Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiclass Support Vector Machines for Articulatory Feature Classification

This ongoing research project investigates articulatory feature (AF) classification using multiclass support vector machines (SVMs). SVMs are being constructed for each AF in the multi-valued feature set (Table 1), using speech data and annotation from the IFA Dutch “Open-Source” (van Son et al. 2001) and TIMIT English (Garofolo et al. 1993) corpora. The primary objective of this research is to assess the AF classification performance of different multiclass generalizations of the SVM, including one-versus-rest, one-versus-one, Decision Directed Acyclic Graph (DDAG), and direct methods for multiclass learning. Observing the successful application of SVMs to numerous classification problems (Bennett and Campbell 2000), it is hoped that multiclass SVMs will outperform existing state-of-the-art AF classifiers. One of the most basic challenges for speech recognition and other spoken language systems is to accurately map data from the acoustic domain into the linguistic domain. Much speech processing research has approached this task by taking advantage of the correlation between phones, the basic units of speech sound, and their acoustic manifestation (intuitively, there is a range of sounds that humans would consider to be an “e”). The mapping of acoustic data to phones has been largely successful, and is used in many speech systems today. Despite its success, there are drawbacks to using phones as the point of entry from the acoustic to linguistic domains. Notably, the granularity of the “phoneticsegmental” model, in which speech is represented as a series of phones, makes it difficult to account for various subphone phenomena that affect performance on spontaneous speech. Researchers have pursued an alternative approach to the acoustic-linguistic mapping through the use of articulatory modeling. This approach more directly exploits the intimate relation between articulation and acoustics: the state of one’s speech articulators (e.g. vocal folds, tongue) uniquely determines the parameters of the acoustic speech signal. Unfortunately, while the mapping from articulator to acoustics is straightforward, the problem of recovering the state of the articulators from an acoustic speech representation, acoustic-to-articulatory inversion, poses a formidable challenge (Toutios and Margaritis 2003). Nevertheless, re-
Modelling the Dynamics of Feral Alfalfa Populations and Its Management Implications

Background Feral populations of cultivated crops can pose challenges to novel trait confinement within agricultural landscapes. Simulation models can be helpful in investigating the underlying dynamics of feral populations and determining suitable management options. Methodology/Principal Findings We developed a stage-structured matrix population model for roadside feral alfalfa populations occurring in southern Manitoba, Canada. The model accounted for the existence of density-dependence and recruitment subsidy in feral populations. We used the model to investigate the long-term dynamics of feral alfalfa populations, and to evaluate the effectiveness of simulated management strategies such as herbicide application and mowing in controlling feral alfalfa. Results suggest that alfalfa populations occurring in roadside habitats can be persistent and less likely to go extinct under current roadverge management scenarios. Management attempts focused on controlling adult plants alone can be counterproductive due to the presence of density-dependent effects. Targeted herbicide application, which can achieve complete control of seedlings, rosettes and established plants, will be an effective strategy, but the seedbank population may contribute to new recruits. In regions where roadside mowing is regularly practiced, devising a timely mowing strategy (early- to mid-August for southern Manitoba), one that can totally prevent seed production, will be a feasible option for managing feral alfalfa populations. Conclusions/Significance Feral alfalfa populations can be persistent in roadside habitats. Timely mowing or regular targeted herbicide application will be effective in managing feral alfalfa populations and limit feral-population-mediated gene flow in alfalfa. However, in the context of novel trait confinement, the extent to which feral alfalfa populations need to be managed will be dictated by the tolerance levels established by specific production systems for specific traits. The modelling framework outlined in this paper could be applied to other perennial herbaceous plants with similar life-history characteristics.
Secure Wireless Sensor Network Updates Using OTAP And Performance of Symmetric Encryption Algorithms on Power Consumption

Wireless Sensor Networks (WSNs) face many challenges including reliability, flexibility and security. When WSNs deployed in remote locations need to be reprogrammed, environmental conditions often make it impossible to physically retrieve them. Over the Air Programming (OAP) plays an important role in achieving this task. Over-the-air programming (OAP) is a fundamental service in sensor networks that relies upon reliable broadcast for efficient dissemination. SenSeOP Programming protocols provide a convenient way to update program images via wireless communication. In hostile environments where there may be malicious attacks against wireless sensor networks, the process of reprogramming faces threats from potentially compromised nodes. While existing solutions can provide authentication services, they are insufficient for a new generation of network coding-based reprogramming protocols in wireless sensor networks. The Encryption algorithms play a main role in information security systems. On the other side, those algorithms consume a significant amount of computing resources such as CPU time, memory, and battery power. This paper illustrates the key concepts of security, wireless networks, and security over wireless networks. the most common encryption algorithms on power consumption for wireless devices namely: AES (Rijndael), DES, 3DES, RC2, Blowfish, and RC6. A comparison has been conducted for those encryption algorithms at different settings for each algorithm such as different sizes of data blocks, different data types, battery power consumption, date transmission through wireless network and finally encryption/decryption speed. KeywordsSenSeop, WSN, Security, Encryption Techniques, Power Consumption.
Tree Approximation and Encoding

Tree approximation is a new form of nonlinear approximation which appears naturally in some applications such as image processing and adaptive numerical methods. It is somewhat more restrictive than the usual n-term approximation. We show that the restrictions of tree approximation cost little in terms of rates of approximation. We then use that result to design encoders for compression. These encoders are universal (they apply to general functions) and progressive (increasing accuracy is obtained by sending new bits). We show optimality of the encoders, in the sense that they provide upper estimates for the Kolmogorov entropy of Besov balls.
Appendix of "Calvo vs. Rotemberg in a Trend In‡ation World: An Empirical Investigation" (not intended for publication)

First, we initialized the variance-covariance matrix of the proposal distribution and employed a standard random-walk Metropolis-Hastings for the rst t t0 = 20; 000 draws. To do so, we computed the posterior mode by the "csminwel" algorithm developed by Chris Sims. The inverse of the Hessian of the target distribution evaluated at the posterior mode was used to de ne the variancecovariance matrix C0 of the proposal distribution. The initial VCV matrix of the forecast errors in the Kalman lter was set to be equal to the unconditional
DDoS detection and analysis in SDN-based environment using support vector machine classifier

Software Defined Networking (SDN) provides separation of data plane and control plane. The controller has centralized control of the entire network. SDN offers the ability to program the network and allows dynamic creation of flow policies. The controller is vulnerable to Distributed Denial of Service (DDoS) attacks that leads to resource exhaustion which causes non-reachability of services given by the controller. The detection of DDoS requires adaptive and accurate classifier that does decision making from uncertain information. It is critical to detect the attack in the controller at earlier stage. SVM is widely used classifier with high accuracy and less false positive rate. We analyze the SVM classifier and compare it with other classifiers for DDoS detection. The experiments show that SVM performs accurate classification than others.
Investigations in single document summarization by extraction method

Due to the rapid growth of the Internet and online information services, huge information is readily made available online. There is no time for anybody to read everything but critical decisions are required to be made quickly. This has led to large-scale research efforts in text summarization. This paper combines contributions by term frequency weight, position weight and commendation weight to form an effective extraction based summary. We have analyzed the significance of each feature and we found that a combination of all three weights results in a better summary as close as human generated summary. We also show that our summarizer outperforms commercially available summarizers like Copernic summarizer and Microsoft Summarizer.
A Proteomic Approach for the Discovery of Early Detection Markers of Hepatocellular Carcinoma

Individuals chronically infected with hepatitis B or C virus (HBV, HCV) are at high risk for the development of hepatocellular carcinoma (HCC), with disease progression occurring relentlessly over many years. The diagnosis of HCC usually occurs at late stages in the disease when there are few effective treatment options and the prognosis for patients with HCC is very poor. The long latency period, together with clearly identified at risk populations, provide opportunities for earlier detection that will allow more timely and effective treatment of this devastating cancer. We are using a proteomic approach to test the hypothesis that changes in the amount of certain serum polypeptides, or changes in their post-translational modifications, can be used to predict the onset of HCC. Advances in the standardization of two dimensional gel electrophoresis (2DE) coupled with computerized image analysis now permit the reproducible resolution of thousands of polypeptides per run. Serum polypeptides from individuals at different stages in the disease continuum are being resolved by 2DE to identify those that change with disease progression. Polypeptides found by this method can be further characterized by mass spectrometry. In addition, the potential for changes in the glycan structure of certain polypeptides to serve as a marker for disease progression can be explored. The proteomic approach is expected to liberate us from the need to “cherry pick” or guess the best biomarkers and let the data tell us which are the best indicators of disease. Information may also be gleaned about the pathobiology of the disease process.
Attacks on a Block Based SVD Watermarking Scheme

One major application of a watermarking scheme is to protect the copyright of a content owner by embedding the owner's watermark into the content. Recently, a block based watermarking scheme was proposed by Ghazy et al., which is dependent on singular value decomposition (SVD). In the proposed scheme, the cover image is divided into blocks, and then the watermark is embedded in the singular values of each block separately. In this paper, we present attacks on this watermarking scheme and show how the designers' security claims can be invalidated, namely related to robustness and protection of rightful ownership.
Satellite-Derived Tropical Cyclone Intensity in the North Pacific Ocean Using the Deviation-Angle Variance Technique

AbstractThe deviation-angle variance technique (DAV-T), which was introduced in the North Atlantic basin for tropical cyclone (TC) intensity estimation, is adapted for use in the North Pacific Ocean using the “best-track center” application of the DAV. The adaptations include changes in preprocessing for different data sources [Geostationary Operational Environmental Satellite-East (GOES-E) in the Atlantic, stitched GOES-E–Geostationary Operational Environmental Satellite-West (GOES-W) in the eastern North Pacific, and the Multifunctional Transport Satellite (MTSAT) in the western North Pacific], and retraining the algorithm parameters for different basins. Over the 2007–11 period, DAV-T intensity estimation in the western North Pacific results in a root-mean-square intensity error (RMSE, as measured by the maximum sustained surface winds) of 14.3 kt (1 kt ≈ 0.51 m s−1) when compared to the Joint Typhoon Warning Center best track, utilizing all TCs to train and test the algorithm. The RMSE obtained when t.
Preserving location and absence privacy in geo-social networks

Online social networks often involve very large numbers of users who share very large volumes of content. This content is increasingly being tagged with geo-spatial and temporal coordinates that may then be used in services. For example, a service may retrieve photos taken in a certain region. The resulting geo-aware social networks (GeoSNs) pose privacy threats beyond those found in location-based services. Content published in a GeoSN is often associated with references to multiple users, without the publisher being aware of the privacy preferences of those users. Moreover, this content is often accessible to multiple users. This renders it difficult for GeoSN users to control which information about them is available and to whom it is available. This paper addresses two privacy threats that occur in GeoSNs: location privacy and absence privacy. The former concerns the availability of information about the presence of users in specific locations at given times, while the latter concerns the availability of information about the absence of an individual from specific locations during given periods of time. The challenge addressed is that of supporting privacy while still enabling useful services. We believe this is the first paper to formalize these two notions of privacy and to propose techniques for enforcing them. The techniques offer privacy guarantees, and the paper reports on empirical performance studies of the techniques.
Real-time hand tracking for rehabilitation and character animation

Hand and finger tracking has a major importance in healthcare, for rehabilitation of hand function required due to a neurological disorder, and in virtual environment applications, like characters animation for on-line games or movies. Current solutions consist mostly of motion tracking gloves with embedded resistive bend sensors that most often suffer from signal drift, sensor saturation, sensor displacement and complex calibration procedures. More advanced solutions provide better tracking stability, but at the expense of a higher cost. The proposed solution aims to provide the required precision, stability and feasibility through the combination of eleven inertial measurements units (IMUs). Each unit captures the spatial orientation of the attached body. To fully capture the hand movement, each finger encompasses two units (at the proximal and distal phalanges), plus one unit at the back of the hand. The proposed glove was validated in two distinct steps: (a) evaluation of the sensors' accuracy and stability over time; (b) evaluation of the bending trajectories during usual finger flexion tasks based on the intra-class correlation coefficient (ICC). Results revealed that the glove was sensitive mainly to magnetic field distortions and sensors tuning. The inclusion of a hard and soft iron correction algorithm and accelerometer and gyro drift and temperature compensation methods provided increased stability and precision. Finger trajectories evaluation yielded high ICC values with an overall reliability within application's satisfying limits. The developed low cost system provides a straightforward calibration and usability, qualifying the device for hand and finger tracking in healthcare and animation industries.
Connection between Suicidal Ideation, Life Meaning, and Leisure Time Activities

ABSTRACT This study is an examination of the links between adolescent suicidal ideation, life meaning, and the ways they spend their leisure time. The sample consisted of 450 students aged 15–18. Findings showed a significant negative correlation between suicidal ideation and sense of life meaning, encompassing factors such as age and gender. Adolescents with involvement in social activities demonstrated lower levels of suicidal ideation (total score), and lower levels of depression and anxiety, than the other two groups. The study discusses the research and practical implications of these findings. The findings suggest the possibility of establishing prevention, intervention, and therapy programs for adolescents based on life meaning.
The Mazur Intersection Property and Farthest Points

K. S. Lau had shown that a reflexive Banach space has the Mazur Intersection Property (MIP) if and only if every closed bounded convex set is the closed convex hull of its farthest points. In this work, we show that in general this latter property is equivalent to a property stronger than the MIP. As corollaries, we recapture the result of Lau and characterize the w*-MIP in dual of RNP spaces.
Deep Learning for Image Captioning

Image Captioning is an application which provides a meaningful textual summary of the scene in the image. The application is developed on the Android platform. When using the application, the user takes a picture and sends it to the server. The server has a model which generates captions for the image as a whole, which can be read out to the user via text to voice feature of Android devices. Flickr30k [36] and MSCOCO [4] image data-sets were used to develop the model. Since, its a supervised learning the data-sets comprise of images with 4 textual annotations for every image. The model was developed using Neural Talk which is a deep learning framework which performs operations such as convolutional neural network for object recognition in images and a bi-directional recurrent neural network for captioning the image [18]. Experiments were carried out to test the effectiveness of the model with respect to scale and color augmentation. These experiments provided some fascinating results on how the natural language descriptions were generated based on image characteristics. This application was developed with the intent of providing aid to visually impaired individuals.
A Versatile Strategy for Production of Membrane Proteins with Diverse Topologies: Application to Investigation of Bacterial Homologues of Human Divalent Metal Ion and Nucleoside Transporters

Membrane proteins play key roles in many biological processes, from acquisition of nutrients to neurotransmission, and are targets for more than 50% of current therapeutic drugs. However, their investigation is hampered by difficulties in their production and purification on a scale suitable for structural studies. In particular, the nature and location of affinity tags introduced for the purification of recombinant membrane proteins can greatly influence their expression levels by affecting their membrane insertion. The extent of such effects typically depends on the transmembrane topologies of the proteins, which for proteins of unknown structure are usually uncertain. For example, attachment of oligohistidine tags to the periplasmic termini of membrane proteins often interferes with folding and drastically impairs expression in Escherichia coli. To circumvent this problem we have employed a novel strategy to enable the rapid production of constructs bearing a range of different affinity tags compatible with either cytoplasmic or periplasmic attachment. Tags include conventional oligohistidine tags compatible with cytoplasmic attachment and, for attachment to proteins with a periplasmic terminus, either tandem Strep-tag II sequences or oligohistidine tags fused to maltose binding protein and a signal sequence. Inclusion of cleavage sites for TEV or HRV-3C protease enables tag removal prior to crystallisation trials or a second step of purification. Together with the use of bioinformatic approaches to identify members of membrane protein families with topologies favourable to cytoplasmic tagging, this has enabled us to express and purify multiple bacterial membrane transporters. To illustrate this strategy, we describe here its use to purify bacterial homologues of human membrane proteins from the Nramp and ZIP families of divalent metal cation transporters and from the concentrative nucleoside transporter family. The proteins are expressed in E. coli in a correctly folded, functional state and can be purified in amounts suitable for structural investigations.
PERSONALIZED ADAPTIVE PDA INTERFACE 1

User demands for usability in mobile context due to the small size of personal data assistants (PDAs) challenge traditional input design. An on-screen keyboard that offers an easier and faster method of entering text with a pen on PDAs, has been developed. We have developed a method for adapting its predictive ability according to user’s personal word usage, input context and syntax rules. Frequently used characters are presented to the users in different key sizes and color contrasts according to their relative probabilities to aid visual searching. For this purpose, an experiment has been conducted on which and how to use (user’s) data source for faster prediction. In this experiment, we compared four dictionaries recorded from the British National Corpus, personal documents, chat logs and personal e-mails. The experimental results show ways to improve the performance of the word prediction and the language coverage of the word completion.
Approches spatiales cyclostationnaires pour le traitement des interférences en radioastronomie

L'environnement electromagnetique est de plus en plus envahi par les activites de telecommunications, limitant ainsi la sensibilite et les performances des radiotelescopes. Il devient donc necessaire de developper des traitements efficaces afin de limiter l'impact de ces interferences radioelectriques (RFI). A ce titre, l'exploitation de la propriete de cyclostationnarite, inherente a la plupart des signaux de telecommunication, est une piste de developpement prometteuse pour la radioastronomie et notamment pour les futures generations de radiotelescopes tels que LOFAR et SKA. Dans cet article, plusieurs utilisations de cette propriete de cyclostationnarite sont proposees pour permettre la detection, le filtrage ou l'estimation des brouilleurs dans le cadre de reseaux a antennes phasees.
Visually Searching the Web for Content

New visual information in the form of images, graphics, animations and videos is published on the World Wide Web at an incredible rate. However, cataloging it exceeds the capabilities of current text-based Web search engines. WebSeek provides a complete system that collects visual information from the Web by automated agents, then catalogs and indexes it for fast searching and retrieval.