MODELING AND AUGMENTING GAME ENTERTAINMENT THROUGH CHALLENGE AND CURIOSITY This paper presents quantitative measurements/metrics of qualitative entertainment features within computer game environments and proposes artificial intelligence (AI) techniques for optimizing entertainment in such interactive systems. A human-verified metric of interest (i.e. player entertainment in real-time) for predator/prey games and a neuro-evolution on-line learning (i.e. during play) approach have already been reported in the literature to serve this purpose. In this paper, an alternative quantitative approach to entertainment modeling based on psychological studies in the field of computer games is introduced and a comparative study of the two approaches is presented. Feedforward neural networks (NNs) and fuzzy-NNs are used to model player satisfaction (interest) in real-time and investigate quantitatively how the qualitative factors of challenge and curiosity contribute to human entertainment. We demonstrate that appropriate non-extreme levels of challenge and curiosity generate high values of entertainment and we project the extensibility of the approach to other genres of digital entertainment (e.g. mixed-reality interactive playgrounds). Computer games, as examples of human-computer interactive systems, provide an ideal environment for research in AI, because they are based on simulations of highly complex and dynamic multi-agent worlds.. 1,2,3 Moreover, such systems offer a promising ground for cognitive modeling since they embed rich forms of interactivity between humans and nonplayer characters (NPCs). 4 Being able to capture quantitatively the level of user (gamer) engagement or satisfaction in real-time can grant insights to the appropriate AI methodology for enhancing the quality of playing experience and furthermore be used to adjust digital entertainment environments according to individual user preferences. 5 An endeavor on capturing player satisfaction during gameplay and providing quantitative measurements of entertainment in real-time is presented in this article. The principal goal in the reported work is to construct a user model of a class of game playing experience. Specifically, the aim is that the model can predict the answers to which variants of a given game are more or less "fun." This approach is referred to as Entertainment Modeling. Herein, entertainment is defined qualitatively primarily as the level of satisfaction generated by the real-time player-game opponent interaction -by 'opponent' we mean any controllable interactive feature of the game. According to this definition, a game is primarily a learning process and the level of entertainment is kept high when game opponents enable new learning patterns ('not too easy a game') for the player that can be perceived and learned by the player ('not too difficult a game'). 6, 7 On the same basis, according to Kapoor et al. learning is highly correlated to interest, curiosity and intrigue perceived within the axis of emotions varying from boredom to fascination. 8 The collection of these emotions is defined as entertainment (or "fun") in this article.. Entertainment capture in this paper is achieved by following the theoretical principles of Malone's intrinsic qualitative factors for engaging gameplay, 9 namely challenge (i.e. This paper introduced an approach to constructing a quantitative value of entertainment motivated by the qualitative principles of Malone's intrinsic factors for engaging game play. 9 More specifically, the quantitative impact of the factors of challenge and curiosity on human entertainment were investigated in computer (Pac-Man) and mixed-reality (BugSmasher) games.. The two neuro-evolution approaches for modeling entertainment examined in the PacMan game demonstrate qualitative features that share principles with the human-verified interest metric (I value) reported in the literature. 6 Both approaches manage to map successfully between the measures of entertainment factors such as challenge and curiosity and the notion of human game play satisfaction. The proposed approaches replace the hand-crafted mathematical formulation of the interest metric with a more general process of machine learning applied to neural network models.. Validation results obtained show that the fittest feedforward NN gets closer to human notion of entertainment than both the I value 19 and the fittest fuzzy-NN. Therefore, it appears that the average and the standard deviation of a human's playing time over a number of games are sufficient in themselves and more effective than the I value (as reported in Ref. 19 ) in capturing player entertainment in real-time in predator/prey games.. The work reported for this approach is most significantly limited by the number of participants in the game survey we devised. Therefore, not all regions of the challengecuriosity search space were sampled by human play which therefore yielded poor NN gen-eralization for these regions. Limited data also restricted the sensible number of inputs to the learning system.. Malone's entertainment factor of fantasy is omitted here since the focus is on the contribution of the opponent behaviors to the generation of entertainment; however, experiments on interactive physical predator/prey games with children have shown that entertainment increases monotonically with respect to the fantasy factor. The foregoing has proposed and demonstrated methods for deriving a quantitative estimate of the level of entertainment experienced by a player of a interactive entertainment system (computer and mixed-reality game), using data that can be derived from or during game play. In this section, we discuss some of the questions raised by the approach and the assumptions on which it is based.. An immediate and natural question is whether the techniques described really capture "entertainment" which, after all, is a complex mental phenomenon depending on the player, the game and (probably) a number of external factors in rather involved ways. We acknowledge that the definition of a quantitative metric for entertainment in this sense is almost certainly infeasible. However, we take a practical approach here: it is sufficient for our purposes if a quantity exists that can be computed from observable data from the player-game interaction and that correlates well with players' expressed preferences. In other words, a numerical value which orders games in the same way as players' judgement of entertainment is sufficient for our purposes.. The foregoing material illustrates a way to construct such a metric: using machine learning to explore the space of possible evaluation functions whose values are consistent with human judgement of entertainment value. The resulting metric is specific to the particular game under consideration, but the general method of construction is applicable to a wide variety of game instances and genres.. To summarize, therefore, the proposed approach does not capture details of the complex mental states associated with enjoyment of computer or mixed-reality games, but it does provide a way to evaluate different instances of game play in terms of how entertaining they are for a player. Such knowledge can be used, for example, for tuning the game to suit the player (see below).. In addition to this general question concerning the approach, there are a number of assumptions (and hence limitations) associated with the methods presented; these are discussed below. Results obtained from both feedforward NN and fuzzy-NN evolutionary approaches are presented in this section. In order to control for the non-deterministic effect of the GA initialization phase, each learning procedure (i.e. GA run) for each NN type is repeated ten times -we believe that this number is adequate to illustrate a clear picture of the behavior of each mechanism -with different random initial conditions.. The experiment presented here tests the hypothesis of the existence of a generic notion of entertainment given the level of challenge and curiosity in dissimilar games. Given the 30 pairs of games, where the games have different levels of S and/or H, a feedforward NN is evolved by following the approach presented in section 5.3. Experiments with NN topologies consisting of (maximum) two hidden layers with up to 30 hidden neurons showed that a single hidden-layered architecture, containing 10 hidden neurons is the minimal NN architecture capable of successfully obtaining solutions of high fitness. The fittest NN found was able to correctly match 20 out of 30 children answers on entertainment. Such a poor fitness indicates the difficulty of adjusting values of challenge and curiosity for inferring entertainment values in an objective manner (without the presence of individual playing characteristics). In contrast with the metrics of challenge (E{t k }) and curiosity (σ{t k }) derived for the Pac-Man game, bug speed (S) and bug spatial diversity (H) do not embed any feature of player-opponent interaction since they define opponent/bug (controllable game feature) characteristics. Therefore, the relation between challenge (S), curiosity (H) and the game's entertainment value (y) illustrated in Fig. 4 projects a rather objective enjoyment model for the Bug-Smasher game.. Despite the best solution's poor fitness, the correlation between entertainment, challenge and curiosity generated through the evolved NN (see Fig. 4 ) appears to be consistent with the entertainment model obtained through Pac-Man and Malone's qualitative principles.. 9 A conclusion derived from experiments in both games is that extreme levels of challenge and curiosity make the game uninteresting. As seen from (see Fig. 1 and Fig. 2) , demonstrates that the proposed approach generalizes to dissimilar games (Pac-Man vs. Bug-Smasher), game platforms (computer vs. mixed-reality Playware) and age groups (adults vs. children).

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Tracing regulatory routes in metabolism using generalised supply-demand analysis : Metabolic control analysis of J 5 , J 9 , J 14 and J 15 for the aspartate metabolism model. Partial response coefficients and their associated elasticity and control coefficients are shown. Control analysis was performed with the concentration of linking metabolite between supply and demand fixed at the reference steady-state value in each case (see Table 2 in main text).

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Flow-based reputation: more than just ranking The last years have seen a growing interest in collaborative systems like electronic marketplaces and P2P file sharing systems where people are intended to interact with other people. Those systems, however, are subject to security and operational risks because of their open and distributed nature. Reputation systems provide a mechanism to reduce such risks by building trust relationships among entities and identifying malicious entities. A popular reputation model is the so called flow-based model. Most existing reputation systems based on such a model provide only a ranking, without absolute reputation values; this makes it difficult to determine whether entities are actually trustworthy or untrustworthy. In addition, those systems ignore a significant part of the available information; as a consequence, reputation values may not be accurate. In this paper, we present a flow-based reputation metric that gives absolute values instead of merely a ranking. Our metric makes use of all the available information. We study, both analytically and numerically, the properties of the proposed metric and the effect of attacks on reputation values. The advent of the Internet has brought new business opportunities and favored the development of collaborative environments. In particular, the Internet provides the basis for the development of electronic communities where strangers interact with each other and possibly do business. However, these interactions involve risks. For instance, in an eCommerce setting, buyers are vulnerable to risks due to potential incomplete or misleading information provided by sellers [34] . Similarly, sellers are subject to the risk that the counterparty in a transaction will be unable to honor its financial obligations. To mitigate those risks, there is the need of a decision support system that is able to determine the trustworthiness of collaborative parties. Reputation systems are widely considered as 'the solution' to assess trust relationships among users and to identify and isolate malicious users [28] . Reputation systems are currently adopted in commercial online applications such as P2P file sharing [8] , web search [9] , electronic marketplaces [3, 15] , and expert systems [2, 16] . Reputation is a collective measure of trustworthiness based on aggregated feedback related to past experiences of users. The basic idea is to let users rate each other and to aggregate ratings about a given user to derive a reputation value. This value is then used to assist other users in deciding whether to interact with that user in the future [21] . In the last years, a number of reputation systems have been proposed to aggregate ratings and calculating reputation values; each system is based on a particular theoretical foundation (see [18, 21] for a survey). The quality of a reputation system is determined by how accurately the computed reputation predicts the future performance of entities [18] . This, however, is difficult to achieve because some users can attempt to manipulate their reputation and the reputation of others for their own benefit. Most existing reputation systems lack the ability to discriminate honest ratings from dishonesty ones. Therefore, such systems are vulnerable to malicious users who provide unfair ratings [34] . The issue of discriminating honest from dishonest ratings is usually addressed by reputation systems using the so called flow model [21] as the mathematical foundation. Examples of such systems are EigenTrust [23] , PageRank [9] , SALSA [26] , and PeerTrust [34] . What makes them appealing is that reputation is computed taking into account the feedback of all the users involved in the system, and the feedback is weighted with respect to the reputation of the user providing the feedback. Flow models are often based on the theory of Markov chains. The feedback provided by the users is aggregated and normalized in order to obtain a Markov chain. Thereby, starting from a vector of initial reputation values, Markov steps are repeatedly applied until a stable state has been reached. Unfortunately, the current state of affairs regarding this kind of reputation model is not very satisfactory.. First of all, those systems only provide a ranking of users rather than an absolute reputation value. Although this can be acceptable in some applications like web search, it is not in others like electronic marketplaces. For instance, a buyer prefers to do business with an honest seller rather than with the most trustworthy one in a pool of dishonest sellers. In a scenario where health care providers are willing to use data created by patients [32] , the quality of the data provided by a patient cannot be assessed by only looking if he is more capable than other patients to do good measurements; an absolute quality metric is required. In addition, most of the flow-based systems ignore a significant part of the available information (e.g., negative feedback). Consequently, the reputation values those systems return may be inaccurate.. To illustrate these points, let us consider an electronic marketplace where users can rate each other after each transaction, as in eBay [15] . Here, each time Alice has a transaction with another user j (e.g., Bob, Charlie, David), she may rate the transaction as positive, neutral, or negative. Let us consider scenarios (a) and (b) in Fig. 1 . From a reputation metric we would expect that Alice has almost neutral opinion of Bob and Charlie and negative opinion of David in (a), and positive opinion of Bob and Charlie and neutral opinion of Charlie in (b). However, if we apply the reputation metric proposed in [23] to these scenarios, we have that in both (a) and (b) Bob has local trust value 1 0.1, Charlie 0.9 and David 0. The formulas used to compute these values will be presented in Section 2. Here, we just want to point out that the metric in [23] is unable to distinguish between cases (a) and (b). This lack of distinguishing power can be risky for users as it can mislead them in their decision whether to do business with other users. For instance, the reputation value of Charlie computed using the metric in [23] in (a) can lead users to think that Charlie is 'very' trustworthy while in fact he is not. These reputation values only indicate that Charlie is more trustworthy than others (i.e., a ranking without an absolute scale). Moreover, it is worth noting that in [23] negative ratings are discarded in order to obtain a Markov chain. Consequently, it is not possible to distinguish between users that have (strong) negative reputation and users that have neutral reputation. This can be observed by comparing the ratings received by David in scenarios (a) and (b) of Fig. 1 : although David received a large number of negative ratings and no positive ratings in (a) and an equal number of positive and negative ratings in (b), his reputation value is equal to 0 in both scenarios. Last but not least, the design of flow-based reputation models requires including a number of parameters which intend to guarantee the convergence of computations. However, a comprehensive and exhaustive study of the impact of such parameters on reputation values and how they can be used to protect the systems against attacks has not been conducted yet.. Our contributions In this paper, we present a reputation metric that enhances existing flow-based reputation metrics (see [9, 23, 31] ) by providing absolute values instead of merely a ranking, and by not discarding any available information. Computing absolute reputation values makes it possible to quantify the trustworthiness of users and therefore provides a measure to univocally compare reputations values. This allows us, for instance, to distinguish cases (a) and (b) in Fig. 1 . In the design of our reputation metric, we study the effect of self-reference (i.e., a user who gives feedback to himself). We demonstrate that our construction minimizes such an effect, leading to reputation values that are closer to intuitive expectations. We formally prove that the proposed reputation metric always has a solution, and that the solution is unique. We also discuss several methods of solving the reputation equation numerically. Our metric depends on a number of parameters: a pattern matrix, which stores the (aggregated) feedback received by the system owner from the users about the interactions they had with other users (hereafter, the pattern matrix is also called indirect evidence matrix), a starting reputation vector, which represents the direct information known to the system owner about the trustworthiness of entities in the system, and an interpolation parameter α, which serves as a weight for direct versus indirect information. We analytically study the impact of changes in the indirect evidence matrix on reputation values. This study allows us to analyze how someone can attack the reputation system by providing unfair ratings. In particular, we analyze self-promoting and slandering attacks [18] as well as Sybil attacks [14] . To study self-promoting (slandering) attacks, we assume that an attacker can manipulate reputation values by giving positive ratings to users who gave positive ratings to him (negative ratings to the target) and negative ratings to users who gave negative ratings to him (positive ratings to the target). We study the effect of Sybil attacks by modeling an attacker who subverts the reputation system by first creating a large number of pseudonymous entities, and then using them to influence the reputation value of a target user in a similar way as is done for self-promoting and slandering attacks. On the other hand, we assume that the starting reputation vector and the weight parameter are defined by the system owner and cannot be modified by the attacker. We numerically study the impact of these parameters on reputation values and analyze how they can be used to mitigate the effect of above mentioned attacks. The analysis allows us to draw some guidelines for choosing the value of these parameters. The guidelines are general and apply to reputation metrics that use similar parameters. In this work we are mainly interested in the study of the mathematical model of reputation systems, rather than in the algorithm implementing the mathematical model. Therefore, we assume throughout the paper the existence of a central authority which collects all ratings and calculates the reputation of every participating user. This assumption is in line with the approach proposed in [9] where a search engine collects information about hyperlinks of several million pages and indexes search results on the basis of such an information. The paper is structured as follows. Section 2 provides an overview of reputation systems. Section 3 presents our metric and Section 4 discusses its formal properties. Section 5 discusses several methods for computing the reputation vector. Section 6 evaluates reputations numerically for a number of attack scenarios. Section 7 concludes and discusses directions for future work. We have presented a flow-based reputation metric for aggregated feedback. The metric gives absolute reputation values instead of merely a ranking; it also makes use of all the relevant information without discarding any part of it, leading to reputation values with better discriminating capabilities. We have given a proof that there is always a solution and that it is unique. We have also compared different methods for computing the reputation vector, and studied the properties of the metric numerically, focusing in particular on how attackers can manipulate reputation values. We have analyzed the impact of the initial reputation vector s and the weight parameter α on r. It turns out that the reputations depend on α in a surprisingly linear way, although the equations are nonlinear. They interpolate between the known solutions at α = 0 and α = 1, with small deviations from a straight line. The direct information plays an important role (also for the ranking) even when little weight is given to it. We have also studied how these parameters can be used to make the reputation metric more robust against attacks. The attacks can be direct (attacker y manipulates A xy for target x) as well as indirect (manipulating A zy for other users z = x). A Sybil attack increases the effectiveness. The most evident result is that the α parameter has a much stronger effect on the robustness than s. Robustness against attacks and in particular Sybil attacks is obtained by choosing a smaller α. However, a balance must be kept between resisting attacks and making constructive use of the information provided by users in the A matrix. In particular, α must not be chosen too small because there is a danger from choosing a wrong s. Setting a larger α, the effect of choosing the wrong pre-trusted users is mitigated, as the choice of s hardly matters. This is demonstrated by the jumps in Fig. 7 , which have size 1 − α.. In this paper, we have mainly focused on the mathematical model of the reputation metric. In particular, we have studied its properties both analytically and numerically, which allows the specification of guidelines for making the system more robust against attacks. An interesting challenge for future research is to study whether those properties are preserved in the computation dimension, in particular, when there does not exist a centralized authority computing reputation values, but the computation is distributed across the users of the system.

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


Low-Complexity Constant Multiplication Based on Trigonometric Identities with Applications to FFTs SUMMARY In this work we consider optimized twiddle factor multipliers based on shift-and-add-multiplication. We propose a low-complexity structure for twiddle factors with a resolution of 32 points. Furthermore, we propose a slightly modified version of a previously reported multiplier for a resolution of 16 points with lower round-off noise. For completeness we also include results on optimal coefficients for eight points resolution. We perform finite word length analysis for both coefficients and round-off errors and derive optimized coefficients with a minimum complexity for varying requirements. Computation of the discrete Fourier transform (DFT) and inverse DFT is used in e.g. orthogonal frequencydivision multiplexing (OFDM) communication systems and spectrometers. An N -point DFT can be expressed as. where. N is twiddle factor, the N :th primitive root of unity with its exponent being evaluated modulo N , n is the time index, and k is the frequency index. Various methods for efficiently computing (1) have been the subject of a large body of published literature. These methods are commonly referred to as fast Fourier transform (FFT) algorithms. Also, many different architectures to efficiently map the FFT algorithm to hardware have been proposed [1] .. A commonly used architecture for transforms of length N = b r is the pipelined FFT [2] [3] [4] [5] [6] [7] . The pipeline architecture is characterized by continuous processing of input data. In addition, the pipeline architecture is highly regular, making it straightforward to automatically generate FFTs of various lengths. Figure 1 outlines the architecture of a Radix-2 i , single-path delay feedback (SDF), pipelined FFT architecture for N = 256. This architecture is generic Manuscript received July 07, 2010. † The authors are with the Department of Electrical Engineering, Linköping University, SE-581 83 Linköping, Sweden. http://www.es.isy.liu.se/ a) E-mail: fahadq@isy.liu.se b) E-mail: oscarg@isy.liu.se while the required ranges of each complex twiddle factor multiplier for different algorithm are outlined in Table 1 [5] [6] [7] [8] .. We will from now on denote a multiplier with a twiddle factor resolution of N points around the unit circle a W N -multiplier. For small ranges of the twiddle factor multipliers it is advantageous to use arithmetic circuits optimized for the required coefficients rather than general multipliers. A W 4 multiplier only performs multiplication by one of {1, j, −1, −j}, in practice 1 or −j, and is most commonly realized by combining it in the subsequent butterfly (often denoted BFII as opposed to the standard butterfly BFI following [5] ). For larger N it is common to utilize the octave symmetry of the coefficients. This means that only twiddle factors corresponding to angles in the range 0 ≤ α ≤ π/4 needs to be considered. This is equivalent to twiddle factors in the range 0 ≤ m ≤ N/8. Multiplications for other values of m can be obtained by optionally swapping outputs (symmetry around ℜ(m) = ℑ(m) and ℜ(m) = ℑ(m)) and negating one or both outputs (symmetry around ℜ(m) = 0 and ℑ(m) = 0). A complete complex multiplier based on complex constant multiplication is shown in Fig. 2 . In previous work, the complex multipliers for W 8 and W 16 have been replaced with constant complex multipliers based on shift-andadd networks for performing the multiplication [10] [11] [12] .. In this work, we propose a low complexity complex constant W 32 -multiplier based on trigonometric identities. Furthermore, we revisit and slightly improve the W 16 -multiplier proposed in [7] and, for completeness, calculate the coefficients and complexity of the W 8 -multiplier. A preliminary version of this work was presented in [9] . In this extended version, we have included results on the finite word length properties. It is shown that the coefficient quantization can lead to larger errors than considered in [7, 9] . Furthermore, expressions for the round-off noise are derived. Based on this, a slight modification is proposed for the W 16 -multiplier from [7] . The rest of the paper is arranged as follows. In the next section, the complex constant multipliers are introduced. Then, in Section 3, coefficient quantization and data round off errors are analyzed. Then, in Section 4, results are presented and finally, some conclusions are given in Section 5. The constant multiplier can be realized using a minimum number of adders using the method in [14] . In this work, the design of reconfigurable complex constant multipliers was considered, with the focus of rotators in fast Fourier transforms. A multiplier for 32-point resolution was introduced. In addition, a slightly modified previously proposed multiplier for 16-point resolution was discussed. For these two multipliers, finite word length properties for both data and coefficient quantization was discussed and optimal coefficients were derived. For completeness, the optimal co- Fractional Proposed (Fig. 4) Red. Booth [11] MCM [10] bits Adders MUXs Adders MUXs Adders MUXs

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


Low-complexity high-throughput decoding architecture for convolutional codes Sequential decoding can achieve a very low computational complexity and short decoding delay when the signalto-noise ratio (SNR) is relatively high. In this paper, a low-complexity high-throughput decoding architecture based on a sequential decoding algorithm is proposed for convolutional codes. Parallel Fano decoders are scheduled to the codewords in parallel input buffers according to buffer occupancy, so that the processing capabilities of the Fano decoders can be fully utilized, resulting in high decoding throughput. A discrete time Markov chain (DTMC) model is proposed to analyse the decoding architecture. The relationship between the input data rate, the clock speed of the decoder and the input buffer size can be easily established via the DTMC model. Different scheduling schemes and decoding modes are proposed and compared. The novel high-throughput decoding architecture is shown to incur 3%-10% of the computational complexity of Viterbi decoding at a relatively high SNR. The 57-64GHz unlicensed bandwidth around 60GHz can accommodate multi-gigabits per second (multiGbps) wireless transmission in a short range. There are several standards for 60GHz systems, such as WirelessHD [1] and IEEE 802. 15 .3c [2, 3] . In both WirelessHD and the AV PHY mode in IEEE 802. 15 .3c, a concatenated FEC scheme is used with a RS code as the outer code and a convolutional code as the inner code. In order to achieve the target decoding throughput at multi-Gbps, parallel convolutional encoding has been adopted by the transmitter baseband design in both standards. It is straightforward to use parallel Viterbi decoding in the receiver baseband. However, it has been shown in [4] and [5] that parallel Viterbi decoders in the receiver baseband result in massive hardware complexity and power consumption. The problem will become more severe if a higher decoding throughput is targeted (i.e., 10Gbps) for a battery powered user terminal in the future [6] . Hence it is desirable to find a low-complexity high-throughput decoding method for convolutional codes in such systems.. The Viterbi algorithm (VA) achieves maximum likelihood decoding for convolutional codes [7] . The VA is a breadth-first, exhaustive search approach based on the trellis diagram. Sequential decoding is another method of convolutional decoding and is a depth-first, non-exhaustive searching approach based on the tree diagram. It only explores partial paths locally in the code tree, so it has sub-optimal decoding performance and its computational complexity varies with SNR. There two main types of sequential decoding algorithms which are known as the Stack algorithm [8] and the Fano algorithm [9, 10] . Because the Fano algorithm has low storage and sorting requirements, it can achieve higher decoding throughput compared to the Stack algorithm. Only the Fano algorithm is considered in this paper. Sequential decoding is not widely used in real systems due to the excessive computations and long decoding delay when the SNR is low. However, if a relatively high SNR can be achieved (e.g., for a very short range and/or via beamforming) or required for some applications (e.g., HD video streaming), sequential decoding will on average incur a very low computational complexity and short decoding delay, which results in a high decoding throughput.. In this paper, a novel low-complexity high-throughput decoding architecture based on parallel Fano algorithm decoding with scheduling is proposed. Different scheduling schemes and decoding modes are investigated. A discrete time Markov chain (DTMC) is introduced to model the proposed architecture to establish the relationship between input data rate, input buffer size and clock speed of the decoders. The trade-offs between error rate, computational complexity, scheduling schemes and decoding modes are studied.. It will be shown that the high-throughput decoding architecture can achieve a much lower computational complexity compared to the Viterbi decoding with a similar error rate performance. The rest of the paper is organized as follows. Firstly, the unidirectional Fano algorithm (UFA) and bidirectional Fano algorithm (BFA) are reviewed in Section 2. The novel parallel Fano decoding with scheduling architecture is proposed in Section 3. Different scheduling schemes and decoding modes are also proposed in this section. The DTMC based modelling is applied to the decoding architecture in Section 4. Simulation results are given in Section 5, and the conclusions are drawn in Section 6. This paper considered the application of sequential decoding algorithm in high-throughput wireless communication systems. A novel architecture based on parallel Fano algorithm decoding with scheduling was. proposed. Due to the scheduling of the Fano decoders according to the input buffer occupancy, a high decoding throughput can be achieved by the proposed architecture. Different scheduling schemes and decoding modes were proposed and compared. It was shown that the PBFAS-LQF scheme could achieve the highest decoding throughput. A DTMC model was proposed for the decoding architecture. The relationship between the input data rate, the clock speed of the decoder and the input buffer size can be easily established via the DTMC model. The model was validated by simulation and utilized to determine the number of decoders required for a target decoding throughput. It was shown that the novel high-throughput decoding architecture requires 3%-10% of the computational complexity of the Viterbi decoding with a similar error rate performance. This novel architecture can be employed in high-throughput systems such as 60GHz systems to achieve energy efficient low-complexity convolutional codes decoding.

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


Information assimilation framework for event detection in multimedia surveillance systems Abstract Most multimedia surveillance and monitoring systems nowadays utilize multiple types of sensors to detect events of interest as and when they occur in the environment. However, due to the asynchrony among and diversity of sensors, information assimilation -how to combine the information obtained from asynchronous and multifarious sources is an important and challenging research problem. In this paper, we propose a framework for information assimilation that addresses the issues -"when", "what" and "how" to assimilate the information obtained from different media sources in order to detect events in multimedia surveillance systems. The proposed framework adopts a hierarchical probabilistic assimilation approach to detect atomic and compound events. To detect an event, our framework uses not only the media streams available at the current instant but it also utilizes their two important properties -first, accumulated past history of whether they have been providing concurring or contradictory evidences, and -second, the system designer's confidence in them. The experimental results show the utility of the proposed framework. In recent times, it is being increasingly accepted that most surveillance and monitoring tasks can be better performed by using multiple types of sensors as compared to using only a single type. Therefore, most surveillance systems nowadays utilize multiple types of sensors like microphones, motion detectors and RFIDs, etc. in addition to the video cameras. However, different sensors usually provide the sensed data in different formats and at different rates. For example, a video may be captured at a frame rate which could be different from the rate at which audio samples are obtained, or even two video sources can have different frames rates. Moreover, the processing time of different types of data is also different. Due to the asynchrony and diversity among streams, the assimilation of information in order to accomplish an analysis task is a challenging research problem. Information assimilation refers to a process of combining the sensory and non-sensory information obtained from asynchronous multifarious sources using the context and past experience.. Event detection is one of the fundamental analysis tasks in multimedia surveillance and monitoring systems. In this paper, we propose an information assimilation framework for event detection in multimedia surveillance and monitoring systems.. Events are usually not impulse phenomena in real world, but they occur over an interval of time. Based on different granularity levels in time, location, number of objects and their activities, an event can be a "compound event" or simply an "atomic event". We define the compound and atomic events as follows: The proposed information assimilation framework adopts a hierarchical probabilistic approach in order to detect an event in a surveillance and monitoring environment, and performs assimilation of information at three different hierarchical levels -media-stream level, atomic-event level and the compound-event level. The work flow of the framework is depicted in Fig. 1 . Let a surveillance and monitoring system consists of n heterogeneous sensors that capture data from the environment. We employ n Media Stream Processors (MSP 1 -MSP n ), where each MSP i , 1 ≤ i ≤ n, is a set of media processing tools that extracts features from the media stream M i ; e.g. a blob detector extracts blobs from a video stream. The features extracted from each media stream are stored in their respective databases.. Let the system detect N a number of atomic events. The total number of sets containing two or more atomic events in which the atomic events can occur together can be given by. r . Any kth compound event E k can be expressed as E k = e 1 , e 2 , . . . , e r , where 2 ≤ r ≤ N a , 1 ≤ k ≤ N c , N c being the number of compound events which can be detected by using the system. The total number N E of events (atomic events as well as compound events) can be given by N E = N a + N c .. A compound event E k , which comprises of two or more atomic events occurring together, is detected hierarchically in a bottom-up manner. First, atomic events e j , 1 ≤ j ≤ r are detected using the relevant media streams, and then these decisions are assimilated hierarchically to obtain an overall decision for the compound event E k , as described in the subsequent subsections.. From the total number N a of atomic events that the system can detect, the proposed framework identifies:. • The atomic events (e.g. person's standing/walking/ running and person's talking/shouting) that cannot occur simultaneously.. • The atomic events (e.g. person's walking) that can occur individually as well as can occur together with some other atomic event (e.g. with person's shouting).. • The atomic events (such as person's shouting) that cannot occur individually and must occur together with some other atomic event (such as with person's standing/walking/running). To further illustrate it, we provide the following example.. Example 1 Let us consider a surveillance system that uses two types of sensors -video and audio with the goal of detecting N a = 6 atomic events, namely -person's "standing", "walking", "running", "talking", "shouting" and "door knocking". In this case, as shown in Table 1 , there could be N c = 9 compound events in which any r ≥ 2 atomic event(s) could occur. In total, there could be N E = 12 events. Next, we also identify the types of data sources which can be used to detect each of the atomic events. For instance, the atomic events shown in Example 1, can be detected as follows -standing (V), walking (AV), running (AV), talking (A), shouting (A), door knocking (A); where (A), (V) and (AV) denote audio, video and audio-video streams, respectively. In this paper, we have presented a novel framework for assimilation of information in order to detect events in the surveillance and monitoring systems that utilize multifarious sensors. The experimental results have shown that the use of agreement coefficient among and the confidence information of media streams helps in obtaining more accurate and credible decisions about the events. The results have also shown that the FRR for event detection can be significantly reduced using all the streams together. In future work, there are many other issues which need to explored such as -first, how to determine the minimum time period to confirm different events; second, it would be interesting to see how framework will work when the information from different sources would be made available at different time instances, what would be the ideal sampling rate of event detection and information assimilation; and finally, how the confidence information about a stream (newly added in the system) can be computed over time using its agreement/disagreement with the other streams whose confidence information are known, and how it would evolve over time with the changes in environment. Researchers have used early fusion as well as late fusion strategies in solving diverse problems. For example, feature-level (early) fusion of video and audio has been proposed for the problems-speech processing [10] and recognition [14] , tracking [7] , and monologue detection [15] by using the mutual information among the video and audio features under the assumption that audio and video signals are individually and jointly Gaussian random variables. On the other hand, late fusion strategies have also been used in sensor fusion applications [6, 11, 16] . In late fusion strategy, a global decision is made by fusing the local decisions obtained from each data source. Rao and Whyte [16] presented a sensor fusion algorithm for identification of tracked targets in a decentralized environment. Chair and Varshney [6] established an optimal fusion rule with the assumption that each local sensor made a predetermined decision and each observation was independent. Kam et al. [11] generalize their solution for fusing the correlated local decisions.. Similar to Wu et al. [19] , we employ early (feature level) assimilation as well as late (decision level) assimilation strategy. Since each media stream provides various features (such as blob's location and area in case of a video stream), their assimilation is performed locally for each media stream to obtain a local decision. Once all the local decisions are available, a global decision is derived by assimilating the local decisions incorporating their agreement and confidence information. The late assimilation strategy has an advantage over early assimilation in that the former offers scalability (i.e. graceful upgradation or degradation) in terms of media streams used in the assimilation process [2] . Note that, in late assimilation, we consider the media streams to be "decision-wise correlated". The decision-wise correlation refers to how the decisions obtained based on different media streams co-vary with each other.. Our work is different from the works cited above in following aspects. We explicitly compute and utilize the correlation information (we call it the "agreement coefficient") among the streams. Agreement coefficient among streams is computed based on how concurring or contradictory evidences they provide. Intuitively, higher the agreement among the streams, more would be the confidence in the global decision, and vice versa [17] . The various forms of correlation coefficients that have been used for diverse applications are based on content-wise dependency between the sources, hence are not suitable in our case. Pearson's correlation coefficient, Lin's concordance correlation coefficient [12] and Kappa coefficient [5] cannot be used in our case since they are evaluated to zero when the covariance among the observations is zero. Therefore, the proposed framework models the agreement coefficient and its evolution based on the accumulated past history of how agreeing or disagreeing the media streams have been in their decisions.. Also, the past works in multimodal fusion literature do not consider the notion of having confidences in the different modalities. We incorporate the stream's confidence information. Recently, Siegel and Wu [17] has also pointed out the importance of considering the confidence in sensor fusion. The authors have used the Dempster-Shafer (D-S) 'theory of evidence' to fuse the confidences. In contrast, we propose a model for confidence fusion by using a Bayesian formulation because it is both simple and computationally efficient [16] .

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


Aortic pressure wave reconstruction during exercise is improved by adaptive filtering: a pilot study Abstract Reconstruction of central aortic pressure from a peripheral measurement by a generalized transfer function (genTF) works well at rest and mild exercise at lower heart rates, but becomes less accurate during heavy exercise. Particularly, systolic and pulse pressure estimations deteriorate, thereby underestimating central pressure. We tested individualization of the TF (indTF) by adapting its resonance frequency at the various levels of exercise. In seven males (age 44-57) with coronary artery disease, central and peripheral pressures were measured simultaneously. The optimal resonance frequency was predicted from regression formulas using variables derived from the individual's peripheral pressure pulse, including a pulse contour estimation of cardiac output (pcCO). In addition, reconstructed pressures were calibrated to central mean and diastolic pressure at each exercise level. Using a genTF and without calibration, the error in estimated aortic pulse pressure was -7.5 ± 6.4 mmHg, which was reduced to 0.2 ± 5.7 mmHg with the indTFs using pcCO for prediction. Calibration resulted in less scatter at the cost of a small bias (2.7 mmHg). In exercise, the indTFs predict systolic and pulse pressure better than the genTF. This pilot study shows that it is possible to individualize the peripheral to aortic pressure transfer function, thereby improving accuracy in central blood pressure assessment during exercise. The relevance of blood pressure changes during exercise is well established and is an independent predictor of cardiovascular morbidity and mortality [6, 13, 15] . Finger arterial blood pressure can easily be measured during exercise with the Finapres Methodology TM , using the volume clamp method by Peňáz [18, 27] and the 'Physiocal' criteria by Wesseling [28] . However, changes in finger pressure during exercise are not representative of changes in aortic pressure. In general, systolic pressure is higher in peripheral arteries like the finger [3, 5] . This physiological effect can also be observed in radial [19] and brachial arteries [16, 20] . This amplification of systolic and pulse pressure changes with cardiovascular state, thus with workload and is different between subjects [24] .. The purpose of this study is to improve aortic pressure reconstruction during exercise by use of adaptive filtering. Earlier, we found that the major change in the transfer function (TF) during exercise was the shift in peak resonance frequency (Fpeak) of the individual aorta-finger TF [24] . To individualize the TF (indTF), we looked for relations to predict this frequency shift from parameters extracted from the measured peripheral pressure pulse and Berend E. Westerholf and Ilja Guelen own shares of the BMEYE Company. BMEYE develops, manufactures and markets devices using Finapres Methodology TM .. patient characteristics. We used the dataset of seven cardiac patients as in our previous study [3, 24] to test if the bias and scatter in the reconstructed aorta pulse pressure are reduced with the indTF when compared to a general TF (genTF) [24] . In a small group of cardiac patients, individualized fingerto-aortic pressure TFs gave better pulse wave reconstruction during exercise than a genTF. Extra information from the peripheral pulse can aid in enhancing precision of central pressure wave reconstruction for different levels of Regressions between TF resonance frequency (Fpeak) and measured and/or calculated parameters and three regression formulas, respectively. Errors between reconstructed (RecAorPP) and measured AorPP using the three regressions are given for no additional calibration and calibration at each workload. Results for the genTF are also given (Max dP/dt is the maximal value of the time derivate of FinAP; MAP and DBP are FinAP mean and diastolic pressure; pcCO is pulse contour cardiac output; SV is stroke volume; TPR is total peripheral resistance; HR is heart rate and Delay is travel time between central and peripheral pulse wave) exercise. This information can be easily and noninvasively obtained during a measurement, i.e., pulse contour (CO) or peripheral mean and diastolic arterial pressure and HR. In this study, data from only seven subjects were available as 'trainings set'; therefore we could not evaluate our concept on a separate 'test set' group. However, these first results are promising. During exercise, central pressure reconstruction from peripheral measurements is challenging due to the combined effects of shifting of the actual TF's resonance peak (Fpeak) to higher frequencies and the shift in harmonics of the pressure wave with increased HR. In an earlier study, we found that a genTF underestimated central pressures at higher intensities of exercise in a number of the subjects, although it performed well at rest [24] . Similarly, Westerhof et al. [31] concluded that individualization did not improve the aortic wave reconstruction in patients at rest. In the exercise study by Sharman [22] , where peripheral pressure (radial) was measured by tonometry at one exercise level (light to moderate), it was concluded that a genTF may be used during exercise. In our earlier study [24] , we found a considerable spread in the reconstructed pressures during exercise which can be attributed to a higher maximum workload in our study (increases in MAP ?25 ± 16 vs. ?20 ± 10 mmHg and in HR ?51 ± 21 vs. ?15 ± 7 BPM) when compared with the study of Sharman. In effect, in the study of Sharman there was also a tendency to underestimate systolic pressure (-4.7 ± 3.3 mmHg) with the largest deviations at the higher pressures. Here, we show that reconstructed pressure can be improved with adaptive filtering.. The use of genTFs is well accepted [7] . Several methods to individualize aortic-peripheral TFs have been proposed, mostly by model fitting, but without definite success. Segers [21] did not find a relation between the fitted parameters of a transmission line model of the upper limb and the physiological subject parameters. Sugimachi [25] used transfer delay for the individualization, but without significant improvement over a genTF, contrary to what would be expected from oscillatory flow theory [16, 29, 30] . A recently proposed method uses time delay as well as the knowledge that aortic flow is zero during diastole [26] . Karamanoglu [11] used adaptive filtering of the finger pressure wave making use of simultaneously derived carotid tonometric data. However, the latter is difficult to perform during exercise because of movement artifacts and it is unknown whether the aortic to carotid TF will be stable under those circumstances.. In this study, we proposed individualization by direct statistical correlation between one of the main features of the TF and physiological subject parameters, both by using the inter-subject variability and by introducing exercise evoked changes within each subject. Parameters were chosen that could easily be extracted form the finger pressure signal. The applied pcCO algorithm relates the pressure systolic area (PSA) to flow by an estimate of impedance, incorporating corrections for age, MAP and HR [10, 23] . PSA alone did not correlate with Fpeak (R 2 = 0.027). In addition, pressure wave delay between aorta and finger was incorporated on theoretical grounds [16, 25, 30] . This delay can be measured noninvasively using the ECG, but appropriate corrections for changes in pre-ejection period have to be made. However, time delay did not improve reconstruction over and above the more easily obtained pcCO.. During exercise, two major changes occur in the hemodynamic status of a subject: both HR and mean blood pressure increase. HR has no direct effect on pressure transfer, although some authors [8, 14, 32] mention an effect on distensibility or on pulse wave velocity independent of a change in pressure. Increased mean blood pressure will increase wave speed, which has a direct effect on travel time over the arteries and on the TF [30] . Travel time is reduced and the resonance peak of the pressure TF will shift to higher frequencies [16] as was confirmed in our earlier study [24] .. Due to the increased HR during moderate to high workloads the harmonics of the pressure wave also shift to higher frequencies. The combined effect of changes in TF and HR makes the result of AorPP reconstruction with a genTF during exercise rather unpredictable.. The relevance of an increase in HR and the shift in Fpeak in relation to an underestimation of reconstructed pulse pressure can be understood when considering the harmonics of the pressure wave involved. At resting HR, the TF's Fpeak (in our subjects on average at 4.25 Hz) was between the 3rd and 4th harmonic of the pressure wave, whereas most of the energy is in the 1st and 2nd harmonic. With increasing workload and HR, both the TF's Fpeak and the HR harmonics are shifted to higher frequencies [24] . More so for the HR harmonics, but still mainly the higher harmonics are amplified on transmission towards the periphery. In this situation, a general reverse TF, optimized for the resting situation, will reduce the amplitude of the lower two harmonics, leading to a distortion of the reconstructed wave. A change in TF without a change in HR (as under complete autonomic blockade) will have a much lower impact, as only higher harmonics are involved. Pulse pressure will be underestimated to variable extents, an effect also described for the period directly post-exercise in a recent study by Payne [17] . These effects may reduce the applicability of a genTF, although at low exercise loads acceptable results may be obtained [22, 24] .. With the individualized TF as proposed in this study, bias and scatter are reduced, such that central blood pressure can be reliably determined in an individual patient even at higher workloads. The results were well within the AAMI criteria [1] .

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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 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 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 O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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 bi-objective weighted model for improving the discrimination power in MCDEA Envelopment Analysis (DEA) models, which have also hampered the developments in the multiobjective DEA domain. Since the initial multi-criteria DEA (MCDEA) model of Li and Reeves ( 1999) , only one other research by Bal, Örkcü and Çelebioğlu ( 2010) attempted to solve the MCDEA framework through two goal programming approaches, i.e. GPDEA-CCR and GPDEA-BCC. It was claimed that both models improved upon the discrimination power of DEA by balancing the distribution of input-output weights. It was also claimed that both GPDEA models are major improvements to the original MCDEA of Li and Reeves (1999) . In this research we first checked the validity of GPDEA models and found that they do not improve the discrimination power as it has been claimed, we further propose an alternative solution to the formulation using bi-objective linear programming. It is shown that the proposed bi-objective multiple criteria DEA(BiO-MCDEA) performs better than the GPDEA models in the aspects of discrimination power and weight dispersion, as well as requiring less computational codes. An application of energy dependency among 26 European Union member countries is further used to describe the efficacy of our approach. Data envelopment analysis (DEA) was first proposed by Charnes et al. (Charnes, Cooper, & Rhodes, 1978) and remained the leading technique for measuring the relative efficiency of decision-making units (DMUs) based on their respective multiple inputs and outputs. DEA has been the fastest growing discipline in the past three decades covering easily over a thousand papers in the Operations Research and Management Science discipline (see (Emrouznejad, Parker, & Tavares, 2008) ). The efficiency of a DMU is defined as a weighted sum of its outputs divided by the weighted sum of its inputs on a bounded ratio scale.. One of the drawbacks of the DEA is the problem of lack of discrimination among efficient decision making units (DMUs) and hence yielding many DMUs as efficient. The problem is noted when the number of DMUs evaluated is significantly lesser than the number of inputs and outputs used in the evaluation. The weights derived post-hoc from the evaluation exercise may reveal that some inputs or outputs have zero values. This is counter-intuitive especially in a decision making exercise, where one expects to use all the inputs and output values that are rated for the DMUs. Hence, it further implies that some of the variables were not used in the evaluation exercise in achieving the final ranking. On the contrary, unrealistic weight distribution for DEA also occurs when some DMUs are rated as efficient because of extreme large weights in a single output and/or extreme small weights in a single input. Thompson et al. ( 1986) are among the first authors to propose the use of weight restriction to increase the discrimination power of DMUs. The issue was immediately picked up by many authors, including Dyson and Thanassoulis (Dyson & Thanassoulis, 1988) , Charnes et al. (Charnes, Cooper, Huang, & Sun, 1990a) , Thanassoulis et al. (Thanassoulis & Allen, 1998 ). Hence, several methods such as assurance region (AR) procedure (R. G. Thompson, Langemeier, Lee, & Thrall, 1990) , cone ratio envelopment (Charnes, Cooper, Huang, & Sun, 1990b) area adressed in the literature as strategies to solve problems arising from unrealistic weight distribution. Subsequently, other DEA models were introduced in the literature to overcome the discriminant power problems, such as the cross-efficiency evaluation technique (Anderson, Hollingsworth, & Inman, 2002; Doyle & Green, 1994 , 1995 Green, Doyle, & Cook, 1996; Sexton, Silkman, & Hogan, 1986) , super-efficiency model (Andersen & Petersen, 1993; Y. Chen, 2005) , and multiple criteria (or multi-objective) DEA (Y.-W. Chen, Larbani, & Chang, 2009; Li & Reeves, 1999) .. The focus in this paper is on the most recent development in the area; that is, to introduce a weighted model for improving the discrimination power and weight dispersion, which focuses on multiple criteria Data Envelopment Analysis (MCDEA). The rest of the paper is organized as follows. Section 2 gives a brief description of the multiple criteria data envelopment analysis (MCDEA) and the more recent goal programming data envelopment analysis (GPDEA) as a procedure for MCDEA. Section 3 highlights some drawbacks on using GPDEA to represent MCDEA analysis. We therefore introduce an alternative bi-objective multiple criteria model (BiO-MCDEA) to improve the discrimination power of MCDEA in Section 4. An application of energy dependency among 26 EU member countries demonstrates the efficacy of the model in Section 5. Concluding remarks are given in Section 6. Hence, we have illustrated that our bi-objective multiple criteria DEA model outperforms the GPDEA model in terms of both weight dispersion and discrimination power.. Although we have proposed a bi-objective weighted method for solving the MCDEA model, we stress that there may be other procedures that can be used to extract solutions under multiobjective LP environment. We merely show a procedure that performs better than the GPDEA in terms of ease of formulation and mathematical programming (i.e. less computational codes). We hope that future researchers in DEA will provide better solution procedures for the MCDEA model.

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


An inexact interior point method for the large-scale simulation of granular material Non-smooth contact dynamics provides an increasingly popular simulation framework for granular material. In contrast to classical discrete element methods, this approach is stable for arbitrary time steps and produces visually acceptable results in very short computing time. Yet when it comes to the prediction of draft forces, non-smooth contact dynamics is typically not accurate enough. We therefore propose to combine the method class with an interior point algorithm for higher accuracy. Our specific algorithm is based on so-called Jordan algebras and exploits the relation to symmetric cones in order to tackle the conical constraints that are intrinsic to frictional contact problems. In every interior point iteration a linear system has to be solved. We analyze how the interior point method behaves when it is combined with Krylov subspace solvers and incomplete factorizations. We show that efficient preconditioners and efficient linear solvers are essential for the method to be applicable to large-scale problems. Using BiCGstab as a linear solver and incomplete Cholesky factorizations, we substantially improve the accuracy in comparison to the projected Gauß-Jacobi solver. Granular material appears in numerous areas of engineering. As examples, we mention the behavior of powder, which is of interest for toner production, process engineering, which benefits from the simulation of silo discharges, and the mining industry, where one is interested in optimizing hoppers and conveyor belts. Overall, there is an increasing demand for realistic large-scale computer simulations for these application fields.. If we look more closely at the product design of excavators, it turns out that draft forces acting on the machine from the interaction with the soil are of great importance. The realistic prediction, however, of draft forces demands the highest standards from simulation methods for granular matter. Currently, two methods are mainly used in this field: the classical Discrete Element Method (DEM) and Non-Smooth Contact Dynamics (NSCD) methods. The DEM has shown its potential to deliver draft forces that are in agreement with experimental data (Obermayr et al., 2011) . But a simulation of a few seconds can take up days to weeks of calculation time. NSCD provides a class of methods that are substantially faster and more stable, but due to their low accuracy, they fail to reproduce realistic draft forces. To improve the accuracy of NSCD, we propose here the combination with a specialized Interior Point Method (IPM). While being computationally more expensive than standard NSCD solvers, it does not suffer from instabilities as DEM does and it gives direct control over the trade-off between calculation time and accuracy.. In the DEM (Cundall and Strack, 1979) , contact between two particles is modeled locally as a stiff spring that pushes them apart. Particles are allowed to slightly penetrate each other and a reaction force proportional to the overlap is calculated. Combined with frequent changes in contact states, this limits the maximum time step size to maintain a stable simulation. Thus, the classical DEM is computationally very expensive. One way to interpret the DEM is by saying small penetrations emulate microscopic deformations. In this sense, DEM resolves the problem at much smaller time scales than those of interest. From the perspective of larger space and time scales, the granular particles seem perfectly rigid and collisions seem to be resolved instantaneously. One way of eliminating uninteresting time scales from the model is by using a non-smooth formulation for the dynamics.. In NSCD (Moreau, 1988; Moreau and Panagiotopoulos, 1990; Stewart, 2000; Acary and Brogliato, 2008) , contacts and collisions between particles are modeled by inequality constraints, e.g., by demanding that the distance between two particles shall always be greater than or equal to zero. Satisfying these equations leads to absolutely continuous trajectories that need not be differentiable at every point in time. This yields a velocity and impulse based scheme, since forces no longer exist as classical functions in time. The non-smooth formulation combined with a time-stepping scheme, where the times of collision are not resolved exactly, yields a numerical method that is stable for arbitrary time step sizes.. Satisfying the inequality constraints boils down to solving a variational inequality, i.e., a complementarity problem 1 , at every time step of the simulation. In many applications, specifically in soil mechanics, a friction model is indispensable and therefore a large Cone Complementarity Problem (CCP) has to be solved per time step (Anitescu and Potra, 1997; Anitescu and Tasora, 2008; Tasora and Anitescu, 2011) .. A popular iterative solver for large scale CCPs is the Projected Gauß-Jacobi (PGJ) method, since it is easily parallelizable, it can be implemented in a matrix-free fashion, and one iteration is very cheap (Tasora and Anitescu, 2011; Balzer et al., 2013) . Figure 1 shows a snapshot from a simulation with one million particles, computed by PGJ on 48 compute nodes. Its main drawback is that, after good initial convergence, the convergence rate stalls quickly if the problems are large or if large mass ratios are present. Stopping the iteration prematurely leads to artificial compliance in the granular material, incorrect angles of repose and incorrect forces . In practice, a combination of NSCD and PGJ is not necessarily more efficient than classical DEM, as a lot of PGJ iterations are necessary. Sometimes PGJ completely fails to meet the desired accuracy requirements.. A natural next step is to study second-order methods for CCPs to improve the convergence. Noteworthy contributions in this direction are (Daviet et al., 2011) , where the authors employ a semi-smooth Newton method to the Fischer-Burmeister Function associated with a CCP; (Krabbenhoft et al., 2012) where the authors consider Quadratic Programming solvers and Interior Point Methods for Linear Complementarity Problems; , where Krylov subspace methods are generalized for the solution of variational inequalities; and finally, the Ph.D. thesis (Heyn, 2013) , which compares activeset strategies, accelerated gradient-descent methods and IPMs.. In this paper we consider a specialized IPM based on the Jordan-algebraic structure of R 3 . IPMs are very promising due to their good theoretical complexity bound. In practice, the required number of iterations to reach a certain accuracy stays bounded even for very large problems. Symmetric cones play an important role in Jordan algebras and hence, exploiting their structure is one way to tackle the conical constraints resulting from the Coulomb friction law.. In each iteration, a linear system of equations has to be solved. In most publications on this topic it is assumed that this system is solved directly using matrix factorizations. In large granular assemblies it is impractical to use a direct solver due to the dimension of the linear system. We favor the idea presented in (Gondzio, 2012) of using 1 The complementarity problem results from the Karush-KuhnTucker first order optimality conditions of an energy principle subject to inequality constraints.. an iterative method to obtain inexact search directions in every IPM iteration, while taking precautions to maintain good numerical properties of the linear systems.. We give here a self-contained description of the Interior Point Method for NSCD. Moreover, we test different preconditioners and Krylov methods to solve the linear systems and demonstrate that preconditioning is essential to make this method applicable to large-scale problems. Among the analyzed techniques, we found that regularizing the linear systems, preconditioning with Incomplete Cholesky factorizations and solving them with the Bi-Conjugate Gradient method lead to the most efficient approach. Finally, we also show that the IPM solves the CCP to a higher accuracy than PGJ, even as the problem size increases.. In the following section, we outline the physical model and the equations of motion for non-smooth dynamical systems subject to unilateral contact and friction. Some elementary properties of symmetric cones are outlined in Section 3. The IPM is explained in detail in Section 4. Section 5 delivers numerical tests, and some concluding remarks are given in Section 6. We conclude that the presented IPM is well-suited to solve the CCP to a higher accuracy than PGJ. With a direct solver, IPM converges with a constant rate until machine precision is reached. Since the IPM scales with the number of particles just as well as the linear solvers do, a direct solver cannot be applied in reasonable time for large scale problems. We tested three different Krylov solvers and two preconditioners and found that regularizing the subsystems, preconditioning them with Incomplete Cholesky factorizations and solving them with BiCGstab gives the fastest convergence. The inaccuracy of the linear solves decreases the overall convergence rate of the IPM, but the inexact IPM still produces smaller errors than PGJ. IPMs superiority over PGJ becomes especially clear as the problem size increases. We also found that, towards the exact solution, IC(0) does not decrease the range of eigenvalues much further than plain regularization does. The rate of convergence of the IPM and its calculation time depend highly on the efficiency of the preconditioner and the linear solver. While the method has shown its potential, IC(0) and BiCGstab still require a large number of iterations and the calculation time is higher than desirable.. In the future, the highest priority is to further analyze different preconditioners. Possibly there are problemrelated ways to improve the numerical properties of the linear systems, either by taking advantage of the physical model or by manipulating the Interior Point Method itself. State-of-the-art linear solvers such as Algebraic Multigrid Methods could be applied if the accuracy requirement is very high. Once it is clear which solution technique fits best into the IPM framework, there are a lot of further optimizations to think of. One could start solving the CCP using PGJ and once the convergence rate decreases, the PGJ solution can be used to construct a good starting value for the IPM. Similarly, one could exploit the fact that the linear systems behave nicely in the first few IPM iterations. Hence, a simple and cheap linear solver suffices. As the error decreases it might make sense to switch to a more powerful solver. Ideally, the linear solvers should lend themselves for a matrix-free implementation and they should be parallelizable.. For the prediction of draft forces from the interaction of an excavator with soil, we have to demand very high standards from the simulation method. It has to be stable, accurate and it should be able to run a simulation in a reasonably short amount of time. So far, neither DEM nor NSCD are entirely satisfactory: One method is accurate, but instable and slow; while the other is reasonably fast and stable, but inaccurate. In this paper, we use results from abstract algebra, convex analysis, measure theory, optimization, nonlinear programming and numerics to im-prove the accuracy of NSCD. So far, the presented Interior Point Method is little more than a prototype, but it is already substantially more accurate than PGJ and proved to be promising for further development.

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


IT-Intensive Value Innovation in the Electronic Economy: Insights From Marshall Industries The emerging electronic economy is bringing with it new forms of IT-enabled intermediation, virtual supply chains, rapidly changing electronic commerce technologies, increasing knowledge intensity, and unprecedented sensitivity for time-to-market by customers. Customers are demanding more value, customized to their exact needs, at less cost, and as quickly as possible. The enterprises that will survive in such a demanding environment will need to innovate and invent new ways of creating value, and will require different enterprise architectures and different IT infrastructures. This article focuses on providing a framework for guiding an enterprise as it transforms itself to function more effectively in the electronic economy. Using the distribution industry in general and Marshall Industries in particular as a context, the article draws insights for transforming an extended enterprise’s architecture and its IT infrastructure to enable new ways of creating value in the electronic economy. The article provides a staged junction box model for guiding the transformation, and also articulates the elements of the new value logic for enterprises in the electronic economy.

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