Tunable electrochemistry of gold-silver alloy nanoshells

Nano Research - The widespread and increasing interest in enhancing biosensing technologies by increasing their sensitivities and lowering their costs has led to the exploration and application of...     

Interprocedural Array Region Analyses

Many program optimizations require exact knowledge of the sets of array elements that are referenced in or that flow between statements or procedures. Some examples are array privatization, generation of communications in distributed memory machines, or compile-time optimization of cache behavior in hierarchical memory machines. Exact array region analysis is introduced in this article. These regions exactly represent the effects of statements and procedures upon array variables. To represent the flow of these data, we also introduce two new types of array region analyses: in and out regions. The intraprocedural propagation is presented, as well as a general linear framework for interprocedural analyses, which handles array reshapes. The intra- and inter-procedural propagation of array regions is implemented in pips, the interprocedural parallelizer of fortran programs developed at École des mines de Paris.     

Filtering artificial texts with statistical machine learning techniques

Fake content is flourishing on the Internet, ranging from basic random word salads to web scraping. Most of this fake content is generated for the purpose of nourishing fake web sites aimed at biasing search engine indexes: at the scale of a search engine, using automatically generated texts render such sites harder to detect than using copies of existing pages. In this paper, we present three methods aimed at distinguishing natural texts from artificially generated ones: the first method uses basic lexicometric features, the second one uses standard language models and the third one is based on a relative entropy measure which captures short range dependencies between words. Our experiments show that lexicometric features and language models are efficient to detect most generated texts, but fail to detect texts that are generated with high order Markov models. By comparison our relative entropy scoring algorithm, especially when trained on a large corpus, allows us to detect these “hard” text generators with a high degree of accuracy.     

A probabilistic reputation model based on transaction ratings

This work introduces a probabilistic model allowing to compute reputation scores as close as possible to their intrinsic value, according to the model. It is based on the following, natural, consumer-provider interaction model. Consumers are assumed to order items from providers, who each has some intrinsic, latent, “quality of service” score. In the basic model, the providers supply the items with a quality following a normal law, centered on their intrinsic “quality of service”. The consumers, after the reception and the inspection of the item, rate it according to a linear function of its quality - a standard regression model. This regression model accounts for the bias of the consumer in providing ratings as well as his reactivity towards changes in item quality. Moreover, the constancy of the provider in supplying an equal quality level when delivering the items is estimated by the standard deviation of his normal law of item quality generation. Symmetrically, the consistency of the consumer in providing similar ratings for a given quality is quantified by the standard deviation of his normal law of ratings generation. Two extensions of this basic model are considered as well: a model accounting for truncation of the ratings and a Bayesian model assuming a prior distribution on the parameters. Expectation-maximization algorithms, allowing to estimate the parameters based on the ratings, are developed for all the models. The experiments suggest that these models are able to extract useful information from the ratings, are robust towards adverse behaviors such as cheating, and are competitive in comparison with standard methods. Even if the suggested models do not show considerable improvements over other competing models (such as Brockhoff and Skovgaard’s model [12]), they, however, also permit to estimate interesting features over the raters - such as their reactivity, bias, consistency, reliability, or expectation.     

The musculoskeletal system complaints of office workers at a vehicle production factory

This study aimed to determine the prevalence of and factors contributing to musculoskeletal system complaints (MSC) in office workers of a vehicle production factory and absenteeism due to these complaints. A total of 86.2% (n = 333) of the workers completed the survey. Of the workers, 73 (21.9%) were women, and 260 (78.1%) were men, and the mean age was 36.9 ± 8.75 years. The majority of the personnel had more than one symptom with a prevalence of 80.8%. The most frequently observed discomfort was tension and pain in the back muscles (58.6%) and in the neck muscles (58.3%), followed by low back pain (41%) and shoulder pain (30.3%). Pain in the shoulders, neck, and the back and pain and numbness in the fingers were statistically significantly more prevalent in employees who spent more than 5 hours per day performing desk work. Furthermore, all of the complaints, excluding pain in the elbows and knees, were statistically significantly more common in the women. When each complaint and the effects of contributing risk factors were analyzed by logistic regression analysis, pain in the shoulders, neck, and back; pain that spread to the arms; and pain in the fingers were correlated with longer work hours and the female gender (p < 0.05). The number of employees who had used sick leave within the past year due to MSCs was 11.7%. In conclusion, duration of work hours, frequency of breaks, and gender were determined as the most important risk factors in computer users regarding MSCs. © 2011 Wiley Periodicals, Inc.     

Preserving spatial information and overcoming variations in appearance for face recognition

Local feature-based approaches mainly aim to achieve robustness to variations in facial images by assuming that only some parts of the facial images may be affected. However, such approaches may lose spatial information. In this study, a compromise feature extraction scheme is studied which extracts local features while preserving spatial information. The proposed scheme exploits an ensemble of classifiers where each member is constructed using randomly selected design parameters including the size, number and location of sub-images for local feature extraction. Experiments conducted on FERET and ORL databases have shown that proposed scheme surpasses the local feature-based reference systems which focus on either local information or preserving spatial information.     

Three‐dimensional localization for the MagneBike inspection robot

The MagneBike inspection robot is a climbing robot equipped with magnetic wheels. The robot is designed to drive on three‐dimensional (3D) complexly shaped pipe structures; therefore it is necessary to provide 3D visualization tools for the user, who remotely controls the robot out of sight. The localization system is required to provide a 3D map of the unknown environment and the 3D location of the robot in the environment's map. The localization strategy proposed in this paper consists of combining 3D odometry with 3D scan registration. The odometry model is based on wheel encoders and a three‐axis accelerometer. Odometry enables the tracking of the robot trajectory between consecutive 3D scans and is used as a prior for the scan matching algorithm. The 3D scan registration facilitates the construction of a 3D map of the environment and refines the robot position computed with odometry. This paper describes in detail the implementation of the localization concept. It presents the lightweight, small‐sized 3D range finder that has been developed for the MagneBike. It also proposes an innovative 3D odometry model that estimates the local surface curvature to compensate for the absence of angular velocity inputs. The different tools are characterized in detail based on laboratory and field experiments. They show that the localization concepts reliably track the robot moving in the specific application environment. We also describe various techniques to optimize the 3D scanning process, which is time consuming, and to compensate for the identified limitations. These techniques are useful inputs for the future automatization of the robot's control and optimization of its localization process. © 2010 Wiley Periodicals, Inc.     

PolyMAX,a Mobile WiMAX module for the ns-2 simulator with QoS and AMC support

In this paper, we present the PolyMAX module which enhances network simulator 2 (ns-2), the most popular network simulator used in academia, to provide one of the most complete simulation tools to evaluate the performance of Mobile WiMAX networks. PolyMAX is based on the National Institute of Standards and Technology (NIST) module and our specific contributions consist on the design and implementation of the Quality of Service (QoS) classes and QoS management messages, the uplink access grant-request mechanisms, Adaptive Modulation and Coding, and a scheduler handling all five WiMAX QoS classes. We also present validation results for the different components of our module and typical WiMAX simulation scenarios illustrating its flexibility and some of its features. The PolyMAX module represents an important tool enabling researchers to easily implement their Mobile WiMAX scheduling and Adaptive Modulation and Coding (AMC) algorithms and accurately evaluate their performance for realistic scenarios.     

Model‐based code generation for HLA federates

This paper addresses the problem of automated code generation for a High Level Architecture compliant federate application given its behavior model. The behavior model is a part of the architectural model of a federation that the federate can participate in. The federate behavior model is based on Live Sequence Charts, adopted as the behavioral specification formalism in the Federation Architecture Metamodel (FAMM). FAMM serves as a formal language for describing federation architectures. An objective is to help the testing of federation architecture by means of its prototype implementation early in the development lifecycle. A further objective is to help developers construct complete federate applications that are well modularized. The approach to achieve these objectives is aspect‐oriented in that the generated code, which handles the federate's interactions with a federation execution, serves as the base code, where the computation logic is to be weaved as an aspect. Copyright © 2009 John Wiley & Sons, Ltd.