Evaluation of Variable Advisory Speed Limits in Work Zones, TPF-5(081), 2013

Variable advisory speed limit (VASL) systems could be effective at both urban and rural work zones, at both uncongested and congested sites. At uncongested urban work zones, the average speeds with VASL were lower than without VASL. But the standard deviation of speeds with VASL was higher. The increase in standard deviation may be due to the advisory nature of VASL. The speed limit compliance with VASL was about eight times greater than without VASL. At the congested sites, the VASL were effective in making drivers slow down gradually as they approached the work zone, reducing any sudden changes in speeds. Mobility-wise the use of VASL resulted in a decrease in average queue length, throughput, number of stops, and an increase in travel time. Several surrogate safety measures also demonstrated the benefits of VASL in congested work zones. VASL deployments in rural work zones resulted in reductions in mean speed, speed variance, and 85th percentile speeds downstream of the VASL sign. The study makes the following recommendations based on the case studies investigated: 1. The use of VASL is recommended for uncongested work zones to achieve better speed compliance and lower speeds. Greater enforcement of regulatory speed limits could help to decrease the standard deviation in speeds; 2. The use of VASL to complement the static speed limits in rural work zones is beneficial even if the VASL is only used to display the static speed limits. It leads to safer traffic conditions by encouraging traffic to slow down gradually and by reminding traffic of the reduced speed limit. A well-designed VASL algorithm, like the P5 algorithm developed in this study, can significantly improve the mobility and safety conditions in congested work zones. The use of simulation is recommended for optimizing the VASL algorithms before field deployment.

An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease.

Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease.

Practice guidelines for evaluation of Fever in returning travelers and migrants.

BACKGROUND: Fever upon return from tropical or subtropical regions can be caused by diseases that are rapidly fatal if left untreated. The differential diagnosis is wide. Physicians often lack the necessary knowledge to appropriately take care of such patients. OBJECTIVE: To develop practice guidelines for the initial evaluation of patients presenting with fever upon return from a tropical or subtropical country in order to reduce delays and potential fatal outcomes and to improve knowledge of physicians. TARGET AUDIENCE: Medical personnel, usually physicians, who see the returning patients, primarily in an ambulatory setting or in an emergency department of a hospital and specialists in internal medicine, infectious diseases, and travel medicine. METHOD: A systematic review of the literature--mainly extracted from the National Library of Medicine database--was performed between May 2000 and April 2001, using the keywords fever and/or travel and/or migrant and/or guidelines. Eventually, 250 articles were reviewed. The relevant elements of evidence were used in combination with expert knowledge to construct an algorithm with arborescence flagging the level of specialization required to deal with each situation. The proposed diagnoses and treatment plans are restricted to tropical or subtropical diseases (nonautochthonous diseases). The decision chart is accompanied with a detailed document that provides for each level of the tree the degree of evidence and the grade of recommendation as well as the key points of debate. PARTICIPANTS AND CONSENSUS PROCESS: Besides the 4 authors (2 specialists in travel/tropical medicine, 1 clinical epidemiologist, and 1 resident physician), a panel of 11 European physicians with different levels of expertise on travel medicine reviewed the guidelines. Thereafter, each point of the proposed recommendations was discussed with 15 experts in travel/tropical medicine from various continents. A final version was produced and submitted for evaluation to all participants. CONCLUSION: Although the quality of evidence was limited by the paucity of clinical studies, these guidelines established with the support of a large and highly experienced panel should help physicians to deal with patients coming back from the Tropics with fever.

Fuzzy logic algorithm to extract specific interaction forces from atomic force microscopy data

The atomic force microscope is not only a very convenient tool for studying the topography of different samples, but it can also be used to measure specific binding forces between molecules. For this purpose, one type of molecule is attached to the tip and the other one to the substrate. Approaching the tip to the substrate allows the molecules to bind together. Retracting the tip breaks the newly formed bond. The rupture of a specific bond appears in the force-distance curves as a spike from which the binding force can be deduced. In this article we present an algorithm to automatically process force-distance curves in order to obtain bond strength histograms. The algorithm is based on a fuzzy logic approach that permits an evaluation of "quality" for every event and makes the detection procedure much faster compared to a manual selection. In this article, the software has been applied to measure the binding strength between tubuline and microtubuline associated proteins.

Typing less common ovarian tumors: A training tool based on a pattern-based algorithm applied to a set of 20 virtual slides.

Context: Ovarian tumors (OT) typing is a competency expected from pathologists, with significant clinical implications. OT however come in numerous different types, some rather rare, with the consequence of few opportunities for practice in some departments. Aim: Our aim was to design a tool for pathologists to train in less common OT typing. Method and Results: Representative slides of 20 less common OT were scanned (Nano Zoomer Digital Hamamatsu®) and the diagnostic algorithm proposed by Young and Scully applied to each case (Young RH and Scully RE, Seminars in Diagnostic Pathology 2001, 18: 161-235) to include: recognition of morphological pattern(s); shortlisting of differential diagnosis; proposition of relevant immunohistochemical markers. The next steps of this project will be: evaluation of the tool in several post-graduate training centers in Europe and Québec; improvement of its design based on evaluation results; diffusion to a larger public. Discussion: In clinical medicine, solving many cases is recognized as of utmost importance for a novice to become an expert. This project relies on the virtual slides technology to provide pathologists with a learning tool aimed at increasing their skills in OT typing. After due evaluation, this model might be extended to other uncommon tumors.

Evaluation of performance analysis software for Linux computing cluster

Tietokonejärjestelmän osien ja ohjelmistojen suorituskykymittauksista saadaan tietoa,jota voidaan käyttää suorituskyvyn parantamiseen ja laitteistohankintojen päätöksen tukena. Tässä työssä tutustutaan suorituskyvyn mittaamiseen ja mittausohjelmiin eli ns. benchmark-ohjelmistoihin. Työssä etsittiin ja arvioitiin eri tyyppisiä vapaasti saatavilla olevia benchmark-ohjelmia, jotka soveltuvat Linux-laskentaklusterin suorituskyvynanalysointiin. Benchmarkit ryhmiteltiin ja arvioitiin testaamalla niiden ominaisuuksia Linux-klusterissa. Työssä käsitellään myös mittausten tekemisen ja rinnakkaislaskennan haasteita. Benchmarkkeja löytyi moneen tarkoitukseen ja ne osoittautuivat laadultaan ja laajuudeltaan vaihteleviksi. Niitä on myös koottu ohjelmistopaketeiksi, jotta laitteiston suorituskyvystä saisi laajemman kuvan kuin mitä yhdellä ohjelmalla on mahdollista saada. Olennaista on ymmärtää nopeus, jolla dataa saadaan siirretyä prosessorille keskusmuistista, levyjärjestelmistä ja toisista laskentasolmuista. Tyypillinen benchmark-ohjelma sisältää paljon laskentaa tarvitsevan matemaattisen algoritmin, jota käytetään tieteellisissä ohjelmistoissa. Benchmarkista riippuen tulosten ymmärtäminen ja hyödyntäminen voi olla haasteellista.

Traitement pharmacologique de la schizophrénie : évaluation comparative de la qualité des recommandations de pratique clinique = Comparative evaluation of clinical practice guidelines for the treatment of schizophrenia

De nombreuses recommandations de pratique clinique (RPC) ont été publiées, en réponse au développement du concept de la médecine fondée sur les preuves et comme solution à la difficulté de synthétiser et trier l'abondante littérature médicale. Pour faire un choix parmi le foisonnement de nouvelles RPC, il est primordial d'évaluer leur qualité. Récemment, le premier instrument d'évaluation standardisée de la qualité des RPC, appelé " AGREE " pour appraisal of guidelines for research and evaluation, a été validé. Nous avons comparé - avec l'aide de la grille " AGREE " - les six principales RPC publiées depuis une dizaine d'années sur le traitement de la schizophrénie : (1) les Recommandations de l'Agence nationale pour le développement de l'évaluation médicale (ANDEM) ; (2) The American Psychiatric Association (APA) practice guideline for the treatment of patients with schizophrenia ; (3) The quick reference guide of APA practice guideline for the treatment of patients with schizophrenia [APA - guide rapide de référence] ; (4) The schizophrenia patient outcomes research team (PORT) treatment recommandations ; (5) The Texas medication algorithm project " T-MAP " ; (6) The expert consensus guideline for the treatment of schizophrenia. Les résultats de notre étude ont ensuite été comparés avec ceux d'une étude similaire publiée en 2005 par Gæbel et al. portant sur 24 RPC abordant le traitement de la schizophrénie, réalisée également avec l'aide de la grille " AGREE " et deux évaluateurs [Br J Psychiatry 187 (2005) 248-255]. De manière générale, les scores des deux études ne sont pas trop éloignés et les deux évaluations globales des RPC convergent : chacune des six RPC est perfectible et présente différemment des points faibles et des points forts. La rigueur d'élaboration des six RPC est dans l'ensemble très moyenne, la prise en compte de l'opinion des utilisateurs potentiels est lacunaire et un effort sur la présentation des recommandations faciliterait leur utilisation clinique. L'applicabilité des recommandations est également peu considérée par les auteurs. Globalement, deux RPC se distinguent et peuvent être fortement recommandées selon les critères de la grille " AGREE " : " l'APA - guide rapide de référence " et le " T-MAP ".

Trabecular bone score (TBS) as a new complementary approach for osteoporosis evaluation in clinical practice.

Trabecular bone score (TBS) is a recently-developed analytical tool that performs novel grey-level texture measurements on lumbar spine dual X-ray absorptiometry (DXA) images, and thereby captures information relating to trabecular microarchitecture. In order for TBS to usefully add to bone mineral density (BMD) and clinical risk factors in osteoporosis risk stratification, it must be independently associated with fracture risk, readily obtainable, and ideally, present a risk which is amenable to osteoporosis treatment. This paper summarizes a review of the scientific literature performed by a Working Group of the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis. Low TBS is consistently associated with an increase in both prevalent and incident fractures that is partly independent of both clinical risk factors and areal BMD (aBMD) at the lumbar spine and proximal femur. More recently, TBS has been shown to have predictive value for fracture independent of fracture probabilities using the FRAX® algorithm. Although TBS changes with osteoporosis treatment, the magnitude is less than that of aBMD of the spine, and it is not clear how change in TBS relates to fracture risk reduction. TBS may also have a role in the assessment of fracture risk in some causes of secondary osteoporosis (e.g., diabetes, hyperparathyroidism and glucocorticoid-induced osteoporosis). In conclusion, there is a role for TBS in fracture risk assessment in combination with both aBMD and FRAX.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

Design and evaluation of learning algorithms for dynamic resource management in virtual networks

Network virtualisation is considerably gaining attentionas a solution to ossification of the Internet. However, thesuccess of network virtualisation will depend in part on how efficientlythe virtual networks utilise substrate network resources.In this paper, we propose a machine learning-based approachto virtual network resource management. We propose to modelthe substrate network as a decentralised system and introducea learning algorithm in each substrate node and substrate link,providing self-organization capabilities. We propose a multiagentlearning algorithm that carries out the substrate network resourcemanagement in a coordinated and decentralised way. The taskof these agents is to use evaluative feedback to learn an optimalpolicy so as to dynamically allocate network resources to virtualnodes and links. The agents ensure that while the virtual networkshave the resources they need at any given time, only the requiredresources are reserved for this purpose. Simulations show thatour dynamic approach significantly improves the virtual networkacceptance ratio and the maximum number of accepted virtualnetwork requests at any time while ensuring that virtual networkquality of service requirements such as packet drop rate andvirtual link delay are not affected.

THE APPLICATION OF AUTOMATED CORRELATION OPTIMIZED WARPING TO THE QUALITY EVALUATION OF Radix Puerariae thomsonii: CORRECTING RETENTION TIME SHIFT IN THE CHROMATOGRAPHIC FINGERPRINTS

The application of automated correlation optimized warping (ACOW) to the correction of retention time shift in the chromatographic fingerprints of Radix Puerariae thomsonii (RPT) was investigated. Twenty-seven samples were extracted from 9 batches of RPT products. The fingerprints of the 27 samples were established by the HPLC method. Because there is a retention time shift in the established fingerprints, the quality of these samples cannot be correctly evaluated by using similarity estimation and principal component analysis (PCA). Thus, the ACOW method was used to align these fingerprints. In the ACOW procedure, the warping parameters, which have a significant influence on the alignment result, were optimized by an automated algorithm. After correcting the retention time shift, the quality of these RPT samples was correctly evaluated by similarity estimation and PCA. It is demonstrated that ACOW is a practical method for aligning the chromatographic fingerprints of RPT. The combination of ACOW, similarity estimation, and PCA is shown to be a promising method for evaluating the quality of Traditional Chinese Medicine.

Evaluation of thermorregulatory capacity of dairy buffaloes using infrared thermography

ABSTRACT The objective of this study was to evaluate the thermoregulatory response of dairy buffaloes in pre-milking and post-milking. To identify animal thermoregulatory capacity, skin surface temperatures were taken by an infrared thermometer (SST), a thermographic camera (MTBP) as well as respiratory rate records (RR). Black Globe and Humidity Index (BGHI), radiating thermal load (RTL) and enthalpy (H) were used to characterize the thermal environment. Artificial Neural Networks analyzed those indices as well as animal physiological data, using a single layer trained with the least mean square (LMS) algorithm. The results indicated that pre-milking and post-milking environments reached BGHI, RR, SST and MTBP values above thermal neutrality zone for buffaloes. In addition, limits of surface skin temperatures were mostly influenced by changing ambient conditions to the detriment of respiratory rates. It follows that buffaloes are sensitive to environmental changes and their skin temperatures are the best indicators of thermal comfort in relation to respiratory rate.

Evaluation of Bubble Formation and Break Up in Suppression Pools by Using Pattern Recognition Methods

During a possible loss of coolant accident in BWRs, a large amount of steam will be released from the reactor pressure vessel to the suppression pool. Steam will be condensed into the suppression pool causing dynamic and structural loads to the pool. The formation and break up of bubbles can be measured by visual observation using a suitable pattern recognition algorithm. The aim of this study was to improve the preliminary pattern recognition algorithm, developed by Vesa Tanskanen in his doctoral dissertation, by using MATLAB. Video material from the PPOOLEX test facility, recorded during thermal stratification and mixing experiments, was used as a reference in the development of the algorithm. The developed algorithm consists of two parts: the pattern recognition of the bubbles and the analysis of recognized bubble images. The bubble recognition works well, but some errors will appear due to the complex structure of the pool. The results of the image analysis were reasonable. The volume and the surface area of the bubbles were not evaluated. Chugging frequencies calculated by using FFT fitted well into the results of oscillation frequencies measured in the experiments. The pattern recognition algorithm works in the conditions it is designed for. If the measurement configuration will be changed, some modifications have to be done. Numerous improvements are proposed for the future 3D equipment.

Performance evaluation of 3D computer vision techniques

This work presents the implementation and comparison of three different techniques of three-dimensional computer vision as follows: • Stereo vision - correlation between two 2D images • Sensorial fusion - use of different sensors: camera 2D + ultrasound sensor (1D); • Structured light The computer vision techniques herein presented took into consideration the following characteristics: • Computational effort ( elapsed time for obtain the 3D information); • Influence of environmental conditions (noise due to a non uniform lighting, overlighting and shades); • The cost of the infrastructure for each technique; • Analysis of uncertainties, precision and accuracy. The option of using the Matlab software, version 5.1, for algorithm implementation of the three techniques was due to the simplicity of their commands, programming and debugging. Besides, this software is well known and used by the academic community, allowing the results of this work to be obtained and verified. Examples of three-dimensional vision applied to robotic assembling tasks ("pick-and-place") are presented.

Neutron tomography using projection data obtained by Monte Carlo simulation for nondestructive evaluation

This work present the application of a computer package for generating of projection data for neutron computerized tomography, and in second part, discusses an application of neutron tomography, using the projection data obtained by Monte Carlo technique, for the detection and localization of light materials such as those containing hydrogen, concealed by heavy materials such as iron and lead. For tomographic reconstructions of the samples simulated use was made of only six equal projection angles distributed between 0º and 180º, with reconstruction making use of an algorithm (ARIEM), based on the principle of maximum entropy. With the neutron tomography it was possible to detect and locate polyethylene and water hidden by lead and iron (with 1cm-thick). Thus, it is demonstrated that thermal neutrons tomography is a viable test method which can provide important interior information about test components, so, extremely useful in routine industrial applications.