Miracle-dz/UniFAR-FTUs huggingface dataset:
A Component-Based Cross-Layer Framework for Software Defined Wireless Networks

Network architectures that exhibit cognitive behavior, such as self-adaptation and reconfiguration, are becoming extremely popular paradigms for the future heterogeneous wireless networks. Towards this direction, in this paper, we leverage on the component-based approach to achieve modular cross-layer design and propose a protocol stack with adaptive features that allows autonomous decision-making using local ambient information. The proposed framework allows segregating control from the data plane and combining different techniques, such as backpressure and Markov Random Fields (MRFs), for more efficient adaptation and flexibility against network variations. We demonstrate the effectiveness of the proposed approach and the component-based features of the architecture by presenting hybrid control plane mechanisms that combine the aforementioned techniques in a modular fashion. Finally, we provide directions for practically exploiting the proposed architecture.
A Wavelet Packets Approach to Electrocardiograph Baseline Drift Cancellation

Baseline wander elimination is considered a classical problem. In electrocardiography (ECG) signals, baseline drift can influence the accurate diagnosis of heart disease such as ischemia and arrhythmia. We present a wavelet-transform- (WT-) based search algorithm using the energy of the signal in different scales to isolate baseline wander from the ECG signal. The algorithm computes wavelet packet coefficients and then in each scale the energy of the signal is calculated. Comparison is made and the branch of the wavelet binary tree corresponding to higher energy wavelet spaces is chosen. This algorithm is tested using the data record from MIT/BIH database and excellent results are obtained.
Beyond What Develops When

There is no single methodology that can fully explain the nature of human development and learning. Yet, headway is being made on how cognitive milestones are achieved during development with the use of magnetic resonance imaging (MRI) technology. With this methodology, it is possible to assess changes in brain structure, function, and connectivity. Recent findings suggest that both progressive and regressive processes—as opposed to simple linear patterns of change—underlie changes in cognitive abilities. Functional MRI studies suggest that both biological maturation and learning correspond to a fine-tuning of neural systems with enhanced recruitment of task-relevant regions. This fine-tuning of cortical systems corresponds with their enhanced connectivity with cortical and subcortical circuitry. In sum, imaging has helped to move the field of cognitive development beyond questions of what develops and when, to how these changes may occur.
Perceptions of inclusive education of parents of children without disabilities

This qualitative study has placed a focus upon the experiences of inclusive education of parents of learners without disabilities. As the advent of inclusive education in South Africa has been accompanied by substantial political, social and legislative changes, an ecosystemic theoretical framework has informed the process of this study in order to acknowledge and better understand the influence of various contexts on individuals in their constructions of reality. Recent South African policy documents have endorsed inclusive education as the conceptual framework within which previously disparate systems of educational provision can be united and learners of all abilities optimally accommodated. These documents have not only drawn attention to the need to recognise the rights and potential and actual contributions of parents to the process of education, but have also called for reporting on inclusive educational practice within various institutional contexts. It is against this backdrop that this study has attempted through an interpretative and constructive research philosophy and design to access and interpret the perceptions and experiences of the parents who voluntarily participated in the research process. Permission was obtained from the Western Cape Education Department to conduct focus group discussions at a school which has included learners with Down Syndrome. Two focus group discussions were conducted with groups of parents of children without disabilities in venues provided within the school buildings. Participating parents were asked to reflect on their experiences of inclusive education initially as part of a written response to the research question and later through interactive discussion within the focus group. Follow up telephonic interviews provided member checks on the initial data analysis and enabled further reflections on the research question. Stellenbosch University http://scholar.sun.ac.za
Ad-hoc synthesis of auditory icons

This article introduces ad-hoc synthesis, an approach to designing auditory icons and synthesis algorithms that emphasizes the perception of the sounds by users instead of the analysis of actual sources and sound. We describe two substractive synthesis algorithms for generating and controlling wind and wave sounds in real-time by means of high-level parameters. Even though these sounds are not audiorealistic, they convey information in a non-intrusive way and therefore are suitable for monitoring background activities. These sounds capture the main invariants of the sounds they imitate, enabling users to recognize and understand them easily. We then push the approach further by showing how an auditory illusion, i.e. a sound that does not exist in the real world, can be used to convey the notion of speed in a natural and non-intrusive way.
Identifying regions of interest for discriminating Alzheimer's disease from mild cognitive impairment

Alzheimer's disease (AD) is one of the most common types of dementia that affects elderly people, with no known cure. Early diagnosis of this disease is very important to improve patients' life quality and slow down the disease progression. Over the years, researchers have been proposing several techniques to analyze brain images, like FDG-PET, to automatically find changes in the brain activity. This paper compares regions of voxels identified by an expert with regions of voxels found automatically, in terms of corresponding classification accuracies based on three well-known classifiers. The automatic identification of regions is made by segmenting FDG-PET images, and extracting features that represent each of those regions. Experimental results show that the regions found automatically are very discriminative, outperforming results with expert's defined regions.
Cosmic chronometers: constraining the equation of state of dark energy. I: H(z) measurements

We present new determinations of the cosmic expansion history from red-envelope galaxies. We have obtained for this purpose high-quality spectra with the Keck-LRIS spectrograph of red-envelope galaxies in 24 galaxy clusters in the redshift range 0.2 < z < 1.0. We complement these Keck spectra with high-quality, publicly available archival spectra from the SPICES and VVDS surveys. We improve over our previous expansion history measurements in Simon et al. (2005) by providing two new determinations of the expansion history: H(z) = 97±62 km sec−1 Mpc−1 at z ≃ 0.5 and H(z) = 90±40 km sec−1 Mpc−1 at z ≃ 0.9. We discuss the uncertainty in the expansion history determination that arises from uncertainties in the synthetic stellar-population models. We then use these new measurements in concert with cosmic-microwave-background (CMB) measurements to constrain cosmological parameters, with a special emphasis on dark-energy parameters and constraints to the curvature. In particular, we demonstrate the usefulness of direct H(z) measurements by constraining the dark-energy equation of state parameterized by w0 and wa and allowing for arbitrary curvature. Further, we also constrain, using only CMB and H(z) data, the number of relativistic degrees of freedom to be 4±0.5 and their total mass to be < 0.2 eV, both at 1σ.
Localization and Dynamics of Nuclear Speckles in Plants1

The generation of mature mRNAs from most genes (about 80%–90%) in autotrophic eukaryotes requires the removal of noncoding sequences (introns) and splicing of the coding regions (exons; [Labadorf et al., 2010][1]). During splicing in some precursor messenger RNAs (pre-mRNAs), the same splice sites
Parallel computation of determinants of matrices with polynomial entries for robust control design

In this paper we consider computing determinants of polynomial matrices symbolically. Determinant computation of matrices with polynomial entries in a small number of variables is of particular interest since it commonly appears in solving engineering design problems. A parallel algorithm based on multivariate Newton polynomial interpolation with "cut-surface" (total degree bound) is presented and its efficiency is demonstrated by showing computational results for some practical examples from control system design.
Differences in prescribed Kt/V and delivered haemodialysis dose--why obesity makes a difference to survival for haemodialysis patients when using a 'one size fits all' Kt/V target.

BACKGROUND Morbid obesity is reported to be a survival factor for haemodialysis patients compared with those with a normal body mass index (BMI), yet morbid obesity (BMI >35) is a mortality risk factor for obese patients in the general population. Traditionally, haemodialysis dosing is prescribed to achieve a target Kt/V corrected for total body water (TBW). As obese patients typically have increased body fat, which contains less water than muscle, then obese patients may have lower levels of body water than their slimmer counterparts, and as such delivered Kt/V could be greater than that estimated using standard anthropomorphic equations, and so increased dialysis dose may help explain the increased survival reported for obese patients. METHODS We compared multi-frequency bioelectrical impedance analysis (MF-BIA) measurements of TBW in healthy haemodialysis outpatients, and compared TBW with that calculated from the Watson equation derived from anthropomorphic measurements. RESULTS Three hundred and sixty-three adult patients, mean age 58.1 ± 16.7 years, 60.9% male and 29.9% diabetic were studied. MF-BIA-measured body composition showed that as BMI increased from <20 to >35, the percentage skeletal muscle mass fell from 42.8 ± 4.9 to 29.2 ± 5.5% (P < 0.01) whereas the % fat mass increased from 24.5 ± 11.6 to 46.7 ± 6.8% (P < 0.01). As such, TBW measured by MF-BIA was significantly lower from that predicted by the Watson equation at higher BMIs (BMI > 35; 38.9 ± 6.8 versus 44.7 ± 6.9 L, P < 0.01 and BMI = 30-35; 37.2 ± 7.5 versus 41.9 ± 7.3 L, P < 0.01), and as such the delivered Kt/V using MF-BIA was much greater than that using the Watson-based urea volume of distribution for the obese patients (BMI > 35; spKt/V 1.63 ± 0.48 versus 1.41 ± 0.35 and BMI 30-35; 1.65 ± 0.3 versus 1.46 ± 0.26, both P < 0.01). CONCLUSIONS Prescribing dialysis or quantifying on-line clearance based on the anthropomorphically derived Watson equation leads to underestimation of the delivered dose to obese patients, due to changes in underlying body composition. As such, when using a 'one size fits all' target Kt/V, obese patients have an advantage over patients with normal BMI, in that they will receive a greater delivered dose of dialysis, and this may potentially explain the paradoxical survival advantage of the morbidly obese haemodialysis patient.
Enhancement of Error Correction in Quantum Cryptography BB84 Protocol

The Quantum Cryptography BB84 protocol has proved to be quite successful in the process of Quantum Key Distribution (QKD). The protocol is used to create a secure key that is shared between two communicating parties. A major phase in this protocol is the correction of errors and discrepancies between keys of sender and receiver. The present work is concerned with enhancing the error correction phase in such protocol so that the keys generated would be created more efficiently; i.e., to enable the creation of longer shared keys in less time. For this purpose, we have introduced an algorithm based on the use of a memory structure between rounds of the error correction phase. The advantages of the algorithm presented in this paper are established using simulated experiments. A performance evaluation parameter is computed as the ratio of key length to the total operations needed to reach it. This value needs to be maximized for best performance. The experimental results have been compared through a parameterization model assuming that the relative increase in evaluation is linear in the block size increment. Parameters deduced from the experiments show that the performance of the enhanced algorithm is better by a factor of approximately 1.7 – 3.1 relative to the standard algorithm for initial block sizes ≥ 0.5 % of the key length, and by a factor of 1.15 – 1.30 for initial block sizes < 0.5 % of the key length.
COMPRESSION SCHEME FOR WIRELESS SENSOR NETWORKS USING A DISTRIBUTED SOURCE CODING ALGORITHM BASED ON RAPTOR CODE

Această lucrare adresează problematica compresiei datelor în re elele de In this paper, the problem of distributed source coding for data compression in wireless sensor networks (WSN) is addressed. To achieve high levels of compression, a complete solution for network architecture, data correlation model and distributed source coding (DSC) algorithm is proposed. DSC is implemented using Raptor codes, the newest class of fountain codes. Rigorous tests proved better performance, in terms of compression rate, of the proposed solution compared to DSC schemes using LDPC or Turbo Codes. As tests also revealed, the differences in architecture between the proposed systematic version and the non-systematic version of Raptor code enable the implementation of DSC in a wide range of WSN applications.
THE EFFICIENT MARKET HYPOTHESIS AND THE DYNAMIC BEHAVIOR OF SUGAR FUTURE PRICES

RESUMO: o presente trabalho examina a hipótese de eficiência de mercado estimando um modelo de series temporais com coeficientes que variam no tempo. A metodologia utilizada foi a do Filtro de Kalman para um modelo autoregressivo e de média móvel (ARMA) com erros modelados com heteroscedasticidade condicional autoregressiva generalizada (GARCH). O modelo foi estimado pelo método da máxima verossimilhança para os retornos dos preços futuros do açúcar. As variáveis de maior ordem de defasagem foram as que mostraram a maior queda em valor absoluto no tempo; o que pode sugerir que variáveis com maior ordem de defasagem perdem peso no tempo a medida que os mercados tornam-se mais eficientes.
Retinal Vascular Calibers and the Risk of Intracerebral Hemorrhage and Cerebral Infarction: The Rotterdam Study

Background and Purpose— Narrower retinal arteriolar calibers and wider venular calibers are associated with cardiovascular disease, including cerebral infarction. We investigated the association between retinal vascular calibers and the long-term risk for stroke and its subtypes with particular focus on intracerebral hemorrhage. Methods— We included 5518 participants (aged ≥55 years) from the prospective population-based Rotterdam Study who were stroke-free at baseline (1990–1993) and of whom digital retinal images were available. Follow-up for incident stroke was complete up to January 1, 2007. Data were analyzed with Cox proportional hazards models adjusted for age and sex and additionally for potential confounders. Arteriolar and venular calibers were entered both separately and simultaneously in the models. Results— During an average follow-up of 11.5 years, 623 participants developed a first-ever stroke (50 hemorrhagic, 361 ischemic, 212 unspecified). Larger venular caliber was independently associated with an increased risk for stroke (hazard ratio [HR] per SD increase: 1.20; 95% confidence interval [CI]: 1.09 to 1.33), cerebral infarction (HR: 1.28; 95% CI: 1.13 to 1.46), and intracerebral hemorrhage (HR: 1.53; 95% CI: 1.09 to 2.15). Much weaker, only borderline significant associations were found between arteriolar caliber and risk for stroke (HR per SD decrease: 1.12; 95% CI: 0.99 to 1.23), cerebral infarction (HR: 1.12; 95% CI, 0.98 to 1.27), and intracerebral hemorrhage (HR: 1.25; 95% CI: 0.87 to 1.79). Retinal vascular calibers were strongly associated with lobar hemorrhages and oral anticoagulant-related hemorrhages. Conclusion— Larger retinal venular caliber is associated with an increased risk for stroke in the general population and, in particular, with an increased risk for intracerebral hemorrhage.
Particle Swarm Optimization on DSI Method for PAPR Reduction in OFDM Systems

Dummy sequence insertion (DSI) structure is a method without side information and changing signal shape to reduce peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signal. The key to enhance its performance is creating more qualified dummy sequence. In this paper, particle swarm optimization (PSO) algorithm is applied to DSI scheme to more effectively mitigate the PAPR problem in OFDM systems. Simulation results show that the proposed method is superior to that of adopting complementary sequence as dummy sequence one.
Robust Optimization of Sums of Piecewise Linear Functions with Application to Inventory Problems

Robust optimization is a methodology that has gained a lot of attention in the recent years. This is mainly due to the simplicity of the modeling process and ease of resolution even for large scale models. Unfortunately, the second property is usually lost when the cost function that needs to be “robustified” is not concave (or linear) with respect to the perturbing parameters. In this paper we study robust optimization of sums of piecewise linear functions over polyhedral uncertainty set. Given that these problems are known to be intractable, we propose a new scheme for constructing conservative approximations based on the relaxation of an embedded mixed-integer linear program and relate this scheme to methods that are based on exploiting affine decision rules. Our new scheme gives rise to two tractable models that, respectively, take the shape of a linear program and a semidefinite program, with the latter having the potential to provide solutions of better quality than the former at the price of heavier computations. We present conditions under which our approximation models are exact. In particular, we are able to propose the first exact reformulations for a robust (and distributionally robust) multi-item newsvendor problem with budgeted uncertainty set and a reformulation for robust multiperiod inventory problems that is exact whether the uncertainty region reduces to a L 1 -norm ball or to a box. An extensive set of empirical results will illustrate the quality of the approximate solutions that are obtained using these two models on randomly generated instances of the latter problem.
PSO-based optimization of broadband antenna array for space-division communication system

This paper describes a pattern synthesis method for a circular array antenna using the particle swarm optimization (PSO) and cubic spline interpolation (CSI). Being an indispensable part of a high speed space-division communication system, the array antenna operates in a wide frequency band (200-400 MHz) and has stable patterns with 60-degree half power beam width (HPBW) in the whole frequency band. Firstly, by establishing a versatile objective function, the complex excitations of the circular array at the selected seven frequency points are determined via the PSO algorithm. Then, the complex excitations of the circular array at arbitrary frequency points in the whole working frequency band are calculated effectively using the CSI method. A uniform circular array with 6 broadband dipole elements is examined. The broadband patterns with 60-degree HPBW and the accuracy of the interpolation method are demonstrated.
A Bayesian Network Based Structure Learning Algorithm

To solve the difficulties of high calculation quantity and low precision in constructing an air transport network, the paper puts forward a kind of hybrid algorithm, which called Bayesian network model based conditional independence test and heuristic search (CIBNS, CI-based Bayesian Network Search). The new algorithm firstly makes use of the conditional independence test to compress the search space, which to ensure the solution quality and speed up the search process simultaneously. Then, the method introduces the heuristic search based on the BDeu Measure score to improve the efficiency of constructing. Experimental results on simulated and real data show that the new algorithm can effectively construct aviation network. Its performance in terms of efficiency and accuracy is better than the hill climbing method and local search method. The solution quality is better and the convergence speed is faster. The CIBNS achieves a better balance in terms of validity and the calculated efficiency of the solution.
Word Sense disambiguation for Arabic language using the variants of the Lesk algorithm

In this paper, we evaluate the variants of the Lesk algorithm to disambiguate Arabic words. In the first experiment we apply the original Lesk algorithm using the dictionary as a resource. As a second experience, we add some modifications for this algorithm, using the different similarity measures to determine the similarity relatedness between two concepts in Arabic Wordnet. We attempted to find the measure that increases the performance of the WSD. These variants affiliate a score for the most relevant sense of the ambiguous word using two different resources.
Looking on the SUNEE side : an analysis of student volunteering on a university sports-based outreach project

This thesis provides an in-depth study into the development of student volunteers’ motivation during their participation in a sports-based outreach project and how their experiences during the programme serve to influence their commitment and retention to it. The Sport Universities North East England (SUNEE) project represents an alliance between the region’s five universities to tackle social exclusion, and promote and nurture social capital and civil responsibility through the vehicle of sport. This joined-up approach to sports development provides the region’s student volunteers with vast opportunities to gain both experience and qualifications as sports coaches, mentors and leaders by working with a range of ‘hard to reach’ groups. This qualitative investigation utilises data generated from semi-structured interviews (n=40) and describes a sequence of social and psychological transitions undertaken by student volunteers over the course of their involvement in the project. This interdisciplinary investigation unravels the socio-cognitive processes underlying volunteer persistence and satisfaction, or conversely, those which serve to forestall motivation and potentially lead to participant drop out. The research makes a contribution to the established body of knowledge by using the example of the SUNEE project to demonstrate how motivations to volunteer change from ‘extrinsic’ (for example, instrumental reasons such as being perceived by students to enhance their employability profile) to ‘intrinsic’ (such as ‘enjoying the experience’) regulators of behaviour, the longer the person has taken part in the project. This contribution is new because it takes the theories of Deci and Ryan and uses them to understand issues of student volunteering in sports-based outreach projects, providing a novel application of their work. Thus, this research provides a framework that can be utilised to identify, interpret and facilitate students’ motivation to volunteer.