Miracle-dz/UniFAR-FTUs huggingface dataset:
A Direct-Conversion Receiver for Wide-Band GNSS Signals

Paul Blunt is an RF systems engineer in the Navigation and Positioning team of QinetiQ. He gained his Ph.D. from the University of Surrey in 2007 for the study of advanced receiver architectures for modernized GPS and Galileo signals. His research interests are acquisition, tracking, multipath and interference mitigation techniques for GNSS receivers. He received a MEng in Electrical Engineering from the University of Liverpool in 2003
Effects of noise and relative overlap on image mosaicing using SURF features

Performance of image mosaicing depends on overlap between the images to be joined and the percentage of noise present. An algorithm is used for joining images based on image matching by comparing the descriptors for different images. This paper is concerned with the analysis of effect of variations in noise and degree of relative overlap on the algorithm and obtaining their limits. Speeded Up Robust Features (SURF) have been used for key point detection. Percentage overlap between the images to be joined is varied to find out the minimum value required for mosaicing. Further, relative overlap is kept constant and noise is increasingly added to the input images to find out the maximum amount of noise the algorithm can sustain. The aforementioned experiments were performed over a set of images. Ultimately, a range for maximum permissible noise and minimum overlap required is defined for acceptable panorama generation.
Social Networks : Status and Trends

The rapid proliferation of Online Social Network (OSN) sites has made a profound impact on the WWW, which tends to reshape its structure, design, and utility. Industry experts believe that OSNs create a potentially transformational change in consumer behavior and will bring a far-reaching impact on traditional industries of content, media, and communications. This chapter starts out by presenting the current status of OSNs through a taxonomy which delineates the spectrum of attributes that relate to these systems. It also presents an overall reference system architecture that aims at capturing the building blocks of prominent OSNs. Additionally, it provides a state-of-the-art survey of popular OSN systems, examining their architectural designs and business models. Finally, the chapter explores the future trends of OSN systems, presents significant research challenges and discusses their societal and business impact.
Access as a Motivational Device: Implications for Human Resource Management

This paper analyzes the employment relationship on the basis of the notion of access. We argue that the degree of access provided by a job is an incentive to activate the employee’s self-actualization needs. We investigate the effect of access on the workers’ performance through an agency model and provide a number of propositions with practical implications for personnel policies. Our results are consistent with the intuition emerged from the real business practice as well as with many of the arguments on the substitutive role between monetary and non-monetary incentives frequently reported in the literature.
Early Prediction of Students Performance using Machine Learning Techniques

Anal Acharya, Department of Computer Science, St Xavier’s College, Kolkata, India. Devadatta Sinha, Department of Computer Science and Engineering, University of Calcutta, Kolkata, India. ABSTRACT In recent years Educational Data Mining (EDM) has emerged as a new field of research due to the development of several statistical approaches to explore data in educational context. One such application of EDM is early prediction of student results. This is necessary in higher education for identifying the “weak” students so that some form of remediation may be organized for them. In this paper a set of attributes are first defined for a group of students majoring in Computer Science in some undergraduate colleges in Kolkata. Since the numbers of attributes are reasonably high, feature selection algorithms are applied on the data set to reduce the number of features. Five classes of Machine Learning Algorithm (MLA) are then applied on this data set and it was found that the best results were obtained with the decision tree class of algorithms. It was also found that the prediction results obtained with this model are comparable with other previously developed models.
SEMI-AUTOMATIC 3D RECONSTRUCTION OF PIECEWISE PLANAR BUILDING MODELS FROM SINGLE IMAGE

This paper presents a novel algorithm that enables the semi-automatic reconstruction of man-made structures (e.g. buildings) into piecewise planar 3D models from a single image, allowing the models to be readily used for data acquisition in 3D GIS or in other virtual or augmented reality applications. Contrary to traditional labor intensive but accurate Single View Reconstruction (SVR) solutions that are based purely on geometric constraints, and recent fully automatic albeit low-accuracy SVR algorithms that are based on statistical inference, the presented method achieves a compromise between speed and accuracy, leading to less user input and acceptable visual effects compared to prior approaches. Most of the user input required in the presented approach is a line drawing that represents an outline of the building to be reconstructed. Using this input, the developed method takes advantage of a newly proposed Vanishing Point (VP) detection algorithm that can simultaneously estimate multiple VPs in an image. With those VPs, the normal direction of planes which are projected onto the image plane as polygons in the line drawing can be automatically calculated. Following this step, a linear system similar to traditional SVR solutions can be used to achieve 3D reconstruction. Experiments that demonstrate the efficacy and visual effects of the developed method are also described.
Optimizing Algorithms for Phrase Recognition

The paper presents a simple algorithm to cull short phrases of interest spoken in a long recorded speech. Listening to a long and boring recording of a suspect who is being wiretapped may irk intelligence investigator if it does not contain any speech segment of interest. It would be much useful if first a preliminary test is run to see if the recorded speech does contain phrases of interest which could help convict a suspect. If so the entire recording can then be reexamined. Vowels spoken in an utterance can be reasonably identified by locating the vowels’ fist two formants i.e., F1 and F2 onto vowel loops similar to the ones drawn by Peterson and Barney for English vowels’ sounds [1]. Using Pratt or a similar type of software can determine the formants of vowels. Two algorithms were designed to map the vowels’ formants spoken in an utterance onto the vowel loops and identify which vowel sounds they represented [2]. The algorithm-1 used the calculated value of F1 and determined in which vowel-loop F2 lied, and algorithm-2 used the calculated value of F2 and determined in which vowelloop F1 lied. In some cases the algoirithm-1 did a better job than algorithm-2 in terms of computational time while in other cases the reverse was true. This paper essentially extends the idea of mapping (F1,F2) onto the vowel loops by another algorithm, called algorithm-3, which is faster than the previous two. The algorithm-3 requires conversion of vowel loops in a particular format to act as our data bank; let us call it conversion table because it will convert any point F1,F2 that is covered by the vowel loops into a corresponding vowel symbol. The calculated values of F1 and F2 of vowels are discretized in suitable steps, and a corresponding vowel symbol is determined from the conversion table. The vowel symbol at the intersection of F1 and F2 is selected.
Histogram of distances for local surface description

3D object recognition is proven superior compared to its 2D counterpart with numerous implementations, making it a current research topic. Local based proposals specifically, although being quite accurate, they limit their performance on the stability of their local reference frame or axis (LRF/A) on which the descriptors are defined. Additionally, extra processing time is demanded to estimate the LRF for each local patch. We propose a 3D descriptor which overrides the necessity of a LRF/A reducing dramatically processing time needed. In addition robustness to high levels of noise and non-uniform subsampling is achieved. Our approach, namely Histogram of Distances is based on multiple L2-norm metrics of local patches providing a simple and fast to compute descriptor suitable for time-critical applications. Evaluation on both high and low quality popular point clouds showed its promising performance.
Probabilistic Model of Pianists' Arm Touch Movements

Measurement of pianists' arm movement provides a signal, which is composed of controlled movements and noise. The noise is composed of uncontrolled movement generated by the interaction of the arm with the piano action and mea- surement error. We propose a probabilistic model for arm touch movements, which allows to estimate the amount of noise in a joint. This estimation helps to interpret the move- ment signal, which is of interest for augmented piano and piano pedagogy applications. from the elbow joint exclusively. Before the touch move- ment begins, the thumb, which will press the key, is located, say, 1cm above the key. The player uses controlled move- ment in the elbow joint to move the thumb towards the key. When the thumb comes in touch with the key, the right fore- arm starts to passively rotate clockwise. The forearm ro- tation signal indicates movement although the user has not used controlled forearm rotation movement. This effect oc- curs before the hammer strikes the string, i.e., during touch execution. We propose a probabilistic model of arm movement, which allows to estimate the amount of uncontrolled move- ment in a joint. A function that estimates mean and standard deviation of the uncontrolled movement in a joint is learned from a large data-set of touch movement samples. The amount of uncontrolled movement in a joint is estimated as a function of the measured movements in the other joints. In the above example, the mean and variance of uncontrolled forearm rotation movement changes when the player uses elbow movement. The probabilistic model can be used in the following way to determine if the player has used controlled movement in a given joint to execute a touch:
Blind separation of tissues in multi-modal MRI using Sparse Component Analysis

We pose the problem of tissue classification in MRI as a Blind Source Separation (BSS) problem and solve it by means of Sparse Component Analysis (SCA). Assuming that most MR images can be sparsely represented, we consider their optimal sparse representation. Sparse components define a physically-meaningful feature space for classification. We demonstrate our approach on simulated and real multi-contrast MRI data. The proposed framework is general in that it is applicable to other modalities of medical imaging as well, whenever the linear mixing model is applicable.
Adam Kilgarriff

A long time ago now (maybe 1988? ), Gerald (Gazdar) and I supervised Adam’s DPhil at the University of Sussex. Adam was my age, give or take a year, having come to academia a little late, and was my first doctoral student. Adam’s topic was polysemy, and I’m not really sure that much supervision was actually required, though I recall fun exchanges trying to model the subtleties of word meaning using symbolic knowledge representation techniques—an experience that was clearly enough to convince Adam later that this was a bad idea. In fact, Adam’s thesis title itself was Polysemy. Much as we encourage short thesis titles, pulling off the one-word title is a tall order, requiring a unique combination of focus and coverage, breadth and depth, and, most of all, authority. Adam completely nailed it, at least from the perspective of the pre-empirical Computational Linguistics of the early 1990s. Three years later, after a spell working for dictionary publishers, Adam joined me as a research fellow, now at the University of Brighton. I had a project to explore the automatic enrichment of lexical databases to support the latest trends in language analysis, and, in particular, task-specific lexical resources. I was really pleased and excited to recruit Adam—he had lost none of his intellectual independence, a quality I particularly valued. Within a few weeks he came to me with his own plan for the research—a “detour,” as he put it, from the original workplan. I still have the e-mail, dated 6 April 1995, in which he proposed that, instead of chasing a prescriptive notion of a single lexical resource that needed to be customized to each domain, we should let the domain determine the lexicon, providing lexicographic tools to explore words, and particularly word senses, that were significant for that domain. In that e-mail, Computational Lexicography at Brighton was born. Over the next eight years or so, Computational Lexicography became a key part of our group’s success, increasingly under Adam’s direct leadership. The key project, WASPS, developed the WASPbench—the direct precursor of the Sketch Engine, recruiting David (Tugwell) to the team. In addition, Adam was one of the founding organizers of SENSEVAL, an initiative to bring international teams of researchers together to work in friendly competition on a pre-determined word sense disambiguation task (and which has now transformed into SEMEVAL). Together we secured funding to support the first two rounds of SENSEVAL; each round required the preparation of standardized data sets, guided by Adam’s highly tuned intuitions about lexical data preparation and management. And we engaged somewhat in the European funding merry-go-round, most fondly in the CONCEDE project, working on dictionaries for Central European languages with amazing teams from the MULTEXT-EAST consortium, and with Georgian and German colleagues in the GREG project.
Psychological Reports, 1985, 56, 759-765. @ Psychological Reports 1985 MOOD STATE-DEPENDENT RETRIEVAL: A FAILURE TO REPLICATE1

Summmy. -The present study attempted a modified replication of Bower, el al.'s 1978 finding of affective state-dependent retrieval. It is argued that Bower's finding confounds two theoretically discinct effects, pure affective state-dependent retrieval and an interference effect. Using the Velten mood induction and an interference list learning task over 24- to 48-hr. intervals, it was impossible to replicate Bower's finding. Considering the difficulry of reproducing affective state-dependent retrieval in many laboratories, one must exercise caution in drawing conclusions about its generalizability. The present study focused on a result reported by Bower, Monteiro, and Gilligan (1978) concerning affective state-dependent retrieval. These investigators found the effect when using an interference task, but not, however, when using free-recall with short (i.e., 30 min.) or long (i.e., 24 hr.) retention intervals. This interesting finding requires further replication and clarification. Bower, et al. predicted that hypnotically induced happy and sad mood states will exhibit "selectivity of learning. " The results supported their hypotheses: Recall is best when mood state at learning matches mood state at recall and differs from mood state at learning an interfering list; recall is worst when mood state at learning differs from mood state at recall and mood state at learning an interfering list matches mood state at retrieval. What Bower, et al.
Cosmic Variance in the Transparency of the Intergalactic Medium after Reionization

Following the completion of cosmic reionization, the mean free path of ionizing photons was set by a population of Lyman limit absorbers. As the mean free path steadily grew, the intensity of the ionizing background also grew, thus lowering the residual neutral fraction of hydrogen in ionization equilibrium throughout the diffuse intergalactic medium (IGM). Lyα photons provide a sensitive probe for tracing the distribution of this residual hydrogen at the end of reionization. Here we calculate the cosmic variance among different lines of sight in the distribution of the mean Lyα optical depths. We find fractional variations in the effective postreionization optical depth that are of order unity on a scale of ~100 comoving Mpc, in agreement with observations toward high-redshift quasars. Significant contributions to these variations are provided by the cosmic variance in the density contrast on the scale of the mean free path for ionizing photons and by fluctuations in the ionizing background induced by delayed or enhanced structure formation. Cosmic variance results in a highly asymmetric distribution of transmission through the IGM, with fractional fluctuations in Lyα transmission that are larger than in Lyβ transmission.
AttachedShock: facilitating moving targets acquisition on augmented reality devices using goal-crossing actions

The prevalence of augmented reality devices in our daily lives offers increasing opportunities for users to navigate the real world. However, as users move, on-screen targets move unpredictably, and eventually disappear from the screen in mobile navigation scenarios. The changing target movement pattern creates difficulty for users in selecting the targets on time before targets escape from the screen. This study proposes a novel target selecting technique, AttachedShock, for easing target selection tasks on augmented reality devices by crossing a naturally expanding wave pattern that is attached to targets. We evaluated the effectiveness of the proposed technique by conducting comparative studies on measuring the performance of four techniques under various mobile navigation scenarios. The results indicate that the proposed technique assists users in selecting moving targets to improve the error rate substantially, by a minimum of 61.75%, and incurs acceptable distractions to users, compared to other techniques.
Visual Sensitivity Analysis in Real Estate Prediction System

Visual Sensitivity analysis has proven its feasibility in data exploration and exposing relationships between the variables in the model. However, it lacks the ability of user direct interaction of outputs. To overcome this drawback for this interdisciplinary field, in this paper we introduce a novel approach of integrating an interactive visualization and a sensitivity analysis method into a visual interactive sensitivity analysis environment. This environment is applied to a property prediction system. The interactive visualization will facilitate user interaction with the sensitivity analysis method to adjust the outputs of the analysis procedure. The results are presented graphically to the non-expert users without the need to a prior knowledge of the sensitivity analysis method being used. Additionally, all the results that the non-expert is presented with, are all compiled together and presented to an expert user for further analysis by means of multidimensional scatter plots.
Attacks on Emerging Architectures

New architectures require careful examination of security properties in order to assess and contain new threats. In light of this, emerging technologies, such as web APIs, medical devices, and applications on mobile phones, are a new security landscape that has recurring security problems. We develop new techniques to analyze these applications for security vulnerabilities, utilizing techniques including: dynamic symbolic execution, binary analysis and reverse engineering, and wide scale application comparison and classification. We develop Kudzu, a system for symbolic execution of JavaScript, and use it to evaluate a wide variety of JavaScript applications in order to find client-side validation vulnerabilities. Secondly, we use this system to evaluate the security, in practice, of new HTML5 primitives. Then, we conduct the first publicly available reverse engineering and security evaluation of a ubiquitous medical device, namely an Automated External Defibrillator. We discovered a wide array of vulnerabilities and we confirm our findings using COTS software components. We offer considerations to help guide future development of medical devices. Finally, we developed Juxtapp, a scalable, efficient system for detecting code reuse in Android Applications. Using Juxtapp we detected instances of piracy, malware and buggy code reuse among Android applications. We demonstrate that these techniques are useful at discovering and/or preventing attacks, in their respective application domains.
Injecting Abstract Interpretations into Linear Cost Models

We present a semantics based framework for analysing the quantitative behaviour of programs with regard to resource usage. We start from an operational semantics equipped with costs. The dioid structure of the set of costs allows for defining the quantitative semantics as a linear operator. We then present an abstraction technique inspired from abstract interpretation in order to effectively compute global cost information from the program. Abstraction has to take two distinct notions of order into account: the order on costs and the order on states. We show that our abstraction technique provides a correct approximation of the concrete cost computations.
Form-From-Motion: MEG Evidence for Time Course and Processing Sequence

The neural mechanisms and role of attention in the processing of visual form defined by luminance or motion cues were studied using magnetoencephalography. Subjects viewed bilateral stimuli composed of moving random dots and were instructed to covertly attend to either left or right hemifield stimuli in order to detect designated target stimuli that required a response. To generate form-from-motion (FFMo) stimuli, a subset of the dots could begin to move coherently to create the appearance of a simple form (e.g., square). In other blocks, to generate form-from-luminance (FFLu) stimuli that served as a control, a gray stimulus was presented superimposed on the randomly moving dots. Neuromagnetic responses were observed to both the FFLu and FFMo stimuli and localized to multiple visual cortical stages of analysis. Early activity in low-level visual cortical areas (striate/early extrastriate) did not differ for FFLu versus FFMo stimuli, nor as a function of spatial attention. Longer latency responses elicited by the FFLu stimuli were localized to the ventral-lateral occipital cortex (LO) and the inferior temporal cortex (IT). The FFMo stimuli also generated activity in the LO and IT, but only after first eliciting activity in the lateral occipital cortical region corresponding to MT/V5, resulting in a 5060 msec delay in activity. All of these late responses (MT/V5, LO, and IT) were significantly modulated by spatial attention, being greatly attenuated for ignored FFLu and FFMo stimuli. These findings argue that processing of form in IT that is defined by motion requires a serial processing of information, first in the motion analysis pathway from V1 to MT/V5 and thereafter via the form analysis stream in the ventral visual pathway to IT.