Miracle-dz/UniFAR-FTUs huggingface dataset:
Gesture Recognition Based on Fuzzy C-Means Clustering Algorithm

Robots of the future should communicate with humans in a natural way. We are especially interested in visionbased gesture interaction. This paper describes a hand gesture recognition system which will be used in a mobile robot. A Fuzzy C-Means (FCM) clustering method is used to classify hand gestures. Testing results reveal a recognition accuracy of 85.83%. We also discuss some general conclusions and future work about our hand gesture recognition system.
Biofilm formation by Streptococcus agalactiae: influence of environmental conditions and implicated virulence factors

Streptococcus agalactiae (Group B Streptococcus, GBS) is an important human pathogen that colonizes the urogenital and/or the lower gastro-intestinal tract of up to 40% of healthy women of reproductive age and is a leading cause of sepsis and meningitis in the neonates. GBS can also infect the elderly and immuno-compromised adults, and is responsible for mastitis in bovines. Like other Gram-positive bacteria, GBS can form biofilm-like three-dimensional structures that could enhance its ability to colonize and persist in the host. Biofilm formation by GBS has been investigated in vitro and appears tightly controlled by environmental conditions. Several adhesins have been shown to play a role in the formation of GBS biofilm-like structures, among which are the protein components of pili protruding outside the bacterial surface. Remarkably, antibodies directed against pilus proteins can prevent the formation of biofilms. The implications of biofilm formation in the context of GBS asymptomatic colonization and dissemination to cause invasive disease remain to be investigated in detail.
Mean-Field Analysis of Ultra-Dense CSMA Networks

Distributed algorithms such as CSMA provide a popular mechanism for sharing the transmission medium among competing users in large-scale wireless networks. Conventional models for CSMA that are amenable for analysis assume that users always have packets to transmit. In contrast, when users do not compete for medium access when their buffers are empty, a complex interaction arises between the activity states and the buffer contents. We develop a meanfield approach to investigate this dynamic interaction for networks with many users. We identify a time-scale separation between the evolution of the activity states and the buffer contents, and obtain a deterministic dynamical system describing the network dynamics on a macroscopic scale. The fixed point of the dynamical system yields highly accurate approximations for the stationary distribution of the buffer contents and packet delay, even when the number of users is relatively moderate.
FI-RED: AQM mechanism for improving fairness among TCP connections in tandem networks

In this paper, we focus on a tandem network, and design an AQM mechanism called FI-RED (fairness improvement for RED) for improving the fairness among heterogeneous TCP connections. In FI-RED, ECN (explicit congestion notification) mechanism is used for differentiating the packet marking probability of RED according to the CE (congestion experienced) bit of arriving packets. Namely, FI-RED suppresses congestion indication to TCP connections with a large number of hops (i.e., connections with a high probability that the CE bit is marked). With such a simple modification to the original RED, a TCP connection with a large number of hops suffers almost the same packet marking probability as one with a small number of hops. Therefore, it is expected that FI-RED improves fairness among TCP connections with different numbers of hops; i.e., bias against the number of hops. We analyze the steady state behavior of FI-RED and perform simulation experiments in several network configurations. We quantitatively show that the fairness among TCP connections is significantly improved compared with RED
A Novel Cytokine Pathway Suppresses Glial Cell Melanogenesis after Injury to Adult Nerve

The neural crest gives rise to numerous cell types, including Schwann cells, neurons, and melanocytes. The extent to which adult neural crest-derived cells retain plasticity has not been tested previously. We report that cutting adult mouse sciatic nerve induces pigmentation around nerve fascicles, among muscle bundles, and in the hypodermis. Pigmented cells are derived from adult nerve, because pigmentation occurs even when nerve fragments are grafted into tyrosinase null albino mice. Pigmentation defects are pervasive in patients with neurofibromatosis type 1 (NF1). Mice hemizygous for Nf1 mutations show enhanced pigmentation after nerve lesion and occasionally form pigmented and unpigmented tumors. TheNf1 nerve and the Nf1 host environment both contribute to enhanced pigmentation. Grafted purifiedNf1 mutant glial cells [S100+–p75NGFR+–GFAP+–EGFR+or S100+–p75NGFR+–GFAP+–EGFR−] mimic nerve-derived pigmentation. The NF1 protein, neurofibromin, is a Ras-GAP that acts downstream of a few defined receptor tyrosine kinases, including [β-common (βc)] the shared common receptor for granulocyte and monocyte colony-stimulating factor, interleukin-3 (IL3), and IL5. Cytokines in the environment have the potential to suppress pigmentation as shown by nerve injury experiments in null mice; when is βc absent orNf1 is mutant, melanogenesis is increased. Thus, the adult nerve glial cell phenotype is maintained after nerve injury by response to cytokines, through neurofibromin.
Evaluation of Moving Object Tracking Techniques for Video Surveillance Applications

This paper presents a comparison between the performance of Kalman filter and particle filter in the single object tracking system. The performance parameters of interest are the processing time of the algorithm and the accuracy of the tracking system. The algorithms are implemented using MATLAB and tested using two video sequences, and the results are compared and discussed.
DEVE LOPING A SPEECH PRODUCTION MATHEMATICAL MODEL IN TERMS OF THE Z-TRANSFORM FOR SPEECH RECOGNITON IMPLEMENTATION IN THE COMPUTER

The use of speech recognition systems allow messages to interact with the computer in natural it is possible to solve Voice control of the computing process(such as speech input commands WINDOWS), Voice control of various technical systems, Automatic entry of textual information in the personal computer to fill in the various documents databases. The use of speech recognition providers Increasing management efficiency through the use of verbal interaction channel (average specialist computer systems from the keyboard can enter only 10-20 words / min ,and the voice can convey 100-200 words /min) A mathematical model of speech production can be described in terms of Z-transform in order to implement it on a computer in the form of the relationship.
Analyzing and comparing the Montgomery multiplication algorithms for their power consumption

This study analyses and compares the most popular Montgomery multiplication algorithms for their power dissipation on FPGA devices. Among various architectures proposed for Montgomery multiplication, we pick the parallel, sequential and systolic variants as the most revealing ones for our experimental needs. The synthesis results indicate that the sequential setting with a single cell gives the most efficient employment of the algorithm for dynamic power dissipation. However, if the energy is considered the parallel architecture is the most appropriate choice. Our analyses provides a fair comparison of power consumption of Montgomery multiplication algorithms on FPGAs giving hints to the engineers realizing the core of the most popular methods used in public-key cryptographic systems such as RSA, Diffle-Hellman, ECC and others.
A Review into eHealth Services and Therapies: Potential for Virtual Therapeutic Communities - Supporting People with Severe Personality Disorder

eHealth has expanded hugely over the last fifteen years and continues to evolve, providing greater benefits for patients, health care professionals and providers alike. The technologies that support these systems have become increasingly more sophisticated and have progressed significantly from standard databases, used for patient records, to highly advanced Virtual Reality (VR) systems for the treatment of complex mental health illnesses. The scope of this paper is to initially explore e-Health, particularly in relation to technologies supporting the treatment and management of wellbeing in mental health. It then provides a case study of how technology in e-Health can lend itself to an application that could support and maintain the wellbeing of people with a severe mental illness. The case study uses Borderline Personality Disorder as an example, but could be applicable in many other areas, including depression, anxiety, addiction and PTSD. This type of application demonstrates how e-Health can empower the individuals using it but also potentially reducing the impact upon health care providers and services.
AFFINE HECKE ALGEBRAS AND POSITIVITY OF LLT AND MACDONALD POLYNOMIALS

We introduce a “hybrid” basis {CTw} of the Hecke algebra of an arbitrary symmetrizable Kac-Moody algebra, depending on the choice of a standard parabolic subgroup WJ of the Weyl group W . We prove that the operator of right multiplication by any Kazhdan-Lusztig basis element has positive matrix coefficients with respect to the hybrid basis. When WJ = W or WJ = {1}, this reduces, respectively, to a theorem of Springer and Lusztig for the Kazhdan-Lusztig basis, or of Dyer and Lehrer for the standard basis. Our theorem also implies an improvement of the positivity theorem of Kashiwara and Tanisaki for Deodhar’s parabolic Kazhdan-Lusztig polynomials, by removing the restriction that WJ be finite. In the affine An case, we obtain as a consequence of our theorem the full positivity theorem for the q-symmetric functions introduced by Lascoux, Leclerc and Thibon, known as LLT polynomials. Special cases of LLT positivity had been proven earlier by Leclerc and Thibon, using the positivity theorem for Deodhar’s polynomials. Our result, combined with the combinatorial formula of Haglund, Haiman and Loehr for Macdonald polynomials, yields a new proof of the positivity theorem for Macdonald polynomials. Our methods also provide a definition and positivity theorem for LLT polynomials of other types. We also give a formula for the expansion of LLT polynomials in terms of generalized Hall-Littlewood polynomials. In certain cases our formula equates a single generalized HallLittlewood polynomial with an LLT polynomial. In particular, we prove a conjecture of Shimozono and Weyman equating generalized Hall-Littlewood polynomials indexed by rectangular Young diagrams with LLT polynomials for GLn.
Optical coherence tomography imaging: Automated binarization of choroid for stromal-luminal analysis

Structural changes in the choroid, interspersed between the retina and sclera, could indicate various vision impairments. So far, choroidal thickness and volume measured from optical coherence tomography (OCT) scans of the rear part of the eye have found clinical applications. However, such gross measurements do not provide vasculature-specific information crucial in managing various chorioretinal diseases. To fill this gap, we propose an automated method of ratiometric quantification of choroidal vascular (luminal) and interstitial (stromal) regions. Specifically, our method removes idiosyncratic artefacts of OCT imaging including speckle noise, exponential dynamic range compression, and depth-dependent attenuation in a targetted manner using median filtering and exponential enhancement. The proposed method assumed significance as manual estimation of the desired ratio is infeasible in view of the inherently fine structure of many choroidal vessels. Further, our technique demonstrated vast superiority over existing protocol based on the generic ImageJ software in terms of quality. Moreover, unlike the existing protocol which is interactive, our method could be applied to high-throuput and volumetric analysis.
On the interaction of inter-relationship constraints

MDE and software evolution call for model-level design support, that includes reasoning capabilities such as query answering, verification and validation, static analysis and model transformation. Automation of all activities requires well-defined semantics for models. This is particularly important for the class diagram model, which is central in UML. However, since UML specification is verbal and imprecise, the exact meaning of many class diagram constructs and their interaction is still obscure. There are major problems with the inter-association constraints subsets, union, redefinition, association specialization, association-class specialization and XOR. Although their standard semantics is ambiguous and their interaction unclear, the UML meta-model intensively uses these constraints. Moreover, some of these interactions have been declared in the UML meta-model as variation points. The paper discusses possible semantics of inter-association constraints (subsets, union, redefinition and association-class specialization), analyzes their interaction, and suggests coherent semantics that minimizes contradictions with the metamodel (association specialization and XOR are left out, due to space limitations). The paper also introduces rules that enforce model correctness. This paper is the first to provide an inclusive analysis of all inter-association constraints.
Efcient Empty Space Skipping for Per-Pixel Displacement Mapping

Displacement mapping is widely recognized as a very useful technique for adding visual detail to low-resolution geometry using simple texture maps. Major investigations have been made to apply displacement maps in real-time rendering. Recently, different approaches using ray-casting on programmable graphics processing units (GPUs) have been proposed. This paper introduces a new technique for speeding up per-pixel displacement mapping for high frequency displacement maps. The technique only needs additional 2D-textures to store minimum and maximum-lter ed versions of the displacement map specifying a safety zone above or below the displacement surface. These zones are used for empty space skipping to nd valid ray section containing all ray surface intersections. Results show, that for relatively high samplerates, which are needed for high quality rendering or displacement maps with high frequencies, the new algorithm increases the rendering frame-rate up to 100%.
A Case for Ordinal Peer-evaluation in MOOCs

MOOCs have been highly successful due to the ease of disseminating information: anyone with an Internet connection can watch videos of the lectures and download study material. However, they still lag far behind conventional classrooms in one critical aspect—feedback to and evaluation of the students—due to severe mismatches in the number of students enrolled and the number of experts available. One means of performing evaluation and feedback is peer evaluation wherein the answers submitted by a student are anonymized and provided to a set of other students to evaluate. As per current peer evaluation techniques, these peer evaluators assign cardinal scores to the given solutions. In this paper, we posit an alternative approach to peer evaluation based on pairwise comparisons. We argue that such an ordinal approach is signiﬁcantly more robust to the lack of expertise of the evaluators, as compared to the conventional cardinal approaches.
Special Section: The Skillful Body as a Concernful System of Possible Actions

For Merleau-Ponty, consciousness in skillful coping is a matter of prereflective `I can' and not explicit `I think that. ' The body unifies many domain-specific capacities. There exists a direct link between the perceived possibilities for action in the situation (`affordances') and the organism's capacities. From Merleau-Ponty's descriptions it is clear that in a flow of skillful actions, the leading `I can' may change from moment to moment without explicit deliberation. How these transitions occur, however, is less clear. Given that Merleau-Ponty suggested that a better understanding of the self-organization of brain and behavior is important, I will re-read his descriptions of skillful coping in the light of recent ideas on neurodynamics. Affective processes play a crucial role in evaluating the motivational significance of objects and contribute to the individual's prereflective responsiveness to relevant affordances.
Emotion Classification by Machine Learning Algorithm using Physiological Signals

Recently, emotion studies have suggested emotion classification using machine learining algorithms based on physiological features. We classified three emotion (boredom, pain, and surprise) by 4 machine learning algorithms (LDA, CART, SOM, and SVM). 200 college students participated in this experiment. EDA, ECG, PPG, and SKT as physiological signals were acquired for 1 minute before emotional state as baseline and for 1-1.5 minutes during emotional state. 23 features were extracted from physiological signals. For emotion classification, the difference values of each feature substracting baseline from the emotional state were used for machine learning algorithms. The result showed that an accuracy of emotion classification by SVM was highest. This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals and it can be applied on human-computer interaction system for emotion detection.
Vocabulary Usage and Intelligibility in Learner Language

In verbal communication, the primary purpose of which is to convey and understand messages, speakers need to make intelligible utterances. The intelligibility of an utterance depends on the sentence structure, discourse, and the vocabulary usage. In foreign-language utterances, “errors” can reduce the intelligibility. The correct and appropriate use of vocabulary is essential for successful message conveyance especially in foreign language communication where people often have difficulty in constructing sentences precisely, and where they rely more on vocabulary because of their lower grammatical competence. Vocabulary skill development has become one of the high-priority issues in recent foreign language education. We analysed on the correlation between vocabulary usage and the intelligibility of utterances made by Japanese learners of English by investigating to what extent lexical errors interfere with the intelligibility of utterances. We did this based on the error-coded learner corpus in which each sentence is labelled with its levels of intelligibility. More precisely, we calculated lexical semantic relatedness between an erroneous word and a correct word, and then observed how the relatedness values are distributed across different levels of intelligibility and different proficiency levels as well. The remainder of this paper is as follows. In Section 2, we discuss how intelligibility is positioned in foreign language learning and teaching. Section 3 explains the corpus data used in the experiment, focusing especially on data annotation of intelligibility as evaluated by humans and the analysis of the relationship between intelligibility and learner errors. Section 4 describes our further investigation into the correlation between lexical errors and intelligibility conducted by focusing on lexical semantic relatedness between an erroneous word and a correct word. In Section 5, we draw some general conclusions.
A New Field-Data Based EAF Model for Power Quality Studies

A new electric arc furnace (EAF)-specific model based on field measurements of instantaneous furnace voltages and currents has been proposed. This model presents the dynamic behavior of the EAF system including all parts, i.e. the EAF transformer, the secondary circuit, the electrode movements and the arc. It consists of a cascade connected variable-resistance and -inductance combination to represent the time variation at the fundamental frequency, and a current source in parallel with it to inject the harmonics and interharmonics of the EAF current. The model takes into account several typical tap-to-tap periods of the specific EAF operation. This model is especially advantageous for power quality (PQ) analysis, and development of FACTS solutions for PQ problem mitigation of a given busbar supplying single- or multi-EAF installations. The validity of the proposed model has been verified by comparing EMTDC/PSCAD simulations of the model with the field measurements. The results obtained have shown quite satisfactory correlation between the proposed model and the actual EAF operation.
A computational investigation into the effect of infarction on clinical human electrophysiology biomarkers

The electrocardiogram (ECG) is often used to diagnose myocardial infarction, but sensitivity and specificity are low. Here we present a computational framework for solving the bidomain equations over an image-based human geometry and simulating the 12 lead ECG. First, we demonstrate this approach by evaluating a population of eight models with varying distributions of local action potential duration, and report that only the model with apicobasal and inter-ventricular heterogeneities produces concordant T waves. Second, we simulate the effects of an old anterior infarct, which causes a reduction in T wave amplitude and width. Our methodology can contribute to the understanding of ECG alterations under challenging conditions for clinical diagnosis.
A Novel Fasting Blood Test for Insulin Resistance and Prediabetes

Background: Insulin resistance (IR) can precede the dysglycemic states of prediabetes and type 2 diabetes mellitus (T2DM) by a number of years and is an early marker of risk for metabolic and cardiovascular disease. There is an unmet need for a simple method to measure IR that can be used for routine screening, prospective study, risk assessment, and therapeutic monitoring. We have reported several metabolites whose fasting plasma levels correlated with insulin sensitivity. These metabolites were used in the development of a novel test for IR and prediabetes. Methods: Data from the Relationship between Insulin Sensitivity and Cardiovascular Disease Study were used in an iterative process of algorithm development to define the best combination of metabolites for predicting the M value derived from the hyperinsulinemic euglycemic clamp, the gold standard measure of IR. Subjects were divided into a training set and a test set for algorithm development and validation. The resulting calculated M score, MQ, was utilized to predict IR and the risk of progressing from normal glucose tolerance to impaired glucose tolerance (IGT) over a 3 year period. Results: MQ correlated with actual M values, with an r value of 0.66. In addition, the test detects IR and predicts 3 year IGT progression with areas under the curve of 0.79 and 0.70, respectively, outperforming other simple measures such as fasting insulin, fasting glucose, homeostatic model assessment of IR, or body mass index. Conclusions: The result, Quantose™, is a simple test for IR based on a single fasting blood sample and may have value as an early indicator of risk for the development of prediabetes and T2DM.
Testing the Dinosaur Hypothesis under different GP algorithms

The Dinosaur Hypothesis states that the behaviour of a market never settles down and that the population of predictors continually co-evolves with this market. This observation had been made and tested under artificial datasets. Recently, we formalized this hypothesis and also tested it under 10 empirical datasets. The tests were based on a GP system. However, it could be argued that results are dependent on the GP algorithm. In this paper, we test the Dinosaur Hypothesis under two different GP algorithms, in order to prove that the previous results are rigorous and are not sensitive to the choice of GP. We thus test again the hypothesis under the same 10 empirical datasets. Results are consistent among all three algorithms and thus suggest that market behavior can actually repeat itself, and have a number of ‘typical states’, where past rules may become useful again.