Miracle-dz/UniFAR-FTUs huggingface dataset:
Wavelet and Hilbert transform-based Brain Computer Interface

Brain Computer Interface (BCI) is a technology that developed over the last three decades has provided a novel and promising alternative method for interacting with the environment. BCI is a system which translates a subject's intentions into a control signal for a device, e.g., a computer application, a wheelchair or a neuroprosthesis. Electroencephalogram-based BCI has become a hot spot in the research of neural engineering, rehabilitation, and brain science. The artifacts are disturbance that can occur during the signal acquisition and that can alter the analysis of the signals themselves. Removing artifacts produced in Electroencephalogram (EEG) data by muscle activity, eye blinks and electrical noise is a common and important problem in EEG analysis. In this research, for artifact rejection, EEG data are filtered to the frequency range between 8 and 32 Hz with a butterworth band-pass filter. Finally two different structures of neural network and a support vector machine used to classify features that are extracted by Hilbert and Wavelet transform.
Large margin based discriminative sparse coding for image classification

Sparse has attractive performance in codebook generation. This paper proposes a Large Margin based discriminative method which utilize the discriminative information. Specifically, the codes corresponding to similar local features of images from different classes are pushed further apart, while the codes corresponding to similar local features of images from the same class are pulled closer together. We formulate the above two issues to generate sparse code of each feature point, and adopt multi-scale spatial max pooling approach to obtain feature representation of each image. Then, a linear SPM kernel is employed in the one-vs-all SVM training for image classification. Experiments on 15 Scenes and Caltech 256 dataset show that our method is effective.
DELAYED URIC ACID ACCUMULATION IN PLASMA PROVIDES ADDITIONAL ANTI-OXIDANT PROTECTION AGAINST IRON-TRIGGERED OXIDATIVE STRESS AFTER A WINGATE TEST

Reactive oxygen species are produced during anaerobic exercise mostly by Fe ions released into plasma and endothelial/muscle xanthine oxidase activation that generates uric acid (UA) as the endpoint metabolite. Paradoxically, UA is considered a major antioxidant by virtue of being able to chelate pro-oxidative iron ions. This work aimed to evaluate the relationship between UA and plasma markers of oxidative stress following the exhaustive Wingate test. Plasma samples of 17 male undergraduate students were collected before, 5 and 60 min after maximal anaerobic effort for the measurement of total iron, haem iron, UA, ferric-reducing antioxidant activity in plasma (FRAP), and malondialdehyde (MDA, biomarker of lipoperoxidation). Iron and FRAP showed similar kinetics in plasma, demonstrating an adequate pro-/antioxidant balance immediately after exercise and during the recovery period (5–60 min). Slight variations of haem iron concentrations did not support a relevant contribution of rhabdomyolysis or haemolysis for iron overload following exercise. UA concentration did not vary immediately after exercise but rather increased 29% during the recovery period. Unaltered MDA levels were concomitantly measured. We propose that delayed UA accumulation in plasma is an auxiliary antioxidant response to post-exercise (iron-mediated) oxidative stress, and the high correlation between total UA and FRAP in plasma (R-Square = 0.636; p = 0.00582) supports this hypothesis.
Mobile Phones as Ubiquitous Social and Environmental Geo-Sensors

Mobile and sensor-rich devices such as today’s smartphones are increasingly leveraged as ubiquitous mobile geo-sensors that are able to sense their immediate surroundings on site in high spatial and temporal detail. Using those devices, the activity or mobility behavior of mobile phone users is being “sensed” since they leave behind digital traces of their whereabouts when using the mobile network – voluntarily or not. Additionally, people themselves can act as human sensors by providing subjective, geo-referenced “observations” in the form of individual perceptions of, e.g., the weather, thereby complementing calibrated measurements from technical geo-sensor networks. Together with other user-generated and increasingly geo-referenced data and information from a variety of Web 2.0 and social media platforms, this results in vast volumes of geo-data that digitally reflect the dynamics of human behavior (e.g., mobility in urban spaces) and environmental phenomena (e.g., the weather). In this chapter we provide an overview of recent literature, influencing scholars, and future research directions in the context of using mobile phones for social and environmental geo-sensing in order to provide additional insights into the space-time behavior of the underlying geographic phenomena.
Acessibilidade por diálogos de mediação: desenvolvimento e avaliação de um assistente de navegação para a web

A acessibilidade na Web e um dos grandes desafios de pesquisa na area das Ciencias da Computacao. Existem muitas iniciativas que visam a melhorar os sistemas, a fim de que usuarios com deficiencias e outras necessidades especiais tenham o pleno acesso as informacoes e servicos disponiveis na internet. Uma delas e o sistema apresentado neste trabalho, o WNH – Web Navigation Helper, um assistente de navegacao na Web, criado para auxiliar usuarios com necessidades especiais a realizarem atividades na internet, por meio de dialogos de mediacao, previamente construidos, com um editor especializado, por pessoas interessadas em ajudar. Mostramos, no texto, a descricao das ferramentas desenvolvidas (editor e assistente) e a analise de tres estudos exploratorios realizados, antes e depois do desenvolvimento do sistema. Apresentamos ainda como os experimentos revelaram aspectos sociais e culturais da sociedade brasileira relevantes para o design do WNH e como eles alteraram a nossa visao original do sistema. Foi preciso repensar a ferramenta, a fim de que se considerasse a variavel cultural no seu desenvolvimento e avaliacao.
The prevention of overweight and obesity in children and adolescents: a review of interventions and programmes

Overweight and obesity are serious, large‐scale, global, public health concerns requiring population‐based childhood overweight and obesity prevention. The overall objective of this review is to identify aspects of successful childhood overweight prevention programmes. This objective will be met by assessing existing interventions quantitatively as well as qualitatively, identifying efficacy, effectiveness and implementation, and evaluating potential adverse effects of previous studies. This review was limited to school‐based studies with a quantitative evaluation using anthropometric outcomes and that intervene on diet or activity‐related behaviours. Quantitative and qualitative approaches are used to identify factors related to successful interventions as well as adverse consequences. Sixty‐eight per cent of the interventions, or 17 of the 25, were ‘effective’ based on a statistically significant reduction in body mass index (BMI) or skin‐folds for the intervention group. Four interventions were effective by BMI as well as skin‐fold measures. Of these, two targeted reductions in television viewing. The remaining two studies targeted direct physical activity intervention through the physical education programme combined with nutrition education. Of the interventions reported here, one was effective in reducing childhood overweight but was also associated with an increase in underweight prevalence. Few other studies reported outcomes for underweight. The majority of overweight/obesity prevention programmes included in this review were effective. Physical education in schools and reducing television viewing are two examples of interventions that have been successful. Because few studies report on underweight prevalence, this review recommends giving more attention to preventing adverse outcomes by reporting the intervention impact on the frequency distribution for both BMI and adiposity measures.
On the Secrecy of Interference-Limited Networks under Composite Fading Channels

This letter deals with the secrecy capacity of the radio channel in interference-limited regime. We assume that interferers are uniformly scattered over the network area according to a Point Poisson Process and the channel model consists of path-loss, log-normal shadowing and Nakagami-m fading. Both the probability of non-zero secrecy capacity and the secrecy outage probability are then derived in closed-form expressions using tools of stochastic geometry and higher-order statistics. Our numerical results show how the secrecy metrics are affected by the disposition of the desired receiver, the eavesdropper and the legitimate transmitter.
Innovation Strategy in Slovak Forest Contractor Firms—A SWOT Analysis

The aim of the study is to determine the innovation strategy of contractor firms in the Slovak forestry service sector in the area of further innovation activities development. The strategy identification was based on the analysis of the strengths, weaknesses, opportunities and threats in this sector. The results indicate that weaknesses of contractor firms exceed their strengths and, considering the degree and importance of their impact, opportunities exceed identified threats. Based on these findings revealing the relations in the area of innovation activities of forestry service contractors, the “Strategy of Partnership” was suggested as the most suitable type of strategy. It can be concluded that such a form of grouping cooperation brings many benefits to contractors in the form of information availability, guidance, training, and management of conflicts, risks and uncertainty, which are associated with the innovation process.
A novel blind watermarking scheme for depth-image-based rendering 3D images

The content protection for image-based 3D data is getting more importance with the advance of low cost 3D display devices. The depth-image-based rendering (DIBR) 3D image is one of the image-based 3D data which consists of the center image and the depth image generated by the content provider. The left-eye image and the right-eye image are rendered from the center image and the depth image at the content consumer side. The blind watermarking for DIBR 3D image is rarely studied in the literature. In this paper, a novel blind multiple watermarking scheme is proposed to deal with the content protection problem of DIBR 3D images. Besides the usual requirement of mutual orthogonality among reference patterns for multiple watermark embedding, we found that proper embedding order plays an even more important role in watermarking the DIBR 3D images. Experimental results show that the proposed scheme is robust against the JPEG compression and noise adding attacks. More interestingly, it is found that the proposed watermarking can also tolerate large range variations of the depth image during rendering.
Rigid Body Simulation with Local Fracturing Effects

Focusing on the real-time and interactive ability features in the Virtual Reality application, we propose a fracture pattern based on local fracture mechanism. Taking advantage of the experience analysis or the offline computation verified fracture characteristic, we abstract fracture patterns with physical reality and then apply it in pattern matching. The geometry model is constructed by octree allowing users to select local fracture region interactively. Finally, the experimental results show that the pre-fracture works well for the rigid body fracture, and the local fracture enables the interactivity and the visual reliability.
Gendered and Sexualized Bullying and Cyber Bullying

Drawing on semistructured interviews with Canadian Grade 4 to 12 students, this article uses a feminist lens to explore gendered and sexualized bullying and cyberbullying among children and youth. Our findings indicate that while boys’ roles and behaviors were frequently made invisible, girls were typically spotlighted, blamed, and criticized. Girls’ experiences were often minimized and normalized by peers and linked to gender norms and stereotypes that were largely invisible to participants. The central theme of invisibility emerged, which encompassed and interconnected the three subthemes: (a) gendered stereotyping, (b) spotlighting girls, and (c) gender surveillance and policing. Gendered and sexualized bullying and cyberbullying were found to be part of a socialization process wherein girls come to expect gender-based aggression, violence, and inequality in their lives. This article makes explicit how bullying and cyberbullying are linked to societal norms that put girls at risk of harassment, violence, abuse, and discrimination.
A novel paragraph embedding method for spoken document summarization

Representation learning has emerged as a newly active research subject in many machine learning applications because of its excellent performance. In the context of natural language processing, paragraph (or sentence and document) embedding learning is more suitable/reasonable for some tasks, such as information retrieval and document summarization. However, as far as we are aware, there is only a dearth of research focusing on launching paragraph embedding methods. Extractive spoken document summarization, which can help us browse and digest multimedia data efficiently, aims at selecting a set of indicative sentences from a source document to express the most important theme of the document. A general consensus is that relevance and redundancy are both critical issues in a realistic summarization scenario. However, most of the existing methods focus on determining only the relevance degree between a pair of sentence and document. Motivated by these observations, three major contributions are proposed in this paper. First, we propose a novel unsupervised paragraph embedding method, named the essence vector model, which aims at not only distilling the most representative information from a paragraph but also getting rid of the general background information to produce a more informative low-dimensional vector representation. Second, we incorporate the deduced essence vectors with a density peaks clustering summarization method, which can take both relevance and redundancy information into account simultaneously, to enhance the spoken document summarization performance. Third, the effectiveness of our proposed methods over several well-practiced and state-of-the-art methods is confirmed by extensive spoken document summarization experiments.
Are You READee for IPs

This paper describes the fundamentals of a retrieval support tool. Such a tool can be used for the selection of electronic components or scalable design concepts. This prototype tool { called READee { is based on Case-Based Reasoning (CBR) techniques. The application domain of the prototype are digital signal processors (DSPs), from which some results are shown. We generalize this application domain to the more general class of IPs (\Intellectual Properties") and present an abstract IP model to support the selection of IPs. This IP model consists of an IP taxonomy, a classi(cid:12)cation of parameters and quality measures for IP characterization, as well as a constraint net representing the design space of an IP. Built upon this abstract IP model, we propose an IP selection (cid:13)ow which will be supported by our tool.
Bariatric Surgery Patients' Perceptions of Weight-Related Stigma in Healthcare Settings Impair Post-surgery Dietary Adherence

Background: Weight-related stigma is reported frequently by higher body-weight patients in healthcare settings. Bariatric surgery triggers profound weight loss. This weight loss may therefore alleviate patients' experiences of weight-related stigma within healthcare settings. In non-clinical settings, weight-related stigma is associated with weight-inducing eating patterns. Dietary adherence is a major challenge after bariatric surgery. Objectives: (1) Evaluate the relationship between weight-related stigma and post-surgical dietary adherence; (2) understand if weight loss reduces weight-related stigma, thereby improving post-surgical dietary adherence; and (3) explore provider and patient perspectives on adherence and stigma in healthcare settings. Design: This mixed methods study contrasts survey responses from 300 postoperative bariatric patients with ethnographic data based on interviews with 35 patients and extensive multi-year participant-observation within a clinic setting. The survey measured experiences of weight-related stigma, including from healthcare professionals, on the Interpersonal Sources of Weight Stigma scale and internalized stigma based on the Weight Bias Internalization Scale. Dietary adherence measures included patient self-reports, non-disordered eating patterns reported on the Disordered Eating after Bariatric Surgery scale, and food frequencies. Regression was used to assess the relationships among post-surgical stigma, dietary adherence, and weight loss. Qualitative analyses consisted of thematic analysis. Results: The quantitative data show that internalized stigma and general experiences of weight-related stigma predict worse dietary adherence, even after weight is lost. The qualitative data show patients did not generally recognize this connection, and health professionals explained it as poor patient compliance. Conclusion: Reducing perceptions of weight-related stigma in healthcare settings and weight bias internalization could enhance dietary adherence, regardless of time since patient's weight-loss surgery.
Genetic Algorithm with Range Selection Mechanism for Dynamic Multiservice Load Balancing in Cloud-Based Multimedia System

Consider a centralized hierarchical cloud-based multimedia system (CMS) which has a resource manager, cluster heads, and server clusters. Resource manager accepts clients’ requests for multimedia service tasks and allocates server clusters based on the task characteristics. Cluster head distributes the task to the servers within its server cluster. An effective genetic algorithm with an immigrant scheme is proposed for load balancing that spreads the multimedia service task load on servers with the minimal cost for transmitting multimedia data between server clusters and clients, by not violating the maximal load limit of each server cluster. Dynamic multiservice scenario is considered in which each server cluster only handles a specific type of multimedia operation, and every client requests a different type of multimedia service at a different time.
Ensemble of Statistically Independent Filters for Robust Contact Lens Detection in Iris Images

Contact lenses are known to degrade the performance of the iris recognition system. Thus, accurate detection of a contact lens is of paramount importance not only in improving the reliability but also the security of an iris recognition system. In this paper we present a novel scheme for detecting contact lenses in iris images. The proposed scheme is based on an ensemble of statistically independent filters whose response on the iris image is processed and further classified using a linear Support Vector Machine (SVM) to detect the contact lens. Extensive experiments are carried out on two publicly available large scale databases, namely: IIIT-Delhi Contact lens iris database (IIITD) and Notre Dame cosmetic contact lens database 2012 (ND) that are comprised of contact lens iris samples captured using four different sensors. The rigorous experiments conducted in this work show the outstanding performance of the proposed scheme, especially in detecting a textured contact lens with a Correct Classification Rate (CCR) of 100%. We also present a comprehensive benchmark of the proposed scheme with six different well established state-of-the-art schemes available for the contact lens detection.
A Computability Perspective on Self-Modifying Programs

In order to increase their stealth, malware commonly use the self-modification property of programs. By doing so, programs can hide their real code so that it is difficult to define a signature for it. But then, what is the meaning of those programs: the obfuscated form, or the hidden one? Furthermore, from a computability perspective, it becomes hard to speak about the program since, its own code varies over time. To cope with these issues, we provide an operational semantics for self-modifying programs and we show that they can be constructively rewritten to a non-modifying program.
Identification of O-glycosylated Proteins That Are Aberrantly Excreted in the Urine of Patients with Early Stage Ovarian Cancer

Cancer is known to induce or alter the O-glycosylation of selective proteins that may eventually be excreted in the patients’ urine. The present study was performed to identify O-glycosylated proteins that are aberrantly excreted in the urine of patients with early stage ovarian cancer (OCa). These urinary glycoproteins are potential biomarkers for early detection of OCa. In this study, urinary proteins of patients with early stage OCa and age-matched OCa negative women were subjected to two-dimensional gel electrophoresis and detection using a lectin that binds to the O-glycosylated proteins. Our analysis demonstrated significant enhanced expression of clusterin and leucine-rich alpha-2-glycoprotein, but lower levels of kininogen in the urine of the OCa patients compared to the controls. The different altered levels of these urinary glycoproteins were further confirmed using competitive ELISA. Our data are suggestive of the potential use of the aberrantly excreted urinary O-glycosylated proteins as biomarkers for the early detection of OCa, although this requires further validation in a large clinically representative population.
Energy saving: Scaling network energy efficiency faster than traffic growth

As the mobile traffic is expected to continue its exponential growth in the near future, energy efficiency has gradually become a must criterion for wireless network design. Three fundamental questions need to be answered before the detailed design could be carried out, namely what energy efficiency network is, where the energy efficiency improvement may come, how the energy efficiency evaluation of a whole mobile network could be conducted. In this paper, we target to shed a light on the answers of the three questions by introducing the bottom-up energy efficiency evaluation methodology for large networks with the combination of different areas and time periods, as well as the basic traffic, deployment, and power models that will be applied therein. Moreover, we shall illustrate where the overall energy saving gain may come by analyzing the power-traffic relation and the three research projects in the GreenTouch Mobile WG.
The Impact of Transmission Power on the Performance of MANET Routing Protocols

A Mobile Ad hoc Network is an infrastructure-less multi-hop wireless network. A node communicates directly with other mobile nodes within the wireless range and indirectly with nodes that are not within the wireless range of each other. Transmission power of the nodes plays an important role here. In a multi hop communication scenario, it is possible to minimize the total energy for reaching a higher distance by repeated low power transmissions. The objective of this work is to study the behavior and performance of the three frequently used MANET routing protocols with respect to different transmission power of individual nodes of the network. We have selected Destination Sequenced Distance Vector (DSDV) Routing Protocol, Ad Hoc On-Demand Distance Vector (AODV) Routing Protocol and Dynamic Source Routing (DSR) Protocol for this study. We analyzed the positive and negative impact of increase in transmission power of individual nodes on the performance of these routing protocols. The arrived results are more significant and can be used in the design of new power aware routing protocols.