Sensors and controllers location in distributed systems—A survey

A survey of the field of optimal sensors and/or controllers location for dynamical distributed parameter systems modelled by partial differential equations is presented. The recent contributions in this field are grouped according to the main goal for which the location problem is developed, namely: system identification, state estimation, and optimal control. In order to pose the sensors and controllers location problem, the semigroup approach for modelling distributed linear systems is briefly reviewed together with its equivalent (infinite dimensional) and approximate (finite dimensional) Fourier expansion representations. After presenting a concise general review of the several methods considered in the current literature, a classification of methods is also proposed. The main classifying factor concerns the use of N-modal approximation schemes, and the different stages of the optimization procedure in which they are required.     

A survey on legal question–answering systems

Many legal professionals think the explosion of information about local, regional, national, and international legislation makes their practice more costly, time-consuming, and error-prone. The two main reasons are that most legislation is usually unstructured, and the tremendous amount and pace with which laws are released causes information overload in their daily tasks. In the case of the legal domain, the research community agrees that a system allowing to generate of automatic responses to legal questions could substantially impact many practical implications in daily activities. The degree of usefulness is such that even a semi-automatic solution could significantly help reduce the workload. This is mainly because a Question–Answering system could automatically process a massive amount of legal resources to answer a question or doubt in seconds. It could save resources in the form of effort, money, and time for many professionals in the legal sector. This work quantitatively and qualitatively survey the existing solutions to meet this challenge.     

Direct methods for studying dynamics of large-scale electric power systems—A survey

This paper attempts to give a unified overview of how direct methods solve the transient stability problem of large-scale power systems. Two distinct methodologies are considered and discussed. The first concerns application of the direct Lyapunov method to the conventional transient stability analysis. Both scalar and vector Lyapunov approaches are envisaged and their respective merits and potentialities are compared. Particular attention is also paid to the estimation of ‘practical’ stability domains, aiming to overcome the usual conservativeness of the Lyapunov criterion. The second methodology focuses on the derivation of stability indices, intended for on-line monitoring, contingency evaluation and security control. The present achievements and future trends are explored and tentatively assessed.     

Dual arm manipulation—A survey

Recent advances in both anthropomorphic robots and bimanual industrial manipulators had led to an increased interest in the specific problems pertaining to dual arm manipulation. For the future, we foresee robots performing human-like tasks in both domestic and industrial settings. It is therefore natural to study specifics of dual arm manipulation in humans and methods for using the resulting knowledge in robot control. The related scientific problems range from low-level control to high level task planning and execution. This review aims to summarize the current state of the art from the heterogenous range of fields that study the different aspects of these problems specifically in dual arm manipulation.     

Intelligent visual surveillance — A survey

Detection, tracking, and understanding of moving objects of interest in dynamic scenes have been active research areas in computer vision over the past decades. Intelligent visual surveillance (IVS) refers to an automated visual monitoring process that involves analysis and interpretation of object behaviors, as well as object detection and tracking, to understand the visual events of the scene. Main tasks of IVS include scene interpretation and wide area surveillance control. Scene interpretation aims at detecting and tracking moving objects in an image sequence and understanding their behaviors. In wide area surveillance control task, multiple cameras or agents are controlled in a cooperative manner to monitor tagged objects in motion. This paper reviews recent advances and future research directions of these tasks. This article consists of two parts: The first part surveys image enhancement, moving object detection and tracking, and motion behavior understanding. The second part reviews wide-area surveillance techniques based on the fusion of multiple visual sensors, camera calibration and cooperative camera systems.     

Structural shape optimization—A survey

This paper is a survey of structural shape optimization with an emphasis on techniques dealing with shape optimization of the boundaries of two- and three-dimensional bodies. Attention is focused on the special problems of structural shape optimization which are due to a finite element model which must change during the optimization process. These problems include the requirement for sophisticated automated mesh generation techniques and careful choice of design variables. They also include special problems in obtaining sufficiently accurate sensitivity derivatives.     

Implementation of digital controllers—A survey

Stimulated by microprocessor technology there is increasing interest in the issues of digital control implementation. This paper reviews these issues, from algorithms through current hardware up to the various problems arising with non-ideal behaviour of digital controllers.     

Software development cost estimation approaches — A survey

This paper summarizes several classes of software cost estimation models and techniques: parametric models, expertise‐based techniques, learning‐oriented techniques, dynamics‐based models, regression‐based models, and composite‐Bayesian techniques for integrating expertise‐based and regression‐based models. Experience to date indicates that neural‐net and dynamics‐based techniques are less mature than the other classes of techniques, but that all classes of techniques are challenged by the rapid pace of change in software technology. The primary conclusion is that no single technique is best for all situations, and that a careful comparison of the results of several approaches is most likely to produce realistic estimates. This revised version was published online in June 2006 with corrections to the Cover Date.     

Robustness of nonlinear state feedback—A survey

A survey of robustness of nonlinear state feedback is given. For series perturbations there are fairly complete results, showing that under mild restrictions an optimal controller can tolerate an infinite increase in gain. For gain reductions there are some results for systems linear in the control. In particular there is a 50% reduction tolerance if the control penalty is quadratic. Usually the optimal controller cannot be computed exactly. There are some results showing the effects of truncation on the robustness. Essentially robustness is maintained but in a reduced (computable) part of the state space.     

Negative selection in anomaly detection—A survey

The remarkable ability to separate and identify self and non-self in a given problem space, makes negative selection a fascinating concept of artificial immune system. Therefore, negative selection has attracted research interest and is studied and explored for complex problem solving across different application areas. Anomaly detection in computer security is a thriving area of research and has witnessed various new explores involving different computational intelligence techniques. Negative selection with its core ability to detect self and non-self along with traits like adaptability, learning, robustness and faster response makes it a suitable and compelling concept for anomaly detection. Over the years, negative selection has evolved from its preliminary theories and it has embraced new improvements from computational intelligence in its several concepts. This paper intends to review various negative selection taxonomies, representations and matching techniques from inception to current scenario in anomaly detection. It attempts to critically evaluate and classify available literature to establish future areas of research for formulating potential solutions to mitigate the complex security challenges.     

Decomposition of binary images—A survey and comparison

We present an overview of the most important methods that decompose an arbitrary binary object into a union of rectangles. We describe a run-length encoding and its generalization, decompositions based on quadtrees, on mathematical morphology, on the distance transform, and a theoretically optimal decomposition based on a maximal matching in bipartite graphs. We compare their performance in image compression, in moment computation and in linear filtering. We show that the choice is always a compromise between the complexity and time/memory consumption. We give advice how to select an appropriate method in particular cases.     

Artificial intelligence and expert systems applications in new product development—a survey

The authors review and categorize the research in applications of artificial intelligence (AI) and expert systems (ES) in new product development (NPD) activities. A brief overview of NPD process and AI is presented. This is followed by a literature survey in regard to AI and ES applications in NPD, which revealed twenty four articles (twenty two applications) in the 1990–1997 period. The applications are categorized into five areas: expert decision support systems for NPD project evaluation, knowledge-based systems (KBS) for product and process design, KBS for QFD, AI support for conceptual design and AI support for group decision making in concurrent engineering. Brief review of each application is provided. The articles are also grouped by NPD stages and seven NPD core elements (competencies and abilities). Further research areas are pointed out.     

Occam—A programming language for multiprocessor systems

The features of concurrency provide important concepts for problem solving in a wide range of application areas. Many languages have now been developed to support this approach, with various notations being proposed. Occam is a programming language which supports concurrency using the process as its program structure, and provides synchronous communication between these processes. This paper presents the main features of occam and illustrates its use through various examples.     

Microcomputer control of high dynamic performance ac-drives—A survey

Alternating current machines, in particular induction motors, are of simple mechanical construction but have a nonlinear, highly interacting multivariable control structure. This has made it difficult in the past to design controlled ac-drives with high dynamic performance, similar to converter-fed dcdrives. A satisfactory solution of this problem has not been available until Blaschke formulated the principle of field orientation, where the machine is controlled in a moving frame of reference. This paper presents a survey of controlling acmachines for use in high dynamic performance drives including different types of machines and converters with their specific control characteristics. It is shown that by combining a suitable machine model with the principle of rotor- or field-orientation a unifying basis for the design of ac-drives is created. The complicated signal structure of the control systems can very effectively be handled by microelectronics, i.e. by using software instead of elaborate hardware. This is shown in the paper with the help of examples.     

Self-optimizing control – A survey

Self-optimizing control is a strategy for selecting controlled variables. It is distinguished by the fact that an economic objective function is adopted as a selection criterion. The aim is to systematically select the controlled variables such that by controlling them at constant setpoints, the impact of uncertain and varying disturbances on the economic optimality is minimized. If a selection leads to an acceptable economic loss compared to perfectly optimal operation then the chosen control structure is referred to as “self-optimizing”. In this comprehensive survey on methods for finding self-optimizing controlled variables we summarize the progress made during the last fifteen years. In particular, we present brute-force methods, local methods based on linearization, data and regression based methods, and methods for finding nonlinear controlled variables for polynomial systems. We also discuss important related topics such as handling changing active constraints. Finally, we point out open problems and directions for future research.     

A survey of applications of threshold cryptography—proposed and practiced

ABSTRACT

Threshold cryptography is a secret sharing technique that finds applications in many fields including cloud computing, authentication, the Internet of Things, ad-hoc and sensor networks, digital signatures, and electronic voting. The technique can effectively reduce the total number of cryptographic keys used for encryption in a group. The article surveys the multifaceted applications of threshold cryptography, portraying the techniques and the secret sharing schemes used. The article also emphasizes the immediate need for reviving the expired Internet Engineering Task Force (IETF) draft of 2010 to establish a threshold cryptography standard.