Miracle-dz/UniFAR-FTUs huggingface dataset:
PLANET: Massively Parallel Learning of Tree Ensembles with MapReduce

Classification and regression tree learning on massive datasets is a common data mining task at Google, yet many state of the art tree learning algorithms require training data to reside in memory on a single machine. While more scalable implementations of tree learning have been proposed, they typically require specialized parallel computing architectures. In contrast, the majority of Google's computing infrastructure is based on commodity hardware. In this paper, we describe PLANET: a scalable distributed framework for learning tree models over large datasets. PLANET defines tree learning as a series of distributed computations, and implements each one using the MapReduce model of distributed computation. We show how this framework supports scalable construction of classification and regression trees, as well as ensembles of such models. We discuss the benefits and challenges of using a MapReduce compute cluster for tree learning, and demonstrate the scalability of this approach by applying it to a real world learning task from the domain of computational advertising.
Mortality by level of emphysema and airway wall thickness.

RATIONALE There is limited knowledge of the prognostic value of quantitative computed tomography (CT) measures of emphysema and airway wall thickness (AWT) on mortality. OBJECTIVES To examine 8-year mortality in relation to CT-measured emphysema and AWT, and assess if potential impact of these predictors remained after adjustment for lung function. METHODS In the Norwegian GenKOLS study of 2003-2005, 947 ever-smokers (49% with COPD) aged 40-85 years performed spirometry and CT examination. Mortality data from 2003-2011 were gathered from the Norwegian Cause of Death Registry. CT emphysema % low-attenuation areas (%LAA) and standardized measure for AWT (AWT-Pi10) were main predictors. We performed Laplace regression for survival data, estimating survival time for specified population percentiles within each emphysema category. Models were adjusted for sex, FEV1, COPD status, age, body mass index, smoking, and inflation level. MEASUREMENTS AND MAIN RESULTS During 8-year follow-up all-cause mortality rate was 15%. Although 4% of the subjects with %LAA less than 3 died, 18% with %LAA 3-10 and 44% with %LAA greater than or equal to 10 died. After adjustment, the comparable percentile subjects with medium and high emphysema had 19 months shorter survival than subjects who died in the lowest emphysema category. Subjects with %LAA greater than or equal to 10 had 33 and 37 months shorter survival than the lowest emphysema category with regard to respiratory and cardiovascular mortality, respectively. No significant associations were found between %LAA and cancer and lung cancer mortality. AWT did not predict mortality independently, but a positive interaction with emphysema was observed. CONCLUSIONS AWT affected mortality with increasing degree of emphysema, whereas CT measure of emphysema was a strong independent mortality predictor.
Benchmark for license plate character segmentation

Abstract. Automatic license plate recognition (ALPR) has been the focus of many researches in the past years. In general, ALPR is divided into the following problems: detection of on-track vehicles, license plate detection, segmentation of license plate characters, and optical character recognition (OCR). Even though commercial solutions are available for controlled acquisition conditions, e.g., the entrance of a parking lot, ALPR is still an open problem when dealing with data acquired from uncontrolled environments, such as roads and highways when relying only on imaging sensors. Due to the multiple orientations and scales of the license plates captured by the camera, a very challenging task of the ALPR is the license plate character segmentation (LPCS) step, because its effectiveness is required to be (near) optimal to achieve a high recognition rate by the OCR. To tackle the LPCS problem, this work proposes a benchmark composed of a dataset designed to focus specifically on the character segmentation step of the ALPR within an evaluation protocol. Furthermore, we propose the Jaccard-centroid coefficient, an evaluation measure more suitable than the Jaccard coefficient regarding the location of the bounding box within the ground-truth annotation. The dataset is composed of 2000 Brazilian license plates consisting of 14000 alphanumeric symbols and their corresponding bounding box annotations. We also present a straightforward approach to perform LPCS efficiently. Finally, we provide an experimental evaluation for the dataset based on five LPCS approaches and demonstrate the importance of character segmentation for achieving an accurate OCR.
Battered Women in Korean Immigrant Families: The Silent Scream

Current myths about Asian Americans as quiet, nonproblematic, and self-managing ignore the problems faced by Korean immigrant battered women. Wife abuse is no stranger to Korean culture. This book provides insights on how Korean immigrant families' cultural conflict during their adjustment period often brings out wife abuse in their homes. The author cites attitudes toward traditionalism as a significant contributing factor, noting that couples who adhere to rigid sex-roles are more violent than couples who are less rigid. The author also illustrates differences between battered and nonbattered groups with regard to stress-evoking factors and reviews patterns in crisis management and problem-solving methods reported by battered Korean women. This is a volume that will be of interest to sociologists, anthropologists, and feminists.
Examining Teachers' Hurdles to ‘Science for All’

The goal of this research is to identify science teachers' beliefs and conceptions that play an important role in shaping their understandings of and attempts to enact inclusive science teaching practices. We examined the work products, both informal (online discussions, email exchanges) and formal (papers, unit plans, peer reviews), of 14 teachers enrolled in a master's degree course focused on diversity in science teaching and learning. These emerging understandings were member-checked via a series of interviews with a subset of these teachers. Our analysis was conducted in two stages: (1) describing the difficulties the teachers identified for themselves in their attempts to teach science to a wide range of students in their classes and (2) analyzing these self-identified barriers for underlying beliefs and conceptions that serve to prohibit or allow for the teachers' understanding and enactment of equitable science instruction. The teachers' self-identified barriers were grouped into three categories: students, broader social infrastructure, and self. The more fundamental barriers identified included teacher beliefs about the ethnocentrism of the mainstream, essentialism/individualism, and beliefs about the meritocracy of schooling. The implications of these hurdles for science teacher education are discussed.
An enhanced operator-oriented genetic search algorithm

This paper proposes a new search process incorporated into an operator-oriented genetic algorithm (GA). The new search algorithm solves problems in the context of invertible symbolic operations on a combinational finite state environment. The algorithm exploits the GA's ability to search for solutions without regard to a priori knowledge of the problem domain. The validity of the algorithm is illustrated by solving Rubik's cube. <<ETX>>
On the Convergence of MMPP and Fractional ARIMA Processes with Long-Range Dependence to Fractional Brownian Motion

Though the various models proposed in the literature for capturing the long-range dependent nature of network traac are all either exactly or asymptotically second order self-similar, their eeect on network performance can be very diierent. We are thus motivated to characterize the limiting distributions of these models so that they lead to parsimonious modeling and a better understanding of network traac. In this paper we consider long-range dependent arrival processes based on Markovian arrival and fractional ARIMA processes and show that the suitably scaled distributions of these processes converge to fractional Brownian motion in the sense of nite dimensional distributions. Subsequently, we prove that they also converge weakly to fractional Brownian motion in the space of continuous functions. Thus, the behavior of network elements fed with traac from these models has similar characteristics to those fed with fractional Brow-nian motion under suitable limiting conditions. Specii-cally, tails of queues fed with these arrivals have a Weibul-lian shape in sharp contrast with the exponential tails of conventional queues. Also, the weak convergence results allow us to accurately estimate the loss probabilities using the expressions for storage models for fractional Browni-nan motion. The seminal paper of 9] introduced the notion of self-similarity and long-range dependence in network traac. This has spurred research in the area of traac models which account for these second order statistical characteristics of network data. Wavelet models 1], Markovian arrival processes 2], the M=G=1 model 5], chaotic maps 6], Fractional Brownian motion 9], fractional ARIMA processes 9] and superposition of ON/OFF sources 14] are some of the models that have been suggested. Though all these models model the long-range dependence and show either exact or asymptotically second order self-similarity, the performance of network elements fed with these diierent sources diier widely. Studies in 10] and 11] show, for example, that queues fed with self-similar traac from M=G=1 sources have an exponentially distributed queue tail while the tails of queues fed with input sources characterized by fractional Brownian motion and superposition of ON/OFF sources have a Weibullian shape. Thus additional insight into the characterization of the arriving work process is necessary to predict the queue behavior. Motivated by this striking variation in queue performance, we try to model the limiting distribution of some of these self-similar sources. Convergence of the limiting distribution to any given model for which the network element performance has already been characterized then allows us to …
Political Media Contests and Confirmatory Bias

This paper models a two-period media contest between two political candidates campaigning to win an election. Two main cases are examined. In the first case voters behave as unbiased Bayesian updaters when assessing political information. The second case considers voters suffering from confirmatory bias. In the first case I find that candidates spend equal amounts of their campaign funds in both periods in equilibrium. In the second case, candidates spend more in period one. A candidate with better media access (in period one) does, however, better if voters suﬀer from confirmatory bias than if they do not.
Fear‐pattern analysis supports the fear‐drive model for antispeeding road‐safety TV ads

Previous studies of fear appeals in advertising have relied on a procedure that measures only the overall level of fear produced by the ad. That procedure cannot validly test the effect of drive reduction, which is the central causal mechanism in Hovland, Janis, and Kelley's (1953) original fear-drive model. To overcome this limitation, the present research identifies the fear pattern of the ad, based on moment-to-moment ratings of fear-to-relief taken for its duration. In Study 1, which examines ratings of seven antispeeding TV commercials, it is shown that a postexposure overall rating of fear is in fact measuring the maximum level of fear experienced, not the average level, and that this static rating of fear cannot distinguish very different patterns, such as the pattern of rising fear with no relief, the “shock” pattern of sudden fear with no relief (both representing positive punishment), and the classic fear-relief pattern (the drivereduction pattern). In Study 2, which is a laboratory experiment using antispeeding road-safety TV commercials and a dependent variable of speed choice on a realistic simulated driving test, it is demonstrated that the fear-relief pattern reduces young drivers' speed choice not only initially but after heavy repetition of the ad, whereas fear without relief increases speed choice initially, then, after heavy repetition, it decreases speed choice, although not down to the driving speed produced by fear-relief. The reason why a shock ad starts to work following heavy repetition is that viewers begin to anticipate the shock and the ad becomes, in effect, a fear-relief ad. The overall results strongly support the fear-drive model. © 2004 Wiley Periodicals, Inc.
Parallel Algorithms for the Spectral Transform Method

The spectral transform method is a standard numerical technique for solving partial differential equations on a sphere and is widely used in atmospheric circulation models. Recent research has identified several promising algorithms for implementing this method on massively parallel computers; however, no detailed comparison of the different algorithms has previously been attempted. In this paper, we describe these different parallel algorithms and report on computational experiments that we have conducted to evaluate their efficiency on parallel computers. The experiments used a testbed code that solves the nonlinear shallow water equations on a sphere; considerable care was taken to ensure that the experiments provide a fair comparison of the different algorithms and that the results are relevant to global models. We focus on hypercube- and mesh-connected multicomputers with cut-through routing, such as the Intel iPSC/860, DELTA, and Paragon, and the nCUBE/2, but we also indicate how the results extend to other parallel computer architectures. The results of this study are relevant not only to the spectral transform method but also to multidimensional fast Fourier transforms (FFTs) and other parallel transforms.
Five years of specialised early intervention versus two years of specialised early intervention followed by three years of standard treatment for patients with a first episode psychosis: randomised, superiority, parallel group trial in Denmark (OPUS II)

Objective To compare the effects of five years of specialised early intervention (SEI) treatment for first episode schizophrenia spectrum disorder with the standard two years of SEI plus three years of treatment as usual. Design Randomised, superiority, parallel group trial with blinded outcome assessment. Randomisation was centralised and computerised with concealed randomisation sequence carried out at an external site. Setting Participants were recruited from six OPUS teams in Denmark between 2009 and 2012. OPUS teams provide SEI treatment to all patients diagnosed with a schizophrenia spectrum disorder in Denmark. Participants 400 participants (51% women) with a mean age of 25.6 (standard deviation 4.3) were randomised to five years of SEI (experimental intervention; n=197) or to two years of SEI plus three years of treatment as usual (control; n=203). Interventions OPUS treatment consists of three core elements—modified assertive community treatment, family involvement, and social skill training—with a patient-case manager ratio of no more than 12:1. For participants randomised to five years of OPUS treatment, the treatment was largely unchanged. Participants randomised to the control group were mostly referred to community health centres after two years of SEI treatment. Main outcomes Follow-up assessments were conducted five years after start of OPUS treatment. Primary outcome was negative symptoms measured on the scale for assessment of negative symptoms (avolition-apathy, anhedonia, alogia, and affective blunting). Secondary outcomes were remission of both negative and psychotic symptoms, psychotic symptoms, suicidal ideation, substance abuse, compliance with medical treatment, adherence with treatment, client satisfaction, days in hospital care, and labour market affiliation. Results Levels of negative symptoms did not differ between the intervention group and control group (1.72 v 1.81 points; estimated mean difference −0.10 (95% confidence interval 0.33 to 0.13), P=0.39). Participants receiving five years of OPUS treatment were more likely to remain in contact with specialised mental health services (90.4% v 55.6%, P<0.001), had higher client satisfaction (estimated mean difference 2.57 points (95% confidence interval 1.36 to 3.79), P<0.001), and had a stronger working alliance (estimated mean difference 5.56 points (95% confidence interval 2.30 to 8.82), P=0.001) than the control group. Conclusions This trial tests SEI treatment for up to five years for patients with first episode schizophrenia spectrum disorder; previous trials have found treatment effects for programmes lasting from one to three years. The prolonged SEI treatment had few effects, which could be due to the high level of treatment provided to control participants and the late start of specialised treatment. Trial registration Clinicaltrial.gov NCT00914238.
Improving Detection Speed and Accuracy with Hybrid Client

Computers connected to a network are at risk of being attacked remotely. In recent years, there has been an increase of a particular type of attack: client-side attacks. These attacks target clients. As the client accesses a malicious server, the server delivers the attack to the client as part of the server’s response to a client request. Common examples of these attacks are web servers that attack web browsers. As the web browser requests content from a web server, the server returns a malicious page that attacks the browser. If successful, the web server could, for example, install arbitrary programs on the client machine. Client honeypots are a computer security technology that can find these malicious servers on a network. Client honeypots are dedicated devices that interact with potential malicious servers. Traditional client honeypots, so called high interaction client honeypots, classify a server as malicious once unauthorized state changes are detected on the client machine. These state changes, for example the appearance of a new file on the client, indicate that the client has been successfully compromised. High interaction client honeypots, however, are slow and it is not feasible to use them to inspect servers on a large network, such as the Internet. Our research is targeted at increasing performance of client honeypots through introduction of a lightweight client honeypot technology, so-called low interaction client honeypots. These client honeypots will detect violation of a security policy by statically analyzing the server response directly. We will employ pattern matching, heuristics and static code analysis algorithms, which are faster than the state-based approach of high interaction client honeypots. Low and high interaction client honeypots are not directly interchangeable as their abilities to correctly identify malicious and benign server responses differ greatly. To optimize speed as well as detection accuracy, we are proposing to explore a hybrid client honeypot system that utilizes the strengths of both technologies. It will contain feedback loops that adjust the static detection algorithms during operation. We expect that a hybrid client honeypot system is able to inspect servers with faster detection speed and an improved false positive/ negative rate over individual client honeypot technologies. We have created a low interaction client honeypot, HoneyC, which can detect malicious web servers via static detection algorithms. We will expand this implementation and evaluate it with a group of web servers. Capture, a high interaction client honeypot, is currently being developed. Similar to HoneyC, it will be evaluated with a group of web servers. HoneyC and Capture will be combined into a hybrid client honeypot system. A set of categorized test data will be created to evaluate the hybrid client honeypot system with respect to speed and detection accuracy. The set of test data will be made available to the research community to allow for testing of other implementations. We expect our research to complete in August 2008.
Culture cushion: inherently positive inter‐cultural tourist experiences

Purpose – The purpose of this paper is to develop and test a new measure called the “culture cushion” to account for the inherent positivity surrounding the inter‐cultural tourist experience.Design/methodology/approach – The first study involved the identification of items for the culture cushion construct and included a semi‐structured questionnaire and a panel discussion. The second study assessed unidimensionality and the convergent, discriminant, and nomological validity of the culture cushion dimensions. Respondents were asked to answer questions about a specific international consumption experience and responded to scale items measuring the culture cushion construct.Findings – A two‐dimensional measure of culture cushion was found to predict satisfaction and behavioral intentions. Judgments were more positive when the encounter was novel relative to previous experiences.Research limitations/implications – Additional studies involving travel locations other than those used in this study should be con.
Closed-Loop Planar Motion Control of a Steerable Probe With a “Programmable Bevel” Inspired by Nature

Percutaneous intervention has attracted significant interest in recent years, but many of today's needles and catheters can only provide limited control of the trajectory between an entry site and soft tissue target. In order to address this fundamental shortcoming in minimally invasive surgery, we describe the first prototype of a bioinspired multipart probe that can steer along planar trajectories within a compliant medium by means of a novel “programmable bevel,” where the steering angle becomes a function of the offset between interlocked probe segments. A kinematic model of the flexible probe and programmable bevel arrangement is derived. Several parameters of the kinematic model are then calibrated experimentally with a fully functional scaled-up prototype, which is 12 mm in diameter. A closed-loop control strategy with feed-forward and feedback components is then derived and implemented in vitro using an approximate linearization strategy that was first developed for car-like robots. Experimental results demonstrate satisfactory 2-D trajectory following of the prototype (0.68 mm tracking error, with 1.45 mm standard deviation) using an electromagnetic position sensor that is embedded at the tip of the probe.
La revalorización de la agroecología andina : estrategia local de diálogo de saberes para enfrentar problemas globales .

Considerando la gestion de sistemas bioculturales en la region, la experiencia practica del Programa Regional BioAndes en la serrania central del Ecuador, especificamente en los sectores rurales de los cantones Riobamba y Guano (zona de amortiguamiento de la Reserva de Produccion Faunistica Chimborazo), ha puesto en marcha un proceso enmarcado en el dialogo entre las visiones de los pueblos indigenas Puruha y varios actores de la sociedad que han asumido la vision y estrategias de vida influidas por la ciencia occidental moderna, tanto urbanos como rurales.