Ab initio determination of heavy oxide perovskite related structures from precession electron diffraction data

Two complex perovskite-related structures were solved by ab initio from precession electron diffraction intensities. Structure models were firstly derived from HREM images and than have been confirmed independently using two and three-dimensional sets of precession intensities. Patterson techniques prove to be effective for ab initio structure resolution, specially in case of projections with no overlapping atoms. Quality of precession intensity data may be suitable enough to resolve unknown heavy oxide structures.     

QoS and energy management with Petri nets: A self-adaptive framework

Energy use is becoming a key design consideration in computing infrastructures and services. In this paper we focus on service-based applications and we propose an adaptation framework that can be used to reduce power consumption according to the observed workload. The adaptation guarantees a trade-off between energy consumption and system performance. The approach is based on the principle of proportional energy consumption obtained by scaling down energy for unused resources, considering both the number of servers switched on and their operating frequencies. Stochastic Petri nets are proposed for the modeling of the framework concerns, their analyses give results about the trade-offs. The application of the approach to a simple case study shows its usefulness and practical applicability. Finally, different types of workloads are analyzed with validation purposes.     

Estimation of spatial-temporal gait parameters in level walking based on a single accelerometer: Validation on normal subjects by standard gait analysis

This paper investigates the ability of a single wireless inertial sensing device stuck on the lower trunk to provide spatial-temporal parameters during level walking. The 3-axial acceleration signals were filtered and the timing of the main gait events identified. Twenty-two healthy subjects were analyzed with this system for validation, and the estimated parameters were compared with those obtained with state-of-the-art gait analysis, i.e. stereophotogrammetry and dynamometry. For each side, from four to six gait cycles were measured with the device, of which two were validated by gait analysis. The new acquisition system is easy to use and does not interfere with regular walking. No statistically significant differences were found between the acceleration-based measurements and the corresponding ones from gait analysis for most of the spatial-temporal parameters, i.e. stride length, stride duration, cadence and speed, etc.; significant differences were found for the gait cycle phases, i.e. single and double support duration, etc. The system therefore shows promise also for a future routine clinical use.     

Methodological design and comparative evaluation of a MAS providing AmI

Researches on Ambient Intelligent and Ubiquitous Computing using wireless technologies have increased in the last years. In this work, we review several scenarios to define a multi-agent architecture that support the information needs of these new technologies, for heterogeneous domain. Our contribution consists of designing in a methodological way a Context Aware System (involving location services) using agents that can be used in very different domains. We describe all the steps followed in the design of the agent system. We apply a hybridizing methodology between GAIA and AUML. Additionally we propose a way to compare different agent architectures for Context Aware System using agent interactions. So, in this paper, we describe the assignment of weight values to agents interaction in two different MAS architectures for Context Aware problems solving different scenarios inspired in FIPA standard negotiation protocols.     

Linking Organizational Resources and Work Engagement to Employee Performance and Customer Loyalty: The Mediation of Service Climate.

This study examined the mediating role of service climate in the prediction of employee performance and customer loyalty. Contact employees (N=342) from 114 service units (58 hotel front desks and 56 restaurants) provided information about organizational resources, engagement, and service climate. Furthermore, customers (N=1,140) from these units provided information on employee performance and customer loyalty. Structural equation modeling analyses were consistent with a full mediation model in which organizational resources and work engagement predict service climate, which in turn predicts employee performance and then customer loyalty. Further analyses revealed a potential reciprocal effect between service climate and customer loyalty. Implications of the study are discussed, together with limitations and suggestions for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Microstereophotolithography using a liquid crystal display as dynamic mask-generator

 A new laser microstereophotolithography process has been developed in our laboratory to manufacture three-dimensional parts with a high accuracy. As usual in laser stereophotolithography or laser microstereophotolithography, the part is manufactured layer by layer by a light-induced space-resolved polymerization. Until now, in all the already existing microstereophotolithography devices a layer is manufactured vector by vector, by moving the part beneath the initiating light source which remains motionless. We developed a simpler and easier process, in which we can manufacture an entire layer by irradiating its whole surface only once: we used a liquid crystal display as a dynamic generator of masks. In the device we set up, we need only one mobile element, the z translator, all the others are fixed. We manufactured several different 3D microparts, in particular a piece of bevel microgearing with helicoidal cogs, the volume of which is less than half a cubic millimetre. Received: 14 December 1995 / Accepted: 16 September 1996     

Analyzing the problem of unsustainable health information systems in less-developed economies: Case studies from Tanzania and Mozambique

Most of donor-supported information technology (IT)–based projects developed or implemented in less-developed economies (LDEs) end up as complete or partial failures or unsustainable. Notably, a number of intra-organizational and external factors are associated with this problem, including inadequate infrastructure and human resource capacity, fragmented donor policy, and lack of policies to manage the sustainability problem. Accordingly, IT initiatives are often donor-driven, top-down, and hijacked by top managers who (normally) do not have adequate skills, but have enormous power to enforce such initiatives across organizational hierarchies.

In analyzing the concepts from sustainability and institutionalization, key insights towards a better understanding of the problem of unsustainability are developed. It is argued that health information systems (HISs) become sustainable if they are institutionalized in the sense of being integrated into the everyday routine of the user organization. However, a sustainable HIS should also be flexible enough to allow changes as the user needs change. Moreover, introduction of a new HIS is not only a technical change, but requires the cultivation and institutionalization of a new kind of culture.

Through a comparative case analysis of the HIS development and implementation processes in Tanzania and Mozambique, we have identified two sets of relationships, between the Ministry of Health (MoH) and donor agencies and between the MoH and software development agencies as critical and contributing factors to the unsustainability of a HIS. Given this setting, we highlight three key strategies for dealing with the problem of unsustainability in LDEs: (a) integration of a HIS, (b) local shaping of new cultures, and (c) cultivation approach to systems development. © 2005 Wiley Periodicals, Inc.     

Is my model any good: differentially private regression diagnostics

Linear and logistic regression are popular statistical techniques for analyzing multi-variate data. Typically, analysts do not simply posit a particular form of the regression model, estimate its parameters, and use the results for inference or prediction. Instead, they first use a variety of diagnostic techniques to assess how well the model fits the relationships in the data and how well it can be expected to predict outcomes for out-of-sample records, revising the model as necessary to improve fit and predictive power. In this article, we develop \(\epsilon \)-differentially private diagnostics tools for regression, beginning to fill a gap in privacy-preserving data analysis. Specifically, we create differentially private versions of residual plots for linear regression and of receiver operating characteristic (ROC) curves as well as binned residual plot for logistic regression. The residual plot and binned residual plot help determine whether or not the data satisfy the assumptions underlying the regression model, and the ROC curve is used to assess the predictive power of the logistic regression model. These diagnostics improve the usefulness of algorithms for computing differentially private regression output, which alone does not allow analysts to assess the quality of the posited model. Our empirical studies show that these algorithms can be effective tools for allowing users to evaluate the quality of their models.     

A viral system algorithm to optimize the car dispatching in elevator group control systems of tall buildings

Nowadays is very common the presence of tall buildings in the business centres of the main cities of the world. Such buildings require the installation of numerous lifts that are coordinated and managed under a unique control system. Population working in the buildings follows a similar traffic pattern generating situations of traffic congestion. The problem arises when a passenger makes a hall call wishing to travel to another floor of the building. The dispatching of the most suitable car is the optimization problem we are tackling in this paper. We develop a viral system algorithm which is based on a bio-inspired virus infection analogy to deal with it. The viral system algorithm is compared to genetic algorithms, and tabu search approaches that have proven efficiency in the vertical transportation literature. The experiments undertaken in tall buildings from 10 to 24 floors, and several car configurations from 2 to 6 cars, provide valuable results and show how viral system outperforms such soft computing algorithms.     

‘Long autonomy or long delay?’ The importance of domain in opinion mining

Nowadays, people do not only navigate the web, but they also contribute contents to the Internet. Among other things, they write their thoughts and opinions in review sites, forums, social networks, blogs and other websites. These opinions constitute a valuable resource for businesses, governments and consumers. In the last years, some researchers have proposed opinion extraction systems, mostly domain-independent ones, to automatically extract structured representations of opinions contained in those texts. In this work, we tackle this task in a domain-oriented approach, defining a set of domain-specific resources which capture valuable knowledge about how people express opinions on a given domain. These resources are automatically induced from a set of annotated documents. Some experiments were carried out on three different domains (user-generated reviews of headphones, hotels and cars), comparing our approach to other state-of-the-art, domain-independent techniques. The results confirm the importance of the domain in order to build accurate opinion extraction systems. Some experiments on the influence of the dataset size and an example of aggregation and visualization of the extracted opinions are also shown.