Comparison of human and computer-based selective cleaning

Abstract

SiMR: A simulator for learning computer architecture

This paper presents SiMR, a simulator of the Rudimentary Machine designed to be used in a first course of computer architecture of Software Engineering and Computer Engineering programmes. The Rudimentary Machine contains all the basic elements in a RISC computer, and SiMR allows editing, assembling and executing programmes for this processor. SiMR is used at the Universitat Oberta de Catalunya as one of the most important resources in the Virtual Computing Architecture and Organisation Laboratory, since students work at home with the simulator and reports containing their work are automatically generated to be evaluated by lecturers. The results obtained from a survey show that most of the students consider SiMR as a highly necessary or even an indispensable resource to learn the basic concepts about computer architecture.

Computational and Energy Costs of Cryptographic Algorithms on Handheld Devices

Networks are evolving toward a ubiquitous model in which heterogeneousdevices are interconnected. Cryptographic algorithms are required for developing securitysolutions that protect network activity. However, the computational and energy limitationsof network devices jeopardize the actual implementation of such mechanisms. In thispaper, we perform a wide analysis on the expenses of launching symmetric and asymmetriccryptographic algorithms, hash chain functions, elliptic curves cryptography and pairingbased cryptography on personal agendas, and compare them with the costs of basic operatingsystem functions. Results show that although cryptographic power costs are high and suchoperations shall be restricted in time, they are not the main limiting factor of the autonomyof a device.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Prácticas docentes con simuladores de vuelo

Este trabajo presenta las prácticas de laboratorio de la asignatura de Tecnología Aaeroespacial, perteneciente a la titulación de Ingeniería Técnica Aeronáutica (especialidad en Aeronavegación) y que se imparte en la Escuela Politécnica Superior de Castelldefels (EPSC) de laUniversidad Politécnica de Catalunya (UPC). Dichas prácticas se desarrollan en grupos de dos estudiantes alrededor de un conocido programa de simulación de vuelo y permiten al alumno ver y profundizar en los diferentes aspectos tratados en las clases teóricas de una manera próxima a la realidad y muy amigable.El alumno debe afrontarse a situaciones que, a lo largo de las diferentes sesiones de laboratorio, aumentan progresivamente en complejidad y conocimientos previos necesarios para resolverlas. Con esto, se llega a la práctica final donde cada pareja de estudiantes realiza un vuelo completosimulado de principio a fin que ha ido preparando y experimentando por partes durante el curso.Además, este vuelo se realiza en un entorno de simulación de tráfico aéreo en tiempo real con control del tráfico aéreo virtual (formado por estudiantes voluntarios de cursos superiores) que da aun más realismo a la simulación.Después de seis cursos consecutivos realizando esta experiencia, este trabajo concluye que este tipo de prácticas motivan significativamente al alumno a profundizar en los aspectos de la asignatura y potencian el trabajo cooperativo y el aprendizaje basado en proyectos.

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

Practical algorithms for a family of waterfilling solutions

Many engineering problems that can be formulatedas constrained optimization problems result in solutionsgiven by a waterfilling structure; the classical example is thecapacity-achieving solution for a frequency-selective channel.For simple waterfilling solutions with a single waterlevel and asingle constraint (typically, a power constraint), some algorithmshave been proposed in the literature to compute the solutionsnumerically. However, some other optimization problems result insignificantly more complicated waterfilling solutions that includemultiple waterlevels and multiple constraints. For such cases, itmay still be possible to obtain practical algorithms to evaluate thesolutions numerically but only after a painstaking inspection ofthe specific waterfilling structure. In addition, a unified view ofthe different types of waterfilling solutions and the correspondingpractical algorithms is missing.The purpose of this paper is twofold. On the one hand, itoverviews the waterfilling results existing in the literature from aunified viewpoint. On the other hand, it bridges the gap betweena wide family of waterfilling solutions and their efficient implementationin practice; to be more precise, it provides a practicalalgorithm to evaluate numerically a general waterfilling solution,which includes the currently existing waterfilling solutions andothers that may possibly appear in future problems.

Quantitative modelling of transcription factor binding sites

Abstract One of the most important issues in molecular biology is to understand regulatory mechanisms that control gene expression. Gene expression is often regulated by proteins, called transcription factors which bind to short (5 to 20 base pairs),degenerate segments of DNA. Experimental efforts towards understanding the sequence specificity of transcription factors is laborious and expensive, but can be substantially accelerated with the use of computational predictions. This thesis describes the use of algorithms and resources for transcriptionfactor binding site analysis in addressing quantitative modelling, where probabilitic models are built to represent binding properties of a transcription factor and can be used to find new functional binding sites in genomes. Initially, an open-access database(HTPSELEX) was created, holding high quality binding sequences for two eukaryotic families of transcription factors namely CTF/NF1 and LEFT/TCF. The binding sequences were elucidated using a recently described experimental procedure called HTP-SELEX, that allows generation of large number (> 1000) of binding sites using mass sequencing technology. For each HTP-SELEX experiments we also provide accurate primary experimental information about the protein material used, details of the wet lab protocol, an archive of sequencing trace files, and assembled clone sequences of binding sequences. The database also offers reasonably large SELEX libraries obtained with conventional low-throughput protocols.The database is available at http://wwwisrec.isb-sib.ch/htpselex/ and and ftp://ftp.isrec.isb-sib.ch/pub/databases/htpselex. The Expectation-Maximisation(EM) algorithm is one the frequently used methods to estimate probabilistic models to represent the sequence specificity of transcription factors. We present computer simulations in order to estimate the precision of EM estimated models as a function of data set parameters(like length of initial sequences, number of initial sequences, percentage of nonbinding sequences). We observed a remarkable robustness of the EM algorithm with regard to length of training sequences and the degree of contamination. The HTPSELEX database and the benchmarked results of the EM algorithm formed part of the foundation for the subsequent project, where a statistical framework called hidden Markov model has been developed to represent sequence specificity of the transcription factors CTF/NF1 and LEF1/TCF using the HTP-SELEX experiment data. The hidden Markov model framework is capable of both predicting and classifying CTF/NF1 and LEF1/TCF binding sites. A covariance analysis of the binding sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism. We next tested the LEF1/TCF model by computing binding scores for a set of LEF1/TCF binding sequences for which relative affinities were determined experimentally using non-linear regression. The predicted and experimentally determined binding affinities were in good correlation.

Probabilistic algorithms for blind adaptive multiuser detection

In this paper, two probabilistic adaptive algorithmsfor jointly detecting active users in a DS-CDMA system arereported. The first one, which is based on the theory of hiddenMarkov models (HMM’s) and the Baum–Wech (BW) algorithm,is proposed within the CDMA scenario and compared withthe second one, which is a previously developed Viterbi-basedalgorithm. Both techniques are completely blind in the sense thatno knowledge of the signatures, channel state information, ortraining sequences is required for any user. Once convergencehas been achieved, an estimate of the signature of each userconvolved with its physical channel response (CR) and estimateddata sequences are provided. This CR estimate can be used toswitch to any decision-directed (DD) adaptation scheme. Performanceof the algorithms is verified via simulations as well as onexperimental data obtained in an underwater acoustics (UWA)environment. In both cases, performance is found to be highlysatisfactory, showing the near–far resistance of the analyzed algorithms.

Performance of noninvasive ventilation algorithms on ICU ventilators during pressure support: a clinical study.

To evaluate the impact of noninvasive ventilation (NIV) algorithms available on intensive care unit ventilators on the incidence of patient-ventilator asynchrony in patients receiving NIV for acute respiratory failure. Prospective multicenter randomized cross-over study. Intensive care units in three university hospitals. Patients consecutively admitted to the ICU and treated by NIV with an ICU ventilator were included. Airway pressure, flow and surface diaphragmatic electromyography were recorded continuously during two 30-min periods, with the NIV (NIV+) or without the NIV algorithm (NIV0). Asynchrony events, the asynchrony index (AI) and a specific asynchrony index influenced by leaks (AIleaks) were determined from tracing analysis. Sixty-five patients were included. With and without the NIV algorithm, respectively, auto-triggering was present in 14 (22%) and 10 (15%) patients, ineffective breaths in 15 (23%) and 5 (8%) (p = 0.004), late cycling in 11 (17%) and 5 (8%) (p = 0.003), premature cycling in 22 (34%) and 21 (32%), and double triggering in 3 (5%) and 6 (9%). The mean number of asynchronies influenced by leaks was significantly reduced by the NIV algorithm (p < 0.05). A significant correlation was found between the magnitude of leaks and AIleaks when the NIV algorithm was not activated (p = 0.03). The global AI remained unchanged, mainly because on some ventilators with the NIV algorithm premature cycling occurs. In acute respiratory failure, NIV algorithms provided by ICU ventilators can reduce the incidence of asynchronies because of leaks, thus confirming bench test results, but some of these algorithms can generate premature cycling.

Computer-assisted two-dimensional preoperative planning for total hip arthroplasty: clinical evaluation.

The purpose of this study is to clinically validate a new two-dimensional preoperative planning software for cementless total hip arthroplasty (THA). Manual and two-dimensional computer-assisted planning were compared by an independent observer for each of the 30 patients with osteoarthritis who underwent THA. This study showed that there were no statistical differences between the results of both preoperative plans in terms of stem size and neck length (<1 size) and hip rotation center position (<5 mm). Two-dimensional computer-assisted preoperative planning provided successful results comparable to those using the manual procedure, thereby allowing the surgeon to simulate various stem designs easily.

Computer-aided volume measurement of posttraumatic orbits reconstructed with AO titanium mesh plates: accuracy and reliability

PURPOSE: To prospectively evaluate the accuracy and reliability of "freehand" posttraumatic orbital wall reconstruction with AO (Arbeitsgemeinschaft Osteosynthese) titanium mesh plates by using computer-aided volumetric measurement of the bony orbits. METHODS: Bony orbital volume was measured in 12 patients from coronal CT scan slices using OsiriX Medical Image software. After defining the volumetric limits of the orbit, the segmentation of the bony orbital region of interest of each single slice was performed. At the end of the segmentation process, all regions of interest were grouped and the volume was computed. The same procedure was performed on both orbits, and thereafter the volume of the contralateral uninjured orbit was used as a control for comparison. RESULTS: In all patients, the volume data of the reconstructed orbit fitted that of the contralateral uninjured orbit with accuracy to within 1.85 cm3 (7%). CONCLUSIONS: This preliminary study has demonstrated that posttraumatic orbital wall reconstruction using "freehand" bending and placement of AO titanium mesh plates results in a high success rate in re-establishing preoperative bony volume, which closely approximates that of the contralateral uninjured orbit.