Use Case for the Development of a Mobile Learning Application

This paper presents use cases developed for a mobile learning application named MLEA （mobile learning environment adapter）, developed in collaboration with the Universidad do Vale do Rio dos Sinos-Unisinos, Brazil and UTP （Universidad Tecnologica de Panama）. MLEA allows users to access, through a single platform, courses in a content management system--Moodle. The objective of this project is to create a communication platform that allows users of Android based mobile devices to use services of the virtual campus of UTP. The work team is composed of six professors and researchers in Panama and three in Brazil, with voluntary students in both countries. A complete, step by step use case is documented, including requirement specifications, interface designs based on Android patterns, as well as programming patterns used for the communication between mobile devices and Moodle platform.     

An analysis of chemical reactor stability and sensitivity — XIV the effect of the steady state hypothesis

This paper is concerned with the effect of neglecting certain chemical species on the stability of a stirred tank chemical reactor as is done when one assumes the steady state hypothesis in chemical kinetics. Two examples, one the HBr reaction and the other a simple consecutive reaction, are considered. It is shown for these two cases that there is no effect on the stability of the reactor when this assumption is made. The analysis is carried out by studying the eigenvalues of the two linearized systems.     

Isothermal oscillations in surface reactions with coverage independent parameters

A procedure for obtaining necessary and sufficient conditions for the existence of periodic solutions in surface reactions with constant temperature and coverage independent parameters is described. An analytic method for the analysis of bifurcation to periodic solutions is developed. This formulation, based on the fundamental matrix of a system of ordinary differential equations, provides a simple means of examining the behavior of system in the neighborhood of a singular point. This method is applied into a reaction model which can yield oscillatory solutions with both single and multiple steady states. When a unique steady state becomes unstable, a limit cycle develops. With three steady states, a state may develop into a stable or unstable limit cycle or may exhibit only periodic solutions without a limit cycle.     

The effects of panresistant bacteria in cystic fibrosis patients on lung transplant outcome

The number of cystic fibrosis (CF) patients undergoing lung transplant continues to rise as long term survival improves. One major contraindication to this potentially life-saving intervention is infection with multi-drug-resistant bacteria. We undertook this retrospective study in 66 transplanted patients over 6 yr to determine the influence of panresistant bacteria on transplant outcome. The in vitro antibiotic susceptibility pattern of respiratory tract bacteria obtained pre- and/or intraoperatively was used to categorize patients into panresistant (n = 27) (Burkholderia cepacia, n = 6, and Pseudomonas aeruginosa, n = 21) or sensitive (n = 39) groups. Postoperative ventilator days, hospital length of stay, and antibiotic days were similar for both groups (p > 0.2). The incidence of bacterial bronchitis (28% and 33%, respectively) and pneumonia (28% and 38%, respectively) did not differ between these groups (p > 0.2) at 6 mo. Likewise, one-year (81% and 83%, respectively) survival was similar for both groups (p > 0.2). As expected, panresistant B. cepacia patients had a lower 1-yr survival (50% versus 90%, p < 0.05) and had a higher mortality attributable to B. cepacia (50% versus 0%, p < 0.01) compared with panresistant P. aeruginosa patients. Our results indicate that CF patients infected with panresistant P. aeruginosa have similar transplant outcomes as patients with sensitive bacteria and should not be excluded from lung transplant based solely on this criterion.     

Implementation of an ADI Method on parallel computers

In this paper we discuss the implementation of an ADI method for solving the diffusion equation on three parallel/vector computers. The computers were chosen so as to encompass a variety of architectures. They are the MPP, an SIMD machine with 16-Kbit serial processors; Flex/32, an MIMD machine with 20 processors; and Cray/2, an MIMD machine with four vector processors. The Gaussian elimination algorithm is used to solve a set of tridiagonal systems on the Flex/32 and Cray/2 while the cyclic elimination algorithm is used to solve these systems on the MPP. The implementation of the method is discussed in relation to these architectures and measures of the performance on each machine are given. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally conclusions are presented.     

A fast routine for fitting Cox models with time varying effects of the covariates

The S-plus and R statistical packages have implemented a counting process setup to estimate Cox models with time varying effects of the covariates. The data set has to be re-arranged in a repeated measurement setting: the time is divided into small time intervals where a single event occurs and for each time interval, the covariate values and outcome in the interval for each subject still under observation are stacked to a large data set. This is the known (Tstart,Tstop] algorithm implemented in Therneau's Survival library (S-plus), which has been ported into an R package by Thomas Lumley. However, the expansion of a data set leads to a larger set, which can be hard to handle even with fast modern computers. We propose the use of a fast and efficient algorithm, written in R, which works on the original data without the use of an expansion. The computations are done on the original data set, with significant less memory resources used. This improves the computational time by orders of magnitude. The algorithm can also fit reduced rank Cox models with time varying effects. We illustrate the method on a large data set of 2433 breast cancer patients, a smaller study of 358 ovarian cancer patients, and compare the computational times on simulated data of up to 10,000 cases with SAS proc phreg and survival package in R. For larger data sets our algorithm was several times faster, and was able to handle larger data sets then SAS and R.     

Targeted interest-driven advertising in cities using Twitter

Targeted advertising is a key characteristic of online as well as traditional-media marketing. However it is very limited in outdoor advertising, that is, performing campaigns by means of billboards in public places. The reason is the lack of information about the interests of the particular passersby, except at very imprecise and aggregate demographic or traffic estimates. In this work we propose a methodology for performing targeted outdoor advertising by leveraging the use of social media. In particular, we use the Twitter social network to gather information about users’ degree of interest in given advertising categories and about the common routes that they follow, characterizing in this way each zone in a given city. Then we use our characterization for recommending physical locations for advertising. Given an advertisement category, we estimate the most promising areas to be selected for the placement of an ad that can maximize its targeted effectiveness. We show that our approach is able to select advertising locations better with respect to a baseline reflecting a current ad-placement policy. To the best of our knowledge this is the first work on offline advertising in urban areas making use of (publicly available) data from social networks.     

Fast schemes for online record linkage

The process of integrating large volumes of data coming from disparate data sources, in order to detect records that refer to the same entities, has always been an important problem in both academia and industry. This problem becomes significantly more challenging when the integration involves a huge amount of records and needs to be conducted in a real-time fashion to address the requirements of critical applications. In this paper, we propose two novel schemes for online record linkage, which achieve very fast response times and high levels of recall and precision. Our proposed schemes embed the records into a Bloom filter space and employ the Hamming Locality-Sensitive Hashing technique for blocking. Each Bloom filter is hashed to a number of hash tables in order to amplify the probability of formulating similar Bloom filter pairs. The main theoretical premise behind our first scheme relies on the number of times a Bloom filter pair is formulated in the hash tables of the blocking mechanism. We prove that this number strongly depends on the distance of that Bloom filter pair. This correlation allows us to estimate in real-time the Hamming distances of Bloom filter pairs without performing the comparisons. The second scheme is progressive and achieves high recall, upfront during the linkage process, by continuously adjusting the sequence in which the hash tables are scanned, and also guarantees, with high probability, the identification of each similar Bloom filter pair. Our experimental evaluation, using four real-world data sets, shows that the proposed schemes outperform four state-of-the-art methods by achieving higher recall and precision, while being very efficient.     

The effect of drastic temperature changes on the performance of MBR treating municipal wastewater

A study has been carried out to define the effect of drastic temperature changes on the performance of lab-scale hollow-fibre MBR in treating municipal wastewater at a flux of 10 L m(-2) h(-1) (LMH). The objectives of the study were to estimate the activated sludge properties, the removal efficiencies of COD and NH(3)-N and the membrane fouling tendency under critical conditions of drastic temperature changes (23, 33, 42 & 33 °C) and MLSS concentration ranged between 6,382 and 8,680 mg/L. The study exhibited that the biomass reduction, the low sludge settleability and the supernatant turbidity were results of temperature increase. The temperature increase led to increase in SMP carbohydrate and protein, and to decrease in EPS carbohydrate and protein. The BRE of COD dropped from 80% at 23 °C to 47% at 42 °C, while the FRE was relatively constant at about 90%. Both removal efficiencies of NH(3)-N trended from about 100% at 33 °C to less than 50% at 42 °C. TMP and BWP ascended critically with temperature increase up to 336 and 304 mbar respectively by the end of the experiment. The values of suspended solids (SS) and the turbidity in the final effluent were negligible. The DO in the mixed liquor was varying with temperature change, while the pH was within the range of 6.7-8.3.