Miracle-dz/UniFAR-FTUs huggingface dataset:
A learning resource recommendation method combining user sequential interaction with collaborative filtering

Recommender system can make personalized predictions of resources for users with their learning history automatically. Collaborative filtering is one of the most widely used algorithms in this field. Although various works of collaborative filtering has been researched in elearning, few of them notice the influence of sequential interactions among users. In this paper, we propose a novel collaborative filtering method by using the sequential interaction information of users. The proposed method consists of four steps: (1) fetching sequential interactive information from comments and replies; (2) computing the interaction influence degree among users with data from step (1); (3) filling the sparse user-item matrix with influence data; and (4) applying the new filled matrix to user-based collaborative filtering to find similar users to recommend. The experiment results on TED dataset show that the proposed method outperforms userbased CF and item-based CF on both precision and recall.
Variability in closed phase analysis of speech

Accurate characterization of the vocal tract filter relies on speech data obtained from the closed glottal interval. Use of the electroglottograph (EGG) as a noninvasive and reliable means of monitoring glottal vibratory characteristics has increased the popularity of the two channel approach to speech analysis. The cycle by cycle auxiliary glottal information provided by the EGG facilitates implementation of pitch synchronous closed phase procedures. This paper shows that the closed phase method can yield variable results if the EGG information, or an alternative closed phase indicator, is not used correctly for analysis frame positioning. Synchronized glottal area waveforms obtained from ultra high speed laryngeal films verify true closure for our analyses. Results presented for other known regions also confirm many previous observations.
Identification of nonlinear dynamic systems classical methods versus radial basis function networks

This paper compares radial basis function networks for identification of nonlinear dynamic systems with classical methods derived from the Volterra series. The performance of these different approaches, such as Hammerstein, Wiener and NDE models, is analysed. Since the centres and variances of the Gaussian radial basis functions will be fixed before learning and only the weights are learned, a linear optimization problem arises. Therefore training the network and parameter estimation becomes comparable in computational effort. It is shown that the classical methods can compete or even perform better than the neural network, if the assumptions for the structure are valid. However, in practical applications when the structure is not known the radial basis function network performs much better than the classical methods.
RC4: An Analysis with Respect to Randomness

the paper aims to study one of the most widely used stream cipher, RC4. The bytes generated by the Psedo Random Generator Algorithm (PRGA) of RC4 are evaluated to check the randomness. Some widely known and accepted statistical measures are applied for this purpose. This is then followed by modifying the initial primitive key fed to RC4 using the system clock and compared with the initially generated bytes. Keywords—RC4, PRGA, Randomness, System Clock
Ciba Protek vs. Vistakon One-Day Acuvue: A comparison of antibiotic reservoir and delivery effects

Since the Food and Drug Administration approved the use of hydrophilic lenses as ocular bandages in 1973, they have become the treatment of choice for many corneal problems, not the least being superficial corneal abrasions. Practitioners are opting for the more readily available disposable soft contact lenses because of the limited number of expensive therapeutically approved bandage soft contact lenses. In this study we set out to determine if there is a significant difference in the antibiotic reservoir and delivery effect of these two groups of soft contact lenses. The eyes in this study were divided into three groups: Protek® group, Acuvue® group and control group. Two drops of Tobramycin 0.3% solution were instilled into each eye followed by subsequent isolation of tear samples using diffusion disks. The relative amount of antibiotic in the tears at certain time intervals was inferred using kill zone ring width (KZRW) measures around the diffusion disks. The data were then analyzed using an ANOVA statistical test. From this analysis we found that while there was a significant difference in KZRW between both Protek® versus control and Acuvue® versus control, there was no significant difference between Protek® versus Acuvue®. This study shows that, when used as an antibiotic reservoir and delivery system, the Ciba Protek® therapeutic contact lens and One-day Acuvue® disposable contact lens behave very similarly.
Impacts of H2O variability on accuracy of CH4 observations from MIPAS satellite over tropics

Abstract. Uncertainties of tropical methane concentrations, retrieved from spectra recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), MIPAS version V5R_CH4_220 are large. We explore the relation of these uncertainties with water vapour variability. We further show that these uncertainties have been reduced in MIPAS version V5R_CH4_224. Coincident measurements of CH4 by MIPAS, ground based FTIR and CH4 derived from EOS MLS coincident measurements of atmospheric water vapour (H2O), carbon monoxide (CO) and nitrous oxide (N2O) are used to estimate the standard uncertainty of MIPAS CH4 220, MIPAS CH4 224 and natural variability of H2O. Different methods such as bias evaluation, differential method and correlation coefficient are employed to explore the latitudinal variations of standard uncertainty of MIPAS CH4 220 and natural variability of water vapour as well as its reduction on MIPAS CH4 224. The averaged bias between MIPAS CH4 220 and ground-based FTIR measurements are −12.3 %, 8.4 % and 1.2 % for tropics, mid-latitudes and high latitudes, respectively. The standard deviations of the differences for these latitudinal bands are 5.9 %, 4.8 % and 4.7 %. More-over, the correlation coefficient between MIPAS CH4 220 and MIPAS V5R_N2O_220 is 0.32 in the upper troposphere and lower stratosphere over tropics and larger than the mod-est value 0.5 in mid and high latitudes. The poor correlation between MIPAS CH4 220 and MIPAS N2O 220 over tropics can indicate the large uncertainty of MIPAS CH4 220 over tropics that is related to water variability. Similarly, mean relative difference between MIPAS CH4 224 and ground-based FTIR measurements are 3.9 %, −2.6 % and −2.7 % in altitude 15–21 km and the average estimated uncertainty of MIPAS CH4 224 methane were obtained 2.4 %, 1.4 % and 5.1 % in altitude ranges of 15 to 27 km for tropics, mid and high latitudes, respectively. The estimated measurement uncertainty of MIPAS CH4 224 is different for the three latitude bands in the northern hemisphere, reflecting the latitudinal variation of uncertainties of MIPAS methane. However, the large reduction of uncertainty in MIPAS CH4 224 as com-pared to MIPAS CH4 220 has been confirmed for the tropical measurements. The correlation coefficients between the uncertainty of MIPAS CH4 220 and the variability of water vapour in lower stratosphere are strong (0.88) on monthly temporal scales. Similar methods were used for MIPAS CH4 224. It was found that the uncertainty in methane due to the variability of water vapor has been reduced.
Building a 2D environment map from laser range-finder data

The contribution describes a robust but simple approach to 2D environment mapping making-use of a TOF-based laser ranging system. As the used mobile system has no absolute positioning system the task has been split into two parts. The first deals with preprocessing of odometry and range measurements towards determination of position and heading of the platform in the environment. The other step maintains (updates) the internal world model via search for correspondences between existing map and observed entities with subsequent application of renewal rules.
Amélioration d'un programme de sélection massale sur la croissance chez la truite arc-en-ciel par introduction d'une sélection BLUP pour des caractères de qualités grâce aux empreintes génétiques

Cette these precise les conditions pour introduire une selection sur apparentes de caracteres de qualite assistee par empreintes genetiques dans un programme de selection massale sur la croissance chez la truite arc-enciel. Ce travail confirme l’interet a maitriser l’effet maternel avec une doublement de l’heritabilite du poids a 70 g (0,36 vs 0,16), des estimations d’heritabilites des caracteres mesures de valeurs intermediaires (0,37-0,54), l’interet d’utiliser la residuelle des parties mesurees regressees lineairement au poids vif pour une selection independante du poids pour les rendements, l’interet a remplacer la mesure du rendement au filetage par celle du rendement en carcasse evisceree-etetee plus heritable et tres correle au rendement au filetage (0,97),la correlation genetique elevee entre les rendements avec le ratio echographique e8/e23 (0,72-0,85) permettant une selection sur candidats plus efficace qu’une selection sur apparente sur le rendement lui-meme, des precisions elevees des valeurs genetiques (0.63–0.82) malgre tres peu d’individus par famille (3,5-4) et une efficacite surestimee d’une selection sur apparentes pre-selectionnes (de 14 % a 62 %). Les conclusions sont qu’il est possible d’introduire une selection sur apparentes dans un programme de selection massale avec des gains genetiques au moins equivalents a ceux attendus en selection familiale classique avec familles elevees initialement de facon separees
Design and Optimization of RBCC Powered Suborbital Reusable Launch Vehicle

In response to a demand for fast access to near space, a horizontal take-off and horizontal landing Suborbital Reusable Launch Vehicle (SRLV) concept powered by Rocket Based Combined Cycle (RBCC) engine is proposed in this research. This SRLV is designed to deliver a 20,000 kg payload to an altitude of 50km and a velocity of Mach 8, and to be able to fly back to the launch site. Compared with classical rocket launch vehicles and cruise vehicles, this vehicle applies unconventional configuration, flight path and propulsion working mode, and interactions between disciplines are very distinct. As there is scarce knowledge and data to refer to, we are faced with challenges in conceptual design. In this article, a two-phase design methodology is developed for RBCC powered vehicles. In the first phase, a sequential design flow with several design steps is utilized to find a feasible or near-feasible baseline. The methods used in this phase include: 1) a simplified trajectory for weight & sizing, 2) a multi-point optimization for aerodynamic shape design over a wide range of speeds, 3)a multi-point optimization for RBCC engine design to meet requirements of all working modes, 4) an integrated analysis process for aerodynamic/propulsion performance calculation, 5) a gauss-pseudo spectral based trajectory optimization to find the optimal flight path, 6) a structural design and sizing method, and 7) an automatic thermal protection system concept selection and sizing method. Also, considering the features of the vehicle, interactions between these steps are considered. With these methods and several iterations between them, the baseline of vehicle concept is created. In the second phase, Multi-Disciplinary Optimization (MDO) is applied to improve baseline for a feasible and better design. During this phase, optimization problem of SRLV, including design variables, constraints, and objectives, is created. The disciplinary high-fidelity models of and couplings between them are set up. By applying an asymmetric MDO architecture, the synthesis MDO model is integrated. Response Surface Method and Sequential Quadratic Programming algorithm are used in this architecture to find a closure and optimal solution. The application results from presented SRLV show that for a given launch task, the optimal design with all constraints satisfied can be found by this two-phase design methodology. We also find that this methodology is almost knowledge independent and suitable to conceptual design of unconventional vehicle like RBCC powered SRLV.
Optimization of coagulation–flocculation process for turbidity removal using response surface methodology: a study in Ilam water treatment plant, Iran

Coagulation-flocculation is an important process in removing suspended and colloidal matter from water in treatment plants. In this batch study, response surface methodology (RSM) was used to investigate the interactive influences between selected operating parameters of coagulant and coagulant aid dosage as well as pH for an optimized condition of turbidity removal from Ilam wastewater treatment plant based on data from jar tests. In this study, two common coagulants including aluminum sulfate and ferric chloride were used. LT25 and LT27 were applied as coagulant aids. Aluminum sulfate yielded highest turbidity removal at a dosage of 5 mg L-1 at pH 7. For ferric chloride, the maximum efficiency was observed at dosage 5 mg L-1 at pH 9. Application of aluminum sulfate in the presence of LT27 showed the highest turbidity removal among the studied reagents, and the efficiency increased with the increase in dosage. Based on the results of the present study, aluminum sulfate generally yielded a higher turbidity removal. But, ferric chloride formed larger flocs. Moreover, LT27 had a higher efficiency compared with LT25. Finally, the RSM was indicated as an appropriate tool for the optimization of the coagulation-flocculation process by confirmation experiments.
Is audio useful in immersive visualization

In this article I provide from localization experiments in virtual environment. I define common tasks (orientation, localization, and navigation) in immersive visualization. The above mentioned tasks will be examined with user tests. Two localization experiments have been accomplished. In the first localization experiment the localization accuracy was significantly better (p<<0.01 in ANOVA) with loudspeaker reproduction than with headphone reproduction (nonindividualized HRTF's). The second experiment indicated, that localization accuracy is depending on signal (P<<0.01 in ANOVA). Although the absolute lower limit for auditory localization accuracy in front is one degree for the azimuth, the reality is much worse. For example the screens and room reverberation deteriorate loudspeaker reproduction accuracy. Current results suggest that at least in some tasks the audio is useful addition to immersive visualization tasks.
Towards pattern generation and chaotic series prediction with photonic reservoir computers

Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals that is particularly well suited for analog implementations. Our team has demonstrated several photonic reservoir computers with performance comparable to digital algorithms on a series of benchmark tasks such as channel equalisation and speech recognition. Recently, we showed that our opto-electronic reservoir computer could be trained online with a simple gradient descent algorithm programmed on an FPGA chip. This setup makes it in principle possible to feed the output signal back into the reservoir, and thus highly enrich the dynamics of the system. This will allow to tackle complex prediction tasks in hardware, such as pattern generation and chaotic and financial series prediction, which have so far only been studied in digital implementations. Here we report simulation results of our opto-electronic setup with an FPGA chip and output feedback applied to pattern generation and Mackey-Glass chaotic series prediction. The simulations take into account the major aspects of our experimental setup. We find that pattern generation can be easily implemented on the current setup with very good results. The Mackey-Glass series prediction task is more complex and requires a large reservoir and more elaborate training algorithm. With these adjustments promising result are obtained, and we now know what improvements are needed to match previously reported numerical results. These simulation results will serve as basis of comparison for experiments we will carry out in the coming months.
Multi-Trait Diverse Germplasm Sources from Mini Core Collection for Sorghum Improvement

Sorghum is a multipurpose crop cultivated in over 100 countries, but its productivity is constrained by several biotic and abiotic stresses. Therefore, sorghum improvement programs largely focus on developing high-yielding cultivars with multiple traits including stress resistance, bioenergy and nutritional quality. This study was undertaken to meet breeders’ needs to develop such cultivars and identify diverse germplasm sources with multiple traits. The 242 sorghum mini core accessions were evaluated for agronomic traits (yield, maturity, 100-seed weight) in two post-rainy seasons under optimally irrigated and drought conditions and identified 21 accessions as a sources for agronomic traits. The evaluation of mini core revealed 70 accessions resistant to biotic stress, 12 to abiotic stress, 13 for bioenergy traits and 27 for nutritional traits. The 13,390 single nucleotide polymorphism markers on mini core were used to identify genetically diverse accessions with desirable agronomic traits: IS 23684 (nutrition traits, diseases, insect pests), IS 1212 (earliness, nutrition traits, drought, seedling vigor, diseases), IS 5094 (yield, drought, diseases, insect pests), IS 473 (earliness, diseases), IS 4698 (yield, Brix %, insect pests) and IS 23891 (greater seed weight, yield, Brix %, drought, diseases). These are useful genetic resources that meet breeders needs to develop agronomically superior sorghum cultivars with desirable combinations of multiple traits and a broad genetic base.
A robust linear prediction method for noisy speech

This paper proposes a method to improve the performance of the LP method in a noisy environment. A relationship for the autocorrelation function (ACF) of a periodical signal is derived, and the ACF estimates of noisy speech are transformed into their noiseless ones. The normal equation in which the noiseless ACF is used is efficiently solved by the Levinson-Durbin algorithm. Computer simulations demonstrate that the proposed method provides an improvement in the LPC cepstrum distance.
Is small smarter? Nanomaterial-based detection and elimination of circulating tumor cells: current knowledge and perspectives

Circulating tumor cells (CTCs) are disseminated cancer cells. The occurrence and circulation of CTCs seem key for metastasis, still the major cause of cancer-associated deaths. As such, CTCs are investigated as predictive biomarkers. However, due to their rarity and heterogeneous biology, CTCs’ practical use has not made it into the clinical routine. Clearly, methods for the effective isolation and reliable detection of CTCs are urgently needed. With the development of nanotechnology, various nanosystems for CTC isolation and enrichment and CTC-targeted cancer therapy have been designed. Here, we summarize the relationship between CTCs and tumor metastasis, and describe CTCs’ unique properties hampering their effective enrichment. We comment on nanotechnology-based systems for CTC isolation and recent achievements in microfluidics and lab-on-a-chip technologies. We discuss recent advances in CTC-targeted cancer therapy exploiting the unique properties of nanomaterials. We conclude by introducing developments in CTC-directed nanosystems and other advanced technologies currently in (pre)clinical research.
An Open-Access P300 Speller Database

The P300 Speller is probably the best known application in BCI [1]. Over the years, many improvements over the pioneering systems have been made and some performance comparisons exist [2]. To contribute to the improvement process, we propose an open access to a large database obtained from first-time users of the P300 speller application implemented within the BCI2000 platform [3] (Figure 1). The database is documented with associated classifier designs and objective performance measures, readily available for comparison and reference. We also propose a set of Matlab functions that help in the preparation of data for alternative classifier design and testing.
A random forest application to contact-state classification for robot programming by human demonstration

This paper addresses the non-parametric estimation of the stochastic process related to the classification problem that arises in robot programming by demonstration of compliant motion tasks. Robot programming by demonstration is a robot programming paradigm in which a human operator demonstrates the task to be performed by the robot. In such demonstration, several observable variables, such as velocities and forces can be modeled, non-parametrically, in order to classify the current state of a contact between an object manipulated by the robot and the environment in which it operates. Essential actions in compliant motion tasks are the contacts that take place, and therefore, it is important to understand the sequence of contact states made during a demonstration, called contact classification. We propose a contact classification algorithm based on the random forest algorithm. The main advantage of this approach is that it does not depend on the geometric model of the objects involved in the demonstration. Moreover, it does not rely on the kinestatic model of the contact interactions. The comparison with state-of-the-art contact classifiers shows that random forest classifier is more accurate. Copyright © 2015 John Wiley & Sons, Ltd.
Reduced-complexity sequence detection for E/sup 2/PR4 magnetic recording channel

Hardware complexity required for the implementation of E/sup 2/PR4 magnetic read channel results in slower operation and increased area and power consumption. The Viterbi (1967) sequence detector for E/sup 2/PR4 channel requires 16 states that could be realized as an array of 16 single step or two-step add-compare-select units. The method presented here reduces the complexity of the two-step implementation of the detector, by eliminating less probable branches from the trellis, using the sign of the input sample as a control value. Unlikely taken branches are dynamically eliminated from the detector, decreasing its complexity by roughly 50% with negligible penalty in signal to noise ratio. The resulting detector consists of four four-way, three three-way, three two-way ACS units and one adder that are dynamically assigned to 14 states of the detector.