions to use an obstructing agent that was facially dissimilar than one that was similar. With respect to H1a, on average participants were more willing to use an aiding agent that was facially similar than one that was dissimilar. Regarding H2a, males were less willing to use an obstructing agent that was self-similar than one that was dissimilar. Thus, H1a was supported for all users and H2a for males but not for females.. Participants reported higher involvement with an aiding agent than with an obstructing agent (see Table II ), which fits previous findings [Van Vugt et al. 2006] . As a trend, H1b was confirmed in that all participants were more involved with a helpful self-similar agent than with a dissimilar agent. With obstructing agents, no significant effects occurred on involvement, rejecting H2b.. Further, participants felt less distant with an aiding agent than with an obstructing agent. This result also fits previous findings [Van Vugt et al. 2006] . No significant interaction between similarity and affordances occurred on distance, rejecting H1c and H2c.. Sobel tests indicated that no mediation effects of perceived relevance or perceived valence occurred between designed similarity on the one hand and involvement, distance, or use intentions on the other. Thus, we did not find support for hypotheses H3a and H3b. Designed similarity did not affect the dependents indirectly via perceptions of relevance and valence. Participants did not perceive the facially similar agent as more relevant to their goals nor as having higher outcome expectations than when the agent was facially dissimilar. By contrast, perceived affordances did affect use intentions, albeit indirectly, namely through perceptions of relevance and valence. Perceived affordances also indirectly affected distance towards the agent, through valence and, to a lesser extent, relevance. The effect of affordances on involvement was not mediated by perceived relevance or valence, regardless of similarity. Our hypotheses were partially supported by the data. In general, both affordances and facial similarity impacted user affect and user behavior. Facial similarity had positive effects on use intentions and to a lesser degree on involvement in case of an aiding agent, confirming the idea that similarity attracts. For females, facial similarity as compared to dissimilarity increased use intentions, even with obstructing agents. However, the similarity-attraction hypothesis was not supported by the use intentions of males. When male users were confronted with an obstructing agent that was facially similar, they were less inclined to use it again than an obstructing dissimilar agent.. In terms of specific results, first, for aiding agents, both female and male users felt more involved with an embodied agent with aiding affordances when it was facially similar to them than when it was dissimilar. However, involvement with an embodied agent with obstructing affordances was equal for facially similar and facially dissimilar agents. There was a trend that facial similarity increased involvement, but only when the agent had aiding affordances.. Thus, the facial similarity of an obstructing agent did not have any effect. Psychological distance was unaffected by facial similarity and merely depended on the agent's affordances: Aiding affordances evoked less distance than obstructing affordances. Second, facial similarity affected intentions to use the agent. When the agent had aiding affordances, users were more willing to use a self-similar agent than a dissimilar agent. For females, this was even the case when the agent was obstructing. Males did not want to use self-similar agents that were obstructing. When the agent was obstructing, males preferred to use a facially dissimilar agent. Last, the effects of affordances on user responses were mediated through perceptions of relevance and valence but the effects of facial similarity were not. In line with previous results [Van Vugt et al. 2006 , we found that perceptions of relevance and valence were affected by an agent's affordances. An aiding agent was perceived as more relevant; users expected more positive outcomes from using an aiding agent (positive valence) than from using an obstructing agent. Consequently, users felt less distant from the agent and had higher intentions to use it again. Thus, relevance and valence served as mediators in between affordances and various user responses.. Relevance and valence were not involved in effects of facial similarity on the user responses. Moreover, participants were unaware of the similarity manipulation. Ninety-one percent of the participants did not mention the facial similarity manipulation when asked about the purpose of the experiment, and explicit similarity ratings were equal among the designed similarity conditions. Thus, the facial similarity manipulation influenced participants' responses even though they did not explicitly detect it. Next, we discuss the implications of the study for designers, indicate the limitations of our work, and present ideas for future research.

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


An efficient incremental algorithm for min-area retiming As one of the most effective sequential optimization techniques, retiming is a structural transformation that relocates flip-flops in a circuit without changing its functionality. The min-area retiming problem seeks a solution with the minimum flip-flop area (or number) under a given clock period. Even though having polynomial runtime, the best existing algorithms for this problem still need to first construct a dense path graph and then find a min-cost network flow on it, thus incur huge storage and time expenses for large circuits. Recently, provable incremental algorithms have been discovered for min-period retiming, and heuristic incremental algorithms have been proposed for min-area retiming. However, given the complexity of the problem, min-area retiming is still resisting an efficient provable incremental algorithm. In this paper, we fill the gap by presenting an efficient algorithm to solve the min-area retiming problem incrementally and optimally. Contrary to existing approaches, no dense path graph is constructed; only the active timing constraints are dynamically generated in the algorithm. Experimental results show that the total runtime of our algorithm for all the benchmarks is at least 60× faster than the best existing approach. Retiming [5] is one of the most powerful sequential transformations that relocates the flip-flops (FFs) in a circuit while preserving its functionality. As relocating the FFs could balance the longest combinational paths and reduce the circuit states, the clock period and the FF area (or number) in a circuit can be reduced through retiming optimizations. As the minimum clock period (min-period) retiming minimizes the clock period, and thus might significantly increase the FF area, the minimum area (min-area) retiming minimizes the FF area under a given clock period, thus could be used to minimize the FF area even under the minimum clock period. Therefore, the min-area retiming problem is more important for sequential circuit design, but of higher complexity [10] .. All existing provable approaches to min-area retiming follow the basic ideas of Leiserson and Saxe [5] . Given a circuit represented as a graph of n vertices and m edges, the minimum number of FFs between any two vertices and the maximum delay over the paths of the minimum number of FFs are first computed. Then, besides one constraint for each edge requiring that the FF number is nonnegative, for each pair of the vertices whose computed path delay is larger than the given clock period, i.e. the timing critical path, a constraint is generated requiring that there is at least one FF between them. Minimizing the FF area under those constraints formulates a dual of the min-cost network flow problem. Since each constraint forms an arc in the flow network, the number of arcs in the network is usually Θ(n 2 ). Even though polynomially solvable, min-cost network flow computation (see [1] ) over a dense graph is usually expensive on large problems.. Shenoy et al. [10] were among the first to consider a practical implementation of the min-area retiming algorithm. They found that the storage requirement to compute the timing critical paths and the number of constraints are the bottleneck and proposed techniques to reduce memory usage and to prune some redundant constraints. Minaret, proposed by Maheshwari et al. [8] , further pruned redundant constraints to reduce the size of the flow network by exploring the equivalence of retiming and clock skew optimization as proposed in ASTRA [9] . However, even with these pruning techniques, as experimental results indicate, the flow networks could still be very dense compared to the original circuit graphs. Our experiments with Minaret showed that a circuit with more than 180K gates had to formulate and solve a min-cost network flow problem with more than 122M arcs, which used up all the 2GB virtual memory on our machine.. Recently, Zhou [13] proposed an efficient incremental algorithm for min-period retiming which iteratively moves FFs to decrease the clock period while guarantees to find the optimal solution in a short time. To overcome the expenses of existing approaches to min-area retiming, Singh et al. [11] also proposed to incrementally move FFs in the circuit. However, since they only allow moves that are better in cost and feasible in timing, their approach is a heuristic that may end up with a suboptimal solution. An efficient incremental algorithm with provably optimal solution is evasive till now.. In this paper, we fill the gap with an efficient algorithm named iMinArea that solves the min-area retiming problem incrementally and optimally. Contrary to existing algorithms, iMinArea directly attacks the FF area minimization problem instead of its dual network flow problem. Starting with the circuit satisfying the clock period constraint, iMinArea will iteratively reduce the number of FFs by moving FFs backward over some gates with fanouts larger than fanins. If a fanout edge currently has no FF or is on a timing critical path requesting at least one FF, such a move may require FF moves over other gates. iMinArea dynamically maintains such relations among the gates as a forest. If there is a cluster of gates whose fanouts are larger than its fanins, the number of FFs can be reduced by moving one FF over the cluster; otherwise, the current solution is optimal. An outstanding feature of iMinArea is that a critical timing constraint is dynamically generated only when it is needed. Maintaining a forest on the gates, it requests only linear storage (that is, O(n)) on top of the circuit graph. As can be expected, iMinArea is extremely efficient in handling large circuits. For the same circuit with more than 180K gates that failed Minaret, our iMinArea algorithm solved the min-area retiming problem with 65MB memory in less than 1 minutes, which is at least 100 times faster than Minaret and uses at most 1 30 th of the memory used by Minaret. The rest of this paper is organized as follows. The retiming problems are introduced in Section 2. Our algorithmic idea is presented in Section 3. The iMinArea algorithm is proposed in Section 4. After experimental results are given in Section 5, Section 6 concludes the paper. In this paper, we presented an efficient algorithm named iMinArea to solve the min-area retiming algorithm incrementally and optimally. Instead of attacking the problem by formulating and solving a min-cost network flow problem in a dense flow network, our iMinArea algorithm generates the critical timing constraints dynamically, maintains active constraints in a forest, and retimes a circuit incrementally. Experimental results confirmed that our algorithm is significantly faster and uses much less memory in comparison to the best existing approach.. Even though only backward retiming is discussed in iMinArea, forward retiming can be symmetrically handled and mixed with backward retiming. Therefore, initial state can be easily enforced in the retimed circuits [12, 2] . Moreover, similar to [7] for min-period retiming, if the hold conditions need to be satisfied, iMinArea can be extended to solve the problem optimally.. We should also note that, since it is incremental, iMinArea can be stopped any time when a designer is satisfied (with the area) or impatient (with the runtime). However, we have not (yet) found it necessary to do so.

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


A chain-model genetic algorithm for Bayesian network structure learning Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7] . The super exponential growth of the number of possible networks given the number of factors in the studied problem domain has meant that more often, approximate and heuristic rather than exact methods are used. In this paper, a novel genetic algorithm approach for reducing the complexity of Bayesian network structure discovery is presented. We propose a method that uses chain structures as a model for Bayesian networks that can be constructed from given node orderings. The chain model is used to evolve a small number of orderings which are then injected into a greedy search phase which searches for an optimal structure. We present a series of experiments that show a significant reduction can be made in computational cost although with some penalty in success rate. Bayesian Networks (BNs) are probabilistic models useful for reasoning with, or representing knowledge under uncertainty. Essentially a BN can be defined as a pair (G, P ) where G is a directed acyclic graph (DAG) G = (V, E) with Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. GECCO'07, July 7-11, 2007 the vertices V as the nodes in the network. Each node represents a random variable Xi relevant to the problem domain. The dependencies among these variables are represented by the set of edges E in the underlying DAG factorizing the joint probability distribution P (X) over the set of random variables Xn into a conditionally independent one. with Pa(Xi) as the set of parent nodes for node Xi. To make use of the power of Bayesian Networks in knowledge representation and inference, they have to first be constructed for the given problem. To fully specify a Bayesian network, one has to first define the underlying DAG structure representing the network and then the BN's conditional probability distribution. For the latter, we have to determine the prior probabilities for all the nodes with no incoming links (i.e. root nodes), and all conditional probabilities for the remaining nodes. This is essentially a parameter estimation problem and is not discussed in the present work.. In this paper, we look at the structure learning part of specifying Bayesian networks. Although time consuming and not always possible, this can be achieved manually given extensive knowledge of the domain from experts or available literature. A popular alternative that has emerged, however, from within the artificial intelligence community in recent years, is the attempts to empirically induce BN structures from data. Various algorithms have in fact been developed in order to deal with this problem. Nevertheless, even when an array of assumptions and restrictions are made, structure learning for Bayesian Networks remains a hard problem [8] . This is mainly due to the fact that the number of possible structures for a given problem grows super exponentially given the number of variables in that problem.. Robinson [24] quantifies the number as O(n!2. ) for a problem of size n. So where a 3 variable problem would have 25 possible networks, a 5 variable problem would have 29,281 and a 6 variable problem would have 3,781,503 possible networks. This makes exact methods for structure discovery impractical and seldom used without imposing a great deal of restrictions [17] . More often used nowadays are approximate methods and approaches based on some heuristics. Mainly, these can be classified into two main groups: Search and Score methods and Conditional Independence Testing methods. The latter is a constraint based approach which relies on a number of statistical tests to determine whether two variables are independent or dependent given a set of conditioned variables. Tests such as Pearson's Chi-Square and mutual information are often used. Work by de Campos [12] and Spirtes and Glymour's PC algorithm [25] illustrate this. This approach tends to give good results with sparse networks and small samples of data however it does not scale very well for large datasets and dense networks.. In this work, we are interested in the Search and Score approach and more specifically in the use of genetic algorithms and greedy search in inducing Bayesian network structures from data. A brief overview of work done based on this approach follows in the next section. We then look at research done in learning Bayesian network structures by searching through the space of orderings in which we are particularly interested for this work. In Section 4 we describe our approach and hypothesis with regards to the usefulness of using chain structures in evaluating node orderings. We then describe the experiments carried out for testing this hypothesis in Section 5. We discuss the results in Section 6 and conclude in Section 7. We proposed a method for reducing the computation time needed for learning Bayesian network structures. The proposed method uses a chain-model GA which relies on chain structures for the evaluation of node orderings of which Bayesian network structures are then searched for using K2 search. We applied our model to the Asia, the Car and the Alarm networks; three different benchmark datasets of various complexity. We compared our method to the GA designed by Larrañaga for searching for Bayesian network structures through the space of node orderings. Our preliminary results show that our method obtained comparable results in term of structure score and structure topology to those obtained by K2GA but in a reduced number of factor evaluations. This seems promising although for the Car Diagnosis problem as we have shown, the success rate is lower and although this might be solved with restarts, in future work, we would like to investigate the reasons for this and explore whether or not this is problem related. Moreover, to improve success rate we would like to build on the idea of the chain and investigate the complete structure associated with an ordering. I.e. where each node in the ordering is connected to the nodes coming after it in the node order given (Figure 2b ). Using this complete structure to filter orderings we speculate will result in better quality network structures as the optimal structure should be contained within this complete structure. In practice this might be less efficient than the simple chain structure approach as it will require a greater number of factor evaluations. Preliminary experiments on the Asia dataset have proved this. Work on customizing the scoring metric we use to cater for these chain structures and not penalize them for complexity is also envisaged. Consequently, another avenue we would like to explore is the use of other available scoring metrics such as the MDL principle. For the Asia dataset, an ensemble of 30 experiments were ran for each algorithm. We scored the original network structures and stopped each run when the resulting score is a percentage away from the original network score. As we can see from Figure 4 , both algorithms managed to recover a near optimal Asia network structure with one edge missing from the VisitAsia node to Tuberculosis. Table 3a also shows comparable average network scores and success rates ( Table 2) . The difference is apparent in the number of factor evaluations needed to achieve these structures (Figure 5) . We can notice the same pattern for the Car diagnosis problem, where even though the recovered structures are not identical, they are very similar and close to the original network structure (Figures 7a and 7b ) . The scores illustrated in Table 3b also do not seem to be significantly different. Figures 8a and 8b show the plot of the resulting best scores of all runs for each of the algorithms. Again the noticeable difference seems to be in the number of factor evaluations carried out by each of the algorithms, although the success rate is about 58% for ChainGA (Table 2) for this problem and therefore we might need to run the experiments twice as often to get the same results ( Figure 9 ). More experiments will be carried out in the future in order to explain this result. For the Alarm problem, we ran each experiment 60 times. Table 3c records the results. The difference between the average best scores achieved by each approach is negligible. However, we can see the reduction in the number of factor evaluations when using the ChainGA approach. Indeed K2GA needs nearly as much as double the number to find similar network structures. Furthermore, the number of evaluations reported in the table is when at the K2 search phase of ChainGA, we run the search on 50% of the population, i.e. in this case 5 orderings. In general we would run only a percentage of 10 to 20% of the population at the end of the run by K2, which would need in this case less number of factor evaluations (e.g.1421 for 20% of the population). Figure 10 shows the run length distribution for each of the algorithms. We can see how the ChainGA runs completed need less factor evaluations than their K2GA counterparts. For both algorithms, the success rate is comparable as we can see from Table 2 about 45 runs have completed successfully out of the 60 runs carried out for each. The best scores found for each run for both algorithms can be seen in Figures 11a and 11b .. We speculate that this good performance is somewhat related to the nature of the problems used. All three networks used in this work are diagnostic and rely immensely on the causal relationship between the factors of the problem. The chain structures emphasize a certain choice of causal links given a certain ordering and therefore where the ordering considered is close to the optimal ordering, the chain structure seem to give us enough information about the network structure to build.

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 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 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Adequacy of evolving national standardized terminologies for interdisciplinary coded concepts in an automated clinical pathway Purpose. The purpose of this analysis was to determine the adequacy of evolving national standardized terminologies with regard to coded data elements (concepts) in an automated clinical pathway designed to drive adherence with the American College of Cardiology (ACC)/American Heart Association (AHA) Guidelines for Evaluation and Management of Chronic Heart Failure.Method. Concepts were identified in a previously developed automated clinical pathway and associated tools. Once identified, concepts were categorized according to the conceptual domains identified by Campbell et al. (1997) . A review of evolving national standardized terminologies and coding systems was initiated to determine if the identified concepts had corresponding representation in one of these coding systems. Available codes were then evaluated for adequacy with respect to national guideline adherence measures put forth by the Centers for Medicare/Medicaid Services (CMS) and Joint Commission on Accreditation of Healthcare Organizations (JCAHO).Results. The concept domain model put forth by Campbell et al. (1997) worked well for organizing concepts and for providing a useful framework for data analysis. Using our method, 260 unique pathway concepts were identified, of which, 91.9% (239) are represented by one or more of the standardized coding systems. Logical Observation Identifiers Names and Codes (LOINC) and SNOMED CT alone represented 86.2% of the concepts. Seventy percent (70%) of the clinical pathway concepts are represented using the Health Insurance Portability and Accountability Act (HIPAA) mandated national terminologies alone. Less than 50% of CMS and JCAHO guideline adherence concepts were found to have representation in the HIPAA mandated terminologies. The addition of Logical Observation Identifier Names and Codes (LOINC) and SNOMED CT improved representation up to 86.4%, but did not include representation of all concepts necessary for complete electronic monitoring of guideline adherence.Conclusions. Evolving national standardized terminologies provided matching terms for the majority of the data elements in the automated clinical pathway. Standard clinical terminologies with granular terms such as LOINC and SNOMED CT are required to represent the depth and detail of certain procedures and guideline-based care. Gaps exist in Health Insurance Portability and Accountability Act (HIPAA) mandated terminologies for representing interdisciplinary concepts in national adherence measures. Heart failure is a major public health problem in the United States. It affects 4.9 million Americans and is the primary cause of hospitalization in Medicare beneficiaries. In 1998, $3.6 billion ($5471 per discharge) was paid on behalf of Medicare beneficiaries for treatments related to heart failure [1] . Research over the past decade has identified medications, treatments, and patterns of care with efficacy in heart failure patients. However, prognosis after the diagnosis of heart failure remains poor and the total societal costs associated with this chronic illness in terms of human suffering and medical resources continue to rise as the population ages. Although the characterization of outcomes associated with heart failure is a complex issue, published literature demonstrates that practice variability contributes to suboptimal treatment of acute and chronic heart failure [2] [3] [4] [5] . Automated systems have been found to improve documentation of the application of core practice guideline recommendations [6] [7] [8] [9] [10] and to increase patient knowledge and participation in the decision-making process [11, 12] . Automated knowledge management tools such as clinical pathways, prompts and reminders, automated standard orders, and automated access to evidence in the form of ''Infobuttons'' promote access to evidence [13] and guideline adherence [14] [15] [16] . The purpose of this paper is to evaluate the adequacy of the HIPAA-mandated and other evolving national standardized terminologies with regard to coded data elements (concepts) in an automated clinical pathway that has been integrated with guideline recommendations contained in the American College of Cardiology (ACC)/American Heart Association (AHA) Guidelines for Evaluation and Management of Chronic Heart Failure. Our analysis suggests that the evolving standardized terminologies are not yet adequate for representing all concepts necessary for electronically tracking guideline adherence. The standards set forth by AHRQ related to the evaluation of quality in health care are an important first step towards electronic monitoring of quality. The measures put forth by CMS and JCAHO are evidence that there is movement towards the the AHRQ goal of ''enabling the user to quantify the quality of a selected aspect of care by comparing it to a criterion'' [49] . Recently, CMS and JCAHO have combined their heart failure guideline adherence measures (after completion of the evaluation described in this paper), representing further movement towards precisely defining guideline adherence concepts and measures. However, even given precise definitions of numerators, denominators, and inclusion and exclusion criteria as they exist currently in the joint CMS/JCAHO guideline adherence measures, data elements and how they will be represented with evolving terminologies need to be defined more precisely before adherence tracking can be done electronically on a grand scale. Through this evaluation, it was noted that given current obstacles, matching guideline concepts with CPR concepts is problematic (even before looking at the actual coding). Interagency agreement on guideline adherence measures, as was achieved through the CMS and JCAHO collaboration described above represents one step towards a solution. An additional recommended solution is for guideline developers to identify how such information is documented in a CPR as part of the guideline development process. A final recommendation is that similar processes occur locally as an integral component of the clinical pathway development process. This would foster consensus on precise measures of clinical pathway adherence, define related concepts and identify those concepts necessary for generation of data, information and knowledge as a fundamental part of the pathway design process. The concept domain model put forth by Campbell et al. (1997) worked well for organizing clinical pathway concepts and for providing a useful framework for data analysis. All concepts were represented by these domains and most clinical pathway concepts in this analysis (97.3%) fell within the following domains: Administrative (16.3%), Demographics (5.5%), Attributes (4.1%), Interventions (29.8%), Findings (25.7%), Diagnoses and impressions (10.1%), and Plans (6.1%). Because all of the clinical pathway concepts were extracted from acute, inpatient, guideline-based documents and tools, these seven domains were adequate to classify the data. See Table 7 for CampbellÕs domain classification, percent representation, and examples of matching ACC/ AHA guideline concepts.. We found that two of the Campbell framework domains, Interventions and Plans, lack clarity because of overlapping definitions. For example, in the Campbell model, nursing interventions fall under Plans and all other interventions (e.g., educational interventions) are classified under Interventions. However, several of the educational interventions can be completed by many disciplines, including nurses and if low sodium diet teaching is initiated by a nurse and then followed-up by a dietitian or physician, one might be an educational encounter classified as a Plan and the other as an Intervention. This ambiguity is problematic throughout the Table 6 Heart failure quality measures: CMS and JCAHO Two hundred and sixty unique clinical pathway concepts were identified of which 91.9% (239) were represented by one or more of the evolving national standardized coding systems (one or more exact match). Seventy percent of clinical pathway concepts were represented in HIPAA-mandated terminologies alone (without the addition of the LOINC and SNOMED CT clinical standards). LOINC and SNOMED CT alone represented 86.2% of the clinical pathway concepts.. Data elements related to the Administrative domain, e.g., facilities, institutions, practitioners, standardized terms were found in CPT-4, HCPCS, LOINC, and SNOMED CT. Data elements for the Demographics domain were best represented by SNOMED CT. Attributes, e.g., severity and staging of heart failure with ejection fraction, appropriate matches were available in CPT only. Data elements related to Interventions could be found in all terminologies. Data elements from the Findings domain were mapped to HCPCS, ICD-9-CM, LOINC, and SNOMED CT. Concepts within the Diagnoses and Impressions domain were mapped to HCPCS, ICD-9-CM and SNOMED CT. See Table 2 for percent of representation by domain and by standardized terminology and Table 3 for percent coverage of concepts by mandated terminologies, LOINC and SNOMED CT and total representation.. Sixteen clinical pathway concepts (6.2%) did not have exact matches in the evolving standardized terminologies (HIPAA mandated, LOINC or SNOMED CT). However, on closer examination, most of these terms had close matches within existing terminologies that could be adequately represented with related concepts (see Table 4 ) or could be represented using post-coordination of terms. Of the remaining clinical pathway concepts (n ¼ 7 or 2.7%), almost half are necessary for monitoring guideline adherence, but could not be represented with any of the evolving national standards.. In the CMS measure, 26 concepts were identified by one coder (PCD) and 12 by the other (JJC). A total of 30 concepts were identified, 8 of which were exact matches Table 2 Clinical pathway/practice guideline concepts: percent of representation by domain and by standardized terminology Domain n Table 4 Closest matches and post-coordinated representation for non-matching concepts Domain number Additional guideline adherence concepts identified in the CMS measure by both coders were closely related but displayed varying levels of granularity. Examples include: Clinical pathway concepts were identified through a thorough evaluation of the following guidelinebased documentation tools by a domain expert (PCD):. 1. An automated clinical pathway that was designed based on ACC/AHA practice guidelines. The clinical pathway consists of an interdisciplinary plan of care and standardized order sets built into the electronic medical record. These plans of care and order sets cue clinicians to document against adherence measures and best-practice interventions. 2. Discharge documentation tool. This double-sided form was developed by an interdisciplinary team based on the ACC/AHA practice guidelines, and functions as the patient discharge orders, educational handouts, and Supplemental State of Connecticut W-10 Interagency Transfer form. 3. Guideline adherence data collection tools. The Get With The Guidelines (GWTG) Patient Management Tool is part of an on-line, interactive assessment and reporting system that was developed by Outcome Sciences in conjunction with the American Heart Association and is designed to assist with implementing guideline-based care. This data collection tool provides patient-specific guideline information and the ability for institutions to track its adherence to guidelines against national benchmarks over time [51] . In this institution, the Patient Management Tool is used to track guideline adherence retrospectively. Currently, the data are manually entered into this tool as well as into the electronic medical record. Although the GWTG Patient management tool is useful for quality improvement purposes, the process would be more efficient in an integrated electronic system where the data collected during the documentation process could be reused for such reporting. 4. Patient self-management educational handout. This handout is a single page, double-sided form developed by an interdisciplinary team for teaching patients self-management skills related to heart failure. The form contains basic information about heart failure, weight and symptom monitoring; a Ôheart healthy diet,Õ smoking cessation interventions, medication information, and follow-up care.. Once the clinical pathway concepts were identified, they were categorized according to the following conceptual domains identified by Campbell et al. [38] : Administrative Concepts, Demographics, Attributes, Interventions, Findings, Diagnoses And Impressions, Plans, Equipment and Devices, Events, Human Anatomy, Etiologic Events, Documents, Legal Agreements, and Agents. This model was selected as an organizing framework because its domains represent not only the wide range of conceptual data found in a medical patient record but also a means with which to represent varying levels of detail [38] .. To evaluate the usefulness of evolving clinical terminology standards for electronically tracking national guideline adherence, concepts were extracted from the CMS and the JCAHO key quality indicators for heart failure. To evaluate inter-rater reliability (IRR) for the guideline adherence concepts identified, two coders independently reviewed the CMS and JCAHO quality indicators for discharge instructions, abstracted guideline adherence concepts, and organized the abstracted concepts into the Campbell framework. Once guideline adherence concepts were identified in the CMS and JCAHO quality measures, a review of HIPAA-mandated coding systems plus LOINC and SNOMED CT was initiated to determine if the identified guideline adherence concepts had corresponding representation (e.g., exact matches) in one of these coding systems.

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