Token-based pull production control systems: an introductory overview

Since the advent of Kanban, pull systems have been widely used in practice and have been widely studied by researchers. During the last decades, several types of pull systems have emerged. Numerous articles have been published to introduce new paradigms or new principles for just-in-time systems as well as new approaches to evaluate them or to optimize their performance. An important feature of these systems, which is common to many other production control systems, is the use of tokens, which usually consist of cards that authorize certain production tasks to be performed. Tokens can be used in various manners to control production and can be combined with several other mechanisms with the objective of reducing the work in progress and the lead times, while meeting customers’ demand. This article proposes an introductory overview of existing research works in this area. In this respect, we suggest a classification of pull-inspired production control systems, which allows us to distinguish up to 18 different systems. For each type of system, we study its basic principles, the flow control strategy, and the parameters affecting its performance. This survey aims at facilitating the understanding of the different proposals made by researchers and highlighting their common points and differences.     

Converting scenarios to CSP traces with Mise en Scene for requirements-based programming

The Requirements-to-Design-to-Code (R2D2C) project of NASA’s Software Engineering Laboratory is based on inferring a formal specification expressed in Communicating Sequential Processes (CSP) from system requirements supplied in the form of CSP traces. The traces, in turn, are to be derived from scenarios, a user-friendly medium used to describe the required behavior of computer systems under development. An extensive survey of the “scenario” concept and an overview of scenario-based approaches to system engineering are presented. This work, called Mise en Scene, defines a new scenario medium (scenario notation language, SNL) suitable for control-dominated systems, coupled with a two-stage process for automatic translation of scenarios to a new trace medium (trace notation language, TNL), which encompasses CSP traces. Notes on progress toward a “smart” scenario authoring tool are provided, as well as a detailed case study. This work was originally presented at the Software Engineering Workshop (SEW-31) in March 2007. It was supported by research grants from Canada’s Natural Sciences and Engineering Research Council (NSERC).     

Cognitive and synthetic behavior of avatars in intelligent virtual environments

In intelligent virtual environments (IVEs), it is a challenging research issue to provide the intelligent virtual actors (or avatars) with the ability of visual perception and rapid response to virtual world events. Modeling an avatar’s cognitive and synthetic behavior appropriately is of paramount important in IVEs. We propose a new cognitive and behavior modeling methodology that integrates two previously developed complementary approaches. We present expression cloning, walking synthetic behavior modeling, and an autonomous agent cognitive model for driving an avatar’s behavior. Facial expressions are generated using our own-developed rule-based state transition system. Facial expressions are further personalized for individuals by expression cloning. An avatar’s walking behavior is modeled using a skeleton model that is implemented by seven-motion sequences and finite state machines (FSMs). We discuss experimental results demonstrating the benefits of our approach.     

Socio-Technical and Soft Approaches to Information Requirements Elicitation in the Post-Methodology Era

The contributors to this special issue focus on socio-technical and soft approaches to information requirements elicitation and systems development. They represent a growing body of research and practice in this field. This review presents an overview and analysis of the salient themes within the papers encompassing their common underlying framework, the methodologies and tools and techniques presented, the organisational situations in which they are deployed and the issues they seek to address. It will be argued in the review that the contributions to this special edition exemplify the ‘post-methodological era’ and the ‘contingency approaches’ from which it is formed.     

Symbolic data analysis tools for recommendation systems

Recommender systems have become an important tool to cope with the information overload problem by acquiring data about user behavior. After tracing the user’s behavior, through actions or rates, computational recommender systems use information- filtering techniques to recommend items. In order to recommend new items, one of the three major approaches is generally adopted: content-based filtering, collaborative filtering, or hybrid filtering. This paper presents three information-filtering methods, each of them based on one of these approaches. In our methods, the user profile is built up through symbolic data structures and the user and item correlations are computed through dissimilarity functions adapted from the symbolic data analysis (SDA) domain. The use of SDA tools has improved the performance of recommender systems, particularly concerning the find good items task measured by the half-life utility metric, when there is not much information about the user.     

Intelligent systems using Web-pages as knowledge base for statistical decision making

In this paper, we propose an approach to the construction of an intelligent system that handles various domain information provided on the Internet. The intelligent system adopts statistical decision-making as its reasoning framework and automatically constructs probabilistic knowledge, required for its decision-making, from Web-pages. This construction of probabilistic knowledge is carried out using aprobability interpretation idea that transforms statements in Web-pages into constraints on the subjective probabilities of a person who describes the statements. In this paper, we particularly focus on describing the basic idea of our approach and on discussing difficulties in our approach, including our perspective. Kazunori Fujimoto: He received bachelor’s degree from Department of Electrical Engineering, Doshisha University, Japan, in 1989, and master’s degree from Division of Applied Systems Science, Kyoto University, Japan, in 1992. From there, he joined NTT Electrical Communications Laboratories, Tokyo, Japan, and has been engaged in research on Artificial Intelligence. He is currently interested in probabilistic reasoning, knowledge acquisition, and especially in quantitative approaches to research in human cognition and behavior. Mr. Fujimoto is a member of Decision Analysis Society, The Behaviormetric Society of Japan, Japanese Society for Artificial Intelligence, Information Processing Society of Japan, and Japanese Society for Fuzzy Theory and Systems. Kazumitsu Matsuzawa: He received B.S. and M.S. degrees in electronic engineering from Tokyo Institute of Technology, Tokyo, Japan, in 1975 and 1977. From there, he joined NTT Electrical Communications Laboratories, Tokyo, Japan, and has been engaged in research on computer architecture and the design of LSI. He is currently concerned with AI technology. Mr. Matsuzawa is a member of The Institute of Electronics, Information and Communication Engineers, Information Processing Society of Japan, Japanese Society for Artificial Intelligence, and Japanese Society for Fuzzy Theory and Systems.     

Guest editorial: special issue on a decade of mining the Web

As editors of the Special Issue on a Decade of Mining the Web, we provide a brief overview of how Web mining evolved from the first Web mining workshop (WEBKDD’99) till today. We then introduce the papers of the special issue. Each of them is in a domain of Web mining research; it contains a survey of the past and a vision for the future.     

Industry needs and research directions in requirements engineering for embedded systems

The industry has a strong demand for sophisticated requirements engineering (RE) methods in order to manage the high complexity of requirements specifications for software-intensive embedded systems and ensure a high requirements quality. RE methods and techniques proposed by research are only slowly adopted by the industry. An important step to improve the adoption of novel RE approaches is to gain a detailed understanding of the needs, expectations, and constraints that RE approaches must satisfy. We have conducted an industrial study to gain an in-depth understanding of practitioners’ needs concerning RE research and method development. The study involved qualitative interviews as well as quantitative data collection by means of questionnaires. We report on the main results of our study related to five aspects of RE approaches: the use of requirements models, the support for high system complexity, quality assurance for requirements, the transition between RE and architecture design, and the interrelation of RE and safety engineering. Based on the results of the study, we draw conclusions for future RE research.     

Studying high reliability systems in the probabilistic school of B. V. Gnedenko

We give a survey of the works of B.V. Gnedenko’s reliability school, starting from 1950s and up until the latest years in two directions: (1) invariance of state distributions for queueing systems and networks, (2) asymptotic behavior of a redundant system’s characteristics under low load.     

Using FORAY Models to Enable MPSoC Memory Optimizations

With the technology advances it becomes feasible to implement a large multiprocessor system on a single chip. In such Systems-on-Chip (SoCs), a significant portion of energy is spent in the memory subsystem. There are several approaches reducing this energy, including the ones at physical, architecture and algorithmic levels. Classical approaches, including algorithmic and some architectural approaches, use static analysis and transformation of the application source code. However, often it is not possible to perform static analysis and optimization of a program’s memory access behavior unless the program is written in an easily analyzable form, e.g., free from pointer arithmetic. In this paper, we introduce the FORAY model of a program that allows aggressive analysis of the application’s memory behavior and enables such optimizations on arbitrary code which are not possible to apply otherwise. We then present FORAY-GEN: an automated profile-based approach for extraction of the FORAY model from the original program. We also outline our approach in applying FORAY-GEN for multiprocessor SoCs. We demonstrate how FORAY-GEN enhances applicability of other memory subsystem optimization approaches, resulting in an average of two times increase in the number of memory references that can be analyzed by existing static approaches.     

Cognitive and learning difficulties and how they affect access to IT systems

In October 2005, the IBM Human Ability and Accessibility Center and T.J. Watson Research Center hosted a symposium on “cognitive and learning difficulties and how they affect access to IT systems”. The central premise of the symposium was the recognition that cognitive and learning difficulties have a profound impact on a person’s ability to interact with information technology (IT) systems, but that little support is currently being offered by those systems. By bringing together internationally renowned experts from a variety of different, but complementary, research fields, the symposium aimed to provide a complete overview of the issues related to this topic. This paper summarises the discussions and findings of the symposium.     

Language and Space: a two-level semantic approach based on principles of ontological engineering

An increasing number of applications for dialogue systems presuppose an ability to deal appropriately with space. Dialogues with assistance systems, intelligent mobility devices and navigation systems all commonly involve the use of spatial language. For smooth interaction, this spatial language cannot be interpreted ‘in the abstract’—it must instead be related directly to a user’s physical location, orientation, goals and needs and be embedded appropriately in a system’s interaction. This is far from straightforward. The situated interpretation of natural language concerning space, spatial relationships and spatial activities represents an unsolved challenge at this time. Despite extensive work on spatial language involving many disciplines, there are no generally accepted accounts that provide support for the kind of flexible language use observed in real human-human spatial dialogues. In this paper, I review some recent approaches to the semantics for natural language expressions concerning space in order to motivate a two-level semantic-based approach to the interpretation of spatial language. This draws on a new combination of natural language processing and principles of ontological engineering and stands as a foundation for more sophisticated and natural dialogue system behavior where spatial information is involved.     

Quadruped virtual robot simulation in a virtual environment obeying physical laws

In the development of a robot, the validation of that robot with the use of real machinery takes a considerable amount of time and money. In particular, it is difficult to validate a robot’s behavior in an unsafe place. The developers also have to pay attention to virtual debugging. Using a program validated in VR space makes the verification of a real machine’s behavior more efficient. In this research, we make a virtual robot walk on a road autonomously by using a program where the virtual robot tracks a line in a virtual environment.     

A self-adaptable query allocation framework for distributed information systems

In large-scale distributed information systems, where participants are autonomous and have special interests for some queries, query allocation is a challenge. Much work in this context has focused on distributing queries among providers in a way that maximizes overall performance (typically throughput and response time). However, preserving the participants’ interests is also important. In this paper, we make the following contributions. First, we provide a model to define the participants’ perception of the system regarding their interests and propose measures to evaluate the quality of query allocation methods. Then, we propose a framework for query allocation called Satisfaction-based Query Load Balancing (SQLB, for short), which dynamically trades consumers’ interests for providers’ interests based on their satisfaction. Finally, we compare SQLB, through experimentation, with two important baseline query allocation methods, namely Capacity based and Mariposa-like. The results demonstrate that SQLB yields high efficiency while satisfying the participants’ interests and significantly outperforms the baseline methods. Work partially funded by ARA “Massive Data” of the French ministry of research (Respire project) and the European Strep Grid4All project.     

Text summarisation in progress: a literature review

This paper contains a large literature review in the research field of Text Summarisation (TS) based on Human Language Technologies (HLT). TS helps users manage the vast amount of information available, by condensing documents’ content and extracting the most relevant facts or topics included in them. The rapid development of emerging technologies poses new challenges to this research field, which still need to be solved. Therefore, it is essential to analyse its progress over the years, and provide an overview of the past, present and future directions, highlighting the main advances achieved and outlining remaining limitations. With this purpose, several important aspects are addressed within the scope of this survey. On the one hand, the paper aims at giving a general perspective on the state-of-the-art, describing the main concepts, as well as different summarisation approaches, and relevant international forums. Furthermore, it is important to stress upon the fact that the birth of new requirements and scenarios has led to new types of summaries with specific purposes (e.g. sentiment-based summaries), and novel domains within which TS has proven to be also suitable for (e.g. blogs). In addition, TS is successfully combined with a number of intelligent systems based on HLT (e.g. information retrieval, question answering, and text classification). On the other hand, a deep study of the evaluation of summaries is also conducted in this paper, where the existing methodologies and systems are explained, as well as new research that has emerged concerning the automatic evaluation of summaries’ quality. Finally, some thoughts about TS in general and its future will encourage the reader to think of novel approaches, applications and lines to conduct research in the next years. The analysis of these issues allows the reader to have a wide and useful background on the main important aspects of this research field.     

Particularism,Analogy, and Moral Cognition

‘Particularism’ and ‘generalism’ refer to families of positions in the philosophy of moral reasoning, with the former playing down the importance of principles, rules or standards, and the latter stressing their importance. Part of the debate has taken an empirical turn, and this turn has implications for AI research and the philosophy of cognitive modeling. In this paper, Jonathan Dancy’s approach to particularism (arguably one of the best known and most radical approaches) is questioned both on logical and empirical grounds. Doubts are raised over whether Dancy’s brand of particularism can adequately explain the graded nature of similarity assessments in analogical arguments. Also, simple recurrent neural network models of moral case classification are presented and discussed. This is done to raise concerns about Dancy’s suggestion that neural networks can help us to understand how we could classify situations in a way that is compatible with his particularism. Throughout, the idea of a surveyable standard—one with restricted length and complexity—plays a key role. Analogical arguments are taken to involve multidimensional similarity assessments, and surveyable contributory standards are taken to be attempts to articulate the dimensions of similarity that may exist between cases. This work will be of relevance both to those who have interests in computationally modeling human moral cognition and to those who are interested in how such models may or may not improve our philosophical understanding of such cognition.     

Control and estimation under information constraints: Toward a unified theory of control,computation and communications

An attempt is made to overview an emerging area of research devoted to analysis and design of control systems under constraints caused by limited information capacity of communication channels. The problem’s prehistory dating back to the 1960s–1970s, as well as the new approaches that appeared during the last decade were analyzed. Much attention was paid to various versions of the celebrated data rate theorem. Consideration was given to the problems of control through the communication networks and some results obtained for the nonlinear systems. The basic application areas were listed in brief.     

Security and privacy issues in P2P streaming systems: A survey

Streaming applications over Peer-To-Peer (P2P) systems have gained an enormous popularity. Success always implies increased concerns about security, protection, privacy and all the other ‘side’ properties that transform an experimental application into a service. Research on security for P2P streaming started to flourish, but no comprehensive security analysis over the current P2P solutions has yet been attempted. There are no best practices in system design, no (widely) accepted attack models, no measurement-based studies on security threats to P2P streaming, nor even general surveys investigating specific security aspects for these systems. This paper addresses this last aspect. Starting from existing analyses and security models in the related literature, we give an overview on security and privacy considerations for P2P streaming systems. Our analysis emphasizes two major facts: (i) the Byzantine–Altruistic–Rational (BAR) model offers stronger security guarantees compared to other approaches, at the cost of higher complexity and overhead; and (ii) the general perception (not necessarily the truth, but a commonplace belief) that it is necessary to sacrifice accuracy or performance in order to tolerate faults or misbehaviors, is not always true.