Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Math as you Play : An explorative study

One of the promises of video game training is that, compared to traditional training, it can be more engaging and entertaining (Boot et.al., 2008). However, besides entertainment, games have shown to have the potential to impact a larger variety of cognitive abilities. Previous research has consistently shown that several aspects in cognition such can be enhanced by game play. The present study aimed to explore how arithmetic performance enhancement induced by game play and paper exercises differs. In order to do this, we performed a combined analysis of the changes in two behavioral measurements: accuracy and reaction times. Children were tested at two points in time: before and after the three week period. We compared the reaction times and the accuracy improvements between these two moments and compared different items types (e.g. understanding tenths, understanding hundreds, even or odd up to 100 among other types). We found indirect evidence suggesting that arithmetic performance enhancement induced by game play and paper exercises might rely on slightly different cognitive mechanisms.
Cross-lingual morphological inflection with explicit alignment

This paper describes two related systems for cross-lingual morphological inflection for SIGMORPHON 2019 Shared Task participation. Both sets of results submitted to the shared task for evaluation are obtained using a simple approach of predicting transducer actions based on initial alignments on the training set, where cross-lingual transfer is limited to only using the high-resource language data as additional training set. The performance of the system does not reach the performance of the top two systems in the competition. However, we show that results can be improved with further tuning. We also present further analyses demonstrating that the cross-lingual gain is rather modest.
CONDITIONAL AND UNCONDITIONAL TWO-SAMPLE RANK TESTS FOR TRUNCATED DATA

In the two-sample testing problem for truncated data a class of statistics in analogy to those of Mantel and Haenszel [12] for censored data , consists of sums £ · wj(Ej — EjPj), where £ j is the observed number of failures in the first sample at time tj and E j P j is its conditional expectation, given the past. The weights Wj determine the alternatives for which the corresponding tests are sensitive. In the present paper we derive by a simultaneous proof unconditional and conditional limiting distributions of the above test statistics and of related Renyi-type statistics under the null hypothesis of randomness resp. under the permutational distribution. The proofs work by discrete time martingale theory which allows for certain weights which are nonpredictable in the common framework of continuous time martingale theory. The underlying distributions are quite general s.th. ties may occur.
Classifying Healthy and Preeclamptic Patients from Recurrence-Based Cardiovascular Time Series Using Complex Networks Methods

We analyze cardiovascular time series with the aim of identifying patients suffering of preeclampsia, a pregnancyspecific disorder causing maternal and fetal morbidity and mortality. For that, we use a novel approach, namely theεrecurrence networks applied to a phase space constructed by means of the time series of the variabilities of the heart rat e, and the blood pressure (systolic and diastolic). Four network measures are considered as parameters for our analysis: average path length, mean coreness, global clustering coefficient, and s calelocal transitivity dimension. With these quantities, we perform a quadratic discriminant analysis. This allows us to classif y healthy and preeclamptic patients with a sensitivity of 91.7% and a specificity of 68.1%, thus validating the use of this method.
Convex Optimization meets Parameter Synthesis for MDPs

Probabilistic Systems. Many real-world systems exhibit random behavior and stochastic uncertainties. One major example is in the field of robotics, where the presence of measurement noise or input disturbances requires special controller synthesis techniques [28] that achieve robustness of robot actions against uncertainties in the robot model and the environment. Formal verification offers methods for rigorously proving or disproving properties about the system behavior, and synthesizing strategies that satisfy these properties. In particular, model checking [25] is a well-studied technique that provides guarantees on appropriate behavior for all possible events and scenarios. Model checking can be applied to systems with stochastic uncertainties, including discrete-time Markov chains (MCs), Markov decision processes (MDPs), and their continuous-time counterparts [16]. Probabilistic model checkers are able to verify reachability properties like “the probability of reaching a set of unsafe states is ≤ 10%” and expected costs properties like “the expected cost of reaching a goal state is ≤ 20. ” A rich set of properties, specified by linearand branching-time logics, reduces to such properties [16]. Efficient implementations are readily available in tools like PRISM [9] or STORM [20].
Molecular phylogenetic analysis of a bacterial community in Sulphur River, Parker Cave, Kentucky

Abstract Sulphur River in Parker Cave, Kentucky receives sulfurous water (11-21 mg sulfide/L) from the Phantom Waterfall and contains a microbial mat composed of white filaments. We extend a previous morphological survey with a molecular phylogenetic analysis of the bacteria of the microbial mat. This approach employs DNA sequence comparisons of small subunit ribosomal RNA (SSU rRNA) genes obtained from the mat with those from an extensive database of rRNA sequences. Many of SSU rRNA gene clones obtained from the mat are most similar to rRNA sequences from sulfur-oxidizing bacteria (Thiothrix spp., Thiomicrospira denitrificans, and ‘‘Candidatus Thiobacillus baregensis’’). The Sulphur River SSU rRNA gene clones also show specific affiliations with clones from environmental surveys of bacteria from deep-sea hydrothermal vent communities and subsurface microcosms. Affiliations with sequences from bacteria that are known to have the ability to obtain energy for CO2 fixation from the oxidation of inorganic compounds (chemoautotrophs), in combination with the environmental conditions surrounding the microbial mat, indicate that chemoautotrophic metabolism of bacteria in this mat may contribute to the biomass of Sulphur River. Cave communities, such as the one identified in Sulphur River, provide sites to study such relatively autonomous chemoautotrophic communities that are much more accessible than similar communities associated with deep-sea hydrothermal vents. Subsurface microbiology and the contribution of microbial activity on cave development are also discussed.
Design and Analysis of Dual Band Star Shape Slotted Patch Antenna

This article proposes a new dual-band patch antenna for applications in the wireless local area network (WLAN) using MIMO technology. It consists on star shape slotted microstrip patch antenna, using FR4 substrate. The rectangular slotted patch uses microstrip feed line of 50 Ω characteristic impedance. This designed antenna can operates at 2.4 and 5 GHz resonant frequency. The dual band characteristic is obtained by integration of two open or partial star-shaped slots on the upper side of the patch and the third star slot is embedded in the center of the patch. In order to optimize characteristics of this patch antenna, “Computer Simulation Technology” Software (CST) is used. The results of simulations show that the proposed antenna covers the operating bands of 2.41 GHz (2.382.45 GHz) and 5.075 GHz (4.98-5.16 GHz), with return loss S[1,1]<-10dB, also it presents a good omnidirectional radiation pattern, who meets the requirement of WLAN applications.
Semi-Supervised and Active Learning

Standard supervised learning assumes availability of labeled data. In many settings, however, labels are difficult or expensive to acquire, while unlabeled data is easily available. Semi-supervised learning and active learning are two broad approaches designed to exploit unlabeled data and/or learn from fewer labeled examples. Semi-supervised learning involves directly learning from a relatively small number of labeled examples together with additional unlabeled examples. Active learning allows the learning algorithm to actively request labels for a small number of examples. We consider each of these in turn.
Matrices of Multiple Weights for Test Response Compaction with Unknown Values

Occurrence of unknown states/values in scan chains in response to test vectors is a common phenomenon. This paper presents a method for designing matrices for linear test output compactors by using rows of multiple weights. The proposed method offers superior compaction performance provided that the unknowns are non-uniformally distributed among the scan chains. Our method increases the compaction ratio for multiple output compactors and reduces memory for single output compactors. The paper also provides an evaluation of the convolution and block based X-compactors based on the proposed method.
2395-1621 Multivariate Correlation Analysis For Accurate Network Traffic In Denial-of-Service Attack Detection

ARTICLE INFO Proposed System is a DOS assault recognition framework that utilizations Multivariate Correlation Analysis (MCA) for exact system activity portrayal by separating the geometrical connections between's system movement highlights. Our MCA-based DOS assault identification framework utilizes the standard of inconsistency based location in assault acknowledgment. This makes our answer equipped for identifying known and obscure DOS assaults adequately by taking in the examples of honest to goodness system movement as it were. Besides, a triangle-area-based procedure is proposed to improve and to accelerate the procedure of MCA. Interconnected frameworks, for example, Web servers, database servers, distributed computing servers and so forth, are presently under strings from system assailants. As one of most regular and forceful means, Denial-of-Service (DOS) assaults cause genuine effect on these registering frameworks. The viability of our proposed location framework is assessed utilizing KDD Cup 99 dataset, and the impacts of both nonnormalized information and standardized information on the execution of the proposed identification framework are analyzed. The outcomes demonstrate that our framework beats two other already created best in class approaches as far as discovery precision.
A Brain Network Inspired Algorithm: Pre-trained Extreme Learning Machine

Extreme learning machine (ELM) is a promising learning method for training “generalized” single hidden layer feedforward neural networks (SLFNs), which has attracted significant interest recently for its fast learning speed, good generalization ability and ease of implementation. However, due to its manually selected network parameters (e.g., the input weights and hidden biases), the performance of ELM may be easily deteriorated. In this paper, we propose a novel pre-trained extreme learning machine (P-ELM for short) for classification problems. In P-ELM, the superior network parameters are pre-trained by an ELMbased autoencoder (ELM-AE) and embedded with the underlying data information, which can improve the performance of the proposed method. Experiments and comparisons on face image recognition and handwritten image annotation applications demonstrate that P-ELM is promising and achieves superior results compared to the original ELM algorithm and other ELM-based algorithms.
PolyMap : A 2 D Polygon-based Map format for Multi-Robot Autonomous Indoor Localization and Mapping

Autonomous exploration is an important tasks in many robotic fields such as disaster response scenarios. In time critical situations, the use of multiple robots can reduce the time to create a complete map of the environment. However among the most popular map formats in use today, none are ideal for the multirobot autonomous indoor localization. In terms of memory usage, visualization, and usability in navigation and exploration tasks, all formats have some strengths and weaknesses. In this paper we introduce PolyMap, a map format that is based on simple polygons. Since the polygons are based on line segments, this is a special case of vector-based map formats. This format provides advantages in terms of memory footprint over occupancy grids, while not falling behind in visualization. Its sparse nature is also an advantage for navigation tasks, in particular when the map needs to be shared over a wireless network connection. Additionally the explicit modeling of frontiers helps with autonomous exploration.
Nonlinear Dynamics of Reactive EEG Patterns under Cerebrovascular and Cardiovascular Distortions

We examine the task of estimation of the differences in the human brain lability involving its opportunity to reproduce the external rhythm under cerebrovascular and cardiovascular distortions. For solving the task the electroencephalographic (EEG) patterns before, during and after intermittent photic stimulation are evaluated by the continuous wavelet transform and the recurrence quantification analysis. The degree of the human brain lability is estimated on the basis of changes in wavelet and recurrence features of the EEG patterns taking place under the photic stimulation. The coefficients of photic driving and holding and the energy increase times calculated by the wavelet spectra of the EEG patterns of patients with cerebrovascular and cardiovascular distortions differ significantly from the parameters determined for the healthy subjects. The study demonstrates the opportunity of nonlinear dynamics methods to estimate quantitatively the human brain lability of light stimulus perception for various groups of patients having cerebrovascular and cardiovascular distortions.
Spanning Large Graphs by Combining Work-stealing with Multiple Parallel Granularities on GPU

Graphs are fundamental representations which are extensively used in many kinds of computation domains. Despite its irregular memory accesses and unbalanced workload graph spanning on GPU has recently shown promising results in accelerating those challenging graph problems. In this paper we propose a policy spanning large graphs by combining work-stealing with multiple parallel granularities on GPU. Among them warp-based spanning and threadblock-based spanning can achieve spanning acceleration for graphs with higher degrees skew. Moreover, this coarse-grained spanning can reduce branch divergence and scatter memory accesses. On the other hand work-stealing mechanism can keep workload balanced among stream multi-processors inside GPU and maintain efficient execution of each multi-processor. The relevant experiments of graphs instances have confirmed our method can gain 10x speedup over baseline implementation. Meanwhile our tests also have confirmed that the performance gap between GPU and other architectural machines is predominantly due to memory bandwidth bottleneck.
Communicating with Space and People - Smart Interface Design for Enhancing User Awareness and Interactions

Smart space design has become an important research paradigm because of the emerging information and communication technology, smart materials, and sensory technology. A space equipped with human-computer interfaces, communicates not only with space but also with its occupants. In previous researches, the focus was on developing smart houses which made decisions for its occupants on controlling the condition of space. However, the human tends to make choices and the subtle psychological changes of occupants may derive exceptional decisions. Therefore, this paper aims to propose smart interfaces in house design, i.e., the “Individual Sense” concept is introduced by examining the assumptions and cases. This research probed into how the interface is characterized by individual actions. The “Individual Sense” is implemented on the basis of commonsense for reasoning potential interactions and demonstration and discussion are reported.
Measuring Ankle Angle and Analysis of Walking Gait using Kinovea

Understanding the biomechanics of motion related to human walking gait is important in the area of rehabilitation. Infrared cameras motion capture systems have been widely used. Nevertheless, the system is very expensive and thus alternative solutions are explored. This study is aimed to measure the angle of ankle during walking and then assess the reliability of Kinovea in analysing walking gait. Firstly, a motion capture-analysis system combining HD VideoCam-Kinovea was validated. Then, a motion capture-analysis system combining HD DSLR Camera-Kinovea was used to capture the motion of walking and the relative angles of ankle during walking gait phases are measured. Three volunteered healthy subjects without any gait disorders, age ranged from 20 24 years were recruited for this study. Basic statistical analysis was carried out to compute the mean, standard deviation (SD) and variance. In terms of walking gait analysis that is the main part of the current study, the results revealed no statistically significant difference (variance < 5%) in the measured data for the same subject under five trials. This proves that the protocol is repeatable and the current system combining HD DSLR Camera-Kinovea is reliable.
Zoonotic Hazards of Campylobacteriosis in some areas in Egypt

A total of 2130 samples collected from diarrhea chicken, raw milk, milk products and stool of patient with diarrhea from Menia, Fayoum, Cairo and Qaluobya in Egypt. Samples were subjected to standard phenotypic identification of C.jejuni, and subsequently immunofluorescent technique (IFT) identification and genetic amplification by PCR using specific primers of hippuricase gene. The overall prevalence of Campylobacter jejuni in intestine and liver of chicken were 40.4 % and 37.5 % respectively, 30% tape water, 4.44% raw milk, Karish cheese and yoghurt 6.66% and 13.33% respectively and 70 (35%) children stool. The positive results of C.jejuni were detected by IFT expressed by green fluorescence staining. PCR amplification of hipO gene of C. jejuni isolated from the clinically diseased chicken and the environmental samples have shown identical fingerprints with human isolates at 344bp, indicating the zoonotic hazards of Campylobacter jejuni in Egypt. [Barakat A. M. A. Mona M. Sobhy; El Fadaly, H. A. A. ; Nagwa S. Rabie; Nashwa O. Khalifa; Eman S. Ramadan; Kotb, M. H. R. ; Zeinab M. S. Amin Girh; Dalia M. Sedik and Mona S. Zaki. Zoonotic Hazards of Campylobacteriosis in some areas in Egypt. Life Sci J 2015;12(7):9-14]. (ISSN:1097-8135). http://www.lifesciencesite. com. 2
The International Conference on Technologies and Materials for Renewable Energy , Environment and Sustainability , TMREES 14 Treatment heterogeneous photocatalysis ; Factors influencing the photocatalytic degradation by TiO 2

In order to optimize the purification of water and sewage water, a new technique of degradation «the heterogeneous photocatalysis» of the organic matter was underlined. As catalyst we chose a semiconductor which is dioxide TiO2 the titanium in the presence of a lamp UV as source of energy. One model substances present in many industrial effluents: the 4-iso propyl phenol was selected. The results of our experiments show that the adsorption of the pollutant (10mol/l) on TiO2 supported in absence of radiation UV is negligible. Compared to direct photolysis UV (365nm), the devolution of the pollutant is definitely faster in the presence of TiO2/UV for the same experimental conditions.
Trends for future HVDC Applications

During their development, power systems become more and more interconnected and heavily loaded. With the increasing size and complexity of systems and as the result of the liberalization of the electrical markets, needs for innovative applications and technical improvements of the grids will further increase. HVDC plays an important role for these tasks. Commercial applications of HVDC started in the 1950ies. In the meantime, HVDC became a reliable and economically important alternative for AC transmission, offering advantages in the operation of power systems in addition to the power transfer. The paper discusses expected present and future HVDC applications. Integration of HVDC into AC systems will be used more frequently as it can simplify the system configuration, control load flow and, at the same time, it improves the dynamic system performance and increases the system reliability. For the interconnection of large power systems HVDC offers technical and economical advantages, especially if the interconnection is weak. The connection of remote power stations to the system, e.g. off-shore wind generation, can be effectively put into practice by means of HVDC. Advantages of these applications will be discussed and demonstrated by implemented projects.
On the question of calculating the free energies of biomolecular systems : how much of phase space is actually explored ?

A novel statistical analysis of Molecular Dynamics generated trajectories is applied to various bulk liquids and a peptide in water. The analysis provides unique information on the full dimensional trajectory. In particular, it demonstrates that the phase space exploration is a very slow process that has the time scale of hundreds of nanoseconds even in bulk water and argon. Most importantly, the areas of the phase space visited at these times are different, in contrast to the commonly assumed uniform random search process. For a 21-residue peptide in explicit water it has been found that the peptide exhibits nanoseconds long periods that significantly differ in the rates of the phase space exploration. During these periods the rates remain the same but different from other periods and from the phase space covering rate in water.
Antimicrobial efficacy of a povidone iodine ( PI ) and a one-step hydrogen peroxide contact lens disinfection system

The antimicrobial efficacy of a novel povidone iodine (PI) contact lens disinfection system (Clencide) was compared with a one-step hydrogen peroxide system (AoSept). The PI system showed rapid killing of organisms with a 4.5–6.0 log reduction in bacteria, yeast, mould and Acanthamoeba trophozoites within 5 min and a 2.8–3.6 log kill of Acanthamoeba cysts after 2–4 h. The one-step peroxide gave a 4.0–6.0 log kill of bacteria in 0.5–1 h, 2.0–5.0 log for yeast after 2–6 h and 1.8 log for mould at 6 h. Acanthamoeba polyphaga trophozoites were reduced by 3.6 log at 1 h but cysts by only 1.2 log after 6 h. The study demonstrates that the PI system is an effective disinfection method for contact lenses. # 2004 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.