Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing efficiency of integration methods for cloth simulation

Any cloth simulation system needs efficient numerical methods for integrating the equations that describe the mechanical behavior of the discrete representation of the cloth. Choosing the adequate method should be done with full knowledge of the advantages and weaknesses of the main techniques. This paper presents a quantitative comparison of the efficiency of the most common integration techniques used for cloth simulation, and raises the key considerations for optimal implementations depending on the practical kind of simulation problematic.
A semantic role-based methodology for knowledge acquisition from Spanish documents

The Semantic Web vision grounds on providing the current Web with structural knowledge that can be understandable by the machines without the intervention of human beings. Given that ontologies are a backbone technology for the Semantic Web, different mechanisms and methodologies for designing and building ontologies have been proposed. The need for overcoming the bottleneck provoked by the manual construction of ontologies has generated several studies and research on obtaining semiautomatic methods to build ontologies. Ontology learning from Web documents is considered to be an important activity to promote the Semantic Web. In this paper, an automatic method for acquiring knowledge from Spanish texts is described. The method is based on semantic roles, which have been employed in our research for extracting semantic relations between concepts. The method makes it possible to represent multiple semantic relations. A set of experiments have been performed with the approach implemented in the oncology domain that show promising results.
Land Grab in Africa: A Review Of Emerging Issues and Implications For Policy Options

The intensity and magnitude of large-scale land acquisition in Africa over the past decade is putting severe pressure on the demand for land and the quality of land available for less powerful users. The most heavily targeted countries are DRC, Ethiopia, Madagascar, Mozambique, Sudan, Tanzania and Zambia. There appears to be some divergence of interest between Africans and foreign investors in the demand for African land. African governments? use of land as a commodity is shaped by their quest to transform the agricultural sector with a view to raising productivity, increasing food supply, reducing poverty and expanding livelihoods. However, the motivation for most foreign investors includes investing in countries? food supply chains and security, meeting demand for bio-fuels, mineral resource exploration etc. The exportation of almost all food produced to investors? countries, and non-implementation of agreed contracts, including compensation for displaced people, among other issues, tend to confirm this divergence of objectives and the dichotomies it creates between intentions and reality. (? )
Mitigating Byzantine Attacks in Ad Hoc Wireless Networks

Attacks where adversaries have full control of a number of authenticated devices and behave arbitrarily to disrupt the network are referred to as Byzantine attacks. Traditional secure routing protocols are vulnerable to this class of attacks since they usually assume that once authenticated, a node can be trusted to execute the protocol correctly. We present a detailed description of several Byzantine attacks (black hole, flood rushing, wormhole and overlay network wormhole), analyze their mechanisms and describe the major mitigation techniques. Through simulation, we perform a quantitative evaluation of the impact of these attacks on an insecure on-demand routing protocol. The relative strength of the attacks is analyzed in terms of the magnitude of disruption caused per adversary. An implementation of the On-Demand Secure Byzantine Routing protocol (ODSBR) was created in order to quantify its ability to mitigate the considered attacks. ODSBR was chosen because its design addresses a wide range of Byzantine attacks.
Predicting Quitting on Yammer : An Online Social Enterprise Space

The profusion of social media in daily life has accelerated the co-evolution of the online space and the real-world environment. Given this, we try to understand the manner in which negative real-world events manifest into destructive dynamics in online social behavior, and whether it is possible to infer the latter from the former. Modeling destructive dynamics can be important for organizations, since unsatisfied employees can exhibit various types of dysfunctional behavior. To investigate this, we take the novel approach of analyzing a corporate social network, the Yammer data set of a large corporation. In particular, we study how active employees are in using the social network, and in turn determine if people are likely to (i) quit the yammer space, (ii) quit the parent company or, (iii) quit groups within Yammer. In this paper, we take a data-driven to identify quitters. To this end, a rich set of features including graph based features, content features and, work practice features are derived from the data set and subsequently used to model quitting behavior. Our experiments show that our proposed data-driven approach can be used to predict user engagement levels within Yammer and the probability of users quitting the corporation and Yammer with fair accuracies of approximately 68% and 82% respectively. The corresponding recall rates are also moderately high at 62% and 87%. Given the difficulty of the quitting prediction problem, these accuracies and recall rates are fairly encouraging.
Fractal Measures, p-Adic Numbers And Continues Transition Between Dimensions

Fractal measures of images of continuous maps from the set of p-adic numbers Qp into complex plane C are analyzed. Examples of "anomalous" fractals, i.e. the sets where the D-dimensional Hausdorff measures (HM) are trivial, i.e. either zero, or sigma-infinite (D is the Hausdorff dimension (HD) of this set) are presented. Using the Caratheodory construction, the generalized scale-covariant HM (GHM) being non-trivial on such fractals are constructed. In particular, we present an example of 0-fractal, the continuum with HD=0 and nontrivial GHM invariant w.r. t. the group of all diffeomorphisms C. For conformal transformations of domains in R^n, the formula for the change of variables for GHM is obtained. The family of continuous maps Qp in C continuously dependent on "complex dimension" d in C is obtained. This family is such that: 1) if d=2(1), then the image of Qp is C (real axis in C); 2) the fractal measures coincide with the images of the Haar measure in Qp, and at d=2(1) they also coincide with the flat (linear) Lebesgue measure; 3) integrals of entire functions over the fractal measures of images for any compact set in Qp are holomorphic in d, similarly to the dimensional regularization method in QFT.
Maximal Recovery Network Coding under Topology Constraint

Recent advances have shown that channel codes can be mapped onto networks to realize efficient Network Coding (NC); this has led to the emergence of Code-on-Network-Graphs (CNG). Traditional CNG approaches (e.g Decentralized Erasure Codes) focus on a generating a sequence of encoded symbols from a given input source (of size K), such that the original symbols can be recovered from any subset of the encoded symbols of size equal to or slightly larger than K. However in all cases the number of source symbols recovered falls rapidly if the number of encoded symbols received falls below K. In this paper we determine the CNG code-ensembles (under statistical toplogy constraint) which result in maximal recovery of WSN source data (for different erasure-rates), thereby minimizing the deterioration in data recovery. We also perform fixed point stability analysis on the underlying LDPC code ensemble. We then propose a distributed algorithm for generating a sequence of encoded symbols adhering to the designed code ensemble. Optimal solutions for a sensor network with 1000 nodes is determined using the Differential Evolution algorithm, and the solution sensitivity to variance in number of sensor nodes and node-interconnectivity is evaluated.
Investigation of factors affecting the intelligence quotient (IQ) of intellectually disabled children and adolescents using modern regression approaches

Abstract Background: Research shows that in addition to biological factors, psychological and social risk factors play a role in the development of intellectual disability. Objectives: This study aimed to investigate the familial, personal and educational factors affecting the intelligence quotient (IQ) levels of intellectually disabled children and adolescents via regularized regression approaches (RRAs) and to compare the results with those of conventional regression approach (CRA). Methods: A total of sixty characteristics were examined along with dummy variables of 205 children and adolescents selected according to the study protocol. Compact, Lasso, Ridge and Ridged Lasso RRAs were used in the dataset. Results: The optimal model was obtained with the Lasso approach and contained ten risk factors having a significant effect on IQ levels: diagnosis of cerebral palsy, age at onset of speech, duration of education, age at onset of walking, presence of elimination disorders, presence of attention-deficit hyperactivity disorder, family income, and number of siblings, residence and age. The RRAs provided opportunity to examine more factors than CRAs without requiring the fulfillment of strict CRA assumptions. Conclusions: Due to the advantages of RRAs, expanding their clinical usage for very large datasets was recommended. [Ethiop. J. Health Dev. 2018;32(1):21-28] Keywords: Intelligence quotient, intellectual disability, regularized regression, Lasso, Ridged Lass
Higher Order E¢ ciency of Bias Corrections

The purpose of this paper is to show that the choice of bias correction method does not a¤ect the higher order e¢ ciency of rst-order e¢ cient estimators. We show this result by a formal expansion and verify it by calculations for the bootstrap, jackknife, and sample moment based bias corrections for the maximum likelihood estimator. We also nd that the bootstrap and jacknife bias corrected estimators have the same stochastic expansion to third-order. Bunche Hall 8383, Department of Economics, UCLA Box 951477, Los Angeles, CA 90095-1477. Email: hahn@econ.ucla. edu yMIT, Department of Economics, E52-371A, 50 Memorial Drive, Cambridge, MA 02142. Email: gkuerste@mit.edu. Financial support from NSF grants SES-0095132 and SES-0523186 is gratefully acknowledged. zMIT, Department of Economics, E52-262, 50 Memorial Drive, Cambridge, MA 02142. Email: wnewey@mit.edu.
Filteryedping: Design Challenges and User Performance of Dwell-Free Eye Typing

The ability to use the movements of the eyes to write is extremely important for individuals with a severe motor disability. With eye typing, a virtual keyboard is shown on the screen and the user enters text by gazing at the intended keys one at a time. With dwell-based eye typing, a key is selected by continuously gazing at it for a specific amount of time. However, this approach has two possible drawbacks: unwanted selections and slow typing rates. In this study, we propose a dwell-free eye typing technique that filters out unintentionally selected letters from the sequence of letters looked at by the user. It ranks possible words based on their length and frequency of use and suggests them to the user. We evaluated Filteryedping with a series of experiments. First, we recruited participants without disabilities to compare it with another potential dwell-free technique and with a dwell-based eye typing interface. The results indicate it is a fast technique that allows an average of 15.95 words per minute after 100min of typing. Then, we improved the technique through iterative design and evaluation with individuals who have severe motor disabilities. This phase helped to identify and create parameters that allow the technique to be adapted to different users.
Parallel imaging/manipulation force microscopy

Conventional atomic force microscope nanomanipulation is inefficient because of the serial imaging/manipulation operation. We present here a parallel imaging/manipulation force microscope (PIMM) to improve manipulation efficiency. The PIMM is equipped with two individually actuated cantilevers with protrudent tips. One cantilever acts as an imaging sensor by scanning nano-objects and tip of the other cantilever that is used as a manipulating tool. Two manipulation schemes were introduced to fulfill parallel imaging/manipulation tasks with normal and high-speed image scan, respectively. Performance of the PIMM was validated by the parallel imaging/manipulation of nanoparticles to form a nanopattern with a commonly used pushing operation.
Employment Protection and Migration

We argue in this paper that labor market institutions, and more particularly employment protection (EPL), are an important determinant of migration. Using a bilateral migration database, we empirically show that the employment protection di fferential has a negative impact on bilateral ows. Contrary to pop- ular wisdom which assumes that migrants look for a more protected market, we show that migrants tend to move to countries where employment protection is close to that of their country of origin. Relative preferences over wages or employment, or a distinct impact on wages and employment may explain such results. We also show that these e ffects are stronger for high-skilled workers.
Personalized augmented reality touring of archaeological sites with wearable and mobile computers

This paper presents Archeoguide, a novel system offering augmented reality tours in archaeological sites. The system is based on wearable and mobile computers, networking technology and real-time computer graphics and 3D animation and visualization techniques. The user can participate tours adapted to his profile and automatically receive information based on his position and orientation as calculated by a hybrid technique making use of GPS, compass and image-based tracking. The user can interact with the device via multi-modal interaction techniques and request navigation and other information. Archeoguide has been tested at the archaeological site of Olympia in Greece.
Optimizing user association and activation fractions in heterogeneous wireless networks

We consider the problem of maximizing the alphafairness utility over the downlink of a heterogeneous wireless network (HetNet) by jointly optimizing the association of users to transmission points (TPs) and the activation fractions of all TPs. Activation fraction of each TP is the fraction of the frame duration for which it is active, and together these fractions influence the interference seen in the network. To address this joint optimization problem we adopt an approach wherein the activation fractions and the user associations are optimized in an alternating manner. The sub-problem of determining the optimal activation fractions is solved using an auxiliary function method that we show is provably convergent and is amenable to distributed implementation. On the other hand, the sub-problem of determining the user association is solved via a simple combinatorial algorithm. Meaningful performance guarantees are derived and a distributed variant offering identical guarantees is also proposed. The significant benefits of using the proposed algorithms are then demonstrated via realistic simulations.
Automatic Tagging of Arabic Text: From Raw Text to Base Phrase Chunks

To date, there are no fully automated systems addressing the community's need for fundamental language processing tools for Arabic text. In this paper, we present a Support Vector Machine (SVM) based approach to automatically tokenize (segmenting off clitics), part-of-speech (POS) tag and annotate base phrases (BPs) in Arabic text. We adapt highly accurate tools that have been developed for English text and apply them to Arabic text. Using standard evaluation metrics, we report that the SVM-TOK tokenizer achieves an Fβ=1 score of 99.12, the SVM-POS tagger achieves an accuracy of 95.49%, and the SVM-BP chunker yields an Fβ=1 score of 92.08.
Developmental expression of the Fac gene correlates with congenital defects in Fanconi anemia patients.

Fanconi anemia (FA) is a genetically heterogeneous, autosomal recessive disorder characterized by a variety of congenital and skeletal malformations, progressive pancytopaenia and predisposition to malignancies. While the basic defect in this disease is not known, the cloning of the gene defective in FA group C patients (FAC) allows analysis of its expression pattern, which may provide clues about the functional properties of the protein. This paper describes the distribution of Fac transcripts during murine development (8-19.5 days p.c.), using RNA in situ hybridization. Fac is initially expressed (8-10 days p.c.) in the mesenchyme and its derivatives with osteogenic potential. The transcript is also apparent at later stages of bone development (13-19.5 days p.c.), localized to cells of the inner perichondrium, periosteum and zone of endochondral ossification. In the latter, Fac transcripts are seen in cells from both osteogenic and hematopoietic lineages. Fac mRNA is also seen in intramembranous cranial and facial bones. In addition, Fac signal is detected in non-skeletal tissues: brain, whisker follicles, lung, kidney, gut and stomach. Fac expression is high in progenitor cell populations but is downregulated in differentiating cells that give rise to connective tissue. The pattern of Fac expression is consistent with the skeletal and non-skeletal congenital abnormalities in FA patients. As well, expression in rapidly dividing progenitors is consistent with hypotheses regarding the nature of the basic defect in FA: a role of the protein in DNA repair or protection from oxygen toxicity.
Online and Offline Sales Channels for Enterprise Software: Cannibalization or Complementarity?

Lured by the success of online sales channels in the consumer software market, enterprise software vendors have launched proprietary online channels alongside their traditional offline ones. However, it is disputable whether the online purchase of a software application is as compelling for an organizational buyer as it is for an individual consumer. Relying on a qualitative research strategy and a cross-sectional research design, we have explored the channel adoption decision made by organizational entities when they purchase business software applications. We have constructed a qualitative channel adoption model which takes into account the relevant drivers and barriers, their interdependences, and the buying process phases. Our findings suggest that offline channels will not be cannibalized unless some peculiar characteristics of enterprise software applications change. We have also derived recommendations for the design of multichannel sales systems according to the main classes of enterprise software products and services.
An Immuno-inspired Approach Towards Sentence Generation

Though human beings comprehend, imbibe and subsequently generate syntactically and semantically correct languages, the manner in which they do so has hardly been understood or unearthed. Most of the current work to achieve the same is heavily dependent on statistical and probabilistic data retrieved from a large corpus coupled with a formal grammar catering to the concerned natural language. This paper attempts to portray a technique based on an analogy described by Jerne on how his theory of the Idiotypic Network could possibly explain the human language generation capability. Starting with a repertoire of unigrams (antibodies) weaned from a corpus available a priori, we show how these can be sequenced to generate higher order n-grams that depict full or portions of correct sentences in that language. These sentences or their correct portions form a network similar to the Idiotypic Network that in turn aid in the generation of sentences or portions thereof which are new to the corpus signifying the learning of new and correct sequences. The network is built based on a modified version of the dynamics suggested by Farmer et. al. The paper describes the related dynamics of the network along with the results obtained from a corpus.
Passive direction finding using amplitude and phase comparison techniques

Amplitude and phase comparison methods are practical direction finding (DF) techniques for electronic support and electronic intelligence systems. The combination of amplitude and phase comparison methods improves the direction finding accuracy and at the same time the ambiguities of phase comparison method are resolved by amplitude comparison method. In this research, the important factors that affect the accuracy of direction finding algorithm, such as the number of antennas, antennas' placements and distances between antennas are analyzed with different signal to noise ratio (SNR) values. The root mean square (RMS) error values of direction of arrival estimates are presented and the antenna placement scenarios for high DF accuracy are acquired.
Human Bcl-2 Reverses Survival Defects in Yeast Lacking Superoxide Dismutase and Delays Death of Wild-Type Yeast

We expressed the human anti-apoptotic protein, Bcl-2, in Saccharomyces cerevisiae to investigate its effects on antioxidant protection and stationary phase survival. Yeast lacking copper-zinc superoxide dismutase (sod1Δ) show a profound defect in entry into and survival during stationary phase even under conditions optimal for survival of wild-type strains (incubation in water after stationary phase is reached). Expression of Bcl-2 in the sod1Δ strain caused a large improvement in viability at entry into stationary phase, as well as increased resistance to 100% oxygen and increased catalase activity. In addition, Bcl-2 expression reduced mutation frequency in both wild-type and sod1Δ strains. In another set of experiments, wild-type yeast incubated in expired minimal medium instead of water lost viability quickly; expression of Bcl-2 significantly delayed this stationary phase death. Our results demonstrate that Bcl-2 has activities in yeast that are similar to activities it is known to possess in mammalian cells: (a) stimulation of antioxidant protection and (b) delay of processes leading to cell death.
Music signal separation based on Bayesian spectral amplitude estimator with automatic target prior adaptation

In this paper, we propose a new approach for addressing music signal separation based on the generalized Bayesian estimator with automatic prior adaptation. This method consists of three parts, namely, the generalized MMSE-STSA estimator with a flexible target signal prior, the NMF-based dynamic interference spectrogram estimator, and closed-form parameter estimation for the statistical model of the target signal based on higher-order statistics. The statistical model parameter of the hidden target signal can be detected automatically for optimal Bayesian estimation with online target-signal prior adaptation. Our experimental evaluation can show the efficacy of the proposed method.
The SAMMIE Corpus of Multimodal Dialogues with an MP3 Player

We describe a corpus of multimodal dialogues with an MP3player collected in Wizard-of-Oz experiments and annotated with a richfeature set at several layers. We are using the Nite XML Toolkit (NXT) to represent and further process the data. We designed an NXTdata model, converted experiment log file data and manualtranscriptions into NXT, and are building tools for additionalannotation using NXT libraries. The annotated corpus will be used to (i) investigate various aspects of multimodal presentation andinteraction strategies both within and across annotation layers; (ii) design an initial policy for reinforcement learning of multimodalclarification requests.