Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Change and the Service Sector in Brazil

A key question with a long tradition in development economics is which patterns of structural change are more conducive for economic growth and convergence in the international economy. Although some studies show that industry has been loosing ground in the Brazilian economy (both in terms of employment and value added), there are few studies discussing how this process affects the performance of the Brazilian economy. Evidence regarding the quality of the jobs created in other sectors is yet scarce. Both topics are addressed in this paper. It is suggested that that the Brazilian deindustrialization process is not a virtuous one, i.e. it is not the result of a dynamic response to long run trends in technology and demand. On the contrary, most jobs are generated in low-productivity activities in the service sector.
Power allocation based on Convex Optimization Theory for fading channels in OFDM-based cognitive radio networks

A cognitive radio network (CRN) is formed by allowing the secondary user (SU) to opportunistically access the frequency bands originally allocated to primary user (PU) as long as its interference does not degrade the quality of service (QoS) of PU to an unacceptable level. Specially, by using a suboptimal scheme, we analyze the ergodic capacity under three types of constraints which satisfy primary QoS requirements for delay-insensitive, delay-sensitive and mixed applications, respectively. In particular, considering different fading channel models, we further provide the closed-form expressions for ergodic capacity of SU subject to corresponding constraints. Numerical simulation results corroborating our theoretical analysis were also provided.
FoXtrot: Distributed structural and value XML filtering

Publish/subscribe systems have emerged in recent years as a promising paradigm for offering various popular notification services. In this context, many XML filtering systems have been proposed to efficiently identify XML data that matches user interests expressed as queries in an XML query language like XPath. However, in order to offer XML filtering functionality on an Internet-scale, we need to deploy such a service in a distributed environment, avoiding bottlenecks that can deteriorate performance. In this work, we design and implement FoXtrot, a system for filtering XML data that combines the strengths of automata for efficient filtering and distributed hash tables for building a fully distributed system. Apart from structural-matching, performed using automata, we also discuss different methods for evaluating value-based predicates. We perform an extensive experimental evaluation of our system, FoXtrot, on a local cluster and on the PlanetLab network and demonstrate that it can index millions of user queries, achieving a high indexing and filtering throughput. At the same time, FoXtrot exhibits very good load-balancing properties and improves its performance as we increase the size of the network.
DEC-A*: A Decentralized Multiagent Pathfinding Algorithm

A* is the algorithm of finding the shortest path between two nodes in a graph. When the searching problem is constituted of a set of linked graphs, A* searches solution like if it is face of one graph formed by linked graphs. While researchers have developed solutions to reduce the execution time of A* in multiple cases by multiples techniques, we develop a new algorithm: DEC-A* which is a decentralized version of A* composing a solution through a collection of graph. A* uses a distance-plus-cost heuristic function to determine the order in which the search visits nodes in the tree. Our algorithm DEC-A* extends the evaluation of the distance-plus-cost heuristic to be the sum of two functions : local distance, which evaluates the cost to reach the nearest neighbor node s to the goal, and global distance which evaluates the cost from s to the goal through other graphs. DEC-A* reduces the time of finding the shortest path and reduces the complexity, while ensuring the privacy of graphs.
Traffic-Energy Balanced Routing Protocol with Two-direction Routing

Ad hoc network is usually built up by battery-powered nodes, so the energy is limited, and the network’s lifetime often depends on several hot nodes. This paper puts forward a routing protocol AODV-TEB (Ad hoc On-demand Distance Vector - Traffic-Energy Balanced) to solve this problem. In AODV-TEB, each node calculated its traffic load per second, and got its left battery, then formed a nonlinear weight of the node. When the battery was high, the weight mainly depended on the traffic load. When the battery was low, the weight mainly depended on the battery. Unlike a single-direction routing protocol, each node in AODV-TEB selected its up-link node and its down-link node according to their weights, the smaller, the better. The weight of a route was the maximum weight of the nodes on the link. AODV-TEB got all available routes to the destination, and selected one with the smallest weight. According to the simulations, AODV-TEB averaged the lifetime of the nodes, therefore prolonged the lifetime of the network. And when the battery was enough, AODV-TEB avoided competing with other users for hot nodes, hence reduced the probability of collision, and improved the packet delivery ratio.
OpenCL embedded profile prototype in mobile device

Programmable Graphics Processing Unit (GPU) has over the years become an integral part of today's computing systems. The GPU use-cases have gradually been extended from graphics towards a wide range of applications. Since the programmable GPU is now making its way to mobile devices, it is interesting to study these new use-cases also there. To test this, we created a programming environment based on the embedded profile of the fresh Khronos OpenCL standard and ran it against an image processing workload in a mobile device with CPU and GPU back-ends. The early results on performance and energy consumption with CPU+GPU configuration were promising but also suggest there is room for optimization.
AndroZoo: Collecting Millions of Android Apps for the Research Community

We present a growing collection of Android Applications col-lected from several sources, including the official GooglePlay app market. Our dataset, AndroZoo, currently contains more than three million apps, each of which has beenanalysed by tens of different AntiVirus products to knowwhich applications are detected as Malware. We provide thisdataset to contribute to ongoing research efforts, as well asto enable new potential research topics on Android Apps.By releasing our dataset to the research community, we alsoaim at encouraging our fellow researchers to engage in reproducible experiments.
Computer Creativity in the Automatic Design of Robots

This article demonstrates the possibility that robotic systems can automatically design robots with complex morphologies and tightly adapted control systems at a low cost. These automatic designs are inspired by nature and achieved through an artificial coevolutionary process to adapt the bodies and brains of artificial life-forms simultaneously through interaction with a simulated reality. Through the use of rapid manufacturing, these evolved designs can be transferred from virtual to true reality. The artificial evolution process embedded in realistic physical simulation can create simple designs often recognizable from the history of biology or engineering. This paper provides a brief review of three generations of these robots, from automatically designed LEGO structures, through the GOLEM project of electromechanical systems based on truss structures, to new modular designs that make use of a generative, DNA-like representation.
Timing in multimodal turn-taking interactions

Turn-taking interactions with humans are multimodal and reciprocal in nature. In addition, the timing of actions is of great importance, as it influences both social and task strategies. To enable the precise control and analysis of timed discrete events for a robot, we develop a system for multimodal collaboration based on a timed Petri net (TPN) representation. We also argue for action interruptions in reciprocal interaction and describe its implementation within our system. Using the system, our autonomously operating humanoid robot Simon collaborates with humans through both speech and physical action to solve the Towers of Hanoi, during which the human and the robot take turns manipulating objects in a shared physical workspace. We hypothesize that action interruptions have a positive impact on turn-taking and evaluate this in the Towers of Hanoi domain through two experimental methods. One is a between-groups user study with 16 participants. The other is a simulation experiment using 200 simulated users of varying speed, initiative, compliance, and correctness. In these experiments, action interruptions are either present or absent in the system. Our collective results show that action interruptions lead to increased task efficiency through increased user initiative, improved interaction balance, and higher sense of fluency. In arriving at these results, we demonstrate how these evaluation methods can be highly complementary in the analysis of interaction dynamics.
A method for joint sparse sampling of time and gradient domains in diffusion-ordered NMR spectroscopy

Nuclear magnetic resonance (NMR) spectroscopy is one of the most valuable tools for chemical analysis. In particular, multidimensional NMR spectra can provide an information on structures of large molecules or complex chemical mixtures. However, because of time-consuming sampling of a multidimensional signal, they require days-long data collection process. This problem has been to some extent circumvented by an application of various sparse sampling techniques in last few years. Nevertheless, they were limited to frequency dimensions of NMR spectra. In this paper, we show how to extend sparse sampling to diffusion dimensions. The procedure is based on a minimum ℓ1-norm restrained Fourier and inverted Laplace transforms. The results of simulations indicate, that the approach can be successfully exploited in experimental studies.
Real-Time Tasks Scheduling with Value Control to Predict Timing Faults During Overload

Modern real-time applications are very dynamic and cannot cope with the use of worst case execution time to avoid overload situations. Therefore scheduling algorithms that are able to prevent timing faults during overload are required. In this context, the value parameter has become useful to add generality and flexibility to such systems. In this paper, we present the scheduling algorithm called DMB (dynamic misses based), which is capable of dynamically changing tasks value in order to adjust their importance according to its timing faults rate. The main goal of DMB is to allow the prediction of timing faults during overloads and thereby support a dynamic tuning of tasks fault rate. It is used to enhance the features of the previously defined TAFT (time-aware fault-tolerant) scheduler. Obtained results show that DMB in conjunction with TAFT reached the most promising results during overloads, allowing to control tasks degradation in a graceful and determined way
SAT-DB : An Integrated System for Satisfiability Problem Study

The Satisfiability problem (SAT) is of great importance in several investigation fields, it refers to the task of finding an assignment of truth values that satisfy a boolean arbitrary formula. The SAT problem was the first problem that was demonstrated to be NP-Complete. A large number of works are currently done in relationship to SAT. According to research works review there is no system that allows the integration of algorithms designed for SAT study (SAT generators, SAT preprocessors, SAT solvers and SAT visualizers). This paper presents an Integrated System for Satisfiability Problem Study (SAT-DB), based in software components (JavaBeans) and the Java Web Start technology, client/server model and an approach known as RAD (Rapid Application Development) to design and run an algorithm o SAT execution sequence. Key-Words: Satisfiability, Generators, Preprocessors, Solvers, Visualizers, Component Algorithm, SAT Execution Sequence, JavaBeans, Java Web Start, Client/Server,.
The analysis of some algorithms for generating random variates with a given hazard rate

We analyze the expected time penonnance of two versions of the thinning algorithm of Lewis and Shedler for generating random variates with a given hazard rate on [0,00). For thinning with fixed dominating hazard rate g(x) = c for example, it is shown that the expected number of iterations is cE(X) where X is the random variate tQat is produced. For DHR distributions, we can use dynamic thinning by adjusting the dominating hazard rate as we proceed. With the aid of some inequalities. , we show that this improves the penonnance dramatically. For example, the expected number of iterations is bounded by a constant plus E(log+(h(O)X)) (the logarithmic moment of X).
Leveraging periodicity in human mobility for next place prediction

Periodic transitions from place to place are inherent in human movements. Through visual examination we detect these periodic movements in traces of user tracking data. However such user tracking data sets tend to be sparse and incomplete. In addition, periodic movements are surrounded by noise: transitions to and from less frequently visited places and transitions to one of a kind visits. In this paper, we present algorithms leveraging techniques and models to detect periodicity in individual user movements. Our algorithms predict a user's next place given only the current context of timestamp and location. We apply these algorithms to real user mobility data sets. Prediction accuracy depends on the ratio of periodic movements to noise in user traces. For majority of users in a movement tracking data set collected over a year, our algorithms achieve next place prediction accuracies of 50% and above.
Individual diffe rences in hemispheric lateralization of language processing

INDIVIDUAL DIFFERENCES AND BRAIN LATERALITY IN LANGUAGE PROCESSING by SARAH A. VAN DYKE August 2011 Advisor: R. Douglas Whitman Major: Psychology (clinical) Degree: Doctor of Philosophy Conclusions in the literature regarding the relationship between a lateralized bias in the processing of information and individual differences (e.g., biological sex, gender identity, ability, personality) are inconsistent. Two different measures of laterality were compared: dichotic listening and lateralized semantic priming and their relation to sex, verbal and visual-spatial ability, gender identity, and personality. Eighty-nine adults (44 women, 45 men) were administered the Wechsler Abbreviated Scale of Intelligence, Bem Sex Role Inventory, and Big Five Inventory in addition to a dichotic listening task and a lateralized semantic priming task that compared ipsilateral and contralateral priming in order to determine the role of interhemispheric transfer. Two stimulus onset asynchronies (SOA; 50 ms and 400 ms) and two levels of association strength (high and neutral) between the prime and the target words were used in the priming task. Ipsilateral prime-target reaction times were faster than contralateral prime-target presentations, while contralateral presentations resulted in greater semantic priming, suggesting that the time required for interhemispheric transfer allows for greater
Using PCA algorithm to refine the results of internet traffic identification

Detecting and identification the network traffic attracts many attentions in recent years. Statistical approach using the machining learning algorithm can classify the network traffic efficiently without detecting the payload of every packet. At the same time, the accuracy depends on the statistical features of the training set. However, the traditional process without pre-treatment of the statistical features can lead to the misidentification in many scenarios. In this paper, an improved method is proposed based on the PCA (Principle Component Analysis) algorithm for pre-treatment of the statistical features, which is able to refine the results of traffic identification. Extensive experiments have been done and the results show that the accuracy rate of traffic classification based on the improved statistical method is improved.
A Model Based Security Testing Method for Protocol Implementation

The security of protocol implementation is important and hard to be verified. Since the penetration testing is usually based on the experience of the security tester and the specific protocol specifications, a formal and automatic verification method is always required. In this paper, we propose an extended model of IOLTS to describe the legal roles and intruders of security protocol implementations, and then combine them together to generate the suitable test cases to verify the security of protocol implementation.
Serum Alkaline Phosphatase and Risk of Incident Cardiovascular Disease: Interrelationship with High Sensitivity C-Reactive Protein

Background Alkaline phosphatase (ALP) has been suggested to be associated with cardiovascular disease (CVD) risk, however, important aspects of the association, such as shape and independence from established risk factors, have yet to be characterized in detail. We assessed the association of ALP with CVD risk and determined its utility for CVD risk prediction. Methods Alkaline phosphatase activity was measured at baseline in the PREVEND prospective cohort involving 6,974 participants aged 28-75 years without pre-existing CVD. Hazard ratios (95% confidence intervals [CI]) and measures of risk discrimination and reclassification were assessed. Results During a median follow-up of 10.5 years, 737 participants developed CVD. Serum ALP was correlated with several risk markers for CVD, with strongest correlations for age (r = 0.30; P < 0.001), gamma-glutamyltransferase (r = 0.26; P < 0.001), and C-reactive protein (CRP) (r = 0.25; P < 0.001). There was a non-linear “J-shaped” relationship between ALP and CVD risk. In analyses adjusted for conventional risk factors, the hazard ratio (95% CI) for CVD in a comparison of the top quintile versus bottom quintiles 1-4 of ALP values was 1.34 (1.14 to 1.56; P<0.001), which persisted after additional adjustment for potential confounders 1.33 (1.13 to 1.55; P<0.001). However, the association was somewhat attenuated after adjustment for CRP 1.24 (1.05 to 1.45; P=0.009). Addition of information on ALP to a CVD risk prediction model containing established risk factors did not improve the C-index or net reclassification. Conclusions Available evidence suggests a non-linear association between ALP activity and CVD risk, which is partly dependent on CRP. Taking account of conventional risk factors, additional information on ALP does not improve CVD risk assessment.
The Impact of Media Independence On Firm Performance: A Panel Data Analysis From Emerging Markets

Can media have any influence on firm performance? Do firms in countries with more independent media perform better than firms with less independent media? This paper seeks to answer these questions by documenting the relationship between media independence and firm performance in emerging markets. Using a dataset from twenty seven emerging markets, we show significantly better performance of firms headquartered in countries with relatively more independent media than firms headquartered in countries with relatively less independent media during the period between 2007 and 2011. We argue that independent media reduces information asymmetries for stock market participants. Consequently, it is more difficult for managers to expropriate, thereby improving performance of firms. Our results indicate that media can play a substitute role for traditional governance mechanisms in emerging markets.
Fast and Accurate Part{of{speech Tagging: the Svm Approach Revisited

In this paper we present a very simple and effective part{of{speech tagger based on Support Vector Machines (SVM). Simplicity and ee-ciency are achieved by working with linear sep-arators in the primal formulation of SVM, and by using a greedy left-to-right tagging scheme. By means of a rigorous experimental evaluation, we conclude that the proposed SVM{based tag-ger is robust and exible for feature modelling (including lexicalization), trains eeciently with almost no parameters to tune, and is able to tag thousands of words per second, which makes it really practical for real NLP applications. Regarding accuracy, the SVM{based tagger significantly outperforms the TnT tagger exactly under the same conditions, and achieves a very competitive accuracy of 97.0% on the WSJ corpus , which is comparable to the best taggers reported up to date.
Political Trust and Distrust in Post-Authoritarian Contexts

This paper tests six hypotheses about why trust in political institutions varies according to individual characteristics and differences in national and in temporal contexts. It does so by analyzing 67 New Europe Barometer surveys from 14 post-Communist countries between 1993 and 2004. Ten countries are now in the European Union, while Russia, Ukraine, Belarus and Croatia are not. Multi-level modelling shows that political and economic performance are the most important influences on trust, and that how performance is perceived is more important than so-called objective measures of context. The extent to which specific performance measures are important is also subject to variation across time. Since trust is not inherent in individual socialization, the findings suggest that if the performance of government improves, so trust should increase.
Clock Skew Compensation by Speech Interpolation

A common synchronization approach used in telecommunication networks is clock adjustment via a synchronous digital hierarchy. In packet based networks this is however not always feasible and differences in local clock frequencies, clock skew, needs to be handled by proper signal processing. This paper proposes a clock skew compensation algorithm that effectively changes the number of samples in the receiver's play-out buffer, dependent on estimated clock skew, thereby avoiding systematic over/under-runs of the buffer
James Douglas and the Surgery of the Peritoneum

It is obvious that the surgery of the peritoneum, or any of the other serous membranes per se, would include only a very limited field. However, it is equally patent that it is because of their extent and relations that they came to play so important a part in the surgery of the cavities and organs which they enclose. It is appropriate on this two-hundredth anniversary of the paper published by James Douglas on the "Situation and Structure of the Peritoneum" to trace briefly the evolution of our knowledge of this membrane. The serous membranes have played a dominant role in the development of the surgery of the cavities which they surround. Even with modern technic, when nearly every portion of the anatomy can be made open to surgical manipulation with relative impunity, there is even now somewhat more concern when it becomes necessary to open the meninges, pleura, peritoneum, pericardium or the serous membranes of A
On Feasibility, Stability and Performance in Distributed Model Predictive Control

In distributed model predictive control (DMPC), where a centralized optimization problem is solved in distributed fashion using dual decomposition, it is important to keep the number of iterations in the solution algorithm small. In this technical note, we present a stopping condition to such distributed solution algorithms that is based on a novel adaptive constraint tightening approach. The stopping condition guarantees feasibility of the optimization problem and stability and a prespecified performance of the closed-loop system.