Miracle-dz/UniFAR-FTUs huggingface dataset:
The Use of Role-Plays as a Teaching Technique to Develop Foreign Language Learners’ Oral Proficiency Case Study: Second Year Students at Biskra University

Speaking is one of the most challenging and troublesome skills in our universities. This research attempts to investigate developing students’ speaking skill through the role play technique. The main problem we notice is that students’ speaking skill is poor. Therefore we believe, that there are number of ways through which teachers can help their students to improve their speaking ability. Due to the complexity of this skill, our students find it had to master all the aspects of speaking and use them appropriately in different social contexts. Therefore, they do not perform acceptable speaking tasks. We believe that the problem resides in the lack of efficient teaching strategies. The present study aims at shedding the light on improving learners oral proficiency by acting in role plays as a good model for bringing real-life situations into the classroom, such kind of technique helps in promoting students self-confidence through expressing their ideas during the practice of role plays activities. Our other aim through this study is to suggest the role play as an appropriate and an effective way to develop students’ speaking skill. Accordingly, we believe that using role-plays activities in the classroom make students of university feel interesting to speak English and communicate effectively in different social situations. Therefore, we hypothesize that using role play activity is effective in arousing students’ speaking in English. In order to confirm or refute hypothesis. We adopt a qualitative method that consists of administering questionnaires to both teachers and learners. In attempting to raise the teachers’ and students’ awareness about role plays, we have directed a questionnaires to second year students LMD at Mohammed Kheider University of Biskra and all the teachers of English to investigate their attitudes towards using Role plays technique. The results from the analysis of those questionnaires confirm the research hypothesis and have shown that teachers and students hold favorable attitudes towards using Role play techniques. Thus, we recommend the using of different techniques such as Role play, discussions, simulation activities in teaching speaking to develop students speaking skill.
Report by the ESA-ESO Working Group on Extra-Solar Planets

Various techniques are being used to search for extra-solar planetary signatures, including accurate measurement of radial velocity and positional (astrometric) displacements, gravitational microlensing, and photometric transits. Planned space experiments promise a considerable increase in the detections and statistical knowledge arising especially from transit and astrometric measurements over the years 2005-15, with some hundreds of terrestrial-type planets expected from transit measurements, and many thousands of Jupiter-mass planets expected from astrometric measurements. Beyond 2015, very ambitious space (Darwin/TPF) and ground (OWL) experiments are targeting direct detection of nearby Earth-mass planets in the habitable zone and the measurement of their spectral characteristics. Beyond these, `Life Finder' (aiming to produce confirmatory evidence of the presence of life) and `Earth Imager' (some massive interferometric array providing resolved images of a distant Earth) appear as distant visions. This report, to ESA and ESO, summarises the direction of exo-planet research that can be expected over the next 10 years or so, identifies the roles of the major facilities of the two organisations in the field, and concludes with some recommendations which may assist development of the field. The report has been compiled by the Working Group members and experts over the period June-December 2004.
What To Do (and Not to Do) with Time-Series Cross-Section Data

We examine some issues in the estimation of time-series cross-section models, calling into question the conclusions of many published studies, particularly in the field of comparative political economy. We show that the generalized least squares approach of Parks produces standard errors that lead to extreme overconfidence, often underestimating variability by 50% or more. We also provide an alternative estimator of the standard errors that is correct when the error structures show complications found in this type of model. Monte Carlo analysis shows that these “panel-corrected standard errors” perform well. The utility of our approach is demonstrated via a reanalysis of one “social democratic corporatist” model.
Lie Superalgebras Over 𝔤𝔩2

Finite-dimensional real and complex Lie superalgebras having either 𝔰𝔩2 or 𝔤𝔩2 = ⟨ I 2 ⟩ ⊕ 𝔰𝔩2 as their underlying even Lie algebra 𝔤0, are classified up to isomorphism. It is shown that the number N(𝔤) of nonisomorphic Lie superalgebras defined in 𝔤 = 𝔤0 ⊕ V associated to a given representation ρ: 𝔤0 → 𝔤𝔩(V) only depends on the multiplicities of the irreducible modules of dimensions 1, 2, and 2ℓ +1, when 𝔤0 = 𝔤𝔩2; if 𝔤0 = 𝔰𝔩2, it depends only on the multiplicities of the irreducible modules of dimensions 1, 2, and 3. In dealing with any finite-dimensional representation ρ: 𝔤𝔩2 → 𝔤𝔩(V), the representation space V can be decomposed in the form V 1 ⊕ V 2, with a completely reducible V 1 associated to diagonal Jordan blocks of ρ(I 2), and a noncompletely reducible V 2 associated to nondiagonal Jordan blocks of ρ(I 2). It is then proved that the given classification only depends on the representation in V 1. The question of which isomorphism classes admit invariant orthogonal-like geometric structures is also settled; in other words, it is determined which superalgebras studied in this work are quadratic in the sense of [2]. It is shown in particular that the only quadratic Lie superalgebra of the form 𝔰𝔩2 ⊕ V is 𝔬𝔰𝔭1, 2.
Programming by example: programming by analogous examples

Publisher Summary In programming by example (PBE), the representation that the user sees at the graphical user interface (GUI) level may be vastly different from the representation a user is faced with at the program level. In PBE systems, special representations are often used to make the transition between the two levels easier for an end user. These representational features enable programming by analogous examples, which in turn simplify program reuse. Analogies are powerful cognitive mechanisms that people use to construct new knowledge from knowledge already acquired and understood. The combination of some semantic information with structural information has allowed reuse of complex behaviors in the context of interactive simulations. When analogies are used with programming by example (PBE), the result is a new end-user programming paradigm combining the elegance of PBE to create programs with the power of analogies to reuse programs. The combination of PBE with analogies is called programming by analogous examples (PBAE).
Appendix Describing the Numerical Method Used in 'When Can Life-Cycle Investors Benefit from Time-Varying Bond Risk Premia?'

We rigorously explain the numerical approach used in the above-mentioned paper. The methodology is based on Brandt, Goyal, Santa-Clara, and Stroud (2005) (Review of Financial Studies) and Carroll (2006) (Economics Letters). In addition to combining these numerical techniques, we suggest two extensions. First, the approach of Brandt, Goyal, Santa-Clara, and Stroud (2005) approximates the conditional expectations encountered in optimizing the utility function via polynomial expansions in the state variables. The coefficients in these expansions are estimated using cross-sectional regressions across a set of simulated trajectories of returns and state variables. We develop an accurate approximation of these regression coefficients to facilitate fast optimization over the portfolio weights. This allows us to deal with a large number of decision variables without relying on iterative procedures. Second, to approximate the conditional expectations that lead to the optimal consumption strategy, we ensure that the approximation remains strictly positive, while keeping the approximation computationally tractable.
Invs: A New Congestion Control Algorithm for Heterogeneous Networks

The available bandwidth, round trip time (RTT) and packet loss rate in the Internet can vary over many orders of magnitude, which is known as the heterogeneity of the Internet. To cope with the heterogeneity in Internet Congestion Control, we propose a new TCP protocol, namely Invs, that has three key components. First, it employs a novel increase function of congestion window with an adaptive increase factor that adjusts through estimation of path bandwidth-delay product (BDP) and minimum RTT. The increase function can modulate the window growth rate to fit with the path condition. Second, Invs adopts a novel scheme that adaptively adjusts the queue threshold in loss classification, which distinguishes non-congestion loss from congestion loss. Third, Invs introduces a new back-off scheme to enable quick convergence of congestion window. The performance analysis and evaluation show that Invs achieves good fairness, friendliness, RTT fairness and utilization in heterogeneous networks.
Packet filter performance monitor (anti-DDOS algorithm for hybrid topologies)

Ibrahim M. Waziri, Jr. Ph.D., Purdue University, August 2016. Packet Filter Performance Monitor (Anti-DDoS Algorithm for Hybrid Topologies). Major Professors: Victor Raskin & Julia Taylor. DDoS attacks are increasingly becoming a major problem. According to Arbor Networks, the largest DDoS attack reported by a respondent in 2015 was 500 Gbps. Hacker News stated that the largest DDoS attack as of March 2016 was over 600 Gbps, and the attack targeted the entire BBC website. With this increasing frequency and threat, and the average DDoS attack duration at about 16 hours, we know for certain that DDoS attacks will not be going away anytime soon. Commercial companies are not effectively providing mitigation techniques against these attacks, considering that major corporations face the same challenges. Current security appliances are not strong enough to handle the overwhelming traffic that accompanies current DDoS attacks. There is also a limited research on solutions to mitigate DDoS attacks. Therefore, there is a need for a means of mitigating DDoS attacks in order to minimize downtime. One possible solution is for organizations to implement their own architectures that are meant to mitigate DDoS attacks. In this dissertation, we presented and implemented an architecture that utilizes an activity monitor to change the states of firewalls based on their performance in a hybrid network. Both firewalls are connected inline. The monitor is mirrored to monitor the firewall states. The monitor reroutes traffic when one of the firewalls becomes overwhelmed due to a HTTP DDoS flooding attack. The monitor connects to the API of both firewalls. The communication between the firewalls and monitor is encrypted using AES, based on PyCrypto python implementation. A hybrid network is a network comprised of both hardware and virtual firewalls
Heteroscedastic Change Point Analysis and Application to Footprint Data

Analysis of footprint data is important in the tire industry. Estimation procedures for multiple change points and unknown parameters in a segmented regression model with unknown heteroscedastic variances are developed for analyzing such data. Our approaches include both likelihood and Bayesian, with and without continuity constraints at the change points. A model selection procedure is also proposed to choose among competing models for fitting a middle segment of the data between change points. We study the performance of the two approaches and apply them to actual tire data examples. Our Maximization－Maximization－Posterior (MMP) algorithm and the likelihood－based estimation are found to be complimentary to each other.
Generalization Of Taylor's Theorem And Newton's Method Via A New Family Of Determinantal Interpolation Formulas

The general form of Taylor's theorem gives the formula, f = P n +R n , where P n is the Newton's interpolating polynomial, computed with respect to a con uent vector of nodes, and R n is the remainder. When f 0 6= 0, for each m = 2; : : : ; n+ 1, we describe a \determinantal interpolation formula", f = P m;n +R m;n , where P m;n is a rational function in x and f itself. These formulas play a dual role in the approximation of f or its inverse. For m = 2, the formula is Taylor's and for m = 3 it gives Halley's iteration function, as well as a Pad e approximant. By applying the formulas to P n , for each m 2, P m;m 1 ; : : : ; P m;m+n 2 , is a set of n rational approximations that includes P n , and may provide a better approximation to f , than P n . Thus each Taylor polynomial unfolds into an in nite spectrum of rational approximations. The formulas also give an in nite spectrum of rational inverse approximations, as well as a family of iteration functions for real or complex root nding, more fundamental than the Euler-Schroder family, or any other family. Given m 2, for each k m, we obtain a k-point iteration function, de ned as the ratio of two determinants that depend on the rst m k derivatives, and Toeplitz for k = 1. The order of convergence ranges from m to the limiting ratio of the generalized Fibonacci numbers of order m. By applying these formulas, Hadamard's inequality, Gerschgorin's theorem, and a new lower bound on determinants, we express roots of numbers, e, and , as the limiting ratio of Toeplitz determinants.
Rational L 1 Suboptimal Compensators for Continuous-Time Systems

The persistent disturbance rejection problem (L1 Optimal Control) for continuous time-systems leads to non-rational compensators, even for SISO systems [1-3]. As noted in [2], the difficulty of physically implementing these controllers suggest that the most significant applications of the continuous time L1 theory is to furnish bounds for the achievable performance of discrete-time controllers. However, at the present time, there are no theoretical results relating the optimal l1 norm of the discrete time system with the actual performance obtained when the controller is used in the continuous-time system. In this paper we use the theory of positively invariant sets to provide a design procedure, based upon the use of the discrete Euler approximating system, for suboptimal rational L1 controllers. The main results of the paper show that i) the L1 norm of the resulting continuous-time system is bounded above by the l1 norm of the discrete-time counterpart and ii) the proposed rational compensators yield L1 cost arbitrarily close to the optimum, even in cases where the design procedure proposed in [2] fails due to the existence of plant zeros on the stability boundary.
A Survey on Twitter Data Analysis Techniques to Extract Public Opinion

This paper aims to provide a survey on various techniques used to mine emotions or opinions of people. Sentimental analysis has gained a considerable amount of attention from researchers since it plays a vital role in people life. The information shared in twitter has been affecting markets, political events etc. and the number of tweets per day is extremely large. So extracting public opinion from tweets is required. Most the twitter data analysis techniques are dictionary based where the words are extracted from tweets and compared against a dictionary. But these techniques lack in domain or context based semantics at the same time the strength of the techniques depends on the strength of dictionary. Later the approaches using machine learning algorithms were proposed in which a feature vector is constructed with the emotion describing words from tweets and are fed to the classifier that classifies the sentiment or opinion. This article discusses various twitter data analysis techniques that are based on dictionary and that are using the machine learning approaches.
GEL CRITERIA FOR MOMENT CONDITION MODELS

GEL methods that generalize and extend previous contributions are defined and analyzed for moment condition models specified in terms of weakly dependent data. These procedures offer alternative one-step estimators and tests that are asymptotically equivalent to their efficient two-step GMM counterparts. The basis for GEL estimation is via a smoothed version of the moment indicators using kernel function weights that incorporate a bandwidth parameter. Examples for the choice of bandwidth parameter and kernel function are provided. Efficient moment estimators based on implied probabilities derived from the GEL method are proposed, a special case of which is estimation of the stationary distribution of the data. The paper also presents a unified set of test statistics for overidentifying moment restrictions and combinations of parametric and moment restriction hypotheses.
COMPARISON OF THE LANGRANGIAN FOOTPRINT MODEL LPDM-B WITH AN ANALYTICAL FOOTPRINT MODEL Research Note

We compare flux and concentration footprint estimates of a three-dimensional Lagrangian stochastic dispersion model applying backward trajectories with the results of an analytical footprint model by Kormann and Meixner. The comparison is performed for varying stability regimes of the surface layer as well as for different measurement heights. In general, excellent correspondence is found.
The Strategy of Feature Weight Optimizing and Feature Words Recommendation based on the Classificationof Weibo Users

The solutions presented in this article isthat update the weight with time factor and the new feature words recommendation strategy combine with TF-IDF. The data bear out that it can update the weight timely and improve the microblogusers classification,and the high degreeofaccurancy in feature words recommendation.The two strategies presented in this paper do well in the actual word, and the data bear out that two strategies is feasible.
Hierarchical Inspection System Using Visual and MFL Probe Robots

Structural Health Monitoring (SHM) represents a critical appurtenance to modern engineering that amalgamates the skills and techniques from various disciplines of engineering and computational science. Modern civil architectures, involving high-rise buildings, complex structural designs, and innovative shapes, on one hand represent the urban development, but at the same time is a challenge from sustainability perspective. In order to ensure the tenability of such structures, advanced SHM procedures need to be developed. The presented work in this paper is an effort on these lines. The wear and tear in the buildings related to weather, as well as other natural disasters, needs to be monitored regularly and systematically in order to prevent any serious structural damage. In current SHM practices, human experts are deployed at various structurally critical places on these buildings to perform specific measurements and analyze them to decide on the structural health condition. This simple approach is becoming more and more complicated as well as perilous for the human personnel involved, due to the modern architecture that involves greater heights, and complex structures. The proposed system utilizes flying and crawling/roving robots for this purpose. The flying robots, first, scan the surface of the building to any height needed, and then the custom-designed algorithms analyze the images from these scans in order to discern the possible defects/anomalies in the structure. Using these defect pointers, the custom-designed rover robot on top of the structure lowers a robotic probe that scans only those areas for substantiating the anomalies and the degree of defects present.
Dynamic Cluster Configuration Strategy for Energy Conservation Based on Online Load Prediction

Previous dynamic cluster configuration methods are based on the specific physical experimental models without the description of mathematical models.Aiming at the problem,this paper proposes a prediction-based dynamic clusters configuration strategy,which uses least mean square to predict the situation of service requests in the future time according to the network historical information of service requests.On the basis of the load requests and the clusters processing power,it decides the servers' scale and dynamically adjusts the opening and shutdown of the computers in the server cluster.Experimental result verifies the feasibility and superiority of the schedule strategy.
An Actor-critic Algorithm Using Cross Evaluation of Value Functions

In order to overcome the difficulty of learning a global optimal policy caused by maximization bias in a continuous space, an actor-critic algorithm for cross evaluation of double value function is proposed. Two independent value functions make the critique closer to the real value function. And the actor is guided by a crossover function to choose its optimal actions. Cross evaluation of value functions avoids the policy jitter phenomenon behaved by greedy optimization methods in continuous spaces. The algorithm is more robust than CACLA learning algorithm, and the experimental results show that our algorithm is smoother and the stability of policy is improved obviously under the condition that the computation remains almost unchanged.
Usability Evaluation Approaches for (Ubiquitous) Mobile Applications: A Systematic Mapping Study

In case of ubiquitous mobile applications, there is an increased need for effective/efficient approaches to evaluate the usability of these applications. The technical literature provides several evaluation approaches found in several sources, with different characteristics and classifications. This paper presents the results of a systematic mapping study that investigated usability evaluation approaches for (ubiquitous) mobile applications. In total, we identified 101 usability evaluation approaches for mobile applications, 28 of which applied to ubiquitous mobile applications. They were classified according to some attributes, such as: type of evaluation technique, type of mobile apps to be evaluated, experiment used to evaluate the approach, usability attribute/factors to be evaluated, and characteristics of ubiquity evaluated by each approach, representing the state-of-art in this research field. Keywords-Usability; Mobile apps; Systematic Mapping;
Planning for Social Equity and Emerging Technologies

Emerging technologies such as autonomous vehicles, connected vehicles, and the internet of things are rapidly advancing. Testing of autonomous vehicles is being undertaken in 24 cities across the U.S.A. , and an additional 74 cities worldwide (1). The introduction and expansion of these new modes of transport and supporting technologies will have vast implications for social equity, depending on planning practices and policymaking. This paper explores how 20 metropolitan planning organizations prepare for emerging technologies and consider their implications for equity. A qualitative content analysis of Regional Transportation Plans (RTPs) was conducted looking for evidence of these efforts. It found that 80% of plans included planning for social equity beyond the current environmental justice requirements, 70% mentioned emerging technologies, and 20% considered the equity implications of those technologies. The results showed promising practices from a number of areas, with the Southern California Association of Governments leading the way in addressing both equity and emerging technology planning; and the RTP of Madison, WI providing the best consideration of the equity implications of emerging technologies.