Utilization of a systemic business process re-engineering method as a tool to improve software process quality

This paper suggests that a software process can be viewed as an instance of a business process. Therefore software process improvement might be achieved by applying the concepts of Business Process Re-engineering (BPR). BPR is introduced and the recent work of Jacobson, using object-oriented concepts to construct a BPR framework, is described. The paper critiques Jacobson's approach as being essentially reductionist, and presents an alternative approach, State-Behaviour Modelling (SBM), that utilizes systems principles in the analysis of problem situations, while generating object models. The application of SMB to model and improve a component of a software development process, is presented.     

‘Use’ discourses in system development: Can communication be improved?

This paper aims to provide a basis for renewed talk about use in computing. Four current discourse arenas are described. Different intentions manifest in each arena are linked to failures in translation, different terminologies crossing disciplinary and national boundaries non-reflexively. Analysis of transnational use discourse dynamics shows much miscommunication. Conflicts like that between the Scandinavian System Development School and the usability approach have less current salience. Renewing our talk about use is essential to a participatory politics of information technology and will lead to clearer perception of the implications of letting new systems becoming primary media of social interaction.     

Shakespeare vs. fletcher: A stylometric analysis by radial basis functions

In this paper we show, for the first time, how Radial Basis Function (RBF) network techniques can be used to explore questions surrounding authorship of historic documents. The paper illustrates the technical and practical aspects of RBF's, using data extracted from works written in the early 17th century by William Shakespeare and his contemporary John Fletcher. We also present benchmark comparisons with other standard techniques for contrast and comparison.David Lowe is Professor of Neural Computing at Aston University, UK. His research interests span from the theoretical aspects of dynamical systems theory and statistical pattern processing, to a wide range of application domains, from financial market analysis (Novel Exploitation of Neural Network Methods in Financial Markets, invited paper,World Conference on Computational Intelligence, vol. VI, pp. 3623–28, 1994) to the artificial nose (Novel Topographic Nonlinear Feature Extraction using Radial Basis Functions for Concentration Coding in the Artificial Nose,3 ^rd IEE International Conference on Artificial Neural Networks, pp. 95–99, Conference Publication number 372, The Institute of Electrical Engineers, 1993).Robert Matthews is a visiting research fellow at Aston University. His research interests include probability, number theory and astronomy. His recent paper inNature (vol. 374, pp. 681–82, 1995) somehow managed to combine all three.     

Obvious inferences

The notion of obvious inference in predicate logic is discussed from the viewpoint of proof-checker applications in logic and mathematics education. A class of inferences in predicate logic is defined and it is proposed to identify it with the class of obvious logical inferences. The definition is compared with other approaches. The algorithm for implementing the obviousness decision procedure follows directly from the definition.     

Collaboration and Teamwork: Immersion and Presence in an Online Learning Environment

In the world of OTIS, an online Internet School for occupational therapists, students from four European countries were encouraged to work collaboratively through problem-based learning by interacting with each other in a virtual semi-immersive environment. This paper describes, often in their own words, the experience of European occupational therapy students working together across national and cultural boundaries. Collaboration and teamwork were facilitated exclusively through an online environment, since the students never met each other physically during the OTIS pilot course. The aim of the paper is to explore the observations that (1) there was little interaction between students from different tutorial groups and (2) virtual teamwork developed in each of the cross-cultural tutorial groups. Synchronous data from the students was captured during tutorial sessions and peer-booked meetings and analyzed using the qualitative constructs of immersion, presence and reflection in learning. The findings indicate that immersion was experienced only to a certain extent. However, students found both presence and shared presence, within their tutorial groups, to help collaboration and teamwork. Other evidence suggests that communities of interest were established. Further study is proposed to support group work in an online learning environment. It is possible to conclude that collaborative systems can be designed, which encourage students to build trust and teamwork in a cross cultural online learning environment.This revised version was published online in March 2005 with corrections to the cover dateFunded by the European Union through the TENTelecom programme.     

An analysis of a contention resolution algorithm

Summary A single multiaccess channel is studied with the outcome of a transmission being either idle, success, or collision (ternary channel). Packets involved in a collision must be retransmitted, and an efficient way to solve a collision is known in the literature as Gallager-Tsybakov-Mikhailov algorithm. Performance analysis of the algorithm is quite hard. In fact, it bases on a numerical solution of some recurrence equations and on a numerical evaluation of some series. The obvious drawback of it is lack of insight into the behavior of the algorithm. We shall present a new approach of looking at the algorithm and discuss some attempts of analyzing its performance. In particular, expected lengths of a resolution interval and a conflict resolution interval as well as throughput of the algorithm will be discussed using asymptotic approximation and a small input rate approximation.     

Physically touching and tasting virtual objects enhances the realism of virtual experiences

Experiment 1 explored the impact of physically touching a virtual object on how realistic the virtual environment (VE) seemed to the user. Subjects in a no touch group picked up a 3D virtual image of a kitchen plate in a VE, using a traditional 3D wand. See and touch subjects physically picked up a virtual plate possessing solidity and weight, using a technique called tactile augmentation. Afterwards, subjects made predictions about the properties of other virtual objects they saw but did not interact with in the VE. See and touch subjects predicted these objects would be more solid, heavier, and more likely to obey gravity than the no touch group. In Experiment 2 (a pilot study), subjects physically bit a chocolate bar in one condition, and imagined biting a chocolate bar in another condition. Subjects rated the event more fun and realistic when allowed to physically bite the chocolate bar. Results of the two experiments converge with a growing literature showing the value of adding physical qualities to virtual objects. This study is the first to empirically demonstrate the effectiveness of tactile augmentation as a simple, safe, inexpensive technique with large freedom of motion for adding physical texture, force feedback cues, smell and taste to virtual objects. Examples of practical applications are discussed.Based in part on Physically touching virtual objects using tactile augmentation enhances the realism of virtual environments' by Hunter Hoffman which appeared in the Proceedings of the IEEE Virtual Reality Annual International Symposium '98, Atlanta GA, pp 59–63. ¢ 1998 IEEE.     

Design sensitivity analysis of nonlinear dynamic response of structural and mechanical systems

This paper describes a unified variational theory for design sensitivity analysis of nonlinear dynamic response of structural and mechanical systems for shape, nonshape, material and mechanical properties selection, as well as control problems. The concept of an adjoint system, the principle of virtual work and a Lagrangian-Eulerian formulation to describe the deformations and the design variations are used to develop a unified view point. A general formula for design sensitivity analysis is derived and interpreted for usual performance functionals. Analytical examples are utilized to demonstrate the use of the theory and give insights for application to more complex problems that must be treated numerically.Derivatives The comma notation for partial derivatives is used, i.e. G,_u = G/u. An upper dot represents material time derivative, i.e. ü = ²u/t². A prime implies derivative with respect to the time measured in the reference time-domain, i.e. u = du/d.     

Modular Control and Coordination of Discrete-Event Systems

In the supervisory control of discrete-event systems based on controllable languages, a standard way to handle state explosion in large systems is by modular supervision: either horizontal (decentralized) or vertical (hierarchical). However, unless all the relevant languages are prefix-closed, a well-known potential hazard with modularity is that of conflict. In decentralized control, modular supervisors that are individually nonblocking for the plant may nevertheless produce blocking, or even deadlock, when operating on-line concurrently. Similarly, a high-level hierarchical supervisor that predicts nonblocking at its aggregated level of abstraction may inadvertently admit blocking in a low-level implementation. In two previous papers, the authors showed that nonblocking hierarchical control can be guaranteed provided high-level aggregation is sufficiently fine; the appropriate conditions were formalized in terms of control structures and observers. In this paper we apply the same technique to decentralized control, when specifications are imposed on local models of the global process; in this way we remove the restriction in some earlier work that the plant and specification (marked) languages be prefix-closed. We then solve a more general problem of coordination: namely how to determine a high level coordinator that forestalls conflict in a decentralized architecture when it potentially arises, but is otherwise minimally intrusive on low-level control action. Coordination thus combines both vertical and horizontal modularity. The example of a simple production process is provided as a practical illustration. We conclude with an appraisal of the computational effort involved.     

An investigation of the maintenance and support characteristics of commercial software

This study demonstrates an objective method used to evaluate the enhanceability of commercial software. It examines the relationship between enhancement and repair, and suggests that enhancement be considered when developing formal models of defect cause. Another definition of defect-prone software is presented that concentrates attention on software that requires unusually high repair considering the magnitude of planned enhancement.     

Bucket Elimination: a Unifying Framework for Processing Hard and Soft Constraints

This position paper argues that extending the CSP model to a richer set of tasks such as, constraint optimization, probabilistic inference and decision theoretic tasks can be done within a unifying framework called bucket elimination. The framework allows uniform hybrids for combining elimination and conditioning guided by the problem's structure and for explicating the tradeoffs between space and time and between time and accuracy.     

Lattice Image Processing: A Unification of Morphological and Fuzzy Algebraic Systems

This paper explores some aspects of the algebraic theory of mathematical morphology from the viewpoints of minimax algebra and translation-invariant systems and extends them to a more general algebraic structure that includes generalized Minkowski operators and lattice fuzzy image operators. This algebraic structure is based on signal spaces that combine the sup-inf lattice structure with a scalar semi-ring arithmetic that possesses generalized additions and -multiplications. A unified analysis is developed for: (i) representations of translation-invariant operators compatible with these generalized algebraic structures as nonlinear sup- convolutions, and (ii) kernel representations of increasing translation-invariant operators as suprema of erosion-like nonlinear convolutions by kernel elements. The theoretical results of this paper develop foundations for unifying large classes of nonlinear translation-invariant image and signal processing systems of the max or min type. The envisioned applications lie in the broad intersection of mathematical morphology, minimax signal algebra and fuzzy logic.Petros Maragos received the Diploma degree in electrical engineering from the National Technical University of Athens in 1980, and the M.Sc.E.E. and Ph.D. degrees from Georgia Tech, Atlanta, USA, in 1982 and 1985.In 1985 he joined the faculty of the Division of Applied Sciences at Harvard University, Cambridge, Massachusetts, where heworked for 8 years as professor of electrical engineering, affiliated with the interdisciplinary Harvard Robotics Lab. He has also been a consultant to several industry research groups including Xeroxs research on document image analysis. In 1993, he joined the faculty of the School of Electrical and Computer Engineering at Georgia Tech. During parts of 1996-98 he was on academic leave working as a senior researcher at the Institute for Language and Speech Processing in Athens. In 1998, he joined the faculty of the National Technical University of Athens where he is currently working as professor of electrical and computer engineering. His current research and teaching interests include the general areas of signal processing, systems theory, pattern recognition, and their applications to image processing and computer vision, and computer speech processing and recognition.He has served as associate editor for the IEEE Trans. on Acoustics, Speech, and Signal Processing, editorial board member for the Journal of Visual Communications and Image Representation, and guest editor for the IEEE Trans. on Image Processing; general chairman for the 1992 SPIE Conference on Visual Communications and Image Processing, and co-chairman for the 1996 International Symposium on Mathematical Morphology; member of two IEEE DSP committees; and president of the International Society for Mathematical Morphology.Dr. Maragos research work has received several awards, including: a 1987 US National Science Foundation Presidential Young Investigator Award; the 1988 IEEE Signal Processing Societys Paper Award for the paper Morphological Filters; the 1994 IEEE Signal Processing Societys Senior Award and the 1995 IEEE Baker Award for the paper Energy Separation in Signal Modulations with Application to Speech Analysis; and the 1996 Pattern Recognition Societys Honorable Mention Award for the paper Min-Max Classifiers. In 1995, he was elected Fellow of IEEE for his contributions to the theory and applications of nonlinear signal processing systems.     

Explanations in cognitive science

Cognitive science may be loosely described as the activity of trying to model aspects of human behaviour upon a computer. It has emerged as a blending of the techniques of artificial intelligence and cognitive psychology but these two disciplines have different, and incompatible, philosophies. Searle has detected elements of behaviourism and operationism within artificial intelligence, whereas cognitive psychology is essentially anti-behaviourist. It is argued that cognitive science needs to distinguish between competence and performance in order to clarify this point, and that such a distinction has far-reaching effects on how we view computer simulations of behaviour.     

Coordinating Multiple Agents via Reinforcement Learning

In this paper, we attempt to use reinforcement learning techniques to solve agent coordination problems in task-oriented environments. The Fuzzy Subjective Task Structure model (FSTS) is presented to model the general agent coordination. We show that an agent coordination problem modeled in FSTS is a Decision-Theoretic Planning (DTP) problem, to which reinforcement learning can be applied. Two learning algorithms, coarse-grained and fine-grained, are proposed to address agents coordination behavior at two different levels. The coarse-grained algorithm operates at one level and tackle hard system constraints, and the fine-grained at another level and for soft constraints. We argue that it is important to explicitly model and explore coordination-specific (particularly system constraints) information, which underpins the two algorithms and attributes to the effectiveness of the algorithms. The algorithms are formally proved to converge and experimentally shown to be effective.     

Some Observations on the Semantics of “Information”

The term Information is widely used in the rhetoric of the Information Society, a rhetoric which some critics have judged to be empty, at least in part because of the overextension and inconsistent use of this word. We review the emergence of the concept of Information, identify a number of dimensions of similarity and difference in the way that the concept of Information is used and defined, and point up some specific areas where further critical attention is needed, of especial concern to the field of Information Systems. In particular we highlight some problems in identifying and understanding Information Work, and some research themes relevant to Virtual Organisations and Computer Supported Collaborative Work.     

Toward Cultural Oncology: The Evolutionary Information Dynamics of Cancer

'Racial' disparities among cancers, particularly of the breast and prostate, are something of a mystery. For the US, in the face of slavery and its sequelae, centuries of interbreeding has greatly leavened genetic differences between Blacks and Whites, but marked contrasts in disease prevalence and progression persist. Adjustment for socioeconomic status and lifestyle, while statistically accounting for much of the variance in breast cancer, only begs the question of ultimate causality. Here we propose a more basic biological explanation that extends the theory of immune cognition to include an elaborate tumor control mechanism constituting the principal selection pressure acting on pathologically mutating cell clones. The interplay between them occurs in the context of an embedding, highly structured, system of culturally-specific psychosocial stress. A rate distortion argument finds that larger system able to literally write an image of itself onto the disease process, in terms of enhanced risk behaviour, accelerated mutation rate, and depressed mutation control. The dynamics are analogous to punctuated equilibrium in simple evolutionary systems, accounting for the staged nature of disease progression. We conclude that 'social exposures' are, for human populations, far more than incidental cofactors in cancer etiology. Rather, they are part of the basic biology of the disorder. The aphorism that culture is as much a part of human biology as the enamel on our teeth appears literally true at a fundamental cellular level.     

A predicate transformer for the progress property ‘to-always’

The temporal property to-always has been proposed for specifying progress properties of concurrent programs. Although the to-always properties are a subset of the leads-to properties for a given program, to-always has more convenient proof rules and in some cases more accurately describes the desired system behavior. In this paper, we give a predicate transformerwta, derive some of its properties, and use it to define to-always. Proof rules for to-always are derived from the properties ofwta. We conclude by briefly describing two application areas, nondeterministic data flow networks and self-stabilizing systems where to-always properties are useful.     

Explanation-based interpretation of open-textured concepts in logical models of legislation

In this paper we discuss a view of the Machine Learning technique called Explanation-Based Learning (EBL) or Explanation-Based Generalization (EBG) as a process for the interpretation of vague concepts in logic-based models of law.The open-textured nature of legal terms is a well-known open problem in the building of knowledge-based legal systems. EBG is a technique which creates generalizations of given examples on the basis of background domain knowledge. We relate these two topics by considering EBG's domain knowledge as corresponding to statute law rules, and EBG's training example as corresponding to a precedent case.By making the interpretation of vague predicates as guided by precedent cases, we use EBG as an effective process capable of creating a link between predicates appearing as open-textured concepts in law rules, and predicates appearing as ordinary language wording for stating the facts of a case.Standard EBG algorithms do not change the deductive closure of the domain theory. In the legal context, this is only adequate when concepts vaguely defined in some law rules can be reformulated in terms of other concepts more precisely defined in other rules. We call theory reformulation the process adopted in this situation of complete knowledge.In many cases, however, statutory law leaves some concepts completely undefined. We then propose extensions to the EBG standard that deal with this situation of incomplete knowledge, and call theory revision the extended process. In order to fill in knowledge gaps we consider precedent cases supplemented by additional heuristic information. The extensions proposed treat heuristics represented by abstraction hierarchies with constraints and exceptions.In the paper we also precisely characterize the distinction between theory reformulation and theory revision by stating formal definitions and results, in the context of the Logic Programming theory.We offer this proposal as a possible contribution to cross fertilization between machine learning and legal reasoning methods.     

Personalized Course Navigation Based on Grey Relational Analysis

Web personalization has quickly changed from a value-added facility to a service required in presenting large quantities of information because individual users of the Internet have various needs and preferences in seeking information. This paper presents a novel personalized recommendation system with online preference analysis in a distance learning environment called Coursebot. Users can both browse and search for course materials by using the interface of Coursebot. Moreover, the proposed system includes appropriate course materials ranked according to a users interests. In this work, an analysis measure is proposed to combine typical grey relational analysis and implicit rating, and thus a users interests are calculated from the content of documents and the users browsing behavior. This algorithms low computational complexity and ease of adding knowledge support online personalized analysis. In addition, the user profiles are dynamically revised to provide efficiently personalized information that reflects a users interests after each page is visited.     

Human-oriented and machine-oriented reasoning: Remarks on some problems in the history of Automated Theorem Proving

Examples in the history of Automated Theorem Proving are given, in order to show that even a seemingly mechanical activity, such as deductive inference drawing, involves special cultural features and tacit knowledge. Mechanisation of reasoning is thus regarded as a complex undertaking in cultural pruning of human-oriented reasoning. Sociological counterparts of this passage from human- to machine-oriented reasoning are discussed, by focusing on problems of man-machine interaction in the area of computer-assisted proof processing.