On real-time partitioned multicore systems

Partitioning is a common approach to developing mixed-criticality systems, where partitions are isolated from each other both in the temporal and the spatial domain in order to prevent low-criticality subsystems from compromising other subsystems with high level of criticality in case of misbehaviour. The advent of many-core processors, on the other hand, opens the way to highly parallel systems in which all partitions can be allocated to dedicated processor cores. This trend will simplify processor scheduling, although other issues such as mutual interference in the temporal domain may arise as a consequence of memory and device sharing. The paper describes an architecture for multi-core partitioned systems including critical subsystems built with the Ada Ravenscar profile. Some implementation issues are discussed, and experience on implementing the ORK kernel on the XtratuM partitioning hypervisor is presented.

Controlling systems with a single actuator

In this paper the problem of designing a single actuator control for a class of systems is addressed. The existence of such control is studied and several ways for designing such control are provided. The results depend either on the rational canonical form or on the Jordan structure associated with the matrix which characterizes the system dynamics. The constructed control laws can be employed in the design of minimum cost controllers for a large variety of systems.

A Bayesian modeling approach to multi-dimensional sentiment distributions prediction

Sentiment analysis has long focused on binary classification of text as either positive or negative. There has been few work on mapping sentiments or emotions into multiple dimensions. This paper studies a Bayesian modeling approach to multi-class sentiment classification and multidimensional sentiment distributions prediction. It proposes effective mechanisms to incorporate supervised information such as labeled feature constraints and document-level sentiment distributions derived from the training data into model learning. We have evaluated our approach on the datasets collected from the confession section of the Experience Project website where people share their life experiences and personal stories. Our results show that using the latent representation of the training documents derived from our approach as features to build a maximum entropy classifier outperforms other approaches on multi-class sentiment classification. In the more difficult task of multi-dimensional sentiment distributions prediction, our approach gives superior performance compared to a few competitive baselines. © 2012 ACM.

Limit Behaviour of Dynamic Rule-based Systems

The paper suggests a classification of dynamic rule-based systems. For each class of systems, limit behavior is studied. Systems with stabilizing limit states or stabilizing limit trajectories are identified, and such states and trajectories are found. The structure of the set of limit states and trajectories is investigated.

Study of Queuing Systems with a Generalized Departure Process

This work was supported by the Bulgarian National Science Fund under grant BY-TH-105/2005.

Single-Server Queueing System with Markov-Modulated Arrivals and Service Times

Key words: Markov-modulated queues, waiting time, heavy traffic.

Queue Length Simulations in a Finite Single-line Queueing System with Repeated Calls

2000 Mathematics Subject Classification: 60K25.

Damping Torque Analysis of Power Systems with DFIGs for Wind Power Generation

A grid-connected DFIG for wind power generation can affect power system small-signal angular stability in two ways: by changing the system load flow condition and dynamically interacting with synchronous generators (SGs). This paper presents the application of conventional method of damping torque analysis (DTA) to examine the effect of DFIG’s dynamic interactions with SGs on the small-signal angular stability. It shows that the effect is due to the dynamic variation of power exchange between the DFIG and power system and can be estimated approximately by the DTA. Consequently, if the DFIG is modelled as a constant power source when the effect of zero dynamic interactions is assumed, the impact of change of load flow brought about by the DFIG can be determined. Thus the total effect of DFIG can be estimated from the result of DTA added on that of constant power source model. Applications of the DTA method proposed in the paper are discussed. An example of multi-machine power systems with grid-connected DFIGs are presented to demonstrate and validate the DTA method proposed and conclusions obtained in the paper.

Noncollinear Polarization Gating of Attosecond Pulse Trains in the Relativistic Regime

High order harmonics generated at relativistic intensities have long been recognized as a route to the most powerful extreme ultraviolet pulses. Reliably generating isolated attosecond pulses requires gating to only a single dominant optical cycle, but techniques developed for lower power lasers have not been readily transferable. We present a novel method to temporally gate attosecond pulse trains by combining noncollinear and polarization gating. This scheme uses a split beam configuration which allows pulse gating to be implemented at the high beam fluence typical of multi-TW to PW class laser systems. Scalings for the gate width demonstrate that isolated attosecond pulses are possible even for modest pulse durations achievable for existing and planned future ultrashort high-power laser systems. Experimental results demonstrating the spectral effects of temporal gating on harmonic spectra generated by a relativistic laser plasma interaction are shown.

Multiclass Adaboost Based on an Ensemble of Binary Adaboosts

This paper presents a multi-class AdaBoost based on incorporating an ensemble of binary AdaBoosts which is organized as Binary Decision Tree (BDT). It is proved that binary AdaBoost is extremely successful in producing accurate classification but it does not perform very well for multi-class problems. To avoid this performance degradation, the multi-class problem is divided into a number of binary problems and binary AdaBoost classifiers are invoked to solve these classification problems. This approach is tested with a dataset consisting of 6500 binary images of traffic signs. Haar-like features of these images are computed and the multi-class AdaBoost classifier is invoked to classify them. A classification rate of 96.7% and 95.7% is achieved for the traffic sign boarders and pictograms, respectively. The proposed approach is also evaluated using a number of standard datasets such as Iris, Wine, Yeast, etc. The performance of the proposed BDT classifier is quite high as compared with the state of the art and it converges very fast to a solution which indicates it as a reliable classifier.

Algoritmos construtivos para treino de redes neuronais b-spline

Dissertação de mest. em Engenharia de Sistemas e Computação - Área de Sistemas de Controlo, Faculdade de Ciências e Tecnologia, Univ.do Algarve, 2001

A discrete-time queueing system with feedback and optional service

Queueing systems constitute a central tool in modeling and performance analysis. These types of systems are in our everyday life activities, and the theory of queueing systems was developed to provide models for forecasting behaviors of systems subject to random demand. The practical and useful applications of the discrete-time queues make the researchers to con- tinue making an e ort in analyzing this type of models. Thus the present contribution relates to a discrete-time Geo/G/1 queue in which some messages may need a second service time in addition to the rst essential service. In day-to-day life, there are numerous examples of queueing situations in general, for example, in manufacturing processes, telecommunication, home automation, etc, but in this paper a particular application is the use of video surveil- lance with intrusion recognition where all the arriving messages require the main service and only some may require the subsidiary service provided by the server with di erent types of strategies. We carry out a thorough study of the model, deriving analytical results for the stationary distribution. The generating functions of the number of messages in the queue and in the system are obtained. The generating functions of the busy period as well as the sojourn times of a message in the server, the queue and the system are also provided.

Multiclass Hammersley-Aldous-Diaconis process and multiclass-customer queues

In the Hammersley-Aldous-Diaconis process, infinitely many particles sit in R and at most one particle is allowed at each position. A particle at x, whose nearest neighbor to the right is at y, jumps at rate y - x to a position uniformly distributed in the interval (x, y). The basic coupling between trajectories with different initial configuration induces a process with different classes of particles. We show that the invariant measures for the two-class process can be obtained as follows. First, a stationary M/M/1 queue is constructed as a function of two homogeneous Poisson processes, the arrivals with rate, and the (attempted) services with rate rho > lambda Then put first class particles at the instants of departures (effective services) and second class particles at the instants of unused services. The procedure is generalized for the n-class case by using n - 1 queues in tandem with n - 1 priority types of customers. A multi-line process is introduced; it consists of a coupling (different from Liggett's basic coupling), having as invariant measure the product of Poisson processes. The definition of the multi-line process involves the dual points of the space-time Poisson process used in the graphical construction of the reversed process. The coupled process is a transformation of the multi-line process and its invariant measure is the transformation described above of the product measure.

Exploiting Pulsed Flows for Heating Improvement: Application to Determination of Total Reducing Sugars in Molasses and Sugar-Cane Juices

Laminar and pulsed flows typical of multi-commuted and multi-pumping flow systems, were evaluated in relation to analytical procedures carried out at high temperatures. As application, the spectrophotometric determination of total reducing sugars (TRS, hydrolyzed sucrose plus reducing sugars) in sugar-cane juice and molasses was selected. The method involves in-line hydrolysis of sucrose and alkaline degradation of the reducing sugars at about 98 degrees C. Better results were obtained with pulsed flows, due to the efficient radial mass transport inherent to the multi-pumping flow system. The proposed system presents favorable characteristics of ruggedness, analytical precision (r.s.d. < 0.013 for typical samples), stability (no measurable baseline drift during 4-h working periods), linearity of the analytical curve (r > 0.992, n = 5, 0.05-0.50% w/v TRS) and sampling rate (65 h(-1)). Results are in agreement with ion chromatography.

New stacked photodevices for signal multiplexing and demultiplexing applications in the visible spectrum

Results on the use of a double a-SiC:H p-i-n heterostructure for signal multiplexing and demultiplexing applications in the visible range are presented. Pulsed monochromatic beams together (multiplexing mode), or a single polychromatic beam (demultiplexing mode) impinge on the device and are absorbed, accordingly to their wavelength. Red, green and blue pulsed input channels are transmitted together, each one with a specific transmission rate. The combined optical signal is analyzed by reading out, under different applied voltages, the generated photocurrent. Results show that in the multiplexing mode the output signal is balanced by the wavelength and transmission rate of each input channel, keeping the memory of the incoming optical carriers. In the demultiplexing mode the photocurrent is controlled by the applied voltage allowing regaining the transmitted information. A physical model supported by a numerical simulation gives insight into the device operation.