Miracle-dz/UniFAR-FTUs huggingface dataset:
Taxonomy Induction and Taxonomy-based Recommendations for Online Courses

Taxonomy is a useful and ubiquitous way to organize knowledge. As online education attracting more and more attention, organizing lecture notes or exercises, from different online sources, in a more structured form has become an effective way to navigate users to better access course materials. However, it is expensive and time consuming to manually annotate large amounts of corpora to build a detailed taxonomy. In this paper, we propose a taxonomy induction framework with limited human involvement. We also show that the constructed taxonomy can be used to improve lecture notes/exercises recommendations.
Gabor fused to 2DPCA for face recognition

Automatic visual recognition of human faces is an extremely attractive research subjects. It is motivated by the wide range of commercial and law enforcement application. In the last thirty years numerous algorithms for face recognition have been developed, for detailed surveys see. The state-of-the-art in human face recognition is the subspace methods originated by the Principal Component Analysis (PCA), the Eigenfaces of the facial images. Recently, a technique called Two-Dimensional PCA (2DPCA) was proposed for human face representation and recognition. In this paper, we use the phase and magnitude of Gabor's representations of the face as a new representation followed by a face recognition algorithm, based on the 2D principal component Analysis approach. The performance of the proposed algorithm is tested on the public and largely used databases of FRGCv2 face and ORL. Experimental results on databases show that the use of 2D PCA, can achieve promising results, easier to evaluate the covariance matrix accurately and less time is required to computational.
Monte-Carlo algorithms in graph isomorphism testing

Abstract. We present an O(V 4 log V ) coin flipping algorithm to test vertex-colored graphs with bounded color multiplicities for color-preserving isomorphism. We are also able to generate uniformly distributed random automorphisms of such graphs. A more general result finds generators for the intersection of cylindric subgroups of a direct product of groups in O(n7/2 log n) time, where n is the length of the input string. This result will be applied in another paper to find a polynomial time coin flipping algorithm to test isomorphism of graphs with bounded eigenvalue multiplicities. The most general result says that if AutX is accessible by a chain G0 ≥ · · · ≥ Gk = AutX of quickly recognizable groups such that the indices |Gi−1 : Gi| are small (but unknown), the order of |G0| is known and there is a fast way of generating uniformly distributed random members of G0 then a set of generators of AutX can be found by a fast algorithm. Applications of the main result improve the complexity of isomorphism testing for graphs with bounded valences to exp(n1/2+o(1)) and for distributive lattices to O(n6 log logn). ∗Apart from possible typos, this is a verbatim transcript of the author’s 1979 technical report, “Monte Carlo algorithms in graph isomorphism testing” (Universite de Montreal, D.M.S. No. 79-10), with two footnotes added to correct a typo and a glaring omission in the original. We present an O(V 4 log V ) coin flipping algorithm to test vertex-colored graphs with bounded color multiplicities for color-preserving isomorphism. We are also able to generate uniformly distributed random automorphisms of such graphs. A more general result finds generators for the intersection of cylindric subgroups of a direct product of groups in O(n7/2 log n) time, where n is the length of the input string. This result will be applied in another paper to find a polynomial time coin flipping algorithm to test isomorphism of graphs with bounded eigenvalue multiplicities. The most general result says that if AutX is accessible by a chain G0 ≥ · · · ≥ Gk = AutX of quickly recognizable groups such that the indices |Gi−1 : Gi| are small (but unknown), the order of |G0| is known and there is a fast way of generating uniformly distributed random members of G0 then a set of generators of AutX can be found by a fast algorithm. Applications of the main result improve the complexity of isomorphism testing for graphs with bounded valences to exp(n1/2+o(1)) and for distributive lattices to O(n6 log logn). ∗Apart from possible typos, this is a verbatim transcript of the author’s 1979 technical report, “Monte Carlo algorithms in graph isomorphism testing” (Universite de Montreal, D.M.S. No. 79-10), with two footnotes added to correct a typo and a glaring omission in the original.
Crystal Structure of the HIV-2 Neutralizing Fab Fragment 7C8 with High Specificity to the V3 Region of gp125

7C8 is a mouse monoclonal antibody specific for the third hypervariable region (V3) of the human immunodeficiency virus type 2 (HIV-2)-associated protein gp125. The three-dimensional crystal structure of the Fab fragment of 7C8, determined to 2.7 Å resolution, reveals a deep and narrow antigen-binding cleft with architecture appropriate for an elongated epitope. The highly hydrophobic cleft is bordered on one side by the negatively charged second complementarity determining region (CDR2) and the unusually long positively charged CDR3 of the heavy chain and, on the other side, by the CDR1 of the light chain. Analysis of 7C8 in complex with molecular models of monomeric and trimeric gp125 highlights the importance of a conserved stretch of residues FHSQ that is localized centrally on the V3 region of gp125. Furthermore, modeling also indicates that the Fab fragment neutralizes the virus by sterically impairing subsequent engagement of the gp125 trimer with the co-receptor on the target cell.
Web Viral Marketing Based Construction Strategy of Customer Trust Network

Trust relationship and assessment are two challenges of constructing large scale trust network for web viral marketing applications. Because different customers have different needs and expectations in different aspects of the service and due to the customer's self-property, trading amount, trading time, trading evaluation and trading risk perception factors, etc. The trust assessment among customers is hard to measure and difficult to give accurate quantification. In order to solve the problem, in this paper, a customer trust network model based on the above factors and combined with cognitive theories and methods of e-Business is implemented and three strategies, customer occupation based construction strategy, customer domain based construction strategy and customer occupation and domain based construction strategy, are used for constructing trust network. During the construction process, the method of trust computation in each strategy is introduced. The Experiment results show that the model and these strategies can reduce the complexity of trust relationship and with guaranteed trust value as a premise, improve the coverage rate of trust network.
Black Hole Attractors in Extended Supergravity

We review some aspects of the attractor mechanism for extremal black holes of (not necessarily supersymmetric) theories coupling Einstein gravity to scalars and Maxwell vector fields. Thence, we consider N = 2 and N = 8, d = 4 supergravities, reporting some recent advances on the moduli spaces associated to BPS and non‐BPS attractor solutions supported by charge orbits with non‐compact stabilizers.
Enabling energy-aware mobile data offloading for smartphones through vertical collaboration

Searching for mobile data offloading solutions has become topical in recent years. In the Metropolitan Advanced Delivery Network (MADNet) project, we explore the potential of multiple interfaces on smartphones through a collaborative design to enable energy-aware WiFi-based mobile data offloading. We advocate that the vertical collaboration across different wireless access technologies and network vendors is the key to aggregate the power of mobile operators, WiFi service providers, and end-users. Aiming at reducing the energy consumption on smartphones, we propose an energy-aware algorithm supported by our collaborative architecture to avoid offloading to low-throughput WiFi networks which may consume more energy. The evaluation of streaming applications on our prototyped Nokia N900 smartphones demonstrates that we are able to achieve more than 80% energy saving. Our experiment in the wild also shows that our design can tolerate the minor errors of localization, mobility prediction, and offload capacity estimation.
SCALED EXPERIMENTAL STUDY OF AN AUTOMATIC COLLISION AVOIDANCE SYSTEM FOR PASSENGER CARS

Abstract In this paper, an automatic pre–crash collision avoidance strategy for cars is presented. It produces a collision avoidance manoeuvre, if feasible, or, otherwise, an emergency braking to reduce the energy at the impact. The manoeuvre is generated relying on the use of sliding mode control. The performances of the proposed collision avoidance system are tested on a scaled radio-controlled car and the results are here discussed.
Using Smaller Constituents Rather Than Sentences in Active Learning for Japanese Dependency Parsing

We investigate active learning methods for Japanese dependency parsing. We propose active learning methods of using partial dependency relations in a given sentence for parsing and evaluate their effectiveness empirically. Furthermore, we utilize syntactic constraints of Japanese to obtain more labeled examples from precious labeled ones that annotators give. Experimental results show that our proposed methods improve considerably the learning curve of Japanese dependency parsing. In order to achieve an accuracy of over 88.3%, one of our methods requires only 34.4% of labeled examples as compared to passive learning.
A note on Zeng's technique for color reindexing of palette-based images

Palette reindexing is a well-known and very effective approach for improving the compression of color-indexed images. In this letter, we address the reindexing technique proposed by Zeng et al. and we show how its performance can be improved through a theoretically motivated choice of parameters. Experimental results show the practical appropriateness of the proposed modification.
Auto altitude holding of quadrotor UAVs with Kalman filter based vertical velocity estimation

Altitude regulation is a fundamental control problem of quadrotor UAVs (unmanned aerial vehicles) to ensure required performance for hovering and autonomous navigation. In this paper, under the assumption that the attitude inter loop has been well designed, the stability features of linear P+D+DD controller for altitude control are investigated. To handle the difficulty that the altitude velocity cannot be measured directly, a Kalman filter based ascending/decending velocity estimator using the measurements of acceleromter and barometer/sonser is adopted for velocity feedback. Given the overall dynamics model, P+D+DD controller design procedure and its stability analysis, the effectiveness of the algorithms is validated by field test using our quadrotor. The approaches can be directly extended to the translation velocity estimation and navigation control.
The Diet Factor in Attention-Deficit/Hyperactivity Disorder

This article is intended to provide a comprehensive overview of the role of dietary methods for treatment of children with attention-deficit/hyperactivity disorder (ADHD) when pharmacotherapy has proven unsatisfactory or unacceptable. Results of recent research and controlled studies, based on a PubMed search, are emphasized and compared with earlier reports. The recent increase of interest in this form of therapy for ADHD, and especially in the use of omega supplements, significance of iron deficiency, and the avoidance of the “Western pattern” diet, make the discussion timely. Diets to reduce symptoms associated with ADHD include sugar-restricted, additive/preservative-free, oligoantigenic/elimination, and fatty acid supplements. Omega−3 supplement is the latest dietary treatment with positive reports of efficacy, and interest in the additive-free diet of the 1970s is occasionally revived. A provocative report draws attention to the ADHD-associated “Western-style” diet, high in fat and refined sugars, and the ADHD-free “healthy” diet, containing fiber, folate, and omega-3 fatty acids. The literature on diets and ADHD, listed by PubMed, is reviewed with emphasis on recent controlled studies. Recommendations for the use of diets are based on current opinion of published reports and our practice experience. Indications for dietary therapy include medication failure, parental or patient preference, iron deficiency, and, when appropriate, change from an ADHD-linked Western diet to an ADHD-free healthy diet. Foods associated with ADHD to be avoided and those not linked with ADHD and preferred are listed. In practice, additive-free and oligoantigenic/elimination diets are time-consuming and disruptive to the household; they are indicated only in selected patients. Iron and zinc are supplemented in patients with known deficiencies; they may also enhance the effectiveness of stimulant therapy. In patients failing to respond or with parents opposed to medication, omega-3 supplements may warrant a trial. A greater attention to the education of parents and children in a healthy dietary pattern, omitting items shown to predispose to ADHD, is perhaps the most promising and practical complementary or alternative treatment of ADHD.
Modified Low Energy Adaptive Clustering Hierarchy for Heterogeneous Wireless Sensor Network

In wireless sensor network, it is an important task to collect the data periodically from various sensors node for monitoring and recording the physical conditions of the environment. The sensed data must be transmitted and received between the nodes in the network. The Low Energy Adaptive clustering hierarchy (LEACH) is one of the routing protocol to transmit the data between the nodes in the network. In this work, LEACH protocol is modified and developed the new concept called MLEACH. The proposed protocol is energy efficient for heterogeneous network. The performance was analyzed by considering the time period and it shows that the number of alive nodes was less. Since the alive node is less the energy consumption is also less and thereby increasing the energy efficiency of the network. The comparative analysis was made between the existing and the proposed method. Simulation result shows that the proposed method is more energy efficient than the existing LEACH protocol.
REALISTIC MODEL OF A FIXED-CHARGE MEMBRANE ACCORDING TO THE THEORY OF TEORELL, MEYER, AND SIEVERS

A realistic model of a fixed-charge membrane was constructed to elucidate the principles involved in the Teorell-Meyer-Sievers theory. Polyelectrolyte solutions (polystyrene sulfonic acid or gelatin) were used in a multicompartment cell to serve as the "membrane. " The ionic concentration and potential differences between the compartments served as a finite increment approximation to a continuous membrane phase. The profiles obtained for a positively and negatively charged membrane gave striking support for the theory.
The complexity of counting graph homomorphisms

The problem of counting homomorphisms from a general graph G to a fixed graph H is a natural generalization of graph coloring, with important applications in statistical physics. The problem of deciding whether any homomorphism exists was considered by Hell and Nesetřil. They showed that decision is NP-complete unless H has a loop or is bipartite; otherwise it is in P. We consider the problem of exactly counting such homomorphisms and give a similarly complete characterization. We show that counting is #P-complete unless every connected component of H is an isolated vertex without a loop, a complete graph with all loops present, or a complete unlooped bipartite graph; otherwise it is in P. We prove further that this remains true when G has bounded degree. In particular, our theorems provide the first proof of #P-completeness of the partition function of certain models from statistical physics, such as the Widom–Rowlinson model, even in graphs of maximum degree 3. Our results are proved using a mixture of spectral analysis, interpolation, and combinatorial arguments. © 2000 John Wiley & Sons, Inc. Random Struct. Alg. , 17: 260–289, 2000
An Upscaling Algorithm to Obtain the Representative Ground Truth of LAI Time Series in Heterogeneous Land Surface

Upscaling in situ leaf area index (LAI) measurements to the footprint scale is important for the validation of medium resolution remote sensing products. However, surface heterogeneity and temporal variation of vegetation make this difficult. In this study, a two-step upscaling algorithm was developed to obtain the representative ground truth of LAI time series in heterogeneous surfaces based on in situ LAI data measured by the wireless sensor network (WSN) observation system. Since heterogeneity within a site usually arises from the mixture of vegetation and non-vegetation surfaces, the spatial heterogeneity of vegetation and land cover types were separately considered. Representative LAI time series of vegetation surfaces were obtained by upscaling in situ measurements using an optimal weighted combination method, incorporating the expectation maximum (EM) algorithm to derive the weights. The ground truth of LAI over the whole site could then be determined using area weighted combination of representative LAIs of different land cover types. The algorithm was evaluated using a dataset collected in Heihe Watershed Allied Telemetry Experimental Research (HiWater) experiment. The proposed algorithm can effectively obtain the representative ground truth of LAI time series in heterogeneous cropland areas. Using the normal method of an average LAI measurement to represent the heterogeneous surface produced a root mean square error (RMSE) of 0.69, whereas the proposed algorithm provided RMSE = 0.032 using 23 sampling points. The proposed ground truth derived method was implemented to validate four major LAI products.
Corrected entropy-area relation and modified Friedmann equations

Applying Clausius relation, delta Q = TdS, to apparent horizon of a FRW universe with any spatial curvature, and assuming that the apparent horizon has temperature T = 1/(2 pi(r) over tildeA), and a quantum corrected entropy-area relation, S = A/4G + alpha lnA/4G, where (r) over tildeA and A are the apparent horizon radius and area, respectively, and alpha is a dimensionless constant, we derive modified Friedmann equations, which does not contain a bounce solution. On the other hand, loop quantum cosmology leads to a modified Friedmann equation H-2 = 8 pi G/3 rho(1-rho/rho(crit)). We obtain an entropy expression of apparent horizon of FRW universe described by the modified Friedmann equation. In the limit of large horizon area, resulting entropy expression gives the above corrected entropy-area relation, however, the prefactor alpha in the logarithmic term is positive, which seems not consistent with most of results in the literature that quantum geometry leads to a negative contribution to the area formula of black hole entropy.
Using intraverbal prompts to increase divergent intraverbal responses by a child with autism

We examined the effectiveness of intraverbal prompts to increase the number of divergent responses to categorical questions composed of compound stimuli (e.g., Name some red things) for a 6-year-old child with autism. The intraverbal prompts involved providing the function, feature, and class of the target responses. A multiple probe across behaviors design was used. Results indicated that the child's total number of divergent responses was increased and maintained during 2-week follow-up probe trials. Novel responses were observed across conditions.
Probability of stochastic depletion: an easily interpreted diagnostic
 for stock assessment modelling and fisheries management

Marine fish populations have high variation in cohort strength, and the production of juveniles (recruitment) may have persistent positive or negative residuals (autocorrelation) after accounting for spawning biomass. Autocorrelated recruitment will occur whenever average recruitment levels change between oceanographic regimes or due to predator release, but may also indicate persistent environmental and biological effects on shorter time-scales. Here, we use estimates of recruitment variability and autocorrelation to simulate the stationary distribution of spawning biomass for 100 real-world stocks when unfished, fished at FMSY, or fished following a harvest control rule where fishing mortality decreases as a function of spawning biomass. Results show that unfished stocks have spawning biomass (SB) below its deterministic equilibrium value (SB0) 58% of the time, and below 0.5SB0 5% of the time on average across all stocks. Similarly, stocks fished at the level producing deterministic maximum sustainable yield (FMSY) are below its deterministic prediction of spawning biomass (SBMSY) 60% of the time and below 0.5SBMSY 8% of the time. These probabilities are greater for stocks with high recruitment variability, positive autocorrelation, and high natural mortality—traits that are particularly associated with clupeids and scombrids. An elevated probability of stochastic depletion, i.e. biomass below the deterministic equilibrium expectation, implies that management actions required when biomass drops below a threshold may be triggered more frequently than expected. Therefore, we conclude by suggesting that fisheries scientists routinely calculate these probabilities during stock assessments as a decision support tool for fisheries managers.
Neural network segmentation of images from stained cucurbits leaves with colour symptoms of biotic and abiotic stresses

Abstract The increased production of Reactive Oxygen Species (ROS) in plant leaf tissues is a hallmark of a plant’s reaction to various environmental stresses. This paper describes an automatic segmentation method for scanned images of cucurbits leaves stained to visualise ROS accumulation sites featured by specific colour hues and intensities. The leaves placed separately in the scanner view field on a colour background are extracted by thresholding in the RGB colour space, then cleaned from petioles to obtain a leaf blade mask. The second stage of the method consists in the classification of within mask pixels in a hue-saturation plane using two classes, determined by leaf regions with and without colour products of the ROS reaction. At this stage a two-layer, hybrid artificial neural network is applied with the first layer as a self-organising Kohonen type network and a linear perceptron output layer (counter propagation network type). The WTA-based, fast competitive learning of the first layer was improved to increase clustering reliability. Widrow–Hoff supervised training used at the output layer utilises manually labelled patterns prepared from training images. The generalisation ability of the network model has been verified by K-fold cross-validation. The method significantly accelerates the measurement of leaf regions containing the ROS reaction colour products and improves measurement accuracy.