Multi-aspect permutation tests in shape analysis with small sample size

Inferential methods known in the shape analysis literature make use of configurations of landmarks optimally superimposed using a least-squares procedure or analyze matrices of interlandmark distances. For example, in the two independent sample case, a practical method for comparing the mean shapes in the two groups is to use the Procrustes tangent space coordinates, if data are concentrated, calculate the Mahalanobis distance and then the Hotelling T²-test statistic. Under the assumption of isotropy, another simple approach is to work with statistics based on the squared Procrustes distance and then consider the Goodall F-test statistic. Despite their widespread use, on the one hand it is well known that Hotelling’s T²-test may not be very powerful unless there are a large number of observations available, and on the other hand the underlying model required by Goodall’s F-test is very restrictive. For these reasons, an extension of the nonparametric combination (NPC) methodology to shape analysis is proposed. Focussing on the two independent sample case, through a comparative simulation study and an application to the Mediterranean monk seal skulls dataset, the behaviour of some nonparametric permutation tests has been evaluated, showing that the proposed tests are very powerful, for both balanced and unbalanced sample sizes.     

Instance-Based Learning Algorithms

Storing and using specific instances improves the performance of several supervised learning algorithms. These include algorithms that learn decision trees, classification rules, and distributed networks. However, no investigation has analyzed algorithms that use only specific instances to solve incremental learning tasks. In this paper, we describe a framework and methodology, called instance-based learning, that generates classification predictions using only specific instances. Instance-based learning algorithms do not maintain a set of abstractions derived from specific instances. This approach extends the nearest neighbor algorithm, which has large storage requirements. We describe how storage requirements can be significantly reduced with, at most, minor sacrifices in learning rate and classification accuracy. While the storage-reducing algorithm performs well on several real-world databases, its performance degrades rapidly with the level of attribute noise in training instances. Therefore, we extended it with a significance test to distinguish noisy instances. This extended algorithm's performance degrades gracefully with increasing noise levels and compares favorably with a noise-tolerant decision tree algorithm.     

Self-organization of conceptual generalities and pattern-directed learning

Human expert decision makers can be characterized by their ability to perceive a hypothetical conceptual generality or pattern that is underlying a given collection of objects. The conventional cluster analysis is unable to generate such patterns since its clustering process is far from what the human experts actually do. That is, human experts form some concepts inductively from individual observations based on the conceptual “meaning” which the objects have. In this paper, by introducing an idea of prototype theory from a psychological domain with respect to human concept formation, an algorithm for human classification process is proposed. Based on this, the role of human generalization capability in his classification process is discussed with respect to the background semantic knowledge. The algorithm can be roughly divided into two phases; inductive prototype formation from training examples in a bottom-up fashion, and pattern-directed clustering of the instances being affected by the acquired concepts in a top-down fashion. Using a schematically-modelled example, the algorithm is illustrated with its implemented results. Our modelling method for the human classification process can be utilized for conceptual clustering that classifies a number of unknown objects into a distinguished group being affected by pre-acquired concepts.     

Feedback equivalence of constant linear systems

Two constant linear systems are said to be feedback equivalent if one can be transformed into the other via an element of the “feedback group”, which acts by state space feedback and by change of basis in the state and input spaces. Let C_n,m be the space of n-dimensional completely reachable systems with m-dimensional input (pairs of matrices, n × n and n × m). The action of the feedback group partitions the space C_n,m into finitely many orbits (equivalence classes), and the closure of each orbit is a union of orbits. If one views orbit closure as ‘deformation’, then orbit closure may be considered in terms of perturbations or system failure. In this paper we determine: (1) a classification of the orbits, and (2) the orbits contained in the closure of a given orbit. Both of these problems have been solved previously (see [1,4,6,3]); here we present simple proofs and point out a connection between this problem and the analogous problem for nilpotent matrices.     

Executable structural operational semantics in Maude

This paper describes in detail how to bridge the gap between theory and practice when implementing in Maude structural operational semantics described in rewriting logic, where transitions become rewrites and inference rules become conditional rewrite rules with rewrites in the conditions, as made possible by the new features in Maude 2. We validate this technique using it in several case studies: a functional language Fpl (evaluation and computation semantics), an imperative language WhileL (evaluation and computation semantics), Kahn’s functional language Mini-ML (evaluation or natural semantics), Milner’s CCS (with strong and weak transitions), and Full LOTOS (including ACT ONE data type specifications). In addition, on top of CCS we develop an implementation of the Hennessy–Milner modal logic for describing local capabilities of processes, and for LOTOS we build an entire tool where Full LOTOS specifications can be entered and executed (without user knowledge of the underlying implementation of the semantics). We also compare this method based on transitions as rewrites with another one based on transitions as judgements.     

Verifying task-based specifications in conceptual graphs

A conceptual model is a model of real world concepts and application domains as perceived by users and developers. It helps developers investigate and represent the semantics of the problem domain, as well as communicate among themselves and with users. In this paper, we propose the use of task-based specifications in conceptual graphs (TBCG) to construct and verify a conceptual model. Task-based specification methodology is used to serve as the mechanism to structure the knowledge captured in the conceptual model; whereas conceptual graphs are adopted as the formalism to express task-based specifications and to provide a reasoning capability for the purpose of verification. Verifying a conceptual model is performed on model specifications of a task through constraints satisfaction and relaxation techniques, and on process specifications of the task based on operators and rules of inference inherited in conceptual graphs.     

Two stage packet classification using most specific filter matching and transport level sharing

In this paper we introduce two new concepts to the design of packet classification systems. First, we propose most specific filter matching (MSFM), an improvement over the well known Cross Producting algorithm [V. Srinivasan, S. Suri, G. Varghese, M. Waldvogel, Fast and scalable layer four switching, in: Proceedings of ACM SIGCOMM, 1998] that significantly reduces the memory requirement of the earlier scheme. Second, we suggest that rules specifying the same source–destination IP prefix pair can be grouped together forming shared sets of transport level fields. This property of Transport Level Sharing (TLS), which characterizes real world classification databases is exploited for reducing a classifier’s memory requirement and for hardware acceleration.We split the classification process into two stages. First, we perform classification on source–destination IP prefix pairs using the MSFM algorithm. Second, we perform classification on transport level fields exploiting transport level sharing. It is the combination of most specific filter matching and transport level sharing which results in a scheme that requires no more than 11 dependent memory accesses in the critical path independent of the size of the classification database. The memory access bandwidth of our scheme is also bounded when our scheme is accelerated in hardware. Compared to other schemes which involve a small and predictable number of steps in the critical path (e.g., Cross Producting [V. Srinivasan, S. Suri, G. Varghese, M. Waldvogel, Fast and scalable layer four switching, in: Proceedings of ACM SIGCOMM, 1998] or Recursive Flow Classification [P. Gupta, N. McKeown, Packet classification on multiple fields, in: Proceedings of ACM SIGCOMM, 1999]) the combination of most specific filter matching and transport level sharing is associated with the least memory requirement.     

Conceptual design, manufacturability evaluation and preliminary process planning using function-form relationships in stamped metal parts

A large number of design decisions are made during the conceptual design of a part. However, there are few representation and reasoning tools for decision support during conceptual design. The conceptual design stage is characterized by a lack of complete geometric information. Existing geometric modelers require complete geometric information, while a functional reasoning methodology using a <verb, noun > representation is typically too terse. In this paper, we present a new representation called sketching abstraction for conceptual design, using the function-form relations in a design. The functionally critical part of the geometry is presented using a set of functional features, while the rest of the geometry is abstracted as a set of linkages. Part functionality is correlated with the sketching abstraction using data structures called function-form matrices. The sketching abstraction is annotated using a set of primitives, and a set of grammar rules are used to extract canonical relationships between the functional features. The sketching abstraction can be used for extracting designs that are geometrically dissimilar but functionally similar, thus providing the designer with ideas for design alternatives. The sketching abstraction can also be used to carry out domain-dependent manufacturability evaluation checks. A further use of sketching abstractions is to initiate the development of a process plan for manufacturing. Sketching abstractions are related to the solid model of a part. Thus, this representation provides a link between pure functional and pure geometric representations. The domain of application is stamped metal parts. We present the part functionality and the features used in this domain. We also illustrate the use of sketching abstractions for conceptual design, manufacturability evaluation and preliminary process planning.     

Generating fuzzy rules from training instances for fuzzy classification systems

In recent years, many methods have been proposed to generate fuzzy rules from training instances for handling the Iris data classification problem. In this paper, we present a new method to generate fuzzy rules from training instances for dealing with the Iris data classification problem based on the attribute threshold value α, the classification threshold value β and the level threshold value γ, where α  [0, 1], β  [0, 1] and γ  [0, 1]. The proposed method gets a higher average classification accuracy rate than the existing methods.     

Discovering timely information in MANETs

Timely information refers to information whose ‘most recent’ or ‘latest’ instance is most valuable. In mobile ad hoc networks (MANETs), multiple instances of a piece of timely information may be produced by different nodes at different points in time. The problem is to discover the ‘latest’ instance among all existing instances. Within the context of MANETs, timely information discovery is fundamentally different from the existing resource/service discovery problem whose goal is to discover either any instance or a subset of instances which satisfy a local query constraint that can be specified and evaluated using only local attributes of each individual node. In contrast, the timely information discovery problem imposes the global (timeliness) constraint which should best be evaluated when all the instances are considered to determine the latest instance. The complication of discovering timely information arises from the existence of multiple instances of the information, which are produced at different points in time by different nodes in the network, and the need to collect all these instances to decide the latest instance. For MANETs, the lack of infrastructure supports, frequent topology changes, and potential packet loss in wireless communications further challenge the problem of timely information discovery. This paper describes a self-organizing, peer-to-peer based approach, termed ALADIN, to discovering timely information in MANETs. In ALADIN, nodes that produce instances of the timely information are peers who self-organize an adaptive and distributed ‘search infrastructure’ to facilitate the discovery of the latest instance. A simulation study shows that ALADIN is scalable without incurring network-wide flooding in the case of large-scale networks and popular timely information, and yields a high chance of discovering the latest instance in the presence of mobility.     

Experimental analysis of self-organizing team’s behaviors

This paper is focused on the study of self-organizing team’s behaviors which are dependent on the interaction rules and the decision factors of team members. The self-organizing team’s behavior means that team members work unconditionally with one of the three work attitudes (diligence, average, and shirking). A small-world network is suggested as the basic relationships of team members. Different from the traditional models, Reciprocators encourage their friends if they work diligently and punish them if they shirk work. It is supposed that team member’s decision of choosing work attitude depends on four decision factors, humanity, herd instinct, rationality, and follower tendency. Firstly, all of the four decision factors’ weights are supposed as 0.25. Multiple experiments were conducted to analyze the behavior of a team by a multi-agent experiment system. It is found that, in order to increase the fraction of diligent team members, different strategies should be used under different Reciprocators’ fractions. Increasing Reciprocators’ fraction is beneficial to the increase of diligent members; however, the increase rate will slow down after an inflexion (here it means the inflexion of Reciprocators’ fraction). After the previous experiments study, extended experiments were developed to work on the influence of the four factors’ different weights. A self-adaptive algorithm is suggested to achieve the four decision factors’ weights. The results of self-adaptive algorithm have different influences on the team’s behaviors under different fractions of Reciprocators. Finally, influences of members’ different relationships are studied by other experiments. It is also proved that the fraction of diligent members is not dependent on the structure of team members’ relationships. The results demonstrate that the self-organizing team’s behavior can be significantly influenced by its scenario while managing a self-organizing team.     

MASAHIKO HIGASHI - ECOLOGIST,MASTER WEAVER AUGUST 11, 1954-MARCH 27, 2000

M.C. Escher is a graphic artist whose visual-spatial illusions scientists, and especially mathematicians eagerly study. However, there is much more than that. It seems that Escher's optical illusions have strikingly deeper theoretical, conceptual and philosophical layers not yet revealed. It is worth while using the abductive research method utilizing the possibilities of systems approach to reveal some of their mysteries. Escher's lithograph Reptiles is not only a work belonging to the theme of the illusion of space as Bruno Ernst, a close friend of Escher, states. This paper aims at proving in what ways Reptiles actually illustrates the concepts of onticity as reality and ontology as conceptual representation of reality, and their conceptual intermingling in a complex and systemic way. Thus, it appears that onticity and ontology, which are our ways of conceptual cognition are two facets of our systemic understanding. This paper also touches some aspects of Fuenmayor's phenomenological ontology.     

Methodology Support in CASE Tools and Its Impact on Individual Acceptance and Use: A Controlled Experiment

This paper reports the results of a controlled experiment undertaken to investigate whether the methodology support offered by a CASE tool does have an impact on the tool’s acceptance and actual use by individuals.Subjects used the process modelling tool SPEARMINT to complete a partial process model and remove all inconsistencies. Half the subjects used a variant of SPEARMINT that corrected consistency violations automatically and silently, whilst the other half used a variant of SPEARMINT that told them about inconsistencies both immediately and persistently but without automatic correction. Measurement of acceptance and prediction of actual use was based on the technology acceptance model, supplemented by beliefs about consistency rules. The impact of form of automated consistency assurance applied or hierarchical consistency rules was found to be significant at the 0.05 level with a type I error of 0.027, explaining 71.6% of the variance in CASE tool acceptance. However, intention to use and thus predicted use was of the same size for both variants of SPEARMINT, whereas perceived usefulness and perceived ease of use were affected contrarily.Internal validity of the findings was threatened by validity and reliability issues related to beliefs about consistency rules. Here, further research is needed to develop valid constructs and reliable scales. Following the experiment, a small survey among experienced users of SPEARMINT found that different forms of automated consistency assurance were preferred depending on individual, consistency rule, and task characteristics. Based on these findings, it is recommended that vendors should provide CASE tools with adaptable methodology support, which allow their users to fit automated consistency assurance to the task at hand.This work originates from the author’s time at the Fraunhofer Institute or Experimental Software Engineering (IESE), Sauerwiesen 6, 67661 Kaiserslautern, Germany.     

Moving with the Times: IT Research and the Boundaries of CSCW

The field of CSCW research emerged with the development of distributed computing systems and attempts to understand the socially organized (‘collaborative’ or ‘cooperative’) nature of work in order to embed such systems in the workplace. As a field of interdisciplinary inquiry CSCW was motivated by technological developments and the need to understand the particular contexts within which those developments were intended to resonate. In other words, it is no mere accident that CSCW took work as its topic and resource – the historical nature of IT research from which the field emerged meant that for all practical purposes it could not be otherwise. Yet times change. IT research moves on. Today mobile, ambient, pervasive, ubiquitous, mixed reality and wearable computing, et cetera, are of fundamental concern to the contemporary computing research community. Furthermore, these developments are accompanied by a movement away from the workplace to focus on diverse settings in everyday life: homes, games, museums, photography, tourism, performances, indeed diverse bodies of people and pursuits that generally fall under the conceptual rubric of the ‘ludic’. Accompanying this shift away from work is a call for new approaches and concepts that will enable researchers to better understand the ludic and inform design appropriately. In this paper we seek to address the boundaries of CSCW and the ability of CSCW to respond to contemporary research agendas. We present an ethnomethodological study of a location-based mixed reality game to demonstrate the continued relevance of CSCW approaches and concepts to contemporary agendas in IT research.     

Toward a well-founded theory for multi-level conceptual modeling

Multi-level conceptual modeling addresses the representation of subject domains dealing explicitly with multiple classification levels. Despite the recent advances in multi-level modeling techniques, we believe that the literature in multi-level conceptual modeling would benefit from a theory that: (1) formally characterizes the nature of classification levels and (2) precisely defines the structural relations that may occur between elements of different classification levels. This work aims to fill this gap by proposing an axiomatic theory that can be considered a reference top-level ontology for types in multi-level conceptual modeling. The theory provides the modeler with basic concepts and patterns to articulate domains that require multiple levels of classification as well as to inform the development of well-founded languages for multi-level conceptual modeling. The whole theory is founded on a basic instantiation relation and characterizes the concepts of individuals and types, with types organized in levels related by instantiation. Further, it includes intra-level structural relations that are used to define expressive multi-level models and cross-level relations that allow us to account for and incorporate the different notions of power type in the literature.     

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.     

Ontology oriented programming in go!

In this paper we introduce the knowledge representation features of a new multi-paradigm programming language called go! that cleanly integrates logic, functional, object oriented and imperative programming styles. Borrowing from L&O [1] go! allows knowledge to be represented as a set of labeled theories incrementally constructed using multiple-inheritance. The theory label is a constructor for instances of the class. The instances are go!’s objects. A go! theory structure can be used to characterize any knowledge domain. In particular, it can be used to describe classes of things, such as people, students, etc., their subclass relationships and characteristics of their key properties. That is, it can be used to represent an ontology. For each ontology class we give a type definition—we declare what properties, with what value type, instances of the class have—and we give a labeled theory that defines these properties. Subclass relationships are reflected using both type and theory inheritance rules. Following [2], we shall call this ontology oriented programming. This paper describes the go! language and its use for ontology oriented programming, comparing its expressiveness with Owl, particularly Owl Lite[3]. The paper assumes some familiarity with ontology specification using Owl like languages and with logic and object oriented programming.     

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.