Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-time monocular people tracking by sequential Monte-Carlo filtering

We present a solution to the people tracking problem using a monocular vision approach from a bird's eye view and Sequential Monte-Carlo Filtering. Each tracked human is represented by an individual Particle Filter using spheroids as a three-dimensional approximation to the shape of the upstanding human body. We use the bearings-only model as the state update function for the particles. Our measurement likelihood function to estimate the probability of each particle is imitating the image formation process. This involves also partial occlusion by dynamic movements from other humans within neighbored areas. Due to algorithmic optimization the system is real-time capable and therefore not only limited to surveillance or human motion analysis. It could rather be used for Human-Computer-Interaction (HCI) and indoor location. To demonstrate this capabilities we evaluated the accuracy of the system and show the robustness in different levels of difficulty.
The abortion referendum of 2018 and a timeline of abortion politics in Ireland to date

ABSTRACT In 2018, Ireland voted to remove its constitutional ban on abortion in almost all circumstances. This overturned a previous decision by referendum to institute such a ban in 1983. The scale of the change in Irish society that this vote has displayed is significant, representing an even further shift towards a more socially liberal outlook than that seen in the marriage referendum of 2015. As with the previous referendum, this referendum is also of interest to scholars of deliberative processes, given the key role played by Ireland’s Citizens’ Assembly in progressing the debate and shaping both the referendum question and the draft legislation that was to follow. This report provides the historical context of this referendum with regard to Ireland’s previous abortion regime and antecedent referendums on this topic, as well as discussing the deliberative processes and the dynamics of the referendum campaign itself.
Biometrics Based Identification : A Survey By Nishant Khattar

The goal of this paper " Biometrics Based Identification: A Survey " , is to present a brief overview of how our body uniquely identifies us and how this fact can be used to provide us with the much needed security in this hi-tech world that we live in. Keeping this aim in mind, the paper takes a look at the different techniques for identification/verification of an individual based on what he is and not what he knows or possesses. As a road map through the content to follow, we shall take a look at the four most widely used modalities, namely: Fingerprints, Face recognition, Iris recognition and hand geometry. Apart from comparing the accuracy of these four modalities, the paper also compares, in the case of each modality, the various algorithms used to implement that modality based system. In some cases, I have also compared the output results when two or more algorithms, for a particular modality, are combined with the outcome of a more accurate system. The paper commences with the introduction which answers the question of why security systems based on biometrics have become an integral part of out world, following which is given the important traits for something to be considered as a biometric and how there broad classification of parameters to measure the practicality of such a biometric based system. For the first biometric based system, we take a look at the sys tem based on fingerprints, which are also the most widely used and accepted biometric. I shall be describing a minutiae based fingerprint identification algorithm which makes use of an adaptive bounding box technique in order to alleviate the discrepancy c aused due to non linear deformations which may arise during the fingerprint acquisition process and comparing it to a previously used feature extraction algorithm based on ridge flow orientation. For the face as a biometric, the paper concentrates on addressing of the question " Does the combination of different Face Experts help in reduction of the Total error during classification? " I have considered five different face experts for the same: three based on Linear Discriminant Analysis and two on the Probability Matching Algorithm. Results are shown for the combination of two, three and four face experts from which, it can be clearly concluded that as the number of face experts combined increases, so does the accuracy. The Iris based identification/verification system …
Observations of pulsars at 9 millimetres

Aims. The behaviour of the pulsar spectrum at high radio frequencies can provide decisive information about the nature of the radio emission mechanism. Methods. We report recent observations of a selected sample of pulsars at λ = 9 mm (32 GHz) with the 100-m Effelsberg radio telescope. Results. Three pulsars, PSR B0144+59, PSR B0823+26, and PSR B2022+50, were detected for the first time at this frequency. We confirm the earlier flux density measurements for a sample of six pulsars, and we are able to place upper flux density limits for another 12 pulsars. We find that all pulsar spectra have a simple form that can be described using only three parameters, one of which is the lifetime of short nano-pulses in the emission region. The study of the transition region from coherent to incoherent emission needs further and more sensitive observations at even higher radio frequencies.
Word Ordering with Phrase-Based Grammars

We describe an approach to word ordering using modelling techniques from statistical machine translation. The system incorporates a phrase-based model of string generation that aims to take unordered bags of words and produce fluent, grammatical sentences. We describe the generation grammars and introduce parsing procedures that address the computational complexity of generation under permutation of phrases. Against the best previous results reported on this task, obtained using syntax driven models, we report huge quality improvements, with BLEU score gains of 20+ which we confirm with human fluency judgements. Our system incorporates dependency language models, large n-gram language models, and minimum Bayes risk decoding.
Early initiation of enteral nutrition improves outcomes in burn disease.

BACKGROUND Burned patients have increased level of mortality, possibly due to late introduction of enteral feeding. The aim of this study was to compare the benefits and safety of very early enteral nutrition introduction compared to the normal diet among burns patients in an intensive care unit. PARTICIPANTS AND METHODS Participants consisted of 101 patients, aged 20-76 years (mean age 48 years), 49 men and 52 women, with burns that covered more than 20% of the body. The intervention group consisted of 52 subjects fed via introduced nasojejunal probe that started within four hours after admission to the hospital. The control group consisted of fifty patients fed in standard manner per os (three standard hospital meals) immediately after the first wound dressing. RESULTS The average decline BMI in control group was 2.27±0.56 kg/m2, while the average reduction in BMI in the intervention group was 1.77±0.38 kg/m2 (p<0.001). The largest drop of albumin concentration in the control group was 28.5%, whereas in the intervention group was 23.8%. (p<0.001). The greatest decrease of transferrin concentration in the control group was 31.1%, while the average reduction in the intervention group was 18.3%. (p<0.001). C-reactive protein values were statistically higher in control group (p<0.001). Intervention group had lower rate of complications and infection rates. CONCLUSION Enteral nutrition in burned patients should begin within few hours of burn onset. Such approach leads to better outcomes, reduces complications, and improves nutritional profile.
Statistical Timing-Yield Optimization via Latch Substitution ∗

The continuous miniaturization of semiconductor devices imposes serious threats to design robustness against process variations and environmental fluctuations. Modern circuit designs may suffer from uncertain delays, not predictable in the design phase or even after manufacturing. This paper presents an optimization technique to make sequential circuits robust against delay variations and thus maximize timing yield. By trading larger flip-flops for smaller latches, the proposed approach can be used as a post-synthesis or post-layout optimization tool, allowing accurate timing information to be available. Experimental results show an average of 26% timing yield improvement, and suggest that our method is promising for high speed designs tolerating clock variations.
Structured text retrieval by means of affordances and genre

This paper offers a proposal for some preliminary research on the retrieval of structured text, such as extensible mark-up language (XML). We believe that capturing the way in which a reader perceives the meaning of documents, especially genres of text, may have implications for information retrieval (IR) and in particular, for cognitive IR and relevance. Previous research on 'shallow' features of structured text has shown that categorization by form is possible. Gibson's theory of 'affordances' and genre offer the reader the meaning and purpose - through structure - of a text, before the reader has even begun to read it, and should therefore provide a good basis for the 'deep' skimming and categorization of texts. We believe that Gibson's 'affordances' will aid the user to locate, examine and utilize shallow or deep features of genres and retrieve relevant output. Our proposal puts forward two hypotheses, with a list of research questions to test them, and culminates in experiments involving the studies of human categorization behaviour when viewing the structures of emails and web documents. Finally, we will examine the effectiveness of adding structural layout cues to a Yahoo discussion forum (currently only a bag-of-words), which is rich in structure, but only searchable through a Boolean search engine.
Bacillus cereus-induced food-borne outbreaks in France, 2007 to 2014: epidemiology and genetic characterisation

The aim of this study was to identify and characterise Bacillus cereus from a unique national collection of 564 strains associated with 140 strong-evidence food-borne outbreaks (FBOs) occurring in France during 2007 to 2014. Starchy food and vegetables were the most frequent food vehicles identified; 747 of 911 human cases occurred in institutional catering contexts. Incubation period was significantly shorter for emetic strains compared with diarrhoeal strains A sub-panel of 149 strains strictly associated to 74 FBOs and selected on Coliphage M13-PCR pattern, was studied for detection of the genes encoding cereulide, diarrhoeic toxins (Nhe, Hbl, CytK1 and CytK2) and haemolysin (HlyII), as well as panC phylogenetic classification. This clustered the strains into 12 genetic signatures (GSs) highlighting the virulence potential of each strain. GS1 (nhe genes only) and GS2 (nhe, hbl and cytK2), were the most prevalent GS and may have a large impact on human health as they were present in 28% and 31% of FBOs, respectively. Our study provides a convenient molecular scheme for characterisation of B. cereus strains responsible for FBOs in order to improve the monitoring and investigation of B. cereus-induced FBOs, assess emerging clusters and diversity of strains.
ITA: Innocuous Topology Awareness for Unstructured P2P Networks

One of the most appealing characteristics of unstructured P2P overlays is their enhanced self-* properties, which results from their loose, random structure. In addition, most of the algorithms which make searching in unstructured P2P systems scalable, such as dynamic querying and 1-hop replication, rely on the random nature of the overlay to function efficiently. The underlying communications network (i.e., the Internet), however, is not as randomly constructed. This leads to a mismatch between the distance of two peers on the overlay and the hosts they reside on at the IP layer, which in turn leads to its misuse. The crux of the problem arises from the fact that any effort to provide a better match between the overlay and the IP layer will inevitably lead to a reduction in the random structure of the P2P overlay, with many adverse results. With this in mind, we propose ITA, an algorithm which creates a random overlay of randomly connected neighborhoods providing topology awareness to P2P systems, while at the same time has no negative effect on the self-* properties or the operation of the other P2P algorithms. Using extensive simulations, both at the IP router level and autonomous system level, we show that ITA reduces communication latencies by as much as 50 percent. Furthermore, it not only reduces by 20 percent the number of IP network messages which is critical for ISPs carrying the burden of transporting P2P traffic, but also distributes the traffic load more evenly on the routers of the IP network layer.
Program Optimization of Array-Intensive SPEC2k Benchmarks on Multithreaded GPU Using CUDA and Brook+

Graphic Processing Unit (GPU), with many light-weight data-parallel cores, can provide substantial parallel computing power to accelerate several general purpose applications. Both the AMD and NVIDIA corps provide their specific high performance GPUs and software platforms. As the floating-point computing capacity increases continually, the problem of ``memory-wall'' becomes more serious, especially for array-intensive applications. In this paper, we optimize and implement two SPEC2k benchmarks mgrid and swim on multithreaded GPU using CUDA and Brook+. In order to reduce the pressure on off-chip memory, we make use of data locality in multi-level memory hierarchies and hide long memory access latency via double-buffers. To balance inter-thread parallelism and intra-thread locality, we further tune thread granularity for each kernel and empirically study the best equilibrium point for this problem. Flow control instruction can significantly impact the effective instruction throughput. Oriented to this problem, we introduce a diverge elimination technology to convert condition expression into computing operation. Through all the optimizations, we gain the speedup of 10x-34x to the CPU implementation on the GPUs of AMD and NVIDIA respectively. Finally, we summarize and compares the GPUs from AMD and NVIDIA in hardware and software.
High-resolution analysis of the human retina miRNome reveals isomiR variations and novel microRNAs

MicroRNAs play a fundamental role in retinal development and function. To characterise the miRNome of the human retina, we carried out deep sequencing analysis on sixteen individuals. We established the catalogue of retina-expressed miRNAs, determined their relative abundance and found that a small number of miRNAs accounts for almost 90% of the retina miRNome. We discovered more than 3000 miRNA variants (isomiRs), encompassing a wide range of sequence variations, which include seed modifications that are predicted to have an impact on miRNA action. We demonstrated that a seed-modifying isomiR of the retina-enriched miR-124-3p was endowed with different targeting properties with respect to the corresponding canonical form. Moreover, we identified 51 putative novel, retina-specific miRNAs and experimentally validated the expression for nine of them. Finally, a parallel analysis of the human Retinal Pigment Epithelium (RPE)/choroid, two tissues that are known to be crucial for retina homeostasis, yielded notably distinct miRNA enrichment patterns compared to the retina. The generated data are accessible through an ad hoc database. This study is the first to reveal the complexity of the human retina miRNome at nucleotide resolution and constitutes a unique resource to assess the contribution of miRNAs to the pathophysiology of the human retina.
Influence of a physical education teacher’s perceived age on high school pupils’ perceptions of effectiveness and learning

Few studies have focused on the issues older physical education (PE) teachers encounter which may limit their effectiveness. The purpose of this study was to examine the influence of a PE teacher’s apparent age on high school pupils’ learning and perceptions of the teacher. Participants were 114 ninth, tenth, eleventh, and twelfth grade pupils. They were randomly assigned to watch one of two virtually identical filmed swimming lessons taught by the same teacher. In the young-appearance lesson, the teacher taught as his normal and relatively youthful self. In the middle-aged lesson (MAL), his appearance had been aged by a theatrical makeup artist. Following the viewing of their assigned lesson, pupils completed an examination over lesson content and a questionnaire asking them about their perceptions of the teacher. Inferential statistical tests indicated that the pupils who watched the MAL perceived the teacher more favorably. Performance on the content examination was similar for pupils who watched either film. These findings provided support for a psychological/developmental explanation of how and why pupils respond to and learn from PE teachers of different ages.
An improved low-resolution face tracker system using gradient logarithm field feature space and bi-cubic interpolation

Face tracking has become an active area of research it is very much helpful in applications such as video surveillance. The factors like illumination discrepancy, face pose variations, occlusions, and background clutter makes face tracking a challenging issue. Even though, a number of related work have been proposed to assist face tracking in unrestrained videos, the existing approaches may not be productive in video surveillance applications. This is mainly because of the fact that low-resolution face comprises of lesser informative data, and main transformations in illumination on the face make the tracking unproductive. In order to overcome this issue, this paper proposes a novel algorithm for illumination normalization and it is combined with the GLF for face tracking for improving the overall performance of the tracker system. Experimental results show that the proposed GLF-based tracker works well under significant clarification changes and outperforms many existing tracking algorithms.
Dynamical balance of a humanoid robot grasping an environment

This paper shows some preliminary results on the dynamical balance of a humanoid robot grasping an environment. By grasping an environment, it becomes easier for the robot to keep balance. By using the linear programming, a necessary condition for keeping balance of the robot is formulated taking the grasping force into consideration. We show that the occasion exists where the stronger the hand of a humanoid robot grasps the handrail, the larger the region of ZMP for keeping balance becomes. We further show an experimental result of a humanoid robot climbing up a big gap increasing the stability by grasping a handrail.
Vadara: Predictive Elasticity for Cloud Applications

Elasticity is a key feature in cloud computing, and perhaps what distinguishes it from other computing paradigms. Despite the advantages of elasticity, realizing its full potential is hard due to multiple challenges stemming from the need to estimate workload demand. A desirable solution would require predicting system workload and allocating resources a priori, i.e., A predictive approach. Instead, what is mainly available are reactive solutions, requiring difficult parameter tuning. Since each Cloud Provider (CP) has its own implementation idiosyncrasies, it's impossible for developers to: (i) learn only about one platform and re-use that knowledge in others, (ii) migrate developed elasticity solutions between different CPs, and (iii) to develop reusable predictive elasticity rules or algorithms. This paper makes three contributions to provide an effective elasticity environment. First, Vadara, a totally generic elasticity framework, that transparently connects and abstracts several CPs API behaviour, and enables the use of pluggable CP-agnostic elasticity strategies. Second, it presents a predictive workload forecasting approach, which ensembles several individual forecasting methods, and introduces a padding system based on the most recent prediction errors for both under- and over-provisioning. Finally, results show (1) Vadara's successful connection to well-known CPs, (2) the improvements made regarding under- and over-provisioning due to our padding system, and (3) the effectiveness of our ensemble forecasting technique.
Modified Mel Filter Bank to Compute MFCC of Subsampled Speech

Mel Frequency Cepstral Coefficients (MFCCs) are the most popularly used speech features in most speech and speaker recognition applications. In this work, we propose a modified Mel filter bank to extract MFCCs from subsampled speech. We also propose a stronger metric which effectively captures the correlation between MFCCs of original speech and MFCC of resampled speech. It is found that the proposed method of filter bank construction performs distinguishably well and gives recognition performance on resampled speech close to recognition accuracies on original speech.
DYNAMICS OF REVERSE SACCADES OF READING TEXTS AND ITS CONNECTION WITH THE PECULIARITIES OF EYE MOVEMENT

The study of the work of the human visual apparatus is of interest both for the purpose of an in-depth understanding of the vision mechanisms and for the possibility of penetrating the cognitive links of the work of the vision canal with the process of the brain. The dynamics of eye movement in the perception of graphic information and, in particular, when reading different texts makes it possible for investigating the individual physiological parameters of the human visual apparatus. In the work, specific features of the eye movement on reverse saccades related to reading the text and rapid translation of the view from one line to another were studied. This process is not connected with the cognitive work of the brain and, apparently, is determined only by the physiological features of the visual apparatus.
Enforcing code security in database web applications using libraries and object models

Libraries are commonly though as toolboxes offering reusable components and algorithms. In this paper, we show that a properly designed library can also be used to enforce security, and hence to help in the creation of robust and secure applications. As an illustration, we choose database web applications, because they are the kind of applications that suffers from the highest amount of vulnerabilities. SQL injection or Cross Site Scripting are common examples. We present how a library can be designed in such a way to completely mitigate these vulnerabilities. We also show how a properly designed library does not only allow a programmer to write secure code, but can also make vulnerable code impossible to write. We validate our theories through the presentation of a concrete Java library named "Stones" that follows and applies our ideas. Finally, our approach is compared with related work and various practical results are stated.
A landmark-based algorithm for automatic pattern recognition and abnormality detection

We study a class of mathematical and statistical algorithms with the aim of establishing a computer-based framework for fast and reliable automatic abnormality detection on landmark represented image templates. Under this framework, we apply a landmark-based algorithm for finding a group average as an estimator that is said to best represent the common features of the group in study. This algorithm extracts information of momentum at each landmark through the process of template matching. If ever converges, the proposed algorithm produces a local coordinate system for each member of the observing group, in terms of the residual momentum. We use a Bayesian approach on the collected residual momentum representations for making inference. For illustration, we apply this framework to a small database of brain images for detecting structure abnormality. The brain structure changes identified by our framework are highly consistent with studies in the literature.