Two new control signal approaches for obtaining the MRAS-CDM and a real-time application

The coefficient diagram method (CDM) is one of the most effective control design methods. It creates control systems that are very stable and robust with responses without the overshoot and small settling time. Furthermore, all control parameters of the control systems are changed by varying some adjustment parameters in CDM depending on the demands. The model reference adaptive systems (MRAS) are the systems that follow and change the control parameters according to a given model reference system. There are several methods to combine the CDM with MRAS. One of these is to use the MRAS parameters as a gain of the CDM parameters. Another is to directly use the CDM parameters as the MRAS parameters. In the industrial applications, the system parameters can be changed frequently, but if the controller, by self-tuning, recalculates and develops its own parameters continuously, the system becomes more robust. Also, if the poles of the controlled systems approach the jw axis, the response of the closed-loop MRAS becomes more and more insufficient. In order to obtain better results, CDM is combined with a self-tuning model reference adaptive system. Systems controlled by a model reference adaptive controller give responses with small or without overshoot, have small settling times, and are more robust. Thus, in this paper, a hybrid combination of MRAS and CDM is developed and two different control structures of the control signal are investigated. The two methods are compared with MRAS and applied to real-time process control systems.     

Augmented AVI video file for road surveying

This paper presents a novel video augmentation approach: a video recording of a real entity augmented by structured data. This augmented video is a self-contained entity integrating values of perceptible and non-perceptible attributes of the same real entity. It simplifies data search, storage and management. Streaming, sharing, collaboration and synchronization are also simplified by the fact that the structured data (so-called augmented data) are integrated in the video file and therefore only one file needs to be manipulated. Our approach was applied to address the issues which road engineers experience while using the ROad Measurement and Data Acquisition System (ROMDAS). The ROMDAS system collects and analyses the road-condition state through video recordings and the data corresponding acquired by specific measuring devices. Currently, however, road engineers have to search the videos manually in order to find details of interest provided by the analysis of the data measured due to the separation of the video from the data. The ROMDAS system manages a large collection of road-condition data. It does not offer history management of video recordings of the same road captured at different time. We present this hybrid video augmentation system: the Augmented Video stream Framework (AVF). It allows creation, search, history management and playback of such augmented video files for effective road surveying based on the discrete data recorded in parallel to the video recordings. The AVF provides road engineers with effective and more comfortable perceptible and non-perceptible data search, storage and history management to be used for (collaborative) road inspection and maintenance.     

Performance evaluation of directory protocols on an optical broadcast-based distributed shared memory multiprocessor

Recent advances in the development of optical technologies suggest the possible emergence of broadcast-based optical interconnects within cache-coherent distributed shared memory (DSM) multiprocessor architectures. It is well known that the cache-coherence protocol is a critical issue in designing such architectures because it directly affects memory latencies. In this paper, we evaluate via simulation the performance of three directory-based cache-coherence protocols; strict request-response, intervention forwarding and reply forwarding on the Simultaneous Optical Multiprocessor Exchange Bus (SOME-Bus), which is a low-latency and high-bandwidth broadcast-based fiber-optic interconnection network supporting DSM. The simulated system contains 64 nodes, each of which has a processor, a cache controller, a directory controller and an output channel. Simulations have been conducted for each protocol to measure average processor utilization, average network latency and average number of packets transferred over the network for varying values of the important DSM parameters such as the ratio of the mean channel service time to mean thread run time (T/R), probability of a cache block being in modified state {P(M)}, the fraction of write misses {P(W)} and home node contention rate. The results reveal that for all cases, except for low values of P(M), intervention forwarding gives the worst performance (lowest processor utilization and highest latency). The performance of strict request-response and reply forwarding is comparable for several values of the DSM parameters and contention rate. For a contention rate of 0%, the increase of P(M) makes reply forwarding perform better than strict request-response. The performance of all protocols decreases with the increase of P(W) and contention rate. However, the performance of strict request-response is the least affected among other protocols due to the negative impact of the increase of P(W) and contention rate. Therefore, for the full contention case (i.e. contention rate of 100%); for low values of P(M), or for mid values of P(M) and high values of P(W), strict request-response performs better than reply forwarding. These results are significant in the sense that they provide an insight to multiprocessor architecture designers for comparing the performance of different directory-based cache-coherence protocols on a broadcast-based interconnection network for different values of the DSM parameters and varying rates of contention.     

Deciding k-Colorability of P 5-Free Graphs in Polynomial Time

The problem of computing the chromatic number of a P ₅-free graph (a graph which contains no path on 5 vertices as an induced subgraph) is known to be NP-hard. However, we show that for every fixed integer k, there exists a polynomial-time algorithm determining whether or not a P ₅-free graph admits a k-coloring, and finding one, if it does.     

Explanation and reliability of prediction models: the case of breast cancer recurrence

In this paper, we describe the first practical application of two methods, which bridge the gap between the non-expert user and machine learning models. The first is a method for explaining classifiers’ predictions, which provides the user with additional information about the decision-making process of a classifier. The second is a reliability estimation methodology for regression predictions, which helps the users to decide to what extent to trust a particular prediction. Both methods are successfully applied to a novel breast cancer recurrence prediction data set and the results are evaluated by expert oncologists.     

Complexity issues in color-preserving graph embeddings

In the context of comparative analysis of protein–protein interaction graphs, we use a graph-based formalism to detect the preservation of a given protein complex (pattern graph) in the protein–protein interaction graph (target graph) of another species with respect to (w.r.t.) orthologous proteins. We give an efficient exponential-time randomized algorithm in case the occurrence of the pattern graph in the target graph is required to be exact. For approximate occurrences, we prove a tight inapproximability result and give four approximation algorithms that deal with bounded degree graphs, small ortholog numbers, linear forests and very simple yet hard instances, respectively.     

A parallel direct solver for the self-adaptive hp Finite Element Method

In this paper we present a new parallel multi-frontal direct solver, dedicated for the hp Finite Element Method (hp-FEM). The self-adaptive hp-FEM generates in a fully automatic mode, a sequence of hp-meshes delivering exponential convergence of the error with respect to the number of degrees of freedom (d.o.f.) as well as the CPU time, by performing a sequence of hp refinements starting from an arbitrary initial mesh. The solver constructs an initial elimination tree for an arbitrary initial mesh, and expands the elimination tree each time the mesh is refined. This allows us to keep track of the order of elimination for the solver. The solver also minimizes the memory usage, by de-allocating partial LU factorizations computed during the elimination stage of the solver, and recomputes them for the backward substitution stage, by utilizing only about 10% of the computational time necessary for the original computations. The solver has been tested on 3D Direct Current (DC) borehole resistivity measurement simulations problems. We measure the execution time and memory usage of the solver over a large regular mesh with 1.5 million degrees of freedom as well as on the highly non-regular mesh, generated by the self-adaptive hp$hp$-FEM, with finite elements of various sizes and polynomial orders of approximation varying from p=1$p=1$ to p=9$p=9$. From the presented experiments it follows that the parallel solver scales well up to the maximum number of utilized processors. The limit for the solver scalability is the maximum sequential part of the algorithm: the computations of the partial LU factorizations over the longest path, coming from the root of the elimination tree down to the deepest leaf.     

Solving subgraph isomorphism problems with constraint programming

The subgraph isomorphism problem consists in deciding if there exists a copy of a pattern graph in a target graph. We introduce in this paper a global constraint and an associated filtering algorithm to solve this problem within the context of constraint programming. The main idea of the filtering algorithm is to label every node with respect to its relationships with other nodes of the graph, and to define a partial order on these labels in order to express compatibility of labels for subgraph isomorphism. This partial order over labels is used to filter domains. Labelings can also be strengthened by adding information from the labels of neighbors. Such a strengthening can be applied iteratively until a fixpoint is reached. Practical experiments illustrate that our new filtering approach is more effective on difficult instances of scale free graphs than state-of-the-art algorithms and other constraint programming approaches.