Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient language model look-ahead probabilities generation using lower order LM look-ahead information

In this paper, an efficient method for language model look- ahead probability generation is presented. Traditional methods generate language model look-ahead (LMLA) probabilities for each node in the LMLA tree recursively in a bottom to up manner. The new method presented in this paper makes use of the sparseness of the n-gram model and starts the process of generating an n-gram LMLA tree from a backoff LMLA tree. Only a small number of nodes are updated with explicitly estimated LM probabilities. This speeds up the bigram and trigram LMLA tree generation by a factor of 3 and 12 respectively.
Poster : Preliminary Investigation of an NFC-Unlock Mechanism for Android [ SOUPS 2013 Poster Abstract ]

Protecting mobile phones with password, pins, gestures and other types of authentication mechanisms is a hot topic, since ever more sensitive information is stored on peoples’ phones and the usability of current systems still leaves much to be desired[3]. New techniques of authentication to a phone unlocking it which are fast, easy to use and secure are needed [1]. In this poster we present a preliminary study of a new unlock method which uses NFC tags as authentication tokens. The NFC based unlocking mechanism was developed by a student of the DCSec group at the University of Hannover [4] and will be described in the next section. To evaluate which features of this system need to be improved and how to proceed with the further development, we designed and conducted a user study. The results of this study will be presented in this poster.
Wearable PIFA antenna for smart glasses application

This paper presents a wearable antenna of 2.4 GHz Bluetooth for smart glasses application. This antenna consists of two elements array planar inverted-F antennas (PIFA) using coaxial cable to connect two antenna elements together. Moreover, Specific Absorption Rate (SAR) in user's head is also calculated using the model provided by CST software. The frequency range for reflection coefficient <; -10 dB is from 2.35 GHz to 2.42 GHz. The maximum gain of the proposed antenna is 2.836 dBi at the center frequency.
An algorithm for stereotype deduction in UML-based formalism and its application in geographic information systems

Stereotypes provide a mechanism for extending the vocabulary of the UML. Present UML-based formalisms for geographic information system use the concept of visual stereotypes in order to represent geographic types. This paper extends the expressiveness of stereotypes currently defined for geographic types and describes an algorithm for the computation of visual stereotypes resulting from aggregation operations.
MODELING WORD DURATION FOR BETTER SPEECH RECOGNITION

We describe a new method of modeling duration at word level. These duration models are easily trained from the acoustic training data and can be used to rescore N−best lists of recognition hypotheses. The models capture some of the well known durational effects such as prepausal lengthening. They incorporate a simple back off mechanism to handle unseen words during rescoring. Experiments with various large vocabulary conversational speech recognition (LVCSR) evaluation sets showed consistent improvements of 0.7−1.0% in word error rate (WER).
An epidemiological model for semantics dissemination

Bio-inspired computing models have gained significant popularity in the engineering of distributed and autonomous systems. Epidemics assist in the direction of collaborative computing where groups of nodes can collectively share semantic content based on the current mobile context and user interests. Semantic information received by a node could infect the node and improve the existing knowledge according to pre-existing semantic structure. The capability of a node to reason with semantic information results in locally inferred information, which becomes a new potential epidemic. The application of epidemiology and context - awareness on semantically enriched information dissemination in ad-hoc mobile networks is analyzed and assessed using simulations.
Optical Microspherical Resonators for Biomedical Sensing

Optical resonators play an ubiquitous role in modern optics. A particular class of optical resonators is constituted by spherical dielectric structures, where optical rays are total internal reflected. Due to minimal reflection losses and to potentially very low material absorption, these guided modes, known as whispering gallery modes, can confer the resonator an exceptionally high quality factor Q, leading to high energy density, narrow resonant-wavelength lines and a lengthy cavity ringdown. These attractive characteristics make these miniaturized optical resonators especially suited as laser cavities and resonant filters, but also as very sensitive sensors. First, a brief analysis is presented of the characteristics of microspherical resonators, of their fabrication methods, and of the light coupling techniques. Then, we attempt to overview some of the recent advances in the development of microspherical biosensors, underlining a number of important applications in the biomedical field.
CREATIVITY, INTELLIGENCE AND GIFTEDNESS: A STUDY WITH PRIMARY SCHOOL CHILDREN

The present work investigated three important constructs in the field of psychology: creativity, intelligence and giftedness. The major objective was to clarify some aspects about each one of these three constructs, as well as some possible correlations between them. Of special interest were: (1) the relationship between creativity and intelligence - particularly the validity of the threshold theory; (2) the development of these constructs within average and above-average intelligent children and throughout grade levels; and (3) the comparison between the development of intelligence and creativity in above-average intelligent primary school children that participated in a special program for children classified as “gifted”, called Entdeckertag (ET), against an age-class- and-IQ matched control group. The ET is a pilot program which was implemented in 2004 by the Ministry for Education, Science, Youth and Culture of the state of Rhineland-Palatinate, Germany. The central goals of this program are the early recognition of gifted children and intervention, based on the areas of German language, general science and mathematics, and also to foster the development of a child’s creativity, social ability, and more. Five hypotheses were proposed and analyzed, and reported separately within five chapters. To analyze these hypotheses, a sample of 217 children recruited from first to fourth grade, and between the ages of six and ten years, was tested for intelligence and creativity. Children performed three tests: Standard Progressive Matrices (SPM) for the assessment of classical intelligence, Test of Creative Thinking – Drawing Production (TCT-DP) for the measurement of classical creativity, and Creative Reasoning Task (CRT) for the evaluation of convergent and divergent thinking, both in open problem spaces. Participants were divided according to two general cohorts: Intervention group (N = 43), composed of children participating in the Entdeckertag program, and a non-intervention group (N = 174), composed of children from the regular primary school. For the testing of the hypotheses, children were placed into more specific groups according to the particular hypothesis that was being tested. It could be concluded that creativity and intelligence were not significantly related and the threshold theory was not confirmed. Additionally, intelligence accounted for less than 1% of the variance within creativity; moreover, scores on intelligence were unable to predict later creativity scores. The development of classical intelligence and classical creativity throughout grade levels also presented a different pattern; intelligence grew increasingly and continually, whereas creativity stagnated after the third grade. Finally, the ET program proved to be beneficial for classical intelligence after two years of attendance, but no effect was found for creativity. Overall, results indicate that organizations and institutions such as schools should not look solely to intelligence performance, especially when aiming to identify and foster gifted or creative individuals.
Attacks on Web browsers with HTML5

The new Web standard HTML5 makes a webpage provide dynamic functions to users without additional plug-ins such as ActiveX, Flash and Silverlight. Most attacks on web browsers uses such plug-ins. HTML5 provides the abilities that can be substituted to plug-ins, so hackers focus their attacks with HTML5. This paper surveys 16 attacks with HTML5 presented and shows their effects. Additionally, three new attacks with HTML5 are also discussed.
Iterative EM Based LDPC CDMA Receiver under Time Varying Interference

The authors of this paper proposed an iterative expectation-maximization (EM) channel estimation based on a low-density parity-check (LDPC) code-division multiple access receiver in their previous work. The receiver algorithm could efficiently estimate both channel coefficients and noise power spectral density (PSD). However, their previous work considered only a single user channel environment, so they tested only for a constant noise PSD. In the current paper, we extend the single user to a more realistic multiuser environment for the testing of a time-varying interference plus noise PSD estimation. Also our proposed adaptive PSD estimation scheme will be compared with a conventional system in which a constant PSD is assumed. It will show that the proposed iterative EM scheme can provide accurate interference plus noise PSD estimates to the LDPC decoder.
Effects of Stereoscopic Presentation, Image Motion, and Screen Size on Subjective and Objective Corroborative Measures of Presence

Recently, we reported that group subjective measures of presence as well as observers' postural responses are sensitive to increasing the realism of a display with motion content, by the addition of stereoscopic information, using a 20-inch stereoscopic screen with an effective horizontal field of view of 28 deg. (Freeman, Avons, Meddis, Pearson, & IJsselsteijn, 2000). The experiment presented here employed a large projection display with a 50 deg. horizontal field of view showing a rally car traversing a curved track at speed. The independent variables included image motion and stereoscopic presentation as within-subjects factors and screen size as a between-subjects factor. Dependent variables included subjective measures of presence, vection, involvement, and sickness, as well as observers' lateral postural responses, which served as a candidate objective corroborative measure of presence. Results demonstrated a noisy yet positive effect of stereoscopic presentation on the lateral postural responses. Post-test subjective ratings revealed a significant effect of stereoscopic presentation on the subjective judgments of presence, but not on those of vection, involvement, or sickness. Image motion had a large and significant effect on the subjective judgments of presence, vection, and involvement. The effect of image motion was considerably larger than that of stereoscopic viewing. By comparing results between experiments, a large effect of screen size on subjective presence ratings could be demonstrated, but only for the video stimulus that contained motion. The postural response measure did not differentiate between screen sizes, thus limiting its utility as an objective corroborative measure of presence, although further research is required to be able to be more firm in our conclusion regarding this issue.
Enhancing Data Flow Testing of Classes through Design by Contract

Design by contract (DbC) is a methodology to construct quality software. DbC associates the contract specification (pre and postconditions of methods of class and class invariant) with the design of a class. In this paper, we combine dataflow testing and Design by Contract to develop a testing technique called "Data flow testing using Contract". In this technique a class flow graph is generated from the contract specification of the class and then conventional data flow testing is applied to find the test cases. The advantage of using contract specification is that: it is executable and hence a method in a test case is only executed if its precondition and class invariant are satisfied. If they are not satisfied then it leads to an infeasible sequence. Also, if after executing a method its postcondition is not satisfied then it leads to implementation error in the method. We also compare the testing of a DbC class with a conventional class and find that the number of du pairs is reduced in a DbC class because some of the conditions in conventional class become the part of the precondition in a DbC class.
Experimental Results on Multiple Pattern Matching Algorithms for Biological Sequences

With the remarkable increase in the number of DNA and proteins sequences, it is very important to study the performance of multiple pattern matching algorithms when querying sequence patterns in biological sequence databases. In this paper, we present a performance study of the running time of well known multiple pattern matching algorithms on widely used biological sequence databases containing the building blocks of nucleotides (in the case of nucleic acid sequence databases) and amino acids (in the case of protein sequence
Obstacle classification through acoustic echolocation

A visually impaired person comes across objects with different attributes in his navigational path, and all of those objects can't be considered as obstacles. One person's obstacle could become a landmark for another. Therefore, getting some insights about the features of the obstacles that come across will provide a significant impact on improving the navigational process of the visually impaired individuals. In this study, a wearable obstacle classification system which extends the currently available obstacle detection approaches using sonar echolocation has been developed. In order to increase the detection range and to improve user-friendliness, an innovative approach based on integration of electronics onto textile environment has been studied. Optimum architecture to embed electronic equipment's and sensors to the textile has been realized. Finally, a smart garment prototype including ultrasonic sensors, coin vibration motors, power supplies and a micro controller has been developed.
Change in intramuscular and intermuscular neural adaptation after resistance training in trained college athletes

The purpose of this study was to investigate the intramuscular and intermuscular neural adaptation after resistance training in trained college athletes. The results indicated that, progressive resistance training significantly (P<0.01) increased MVC and integrated electromyography (IEMG) of MG muscle. There were, however, a significant decrease (P<0.01) in integrated electromyography (IEMG) of TA muscle. It was concluded that, with strength improvement in trained limb agonist muscle activation increased whereas antagonist muscle coactivation decreased. Consequently intermuscular neural adaptation (decrease of muscle coactivation) and intramuscular neural adaptation include increase of motor unit recruitment, firing rate and firing duration, does occur in trained athletes when a new training stimulus is implemented. [Mansoure Shahraki. Change in intramuscular and intermuscular neural adaptation after resistance training in trained college athletes. Journal of American Science 2011;7(8):688-693]. (ISSN: 1545-1003). http://www.americanscience. org.
Position tracking using adaptive control for bilateral teleoperators with time-delays

This paper presents two versions of adaptive controllers for nonlinear bilateral teleoperators, each providing asymptotic convergence of velocity and position errors to zero, independent of constant time-delays. Moreover, the proposed schemes do not rely on the use of the scattering transformation. The paper also proves that the teleoperator is Input-to-State Stable from human operator and environment inputs to some synchronization signals. Simulations show the effectiveness of the proposed controllers.
Caching and capacity allocation game in self-managed content provider networks

In this paper we study the problem of distributed cache management in a self-managed network. We consider a set of autonomously operating edge routers, providing the wide-area connectivity for a local network. Each local network is equipped with a caching server, capable of storing copies of data objects. Objects can be either accessed from a special publisher server, or from any other cache that contains a copy. It is assumed that all data transmissions are carried trough links of limited bandwidth capacity. The problem consists of jointly deciding on the contents of all cache servers and setting appropriate transmission rates, so as the value of network utility is maximized. Due to the distributed nature of the considered system, we employ a game-theoretic analysis, and present how to compute efficiently solutions which constitute pure Nash equilibria. We introduce the concept of conditional equilibrium, which corresponds to a strategy of a game with restricted players' strategy space. Finally, an experimental study is presented, which consists of an application of the presented solution algorithm to existing wide-area network (Pionier optical network).
View Planning For Cloud-Based Active Object Recognition

One of the central problems in computer vision and robotics is to recognize objects in a scene. State-of-the-art algorithms for object recognition are extremely data intensive. Cloud technologies hold the promise to make such algorithms available to robots with limited computation capabilities. However, collecting and transferring large amounts of data with such robots remains a challenge. In this work, we investigate the possibility of enabling cloud-based object recognition by carefully planning the robot’s viewpoints. While view planning techniques for object recognition exist, such techniques are too costly to be executed by robots with limited capabilities. This is unfortunate because these are the robots which would benefit most from cloud-based techniques. In this paper, we present evidence for the existence of universal viewpoints: a small number of viewpoints which guarantee accurate object recognition regardless of the object pose. Our experiments with real data show that such viewpoints exist for common objects. Hence, view-planning for object recognition can be performed in an open-loop fashion without the need for running costly algorithms on small robots.
Supervised principal component analysis for gene set enrichment of microarray data with continuous or survival outcomes

MOTIVATION Gene set analysis allows formal testing of subtle but coordinated changes in a group of genes, such as those defined by Gene Ontology (GO) or KEGG Pathway databases. We propose a new method for gene set analysis that is based on principal component analysis (PCA) of genes expression values in the gene set. PCA is an effective method for reducing high dimensionality and capture variations in gene expression values. However, one limitation with PCA is that the latent variable identified by the first PC may be unrelated to outcome. RESULTS In the proposed supervised PCA (SPCA) model for gene set analysis, the PCs are estimated from a selected subset of genes that are associated with outcome. As outcome information is used in the gene selection step, this method is supervised, thus called the Supervised PCA model. Because of the gene selection step, test statistic in SPCA model can no longer be approximated well using t-distribution. We propose a two-component mixture distribution based on Gumbel exteme value distributions to account for the gene selection step. We show the proposed method compares favorably to currently available gene set analysis methods using simulated and real microarray data. SOFTWARE The R code for the analysis used in this article are available upon request, we are currently working on implementing the proposed method in an R package.
Kinematic Transformations for Remotely-Actuated Planar Continuum Robots

In this work, we consider a class of robotic manipulators generally termed “hyper-redundant”. Spec<fically, we seek to examine some 0.f the kinematic properties of ‘%ontinuum” hyper-redundant robots. Unlike the case with rigidlink’robots, there is no commonly accepted formula ,for describing continuum robot kinematics. Although these manipulators are continuously flexible, they are actuated with a ,finite number of actuators. In this paper, we discuss two possible options ,for mapping desired infinitedimensional robot shapes to the ,finite-dimensional actuator space, using ‘hatural” and “wavelet ” decompositions. We compare and contrast these kinematic descriptions, illustrating how the wavelet decomposition can simplify the inverse kinematics for redundant planar continuum robots.
Notice of Violation of IEEE Publication PrinciplesA Constraint-Based Text-to-Scene Conversion System

This paper describes a system called Text2Scene for automatically converting text into 3D scenes. Text2Scene relies on a large database of 3D models to depict entities and actions. Every 3D module can have associated information, such as spatial tags, color and functional properties for depiction process. Text2Scene takes the implicit and conflicting constraints into account to generate reasonable scenes.
Optimizing the efficacy of transcranial direct current stimulation on cortical neuroplasticity based on a neurovascular coupling model

Transcranial direct current stimulation (tDCS) induces polarity-specific enduring alterations of cortical excitability, and activity. Cortical excitability can be monitored in a limited set of cortical areas in the human brain, to explore the effects of tDCS. For exploring tDCS-induced cortical activity alterations, only indirect measures, such as electroencephalography (EEG), and functional magnetic resonance tomography (fMRI) are available. As presented in the following dissertation, we aimed to explore the relationship between systematically varying stimulation intensities of tDCS with the respective physiological and functional effects in the human motor cortex, with the goal of obtaining stimulation parameters which yield greater and longer lasting neuroplastic effects. We devised a multi-modal experimental approach and set out to answer three questions. First, we investigated the relevance of intrinsic inter-individual variability in the response to tDCS, where baseline sensitivity to TMS was analyzed as a viable and useful predictor. In the second part of the study, we aimed to explore the association between tDCS-induced excitability and activity alterations, obtained by TMS and fMRI, to identify the physiological association between these parameters, as well as which technique may be optimally suited to monitor tDCS-induced cortical activity alterations for the model of the human motor cortex. The current intensity dose-reponse relationship of tDCS was systematically investigated with both techniques within a randomized, repeated-measures sham-controlled design. In the last part, we aimed to functionally validate our findings by combining tDCS with a bimanual motor learning task, and to see whether our findings could also be extended to also helping the aging population (65+ years). Obtaining an optimized model, which is more effective than currently available, is important because tDCS is increasingly applied to alter cognitive processes in healthy humans and clinical symptoms in neurodegenerative diseases.