bluuebunny/crossref_metadata_2025 huggingface dataset:
Association between childhood obesity and use of regular medications in the UK: longitudinal cohort study of children aged 5–11 years
Authors: Solmi Francesca , Morris Stephen
Published: June 2015

Objectives

Increasing rates of childhood obesity have been suggested as a possible cause for the increasing prevalence of chronic conditions among adults and children. Few studies have examined whether obese children are more likely to use medications than normal weight children. We investigate this association in the UK.

Design

A panel study with repeated observations at ages 5, 7 and 11.

Setting

A general population sample drawn from the Millennium Cohort Study, a UK-based birth cohort.

Participants

A sample of 9667 children.

Primary and secondary outcome measures

Our primary outcomes were crude and adjusted probabilities of taking any regular medications and the number of medications among overweight and obese children compared with normal weight children. Our secondary outcome was the distribution of medication use by therapeutic classification across body mass index (BMI) groups.

Results

Obese children were more likely to use any medication (marginal effect (ME)=0.02, 95% CI 0.01 to 0.03) and to use more medications (ME=0.08, 95% CI 0.04 to 0.12) than normal weight children. Obese children used more medications for respiratory conditions than those of other BMI groups.

Conclusions

Obese children are more likely to use regular medications and have comorbid conditions, even at young ages. This suggests that the cost of prescriptions should be considered when evaluating the economic burden of childhood obesity and that preventative strategies to reduce childhood obesity could be cost-effective in the short as well as in the long term. While more research is needed, both clinicians and policymakers should be aware of these findings when planning prevention and treatment strategies.
Women's perception of risks of adverse fetal pregnancy outcomes: a large-scale multinational survey
Authors: Petersen Irene , McCrea Rachel L , Lupattelli Angela , Nordeng Hedvig
Published: June 2015

Objective

To determine pregnant women and new mothers’ perception of risks in pregnancy.

Design, settings and participants

This was a large-scale multinational survey including 9113 pregnant women and new mothers from 18 countries in Europe, North America and Australia.

Main outcomes

Risk perception scores (0–10) for harmful effects to the fetus were derived for: (1) medicines (over-the-counter medicine and prescribed medicine), (2) food substances (eggs and blue veined cheese), (3) herbal substances (ginger and cranberries) (4) alcohol and tobacco, and (5) thalidomide.

Results

Overall, 80% (6453/8131) of women perceived the risk of giving birth to a child with a birth defect to be ≤5 of 100 births. The women rated cranberries and ginger least harmful (mean risk perception scores 1.1 and 1.5 of 10, respectively) and antidepressants, alcohol, smoking and thalidomide as most harmful (7.6, 8.6, 9.2 and 9.4 out of 10, respectively). The perception varied with age, level of education, pregnancy status, profession and geographical region. Noticeably, 70% had not heard about thalidomide, but of those who had (2692/9113), the risk perception scores were 0.4–0.5 points lower in women below 25 years compared to women aged 26–30 years.

Conclusions

In general, women perceived the risks of giving birth to a child with birth defects low, but there were substantial disparities between women's perceived risks and the actual risks when it comes to over-the-counter agents against nausea and prescribed medication. The study revealed that few women knew of thalidomide, suggesting that the general awareness among women of the teratogenic effects of thalidomide is declining, but it has left a general scepticism about safety of medication in pregnancy. This may have some severe consequences if women are left without medical treatments in pregnancy.
Pinpointing the sources of the Asian mortality advantage in the USA
Authors: Acciai Francesco , Noah Aggie J , Firebaugh Glenn
Published: June 2015

Background

Asian–Americans outlive whites by an average of nearly 8 years. By determining the sources of the Asian mortality advantage, we can pinpoint where there is the greatest potential for raising the life expectancy of whites and other groups in the USA.

Methods

Our analyses include all Asian and white deaths in the USA between 2006 and 2010, from the Center for Disease Control. Using the International Classification of Diseases (V.10), we code causes of deaths into 19 categories, based on the most common causes as well as causes particularly relevant to racial differences. We then create life tables and apply a newly-developed demographic method to determine whether Asians have longer life expectancy because they are less likely than whites to die of causes of death that strike at younger ages, or because they tend to outlive whites regardless of cause of death.

Results

Nearly 90% of the Asian–white life expectancy gap is attributable to the fact that Asians tend to outlive whites regardless of the cause of death. The causes that contribute the most to the gap are heart disease (24%) and cancers (18%). Men contribute somewhat more to the gap than women do (55% vs 45%), primarily because Asian–white differences in mortality are greater among men than among women with respect to suicide, traffic accidents and accidental poisoning.

Conclusions

For almost all causes of death, Asian victims tend to be older than white victims. The greatest potential for raising the life expectancy of whites to that of Asians, then, resides in efforts that effectively increase whites’ average age at death for the most common causes of death.
Visualization of diffusion phenomena in porous media by means of X-ray computed tomography (CT) scanning
Authors: Sato Akira , Ikeda Koichi
Published: June 2015

The migration of water and contamination materials in rock structures is a significant issue in projects that utilize deep underground locations such as “carbon-dioxide capture and storage” (CCS) and disposal of high-level nuclear waste. These phenomena are also important in the area of preservation of stone structures of cultural heritage signficance, as such stone structures are usually located outside, exposed to wind and rain. The migration of contamination materials in the underground environment, especially in porous rock mass, is governed mainly by water permeation and diffusion. In this study, one-dimensional diffusion testing was conducted and the process in the porous materials was visualized by X-ray computed tomography (CT) scanning. Diffusion is the process caused by the concentrate or density gradient, and is a suitable phenomenon for X-ray CT analysis. In this paper, information related to diffusion is extracted from X-ray CT image data and the distribution of concentration is estimated. From the obtained density distribution, diffusion coefficients are evaluated. One-dimensional permeation tests were also conducted and intrinsic permeabilities of porous materials are evaluated, then the relation between diffusion coefficients and intrinsic permeability is discussed.
Radial consolidation response upon the application and removal of vacuum and fill loading
Authors: Kianfar Kourosh , Indraratna Buddhima , Rujikiatkamjorn Cholachat , Leroueil Serge
Published: June 2015

This Note presents a laboratory study using a Rowe cell to compare the consolidation responses upon vacuum pressure and fill load application and removal. The influences of the duration of application and removal of fill load and vacuum pressures on radial consolidation were investigated using excess pore-water pressure, axial strain, and overconsolidation ratio. It is shown that the appropriate removal time for vacuum pressure can be determined based on excess pore pressure responses.
A novel displacement-based rigorous limit equilibrium method for three-dimensional landslide stability analysis
Authors: Cheng Hao , Zhou Xiaoping
Published: June 2015

Conventional stability analysis of landslides is investigated using the factor of safety of the entire sliding body, which provides no information concerning displacements of the analyzed landslides. In this paper, a novel displacement-based rigorous limit equilibrium method is proposed to investigate the displacements and stabilities of three-dimensional landslides. The relationship between the shear stresses acting on the base of the columns and the shear displacements is established based on the hyperbolic soil model, which can be directly obtained from direct shear tests. According to the displacement compatibility among the columns, the shear displacements of all columns can be determined by the vertical and horizontal displacements at a key point. Combining the six equilibrium conditions of the discretized columns with the nonlinear constitutive relation between stress and displacement of soils, the vertical displacement at the key point can be determined. By introducing the strength reduction technique into the displacement-based rigorous limit equilibrium method, the relationship between the reduction factor and the vertical displacement can be obtained. The displacement and the safety factor of three-dimensional landslides can be defined. Moreover, two cases are given to verify the robustness and precision of the present method in detail.
A General Approach for Word Reordering in English-Vietnamese-English Statistical Machine Translation
Authors: Nguyen Nhung T. H. , Le Vinh Q. , Nghiem Minh-Quoc , Dinh Dien
Published: June 2015

Word ordering is among the most important problems in machine translation. In this paper, we describe a general approach to solve this problem in English-Vietnamese- English statistical machine translation. Our model automatically extracts short-range and long-range reordering rules based on part-of-speech tags and alignment information. Our method, therefore, covers both local and global word order, and is more versatile than other methods. To obtain a better set of reordering rules, we omit generated rules if their weight is lower than a threshold [Formula: see text]. The experimental results have shown that the translation quality has been improved significantly compared to the distance-based reordering model and comparable to the lexicalized model. Our approach is not only suitable for English-Vietnamese but also for language pairs which have many differences in syntax, such as English-Chinese and Chinese-Vietnamese.
CoABCMiner: An Algorithm for Cooperative Rule Classification System Based on Artificial Bee Colony
Authors: Celik Mete , Koylu Fehim , Karaboga Dervis
Published: June 2015

In data mining, classification rule learning extracts the knowledge in the representation of IF_THEN rule which is comprehensive and readable. It is a challenging problem due to the complexity of data sets. Various meta-heuristic machine learning algorithms are proposed for rule learning. Cooperative rule learning is the discovery process of all classification rules with a single run concurrently. In this paper, a novel cooperative rule learning algorithm, called CoABCMiner, based on Artificial Bee Colony is introduced. The proposed algorithm handles the training data set and discovers the classification model containing the rule list. Token competition, new updating strategy used in onlooker and employed phases, and new scout bee mechanism are proposed in CoABCMiner to achieve cooperative learning of different rules belonging to different classes. We compared the results of CoABCMiner with several state-of-the-art algorithms using 14 benchmark data sets. Non parametric statistical tests, such as Friedman test, post hoc test, and contrast estimation based on medians are performed. Nonparametric tests determine the similarity of control algorithm among other algorithms on multiple problems. Sensitivity analysis of CoABCMiner is conducted. It is concluded that CoABCMiner can be used to discover classification rules for the data sets used in experiments, efficiently.
Intelligent Retrieval for Biodiversity
Authors: Ferro M. Vilares , Gavilanes M. Fernández , González A. Blanco , Gómez-Rodríguez C.
Published: June 2015

A proposal for intelligent retrieval in the biodiversity domain is described. It applies natural language processing to integrate linguistic and domain knowledge in a mathematical model for information management, formalizing the notion of semantic similarity in different degrees. The goal is to provide computational tools to identify, extract and relate not only data but also scientific notions, even if the information available to start the process is not complete. The use of conceptual graphs as a basis for interpretation makes it possible to avoid the use of classic ontologies, whose start-up requires costly generation and maintenance protocols and also unnecessarily overload the accessing task for inexpert users. We exploit the automatic generation of these structures from raw texts through graphical and natural language interaction, at the same time providing a solid logical and linguistic foundation to sustain the curation of databases.
Finite Horizon Game for Voluntary Provision of a Discrete Public Good
Authors: Nishikawa Shizuka
Published: June 2015

This paper analyzes a dynamic game for the provision of a discrete public good that will be provided only when a certain number of contributions are made. In each period players are randomly ordered and each player decides whether to contribute or not to the provision of the public good. If not enough contributions are made to provide the public good, the game goes to the next period and continue until the public good is either provided or the game ends at the final period. The paper first assumes symmetric players and shows that the exact period in which the public good will be provided is determined under subgame-perfect equilibria and that for some cost structures there will be a delay in provision of the public good. Counterintuitively, in some cases the public good is provided earlier at higher costs than at lower costs. The paper then introduces a partial public good, which requires fewer contributions to be provided but has a smaller value. We show that for some costs, introducing the partial public good eliminates the possibility of providing any kind of public good. For other cost structures, introducing the partial public good may improve social welfare. At last, asymmetric costs are introduced. The results are similar to the symmetric case.
INTELLECTUAL CAPITAL, INNOVATION, AND PERFORMANCE: EMPIRICAL EVIDENCE FROM SMEs
Authors: LEITNER KARL-HEINZ
Published: June 2015

This research paper examines the relationship between intellectual capital, product innovation and performance based on a study of Austrian firms covering a 10-year period. It is argued that intellectual capital enhances a firms ability to successfully realise innovations and thus contributes positively to its performance. Our study found that human capital and structural capital were both significantly associated with performance in product innovating firms, but that each had a different impact on this performance. While human capital had a positive impact on profitability and growth in the long run, contrary to expectations, structural capital had a negative effect on profitability and growth indicating that apparent strength can turn into a weakness over time. In addition, the study found that human capital and structural capital had no joint effect on the performance of product innovating firms.
Classical Plasmonics: Wave Propagation Control at Subwavelength Scale
Authors: Coello Víctor , Garcia-Ortiz Cesar E. , Garcia-Mendez Manuel
Published: June 2015

In this paper, surface plasmons polariton propagation and manipulation is reviewed in the context of experiments and modeling of optical images. We focus our attention in the interaction of surface plasmon polaritons with arrays of micro-scatereres and nanofabricated structures. Numerical simulations and experimental results of different plasmonic devices are presented. Plasmonic beam manipulation opens up numerous possibilities for application in biosensing, nanophotonics, and in general in the area of surface optics properties.
Effect of Cr3+ Substitution on Structural, Magnetic and Dielectric Properties of Nanocrystalline Ni0.5Zn0.5CrxFe2-xO4 Ferrite System
Authors: Prasad M. Siva Ram , Babu B. R. , Ramesh K. V. , Trinath K.
Published: June 2015

Polycrystalline Ni – Zn – Cr ferrite nanoparticles with composition Ni 0.5 Zn 0.5 Cr x Fe 2-x O 4 (for x in the range of 0.00–0.25 insteps of 0.05) were prepared through the nitrate-citrate gel autocombustion method. The as-obtained powders were ground and annealed at 1000°C for 4 h and characterized for spinel phase using X-ray diffraction, transmission electron microscopy (TEM) and scanning electron microscopy (SEM). X-ray diffraction revealed the existence of single phase spinel while the TEM micrographs showed the presence of nearly spherical particles with soft agglomeration. Pelleted and toroidal samples of the same ferrite compound were sintered at 1000°C for 4 h. The dielectric constant and the dielectric loss tangent decreased with frequency in the range of 1 kHz–13 MHz while the initial permeability remained almost constant at lower measuring frequencies and thereafter increased with frequency for all samples. The observed variations have been discussed in the light of existing understanding.
Effects of the wall properties on unsteady peristaltic flow of an Eyring–Powell fluid in a three-dimensional rectangular duct
Authors: Riaz Arshad , Nadeem S. , Ellahi R.
Published: June 2015

In the present investigation, peristaltic flow of non-Newtonian fluid model (Eyring–Powell) has been taken into consideration in a cross-section of three-dimensional rectangular channel. The flow is taken to be unsteady and incompressible. The observations are made under the limitations of low Reynolds number and long wavelength which helps in reducing the governing equations. The walls of the channel are supposed to be compliant. The obtained equations are nonlinear partial differential equation of second order and have been solved analytically by using series solution technique. The achieved results are then portrayed graphically to see the variation of various emerging parameters on the profile of velocity. The stream functions have also been sketched in order to discuss the trapping behavior of the circular bolus.
On fluctuations for random band Toeplitz matrices
Authors: Li Yiting , Sun Xin
Published: June 2015

In this paper, we study two one-parameter families of random band Toeplitz matrices: [Formula: see text] where

(1) a0 = 0, {a1, a2, …} in An(t) are independent random variables and a-i = ai;

(2) a0(t) = 0, {a1(t), a2(t), …} in Bn(t) are independent copies of the standard Brownian motion at time t and a-i(t) = ai(t).

As t varies, the empirical measures μ(An(t)) and μ(Bn(t)) are measure valued stochastic processes. The purpose of this paper is to study the fluctuations of μ(An(t)) and μ(Bn(t)) as n goes to ∞. Given a monomial f(x) = xp with p ≥ 2, the corresponding rescaled fluctuations of μ(An(t)) and μ(Bn(t)) are [Formula: see text] respectively. We will prove that the above equations converge to centered Gaussian families {Zp(t)} and {Wp(t)} respectively. The covariance structure 𝔼[Zp(t1)Zq(t2)] and 𝔼[Wp(t1)Wq(t2)] are obtained for all p, q ≥ 2, t1, t2 ≥ 0, and are both homogeneous polynomials of t1 and t2 for fixed p, q. In particular, Z2(t) is the Brownian motion and Z3(t) is the same as W2(t) up to a constant. The main method of this paper is the moment method.
An Interview with Prof. Andreas Zeller
Authors: Tichy Walter
Published: June 2015

In 1976, Les Belady and Manny Lehman published the first empirical growth study of a large software system, IBMs OS 360. At the time, the operating system was twelve years old and the authors were able to study 21 successive releases of the software. By looking at variables such as number of modules, time for preparing releases, and modules handled between releases (a defect indicator), they were able to formulate three laws: The law of continuing change, the law of increasing entropy, and the law of statistically smooth growth. These laws are valid to this day. Belady and Lehman were ahead of their time. They understood that empirical studies such as theirs might lead to a deeper understanding of software development processes, which might in turn lead to better control of software cost and quality. However, studying large software systems proved difficult, because complete records were rare and companies were reluctant to open their books to outsiders. Three important developments changed this situation for the better. The first one was the widespread adoption of configuration management tools, starting in the mid 1980s. Tools such as RCS and CVS recorded complete development histories of software. These tools stored significantly more information, in greater detail, than Belady and Lehman had available. The history allowed the reconstruction of virtually any configuration ever compiled in the life of the system. I worked on the first analysis of such a history to assess the cost of several different choices for smart recompilation (ACM TOSEM, Jan. 1994). The second important development was the inclusion of bug reports and linking them to offending software modules in the histories. This information proved extremely valuable, as we shall see in this interview. The third important development was the emergence of open source, through which numerous and large development histories became available for study. Soon, workers began to analyze these repositories. Workshops on mining software repositories have been taking place annually since 2004. I spoke with Prof. Andreas Zeller about the nuggets of wisdom unearthed by the analysis of software repositories. Andreas works at Saarland University in Saarbrücken, Germany. His research addresses the analysis of large, complex software systems, especially the analysis of why these systems fail to work as they should. He is a leading authority on analyzing software repositories and on testing and debugging. -- Walter Tichy, Editor
Ubiquity symposium 'What is computation?'
Authors: Frailey Dennis J.
Published: June 2015

Various authors define forms of computation as specialized types of processes. As the scope of computation widens, the range of such specialties increases. Dennis J. Frailey posits that the essence of computation can be found in any form of process, hence the title and the thesis of this paper in the Ubiquity symposium discussion what is computation. --Editor
Reliable Generation of High-Performance Matrix Algebra
Authors: Nelson Thomas , Belter Geoffrey , Siek Jeremy G. , Jessup Elizabeth , Norris Boyana
Published: June 2015

Scientific programmers often turn to vendor-tuned Basic Linear Algebra Subprograms (BLAS) to obtain portable high performance. However, many numerical algorithms require several BLAS calls in sequence, and those successive calls do not achieve optimal performance. The entire sequence needs to be optimized in concert. Instead of vendor-tuned BLAS, a programmer could start with source code in Fortran or C (e.g., based on the Netlib BLAS) and use a state-of-the-art optimizing compiler. However, our experiments show that optimizing compilers often attain only one-quarter of the performance of hand-optimized code. In this article, we present a domain-specific compiler for matrix kernels, the Build to Order BLAS (BTO), that reliably achieves high performance using a scalable search algorithm for choosing the best combination of loop fusion, array contraction, and multithreading for data parallelism. The BTO compiler generates code that is between 16% slower and 39% faster than hand-optimized code.
odeToJava
Authors: Kroshko Andrew , Spiteri Raymond J.
Published: June 2015

Problem-solving environments (PSEs) offer a powerful yet flexible and convenient means for general experimentation with computational methods, algorithm prototyping, and visualization and manipulation of data. Consequently, PSEs have become the
modus operandi
of many computational scientists and engineers. However, despite these positive aspects, PSEs typically do not offer the level of granularity required by the specialist or algorithm designer to conveniently modify the details. In other words, the level at which PSEs are black boxes is often still too high for someone interested in modifying an algorithm as opposed to trying an alternative.

In this article, we describe odeToJava, a Java-based PSE for initial-value problems in ordinary differential equations. odeToJava implements explicit and linearly implicit implicit-explicit Runge--Kutta methods with error and stepsize control and intra-step interpolation (dense output), giving the user control and flexibility over the implementational aspects of these methods. We illustrate the usage and functionality of odeToJava by means of computational case studies of initial-value problems (IVPs).
Rank-Balanced Trees
Authors: Haeupler Bernhard , Sen Siddhartha , Tarjan Robert E.
Published: June 2015

Since the invention of AVL trees in 1962, many kinds of binary search trees have been proposed. Notable are red-black trees, in which bottom-up rebalancing after an insertion or deletion takes O(1) amortized time and O(1) rotations worst-case. But the design space of balanced trees has not been fully explored. We continue the exploration. Our contributions are three: We systematically study the use of
ranks
and
rank differences
to define height-based balance in binary trees. Different invariants on rank differences yield AVL trees, red-black trees, and other kinds of balanced trees. By relaxing AVL trees, we obtain a new kind of balanced binary tree, the
weak AVL tree (wavl tree)
, whose properties we develop. Bottom-up rebalancing after an insertion or deletion takes O(1) amortized time and at most two rotations, improving the three or more rotations per deletion needed in all other kinds of balanced trees of which we are aware. The height bound of a wavl tree degrades gracefully from that of an AVL tree as the number of deletions increases and is never worse than that of a red-black tree. Wavl trees also support top-down, fixed look-ahead rebalancing in O(1) amortized time. Finally, we use exponential potential functions to prove that in wavl trees rebalancing steps occur exponentially infrequently in rank. Thus, most of the rebalancing is at the bottom of the tree, which is crucial in concurrent applications and in those in which rotations take time that depends on the subtree size.
Parallel Massive Clustering of Discrete Distributions
Authors: Zhang Yu , Wang James Z. , Li Jia
Published: June 2015

The trend of analyzing big data in artificial intelligence demands highly-scalable machine learning algorithms, among which clustering is a fundamental and arguably the most widely applied method. To extend the applications of regular vector-based clustering algorithms, the Discrete Distribution (D2) clustering algorithm has been developed, aiming at clustering data represented by bags of weighted vectors which are well adopted data signatures in many emerging information retrieval and multimedia learning applications. However, the high computational complexity of D2-clustering limits its impact in solving massive learning problems. Here we present the parallel D2-clustering (PD2-clustering) algorithm with substantially improved scalability. We developed a hierarchical multipass algorithm structure for parallel computing in order to achieve a balance between the individual-node computation and the integration process of the algorithm. Experiments and extensive comparisons between PD2-clustering and other clustering algorithms are conducted on synthetic datasets. The results show that the proposed parallel algorithm achieves significant speed-up with minor accuracy loss. We apply PD2-clustering to image concept learning. In addition, by extending D2-clustering to symbolic data, we apply PD2-clustering to protein sequence clustering. For both applications, we demonstrate the high competitiveness of our new algorithm in comparison with other state-of-the-art methods.
Mathematical Modeling and Analysis of Product Rating with Partial Information
Authors: Xie Hong , Lui John C. S.
Published: June 2015

Many Web services like Amazon, Epinions, and TripAdvisor provide historical product ratings so that users can evaluate the quality of products. Product ratings are important because they affect how well a product will be adopted by the market. The challenge is that we only have partial information on these ratings: each user assigns ratings to only a small subset of products. Under this partial information setting, we explore a number of fundamental questions. What is the minimum number of ratings a product needs so that one can make a reliable evaluation of its quality? How may users’ misbehavior, such as cheating in product rating, affect the evaluation result? To answer these questions, we present a probabilistic model to capture various important factors (e.g., rating aggregation rules, rating behavior) that may influence the product quality assessment under the partial information setting. We derive the minimum number of ratings needed to produce a reliable indicator on the quality of a product. We extend our model to accommodate users’ misbehavior in product rating. We derive the maximum fraction of misbehaving users that a rating aggregation rule can tolerate and the minimum number of ratings needed to compensate. We carry out experiments using both synthetic and real-world data (from Amazon and TripAdvisor). We not only validate our model but also show that the “average rating rule” produces more reliable and robust product quality assessments than the “majority rating rule” and the “median rating rule” in aggregating product ratings. Last, we perform experiments on two movie rating datasets (from Flixster and Netflix) to demonstrate how to apply our framework to improve the applications of recommender systems.
Process Discovery under Precedence Constraints
Authors: Greco Gianluigi , Guzzo Antonella , Lupia Francesco , Pontieri Luigi
Published: June 2015

Process discovery has emerged as a powerful approach to support the analysis and the design of complex processes. It consists of analyzing a set of traces registering the sequence of tasks performed along several enactments of a transactional system, in order to build a process model that can explain all the episodes recorded over them. An approach to accomplish this task is presented that can benefit from the background knowledge that, in many cases, is available to the analysts taking care of the process (re-)design. The approach is based on encoding the information gathered from the log and the (possibly) given background knowledge in terms of
precedence constraints
, that is, of constraints over the topology of the resulting process models. Mining algorithms are eventually formulated in terms of reasoning problems over precedence constraints, and the computational complexity of such problems is thoroughly analyzed by tracing their tractability frontier. Solution algorithms are proposed and their properties analyzed. These algorithms have been implemented in a prototype system, and results of a thorough experimental activity are discussed.
Similarity Search over the Cloud Based on Image Descriptors' Dimensions Value Cardinalities
Authors: Antaris Stefanos , Rafailidis Dimitrios
Published: June 2015

In recognition that in modern applications billions of images are stored into distributed databases in different logical or physical locations, we propose a similarity search strategy over the cloud based on the dimensions value cardinalities of image descriptors. Our strategy has low preprocessing requirements by dividing the computational cost of the preprocessing steps into several nodes over the cloud and locating the descriptors with similar dimensions value cardinalities logically close. New images are inserted into the distributed databases over the cloud efficiently, by supporting dynamical update in real-time. The proposed insertion algorithm has low computational complexity, depending exclusively on the dimensionality of descriptors and a small subset of descriptors with similar dimensions value cardinalities. Finally, an efficient query processing algorithm is proposed, where the dimensions of image descriptors are prioritized in the searching strategy, assuming that dimensions of high value cardinalities have more discriminative power than the dimensions of low ones. The computation effort of the query processing algorithm is divided into several nodes over the cloud infrastructure. In our experiments with seven publicly available datasets of image descriptors, we show that the proposed similarity search strategy outperforms competitive methods of single node, parallel and cloud-based architectures, in terms of preprocessing cost, search time and accuracy.
QuGu
Authors: Li Yang , Boukerche Azzedine
Published: June 2015

Video dissemination over Vehicular Ad Hoc Networks is an attractive technology that supports many novel applications. The merit of this work lies in the design of an efficient video dissemination protocol that provides high video quality at different data rates for urban scenarios. Our objective is to improve received video quality while meeting delay and packet loss. In this work, we first employ a reliable scheme known as connected dominating set, which is an efficient receiver-based routing scheme for broadcasting video content. To avoid repeated computing of the connected dominating set, we add three statuses to each node. In nonscalable video coding, the distribution of lost frames can cause a major impact on video quality at the receiver's end. Therefore, for the second step, we employ Interleaving to spread out the burst losses and to reduce the influence of loss distributions. Although Interleaving can reduce the influence of cluster frame loss, single packet loss is also a concern due to collisions, and to intermittent disconnection in the topology. In order to fix these single packet losses, we propose a store-carry-forward scheme for the nodes in order to retransmit the local buffer stored packets. The results, when compared to the selected base protocols, show that our proposed protocol is an efficient solution for video dissemination over urban Vehicular Ad Hoc Networks.
Measuring the Performance of a Location-Aware Text Prediction System
Authors: Garcia Luís Filipe , Oliveira Luís Caldas De , Matos David Martins De
Published: June 2015

In recent years, some works have discussed the conception of location-aware Augmentative and Alternative Communication (AAC) systems with very positive feedback from participants. However, in most cases, complementary quantitative evaluations have not been carried out to confirm those results. To contribute to clarifying the validity of these approaches, our study quantitatively evaluated the effect of using language models with location knowledge on the efficiency of a word and sentence prediction system. Using corpora collected for three different locations (classroom, school cafeteria, home), location-specific language models were trained with sentences from each location and compared with a traditional all-purpose language model, trained on all corpora. User tests showed a modest mean improvement of 2.4% and 1.3% for Words Per Minute (WPM) and Keystroke Saving Rate (KSR), respectively, but the differences were not statistically significant. Since our text prediction system relies on the concept of sentence reuse, we ran a set of simulations with language models having different sentence knowledge levels (0%, 25%, 50%, 75%, 100%). We also introduced in the comparison a second location-aware strategy that combines the location-specific approach with the all-purpose approach (mixed approach). The mixed language models performed better under low sentence-reuse conditions (0%, 25%, 50%) with 1.0%, 1.3%, and 1.2% KSR improvements, respectively. The location-specific language models performed better under high sentence-reuse conditions (75%, 100%) with 1.7% and 1.5% KSR improvements, respectively.
ApproxHadoop
Authors: Goiri Inigo , Bianchini Ricardo , Nagarakatte Santosh , Nguyen Thu D.
Published: June 2015

We propose and evaluate a framework for creating and running approximation-enabled MapReduce programs. Specifically, we propose approximation mechanisms that fit naturally into the MapReduce paradigm, including input data sampling, task dropping, and accepting and running a precise and a user-defined approximate version of the MapReduce code. We then show how to leverage statistical theories to compute error bounds for popular classes of MapReduce programs when approximating with input data sampling and/or task dropping. We implement the proposed mechanisms and error bound estimations in a prototype system called ApproxHadoop. Our evaluation uses MapReduce applications from different domains, including data analytics, scientific computing, video encoding, and machine learning. Our results show that ApproxHadoop can significantly reduce application execution time and/or energy consumption when the user is willing to tolerate small errors. For example, ApproxHadoop can reduce runtimes by up to 32x when the user can tolerate an error of 1% with 95% confidence. We conclude that our framework and system can make approximation easily accessible to many application domains using the MapReduce model.
NumaGiC
Authors: Gidra Lokesh , Thomas Gaël , Sopena Julien , Shapiro Marc , Nguyen Nhan
Published: June 2015

On contemporary cache-coherent Non-Uniform Memory Access (ccNUMA) architectures, applications with a large memory footprint suffer from the cost of the garbage collector (GC), because, as the GC scans the reference graph, it makes many remote memory accesses, saturating the interconnect between memory nodes. We address this problem with NumaGiC, a GC with a mostly-distributed design. In order to maximise memory access locality during collection, a GC thread avoids accessing a different memory node, instead notifying a remote GC thread with a message; nonetheless, NumaGiC avoids the drawbacks of a pure distributed design, which tends to decrease parallelism. We compare NumaGiC with Parallel Scavenge and NAPS on two different ccNUMA architectures running on the Hotspot Java Virtual Machine of OpenJDK 7. On Spark and Neo4j, two industry-strength analytics applications, with heap sizes ranging from 160GB to 350GB, and on SPECjbb2013 and SPECjbb2005, ourgc improves overall performance by up to 45% over NAPS (up to 94% over Parallel Scavenge), and increases the performance of the collector itself by up to 3.6x over NAPS (up to 5.4x over Parallel Scavenge).
DIABLO
Authors: Tan Zhangxi , Qian Zhenghao , Chen Xi , Asanovic Krste , Patterson David
Published: June 2015

Motivated by rapid software and hardware innovation in warehouse-scale computing (WSC), we visit the problem of warehouse-scale network design evaluation. A WSC is composed of about 30 arrays or clusters, each of which contains about 3000 servers, leading to a total of about 100,000 servers per WSC. We found many prior experiments have been conducted on relatively small physical testbeds, and they often assume the workload is static and that computations are only loosely coupled with the adaptive networking stack. We present a novel and cost-efficient FPGAbased evaluation methodology, called Datacenter-In-A-Box at LOw cost (DIABLO), which treats arrays as whole computers with tightly integrated hardware and software. We have built a 3,000-node prototype running the full WSC software stack. Using our prototype, we have successfully reproduced a few WSC phenomena, such as TCP Incast and memcached request latency long tail, and found that results do indeed change with both scale and with version of the full software stack.
SPECS
Authors: Hicks Matthew , Sturton Cynthia , King Samuel T. , Smith Jonathan M.
Published: June 2015

Processor implementation errata remain a problem, and worse, a subset of these bugs are security-critical. We classified 7 years of errata from recent commercial processors to understand the magnitude and severity of this problem, and found that of 301 errata analyzed, 28 are security-critical. We propose the SECURITY-CRITICAL PROCESSOR ER- RATA CATCHING SYSTEM (SPECS) as a low-overhead solution to this problem. SPECS employs a dynamic verification strategy that is made lightweight by limiting protection to only security-critical processor state. As a proof-of- concept, we implement a hardware prototype of SPECS in an open source processor. Using this prototype, we evaluate SPECS against a set of 14 bugs inspired by the types of security-critical errata we discovered in the classification phase. The evaluation shows that SPECS is 86% effective as a defense when deployed using only ISA-level state; incurs less than 5% area and power overhead; and has no software run-time overhead.
iThreads
Authors: Bhatotia Pramod , Fonseca Pedro , Acar Umut A. , Brandenburg Björn B. , Rodrigues Rodrigo
Published: June 2015

Incremental computation strives for efficient successive runs of applications by re-executing only those parts of the computation that are affected by a given input change instead of recomputing everything from scratch. To realize these benefits automatically, we describe iThreads, a threading library for parallel incremental computation. iThreads supports unmodified shared-memory multithreaded programs: it can be used as a replacement for pthreads by a simple exchange of dynamically linked libraries, without even recompiling the application code. To enable such an interface, we designed algorithms and an implementation to operate at the compiled binary code level by leveraging MMU-assisted memory access tracking and process-based thread isolation. Our evaluation on a multicore platform using applications from the PARSEC and Phoenix benchmarks and two case-studies shows significant performance gains.
Watson and the Era of Cognitive Computing
Authors: Banavar Guruduth
Published: June 2015

In the last decade, the availability of massive amounts of new data, and the development of new machine learning technologies, have augmented reasoning systems to give rise to a new class of computing systems. These "Cognitive Systems" learn from data, reason from models, and interact naturally with us, to perform complex tasks better than either humans or machines can do by themselves. In essence, cognitive systems help us perform like the best by penetrating the complexity of big data and leverage the power of models. One of the first cognitive systems, called Watson, demonstrated through a Jeopardy! exhibition match, that it was capable of answering complex factoid questions as effectively as the world's champions. Follow-on cognitive systems perform other tasks, such as discovery, reasoning, and multi-modal understanding in a variety of domains, such as healthcare, insurance, and education. We believe such cognitive systems will transform every industry and our everyday life for the better. In this talk, I will give an overview of the applications, the underlying capabilities, and some of the key challenges, of cognitive systems.
CoolAir
Authors: Goiri Íñigo , Nguyen Thu D. , Bianchini Ricardo
Published: June 2015

Despite its benefits, free cooling may expose servers to high absolute temperatures, wide temperature variations, and high humidity when datacenters are sited at certain locations. Prior research (in non-free-cooled datacenters) has shown that high temperatures and/or wide temporal temperature variations can harm hardware reliability. In this paper, we identify the runtime management strategies required to limit absolute temperatures, temperature variations, humidity, and cooling energy in free-cooled datacenters. As the basis for our study, we propose CoolAir, a system that embodies these strategies. Using CoolAir and a real free-cooled datacenter prototype, we show that effective management requires cooling infrastructures that can act smoothly. In addition, we show that CoolAir can tightly manage temperature and significantly reduce temperature variation, often at a lower cooling cost than existing free-cooled datacenters. Perhaps most importantly, based on our results, we derive several principles and lessons that should guide the design of management systems for free-cooled datacenters of any size.
Protecting Data on Smartphones and Tablets from Memory Attacks
Authors: Colp Patrick , Zhang Jiawen , Gleeson James , Suneja Sahil , de Lara Eyal , Raj Himanshu , Saroiu Stefan , Wolman Alec
Published: June 2015

Smartphones and tablets are easily lost or stolen. This makes them susceptible to an inexpensive class of memory attacks, such as cold-boot attacks, using a bus monitor to observe the memory bus, and DMA attacks. This paper describes Sentry, a system that allows applications and OS components to store their code and data on the System-on-Chip (SoC) rather than in DRAM. We use ARM-specific mechanisms originally designed for embedded systems, but still present in today's mobile devices, to protect applications and OS subsystems from memory attacks.
GhostRider
Authors: Liu Chang , Harris Austin , Maas Martin , Hicks Michael , Tiwari Mohit , Shi Elaine
Published: June 2015

This paper presents a new, co-designed compiler and architecture called GhostRider for supporting privacy preserving computation in the cloud. GhostRider ensures all programs satisfy a property called memory-trace obliviousness (MTO): Even an adversary that observes memory, bus traffic, and access times while the program executes can learn nothing about the program's sensitive inputs and outputs. One way to achieve MTO is to employ Oblivious RAM (ORAM), allocating all code and data in a single ORAM bank, and to also disable caches or fix the rate of memory traffic. This baseline approach can be inefficient, and so GhostRider's compiler uses a program analysis to do better, allocating data to non-oblivious, encrypted RAM (ERAM) and employing a scratchpad when doing so will not compromise MTO. The compiler can also allocate to multiple ORAM banks, which sometimes significantly reduces access times.We have formalized our approach and proved it enjoys MTO. Our FPGA-based hardware prototype and simulation results show that GhostRider significantly outperforms the baseline strategy.
DEUCE
Authors: Young Vinson , Nair Prashant J. , Qureshi Moinuddin K.
Published: June 2015

Phase Change Memory (PCM) is an emerging Non Volatile Memory (NVM) technology that has the potential to provide scalable high-density memory systems. While the non-volatility of PCM is a desirable property in order to save leakage power, it also has the undesirable effect of making PCM main memories susceptible to newer modes of security vulnerabilities, for example, accessibility to sensitive data if a PCM DIMM gets stolen. PCM memories can be made secure by encrypting the data. Unfortunately, such encryption comes with a significant overhead in terms of bits written to PCM memory, causing half of the bits in the line to change on every write, even if the actual number of bits being written to memory is small. Our studies show that a typical writeback modifies, on average, only 12% of the bits in the cacheline. Thus, encryption causes almost a 4x increase in the number of bits written to PCM memories. Such extraneous bit writes cause significant increase in write power, reduction in write endurance, and reduction in write bandwidth. To provide the benefit of secure memory in a write efficient manner this paper proposes Dual Counter Encryption (DEUCE). DEUCE is based on the observation that a typical writeback only changes a few words, so DEUCE reencrypts only the words that have changed. We show that DEUCE reduces the number of modified bits per writeback for a secure memory from 50% to 24%, which improves performance by 27% and increases lifetime by 2x.