“Probability transforms” of digital pictures

Let g be any local property (e.g., gray level or gradient magnitude) defined on a digital picture. Let p_g(z) be the relative frequency with which g has value z. At each point (x,y) of the picture we can display p_g[g(x,y)], appropriately scaled; the result is called the p_g transform of the picture. Alternatively, we can use joint or conditional frequencies of pairs of local properties to define transforms. This note gives examples of such transforms for various gs and discusses their possible uses and limitations.     

Comment on “Nonlinear optimal tracking control with application to super-tankers for autopilot design” by T. Çimen and S.P. Banks

A recent paper by Çimen and Banks [2004. Nonlinear optimal tracking control with application to super-tankers for autopilot design. Automatica, 40(11), 1845–1863] on optimal control system design for oil tanker propulsion and heading highlighted the importance of accurately representing the dynamics of such a vessel. Results presented in that paper are based on a simulation model that provides unrealistic results for an oil tanker of the size considered. Therefore, the results obtained from the simulated ship control problem are not representative of the physical system being considered. In this communication an alternative, more realistic model is presented and discussed with reference to the original publications that define the ship model dynamics.     

An ergonomic evaluation of VDTs“”

Eight VDTs of different trademarks were analysed in relation to the following properties:

( a) Contrasts of luminance between the screens on the one hand and source documents, as well as other surfaces of the VDT, on the other.

(b) Oscillation degree, sharpness and stability of characters.

( c) Face and legibility of characters.

( d) Dimensions, mobility and reflection degrees of the keyboards.

Special equipment was developed and standardized conditions were applied to the measurements.

The eight VDTs showed essential differences for all the parameters, which might be partially responsible for eye strain and postural complaints. It can be concluded that customers should pay more attention to ergonomic qualities when choosing a VDT. But such an endeavour remains useless if the customer does not, at the same time, look for a proper design of the whole workstation including the working environment.     

Enhanced fault tolerant routing algorithms using a concept of “balanced ring”

Fault rings can be used to guide messages bypass faulty nodes/links in a fault tolerant interconnection network. However, nodes on the fault ring become hot spots, thus causing uneven distribution of the traffic loads. To avoid such traffic congestion, a concept of the balanced ring is proposed in this paper. The proposed balanced ring, defined as concentric rings of a given fault ring, can be applied to the fault tolerant routing algorithms for mesh and torus topologies. By properly guiding messages to route on the balanced ring and the fault ring, more balanced link utilization and greatly reduced traffic congestion can be achieved on a fault tolerant network. Methods of applying the balanced ring concept to some published fault tolerant routing algorithms are discussed. Proof of deadlock and livelock freedom is also presented. The use of balanced ring does not need to add new virtual channels. The performance of two routing algorithms with and without the balanced ring is simulated and evaluated. The results indicate that routing algorithms with the balanced rings constantly yield larger throughput and smaller latency than those without.     

Congestion control in high-speed communication networks using the Smith principle

High-speed communication networks are characterized by large bandwidth-delay products. This may have an adverse impact on the stability of closed-loop congestion control algorithms. In this paper, classical control theory and Smith’s principle are proposed as key tools for designing an effective and simple congestion control law for high-speed data networks. Mathematical analysis shows that the proposed control law guarantees stability of network queues and full utilization of network links in a general network topology and traffic scenario during both transient and steady-state condition. In particular, no data loss is guaranteed using buffers with any capacity, whereas full utilization of links is ensured using buffers with capacity at least equal to the bandwidth-delay product. The control law is transformed to a discrete-time form and is applied to ATM networks. Moreover a comparison with the ERICA algorithm is carried out. Finally, the control law is transformed to a window form and is applied to Internet. The resulting control law surprisingly reveals that today's Transmission Control Protocol/Internet Protocol implements a Smith predictor for congestion control. This provides a theoretical insight into the congestion control mechanism of TCP/IP along with a method to modify and improve this mechanism in a way that is backward compatible.     

A tandem queue with general bulk service and servers' “vacation”

This paper analyses two queueing models consisting of two units I and II connected in series, separated by a finite buffer of size N. In both models, unit I has only one exponential server capable of serving customers one at a time and unit II consist of c parallel exponential servers, each of them serving customers in groups according to general bulk service rules. When the queue length in front of unit II is less than the minimum of batch size, the free servers take a vacation. On return from vacation, if the queue length is less than the minimum, they leave for another vacation in the first model, whereas in the second model they wait in the system until they get the minimum number of customers and then start servicing. The steady-state probability vector of the number of customers waiting and receiving service in unit I and waiting in the buffer is obtained for both the models, using the modified matrix geometric method. Numerical results are also presented.     

“Chaotic relaxation” in concurrently asynchronous neural networks

In this paper we analyze a fundamental issue which directly impacts the scalability of current theoretical neural network models to applicative embodiments, in both software as well as hardware. This pertains to the inherent and unavoidable concurrent asynchronicity of emerging fine-grained computational ensembles and the consequent chaotic manifestations in the absence of proper conditioning. The latter concern is particularly significant since the computational inertia of neural networks in general and our dynamical learning formalisms manifests itself substantially, only in massively parallel hardward—optical, VLSI or opto-electronic. We introduce a mathematical framework for systematically reconditioning additive-type models and derive a neuro-operator, based on the chaotic relaxation paradigm whose resulting dynamics are neither “concurrently” synchronous nor “sequentially” asynchronous. Necessary and sufficient conditions guaranteeing concurrent asynchronous convergence are established in terms of contracting operators. Lyapunov exponents are also computed to characterize the network dynamics and to ensure that throughput-limiting “emergent computational chaos” behavior in models reconditioned with concurrently asynchronous algorithms was eliminated.     

Evolving networks： from topology to dynamics

A multi-local-world model is introduced to describe the evolving networks that have a localization property such as the Intemet. Based on this model, we show that the traffic load defined by “betweenness centrality” on the multi-local-world scale-flee networks‘ model also follows a power law form. In this kind of network, a few vertices have heavier loads and so play more important roles than the others in the network.     

FQUERY III+: A “human-consistent” database querying system based on fuzzy logic with linguistic quantifiers

Using a fuzzy-logic-based calculus of linguistically quantified propositions we present FQUERY III+, a new, more “human-friendly” and easier-to-use implementation of a querying scheme proposed originally by Kacprzyk and Zio kowski to handle imprecise queries including a linguistic quantifier as, e.g. find all records in which most (almost all, much more than 75%, … or any other linguistic quantifier) of the important attributes (out of a specified set) are as desired (e.g. equal to five, more than 10, large, more or less equal to 15, etc.). FQUERY III+ is an “add-on” to Ashton-Tate's dBase III Plus.     

Continuous-time hidden Markov models for network performance evaluation

In this paper, we study the use of continuous-time hidden Markov models (CT-HMMs) for network protocol and application performance evaluation. We develop an algorithm to infer the CT-HMM from a series of end-to-end delay and loss observations of probe packets. This model can then be used to simulate network environments for network performance evaluation. We validate the simulation method through a series of experiments both in ns and over the Internet. Our experimental results show that this simulation method can represent a wide range of real network scenarios. It is easy to use, accurate and time efficient.     

The indirect k-ary n-cube for a vector processing environment

In an earlier paper we introduced an indirect binary n-cube memory server network which has adaptive properties making it useful in a parallel vector processing environment. The memory server network, due to a special choice in the design of the basic switch node, has the property that N vector processors issuing vector fetches with similar strides are forced into lock step after an initial startup investment.

In this paper we extend this work to the case of the indirect k-any n-cube. As this network has a more favorable memory latency scaling of log_kN, one expects that the short vector performance will be improved as k is increased for a given N. We find this to be the case. We also find that the cost of the memory server system scales in a manner which prefers modest values of k above 2.     

A study of neural network based inverse kinematics solution for a three-joint robot

A neural network based inverse kinematics solution of a robotic manipulator is presented in this paper. Inverse kinematics problem is generally more complex for robotic manipulators. Many traditional solutions such as geometric, iterative and algebraic are inadequate if the joint structure of the manipulator is more complex. In this study, a three-joint robotic manipulator simulation software, developed in our previous studies, is used. Firstly, we have generated many initial and final points in the work volume of the robotic manipulator by using cubic trajectory planning. Then, all of the angles according to the real-world coordinates (x, y, z) are recorded in a file named as training set of neural network. Lastly, we have used a designed neural network to solve the inverse kinematics problem. The designed neural network has given the correct angles according to the given (x, y, z) cartesian coordinates. The online working feature of neural network makes it very successful and popular in this solution.     

Rush Hour is PSPACE-complete, or “Why you should generously tip parking lot attendants”

Rush Hour is a children's game that consists of a grid board, several cars that are restricted to move either vertically or horizontally (but not both), a special target car, and a single exit on the perimeter of the grid. The goal of the game is to find a sequence of legal moves that allows the target car to exit the grid. We consider a slightly generalized version of the game that uses an n×n grid and assume that we can place the single exit and target car at any location we choose on initialization of the game.

In this work, we show that deciding if the target car can legally exit the grid is PSPACE-complete. Our constructive proof uses a lazy form of dual-rail reversible logic such that movement of “output” cars can only occur if logical combinations of “input” cars can also move. Emulating this logic only requires three types of devices (two switches and one crossover); thus, our proof technique can be easily generalized to other games and planning problems in which the same three primitive devices can be constructed.     

ANTS: Agents on Networks, Trees, and Subgraphs

Efficient exploration of large networks is a central issue in data mining and network maintenance applications. In most existing work there is a distinction between the active ‘searcher’ which both executes the algorithm and holds the memory and the passive ‘searched graph’ over which the searcher has no control at all. Large dynamic networks like the Internet, where the nodes are powerful computers and the links have narrow bandwidth and are heavily-loaded, call for a different paradigm, in which a noncentralized group of one or more lightweight autonomous agents traverse the network in a completely distributed and parallelizable way. Potential advantages of such a paradigm would be fault tolerance against network and agent failures, and reduced load on the busy nodes due to the small amount of memory and computing resources required by the agent in each node. Algorithms for network covering based on this paradigm could be used in today’s Internet as a support for data mining and network control algorithms. Recently, a vertex ant walk ( ) method has been suggested [I.A. Wagner, M. Lindenbaum, A.M. Bruckstein, Ann. Math. Artificial Intelligence 24 (1998) 211–223] for searching an undirected, connected graph by an a(ge)nt that walks along the edges of the graph, occasionally leaving ‘pheromone’ traces at nodes, and using those traces to guide its exploration. It was shown there that the ant can cover a static graph within time nd, where n is the number of vertices and d the diameter of the graph. In this work we further investigate the performance of the method on dynamic graphs, where edges may appear or disappear during the search process. In particular we prove that (a) if a certain spanning subgraph S is stable during the period of covering, then the method is guaranteed to cover the graph within time nd_s, where d_s is the diameter of S, and (b) if a failure occurs on each edge with probability p, then the expected cover time is bounded from above by nd((logΔ/log(1/p))+((1+p)/(1−p))), where Δ is the maximum vertex degree in the graph. We also show that (c) if G is a static tree then it is covered within time 2n.     

Parameter identification of aggregated thermostatically controlled loads for smart grids using PDE techniques

This paper develops methods for model identification of aggregated thermostatically controlled loads (TCLs) in smart grids, via partial differential equation (PDE) techniques. Control of aggregated TCLs provides a promising opportunity to mitigate the mismatch between power generation and demand, thus enhancing grid reliability and enabling renewable energy penetration. To this end, this paper focuses on developing parameter identification algorithms for a PDE-based model of aggregated TCLs. First, a two-state boundary-coupled hyperbolic PDE model for homogenous TCL populations is derived. This model is extended to heterogeneous populations by including a diffusive term, which provides an elegant control-oriented model. Next, a passive parameter identification scheme and a swapping-based identification scheme are derived for the PDE model structure. Simulation results demonstrate the efficacy of each method under various autonomous and non-autonomous scenarios. The proposed models can subsequently be employed to provide system critical information for power system monitoring and control.     

Class-specific quality of service guarantees in multimedia communication networks

We consider the problem of quality-of-service (QoS) provisioning in modern high-speed, multimedia, communication networks. We quantify QoS by the probabilities of loss and excessive delay of an arbitrary packet, and introduce the model of a multiclass node (switch) which provides network access to users that may belong to multiple service classes. We treat such a node as a stochastic system which we analyze and control. In particular, we develop an analytical approach to estimate both the delay and the buffer overflow probability per service class, based on ideas from large deviations and optimal control. We exploit these performance analysis results by devising a call admission control algorithm which can provide per class QoS guarantees. We compare the proposed approach to alternative worst-case and effective bandwidth-based schemes and argue that it leads to increased efficiency. Finally, we discuss extensions to the network case in order to provide end-to-end QoS guarantees.     

Uncertain Saturated Discrete‐Time Sliding Mode Control for A Wind Turbine Using A Two‐Mass Model

The aim of this paper is to propose a new design variable speed wind turbine control by discrete‐time sliding mode approach. The control objective is to obtain a maximum extraction of wind energy, while reducing mechanical loads and rotor speed tracking combined with an electromagnetic torque. For this application, we designed a discrete time sliding mode control using the equivalent discrete time reaching law. Furthermore, a systematic and improved design procedure for uncertainties discrete‐time sliding mode control (SMC) with saturation problem is provided in this paper. The saturation constraint is reported on inputs vector. LMI technique and polytopic models are used in the design of the switching surface. To achieve some performance requirements and good robustness, in the sliding mode, the pole clustering method is investigated. Based on the unit vector control approach, a robust control is developed, then, to direct and maintain the system states onto the sliding manifold in finite time. Finally, a systematic design procedure for DSMC required to achieve a given performance level is provided and its effectiveness is varied by applying it to variable speed wind turbine systems.     

Modelling rhetorical legal “logic”—a double syllogism

This paper looks at legal reasoning from the point of view of the work of the lawyer, rather than the law itself. In the case of Common Law systems, this means a more flexible view of how tasks are divided between the humans and the computer system, with an emphasis on decision support rather than complete automation. A process-based model of the lawyer's work is proposed in the form of a double syllogism, which displays an aesthetically pleasing symmetry, but also a significant asymmetry in the role played by perceived precedents. This arises from the use of inductive, rather than deductive, reasoning. The potential complications arising from the issue of the perception of precedents are discussed in depth.The double-syllogism model is then considered in the light of CommonKADS terminology and models. It is suggested that decision support systems using knowledge-based techniques, as required to support lawyers working under Common Law jurisdiction, raise a stronger form of the interaction problem that is well known in knowledge-based systems. This means that such systems are not well catered for in the existing CommonKADS Organisational, Agent, Task and Communication Models. The double-syllogism model is suggested as a supplement to CommonKADS in the development of such systems, at least until a more generic addition is available.     

Reliable optimisation control of a reactive polymer composite moulding process using ant colony optimisation and bootstrap aggregated neural networks

This paper presents a study on the optimisation control of a reactive polymer composite moulding process using ant colony optimisation and bootstrap aggregated neural networks. In order to overcome the difficulties in developing accurate mechanistic models for reactive polymer composite moulding processes, neural network models are developed from process operation data. Bootstrap aggregated neural networks are used to enhance model prediction accuracy and reliability. Ant colony optimisation is able to cope with optimisation problems with multiple local optima and is able to find the global optimum. Ant colony optimisation is used in this study to find the optimal curing temperature profile. In order to enhance the reliability of the optimisation control policy, model prediction confidence bound offered by bootstrap aggregated neural networks is incorporated in the optimisation objective function so that unreliable predictions are penalised. The proposed method is tested on a simulated reactive polymer composite moulding process.