Completeness, decidability and complexity of entailment for RDF Schema and a semantic extension involving the OWL vocabulary

We prove that entailment for RDF Schema (RDFS) is decidable, NP-complete, and in P if the target graph does not contain blank nodes. We show that the standard set of entailment rules for RDFS is incomplete and that this can be corrected by allowing blank nodes in predicate position.We define semantic extensions of RDFS that involve datatypes and a subset of the OWL vocabulary that includes the property-related vocabulary (e.g. FunctionalProperty), the comparisons (e.g. sameAs and differentFrom) and the value restrictions (e.g. allValuesFrom). These semantic extensions are in line with the ‘if-semantics’ of RDFS and weaker than the ‘iff-semantics’ of D-entailment and OWL (DL or Full). For these semantic extensions we present entailment rules, prove completeness results, prove that consistency is in P and that, just as for RDFS, entailment is NP-complete, and in P if the target graph does not contain blank nodes. There are no restrictions on use to obtain decidability: classes can be used as instances.     

On improving the efficiency of truthful routing in MANETs with selfish nodes

In Mobile Ad Hoc Networks (MANETs), nodes depend upon each other for routing and forwarding packets. However, nodes belonging to independent authorities in MANETs may behave selfishly and may not forward packets to save battery and other resources. To stimulate cooperation, nodes are rewarded for their forwarding service. Since nodes spend different cost to forward packets, it is desirable to reimburse nodes according to their cost so that nodes get incentive while the least total payment is charged to the sender. However, to maximize their utility, nodes may tell lie about their cost. This poses the requirement of truthful protocols, which maximizes the utility of nodes only when they declare their true cost. Anderegg and Eidenbenz recently proposed a truthful routing protocol, named ad hoc-VCG. This protocol incurs the route discovery overhead of O(n³), where n is the number of nodes in the network. This routing overhead is likely to become prohibitively large as the network size grows. Moreover, it leads to low network performance due to congestion and interference. We present a low-overhead truthful routing protocol for route discovery in MANETs with selfish nodes by applying mechanism design. The protocol, named LOTTO (Low Overhead Truthful rouTing prOtocol), finds a least cost path for data forwarding with a lower routing overhead of O(n²). We conduct an extensive simulation study to evaluate the performance of our protocol and compare it with ad hoc-VCG. Simulation results show that our protocol provides a much higher packet delivery ratio, generates much lower overhead and has much lower end-to-end delay.     

A spectral characterization of H-optimal feedback performance and its efficient computation

We study the spectral properties of a ‘Toeplitz⁺ Hankel’ operator which arises in the context of the mixed-sensitivity H^∞-optimization problem and whose largest eigenvalue characterizes the optimal achievable performance ε₀. The existence of such an operator was first shown by Verma and Jonckheere [26], who also'noted the potential numerical advantage of computing eo through its eigenvalue characterization rather than through the ε-iteration. Here, we investigate this operator in detail, with the objective of efficiency computing its spectrum. We define an ‘adjoint’ linear-quadratic problem that involves the same ‘Toeplitz⁺ Hankel’ operator, as shown by Jonckheere and Silverman [13–16]. Consequently, a finite polynomial algorithm allows ε₀ to be characterized as simply as the largest root of a polynomial. Finally, a computationally more attractive state space algorithm emerges from the H^t8/LQ relationship. This algorithm yields a very good accuracy evaluation of the performance ε₀ by solving just one algebraic Riccati equation. Thorough exploitation of this algorithm results in a drastic computation reduction with respect to the standard e-iteration.     

A numerical method for deadbeat control of generalized state-space systems

In this paper we give a new numerical method for constructing a rank m correction BF to an n × n matrix A, such that the generalized eigenvalues of λE−(A+BF) are all at λ = 0. In the control literature, this problem is known as ‘deadbeat control’ of a generalized state-space system Ex_i+1 = Ax_i + Bu_i, whereby the matrix F is the ‘feedback matrix’ to be constructed.     

Comparing computer-supported dynamic modeling and ‘paper & pencil’ concept mapping technique in students’ collaborative activity

This study aims at highlighting the collaborative activity of two high school students (age 14) in the cases of modeling the complex biological process of plant growth with two different tools: the ‘paper & pencil’ concept mapping technique and the computer-supported educational environment ‘ModelsCreator’. Students’ shared activity in both cases is carried out in the presence of a facilitator providing technical as well as cognitive support when necessary. The objective of the study is to highlight the ways in which the collaborating students are engaged in the plant growth modeling activity in the two cases and also identify the activity’s similar and different aspects in each one. Our analysis is carried out on two complementary axes, the first of which concerns the process of collaboratively creating a plant growth model with each different tool, while the second has to do with the students’ conceptualizations of the biological aspect of the modeling task in each case. A two-level analytic tool for the modeling process has been derived within the theoretical framework of ‘activity theory’ on the basis of the OCAF scheme for basic modeling operations and the scheme of Stratford et al. [Stratford, S. J., Krajcik, J., & Soloway, E. (1998). Secondary students’ dynamic modeling processes: analyzing, reasoning about, synthesizing, and testing models of stream ecosystems. Journal of Science Education and Technology, 7(3), 215–234.] for higher-order modeling actions. According to our results, four major modeling actions (analysis, synthesis, testing-interpreting, technical and cognitive support) performed through a plethora of modeling operations define the steps of the modeling process in both cases, while specific qualitative differences can be actually identified. Finally, the students’ conceptualizations of the biological aspect of the modeling task in the two-case activity is analyzed in regard with their capability of shifting reasoning between macro- and micro-levels, while educational implications are also discussed.     

Conceptual equivalence for contrast mining in classification learning

Learning often occurs through comparing. In classification learning, in order to compare data groups, most existing methods compare either raw instances or learned classification rules against each other. This paper takes a different approach, namely conceptual equivalence, that is, groups are equivalent if their underlying concepts are equivalent while their instance spaces do not necessarily overlap and their rule sets do not necessarily present the same appearance. A new methodology of comparing is proposed that learns a representation of each group’s underlying concept and respectively cross-exams one group’s instances by the other group’s concept representation. The innovation is fivefold. First, it is able to quantify the degree of conceptual equivalence between two groups. Second, it is able to retrace the source of discrepancy at two levels: an abstract level of underlying concepts and a specific level of instances. Third, it applies to numeric data as well as categorical data. Fourth, it circumvents direct comparisons between (possibly a large number of) rules that demand substantial effort. Fifth, it reduces dependency on the accuracy of employed classification algorithms. Empirical evidence suggests that this new methodology is effective and yet simple to use in scenarios such as noise cleansing and concept-change learning.     

Graph Grammars for Querying Graph-like Data

Recently research has deeply investigated the problem of querying semi-structured data and data which can be represented by means of graphs (e.g. object-oriented data, XML data, etc.). Typically queries on graph-like data, called path queries, are expressed by means of regular expressions denoting paths in the graph. The result of a path query is the set of nodes reachable by means of a path expressed by a specified regular expression. In this paper we investigate the problem of extracting a subgraph satisfying a given property from a given graph representing some information. We propose a new form of queries, called graph queries, whose answers are (marked) graphs having a particular structure, extracted from the source graph. We show that a simple form of graph grammars can be profitably used to define graph queries. The result of a graph query, using a grammar G over a database D, is a marked subgraph of D ‘matching’ a graph derived from G. We consider different types of graph grammars which can be used to query graph-like data and consider their expressiveness and complexity.     

Optimal diagonal scaling for infinity-norm optimization

A solution is presented for the previously unsolved diagonally scaled multivariable infinity-norm optimization problem of minimizing D(s)(A(s) + Ψ(s) X(s))D⁻¹(s)_∞ over the set of stable minimum-phase diagonal D(s) and stable X(s). This problem is of central importance in the synthesis of feedback control laws for robust stability and insensitivity in the presence of ‘structured’ plant uncertainty. The result facilitates the design of feedback controllers which optimize the ‘excess stability margin’ [3] (or, equivalently, the ‘structured singular value μ’ [4]) of diagonally perturbed feedback systems.     

The stuttering principle revisited

It is known that LTL formulae without the ‘next’ operator are invariant under the so-called stutter equivalence of words. In this paper we extend this principle to general LTL formulae with given nesting depths of both ‘next’ and ‘until’ operators. This allows us to prove the semantical strictness of three natural hierarchies of LTL formulae, which are parametrized either by the nesting depth of just one of the two operators, or by both of them. Further, we provide an effective characterization of languages definable by LTL formulae with a bounded nesting depth of the ‘next’ operator.This paper is a revised and extended version of [6].     

A spreadsheet program to optimize kinetic parameters of organic matter from laboratory pyrolysis data

Transformation of sedimentary organic matter (OM) to hydrocarbons is best modeled by assuming the total reaction suite consists of parallel degradations of ‘i’ hypothetical components following the Arrhenius equation and first order kinetics. A kerogen can be defined by characterizing each constituent component by its activation energy (Ei) their initial potentials (Xios) and a single frequency factor (A). We present a user friendly Lotus 1-2-3 program to determine A, Ei and Xio distribution of OMs using a multiple linear regression utility and programmed macros. Rock Eval (RE) S₂ curves of three heating rates are required. Equally spaced time/temperature and peak height data for S₂ curves of ‘n’ temperature steps in increasing order of heating rates are the inputs for the program. The fraction of hydrocarbon generated (f) from 19 hypothetical components of Ei 30, 32,34…78 Kcal/mole for ‘n’ temperature/time steps, by using frequency factor (A) value and assuming Xios=1, are calculated and set up in a ‘n×19’ matrix (matrix M). The fraction of total hydrocarbon generated (f) at ‘n’ temperature steps, obtained from the observed peak heights, are set up in a ‘n×1’ matrix (matrix L). Matrix M is suitably reduced by the program to ‘n×k’ matrix (matrix N) where ‘k’ is a variable, facilitating matrix inversion. Regressing matrix N against matrix L by the program, gives the Xios for ‘k’ Ei components along with a standard error (ERR) of Y estimates and R². Xios and A are then optimized iteratively by varying A values and selecting the solution associated with the lowest ERR value. Results of applying the program on data sets of two widely different types of samples from Indian basins are shown. They match the results obtained from the more sophisticated proprietary software.     

All-to-All Optical Routing in Chordal Rings of Degree 4

We consider the problem of routing in networks employing all-optical routing technology. In such networks, information between nodes of the network is transmitted as light on fiber-optic lines without being converted to electronic form in between. We consider switched optical networks that use the wavelength-division multiplexing (or WDM) approach. A WDM network consists of nodes connected by point-to-point fiber-optic links, each of which can support a fixed number of wavelengths. The switches are capable of redirecting incoming streams based on wavelengths, without changing the wavelengths. Different messages may use the same link concurrently if they are assigned distinct wavelengths. However, messages assigned the same wavelength must be assigned edge-disjoint paths. Given a communication instance in a network, the optical routing problem is the assignment of {routes} to communication requests of the instance, as well as wavelengths to routes so that the number of wavelengths used by the instance is minimal. We focus on the all-to-all communication instance I _A in a widely studied family of chordal rings of degree 4, called optimal chordal rings . For these networks, we prove exact bounds on the optimal load induced on an edge for I _A , over all shortest-path routing schemes. We show an approximation algorithm that solves the optical routing problem for I _A using at most 1.006 times the lower bound on the number of wavelengths. The previous best approximation algorithm has a performance ratio of 8. Furthermore, we use a variety of novel techniques to achieve this result, which are applicable to other communication instances and may be applicable to other networks. Received July 22, 1998; revised October 14, 1999.     

Discovering and Explaining Abnormal Nodes in Semantic Graphs

An important problem in the area of homeland security is to identify suspicious entities in large datasets. Although there are methods from knowledge discovery and data mining (KDD) focusing on finding anomalies in numerical datasets, there has been little work aimed at discovering suspicious instances in large and complex semantic graphs whose nodes are richly connected with many different types of links. In this paper, we describe a novel, domain independent and unsupervised framework to identify such instances. Besides discovering suspicious instances, we believe that to complete the process, a system has to convince the users by providing understandable explanations for its findings. Therefore, in the second part of the paper we describe several explanation mechanisms to automatically generate human understandable explanations for the discovered results. To evaluate our discovery and explanation systems, we perform experiments on several different semantic graphs. The results show that our discovery system outperforms the state-of-the-art unsupervised network algorithms used to analyze the 9/11 terrorist network by a large margin. Additionally, the human study we conducted demonstrates that our explanation system, which provides natural language explanations for its findings, allowed human subjects to perform complex data analysis in a much more efficient and accurate manner.     

An observer-based set-point controller for robot manipulators with flexible joints

We present a globally asymptotically stable controller for point-to-point regulation of robot manipulators with flexible joints that uses only position measurement on the motor side. Existing asymptotically stable schemes for the set point regulation problem without velocity measurement address only the rigid robot case. Furthermore, these solutions ensure only local stability provided some bounds on the dynamic part of the robot model are known. Also, they require the injection of high gains into the loop to enlarge the equilibrium domain of attraction. In contrast, our solution is global, applies for robots with flexible joints and assumes only that the gravity forces are known. The underlying rationale of the design is to ‘shape’ the potential energy of the closed loop system so that it has an absolute minimum at the desired equilibrium, and add the required dampingto achieve asymptotic stability. This is attained by adding a (linear) observer that converges to the position required to compensate the gravity forces and injects the damping, and a ‘spring-like’ effect between the observer and the robot that ‘pulls’ the robot to the desired target. This approach to observer-based controller design differs from the classical certainly equivalent approach and effectively exploits the dynamic properties of the physical system.     

A generalization of ACP using Belnap’s logic

ACP is combined with Belnap’s four-valued logic via conditional composition (if–then–else). We show that the operators of ACP can be seen as instances of more general, conditional operators. For example, both the choice operator + and δ (deadlock) can be seen as instances of conditional composition, and the axiom x + δ = x follows from this perspective. Parallel composition is generalized to the binary conditional merge _ψ where covers the choice between interleaving and synchronization, and ψ determines the order of execution. The instance _BB is ACP’s parallel composition, where B (both) is the truth value that models both true and false in Belnap’s logic. Other instances of this conditional merge are sequential composition, pure interleaving and synchronous merge. We investigate the expression of scheduling strategies in the conditions of the conditional merge.     

On SAT instance classes and a method for reliable performance experiments with SAT solvers

A recent series of experiments with a group of state-of-the-art SAT solvers and several well-defined classes of problem instances reports statistically significant performance variability for the solvers. A systematic analysis of the observed performance data, all openly archived on the Web, reveals distributions which we classify into three broad categories: (1) readily characterized with a simple ²-test, (2) requiring more in-depth analysis by a statistician, (3) incomplete, due to time-out limit reached by specific solvers. The first category includes two well-known distributions: normal and exponential; we use simple first-order criteria to decide the second category and label the distributions as near-normal, near-exponential and heavy-tail. We expect that good models for some if not most of these may be found with parameters that fit either generalized gamma, Weibull, or Pareto distributions. Our experiments show that most SAT solvers exhibit either normal or exponential distribution of execution time (runtime) on many equivalence classes of problem instances. This finding suggests that the basic mathematical framework for these experiments may well be the same as the one used to test the reliability or lifetime of hardware components such as lightbulbs, A/C units, etc. A batch of N replicated hardware components represents an equivalence class of N problem instances in SAT, a controlled operating environment A represents a SAT solver A, and the survival function R ^A (x) (where x represents the lifetime) is the complement of the solvability function S ^A (x)=1–R ^A (x) where x may represent runtime, implications, backtracks, etc. As demonstrated in the paper, a set of unrelated benchmarks or randomly generated SAT instances available today cannot measure the performance of SAT solvers reliably – there is no control on their 'hardness'. However, equivalence class instances as defined in this paper are, in effect, replicated instances of a specific reference instance. The proposed method not only provides a common platform for a systematic study and a reliable improvement of deterministic and stochastic SAT solvers alike but also supports the introduction and validation of new problem instance classes.     

Approximation of satisfactory bisection problems

The Satisfactory Bisection problem means to decide whether a given graph has a partition of its vertex set into two parts of the same cardinality such that each vertex has at least as many neighbors in its part as in the other part. A related variant of this problem, called Co-Satisfactory Bisection, requires that each vertex has at most as many neighbors in its part as in the other part. A vertex satisfying the degree constraint above in a partition is called ‘satisfied’ or ‘co-satisfied,’ respectively. After stating the NP-completeness of both problems, we study approximation results in two directions. We prove that maximizing the number of (co-)satisfied vertices in a bisection has no polynomial-time approximation scheme (unless P=NP), whereas constant approximation algorithms can be obtained in polynomial time. Moreover, minimizing the difference of the cardinalities of vertex classes in a bipartition that (co-)satisfies all vertices has no polynomial-time approximation scheme either.     

Discovering Dependencies via Algorithmic Mutual Information: A Case Study in DNA Sequence Comparisons

Algorithmic mutual information is a central concept in algorithmic information theory and may be measured as the difference between independent and joint minimal encoding lengths of objects; it is also a central concept in Chaitin's fascinating mathematical definition of life. We explore applicability of algorithmic mutual information as a tool for discovering dependencies in biology. In order to determine significance of discovered dependencies, we extend the newly proposed algorithmic significance method. The main theorem of the extended method states thatd bits of algorithmic mutual information imply dependency at the significance level 2^–d+O(1). We apply a heuristic version of the method to one of the main problems in DNA and protein sequence comparisons: the problem of deciding whether observed similarity between sequences should be explained by their relatedness or by the mere presence of some shared internal structure, e.g., shared internal repetitive patterns. We take advantage of the fact that mutual information factors out sequence similarity that is due to shared internal structure and thus enables discovery of truly related sequences. In addition to providing a general framework for sequence comparisons, we also propose an efficient way to compare sequences based on their subword composition that does not require any a priori assumptions about k-tuple length.     

Bisimulation equivalence of a BPP and a finite-state system can be decided in polynomial time

In this paper we consider the problem of deciding bisimulation equivalence of a BPP and a finite-state system. We show that the problem can be solved in polynomial time and we present an algorithm deciding the problem in time O(n⁴). The algorithm also constructs for each state of the finite-state system a ‘symbolic’ semilinear representation of the set of all states of the BPP system which are bisimilar with this state.