Miracle-dz/UniFAR-FTUs huggingface dataset:
Quarter-Sphere SVM: Attribute and Spatio-Temporal correlations based Outlier & Event Detection in wireless sensor networks

Support-Vector Machines (SVM) have received a great interest in the machine learning community since their introduction, especially in Outlier Detection in Wireless Sensor Networks (WSN). The Quarter-Sphere formulation of One-Class SVM (QS-SVM), extends the main SVM ideas from supervised to unsupervised learning algorithms. The QS-SVM formulation is based only on Spatio-Temporal correlations between the sensor nodes (hence the name Spatio-Temporal Quarter-Sphere SVM, ST-QS-SVM). Thus, it has a non-ideal performance. This work presents a new One-Class Quarter-Sphere SVM formulation based on the novel concept of Attribute Correlations between the sensor nodes, hence the name, Spatio-Temporal-Attribute Quarter-sphere SVM (STA-QS-SVM) formulation. Online and partially online approaches to Outlier Detection in WSNs have been presented using this formulation. The results indicate a significant increase in the Outlier Detection rates and a remarkable reduction in the False Positive rates over the previous formulation (ST-QS-SVM). The results of this novel technique also suggest that the partially online approach is as efficient as the online approach, thereby conserving significant computational and communication complexity. Moreover very high Event Detection rates have been reported for STA-QS-SVM, which have not been reported by ST-QS-SVM.
An Exercise in Concurrency: From Non-blocking Objects to Fair Objects

A non-blocking implementation of a concurrent object is an implementation that does not prevent concurrent accesses to the internal representation of the object, while guaranteeing the deadlock-freedom progress condition without using locks. Considering a failure free context, this paper presents a simple modular approach to transform a non-blocking implementation into a starvation-free implementation satisfying a strong fairness requirement. This approach, which is due to G. Taubenfeld, is illustrated with the implementation of a concurrent stack. The spirit of the paper is mainly pedagogical. Its aim is not to introduce new concepts or algorithms, but to show that a powerful, simple, and modular transformation can provide concurrent objects with strong fairness properties.
A Note on the Expectation-Maximization (EM) Algorithm

The Expectation-Maximization (EM) algorithm is a general algorithm for maximum-likelihood estimation where the data are “incomplete” or the likelihood function involves latent variables. Note that the notion of “incomplete data” and “latent variables” are related: when we have a latent variable, we may regard our data as being incomplete since we do not observe values of the latent variables; similarly, when our data are incomplete, we often can also associate some latent variable with the missing data. For language modeling, the EM algorithm is often used to estimate parameters of a mixture model, in which the exact component model from which a data point is generated is hidden from us. Informally, the EM algorithm starts with randomly assigning values to all the parameters to be estimated. It then iterately alternates between two steps, called the expectation step (i.e., the “E-step”) and the maximization step (i.e., the “M-step”), respectively. In the E-step, it computes the expected likelihood for the complete data (the so-called Q-function) where the expectation is taken w.r. t. the computed conditional distribution of the latent variables (i.e., the “hidden variables”) given the current settings of parameters and our observed (incomplete) data. In the M-step, it re-estimates all the parameters by maximizing the Q-function. Once we have a new generation of parameter values, we can repeat the E-step and another M-step. This process continues until the likelihood converges, i.e., reaching a local maxima. Intuitively, what EM does is to iteratively “augment” the data by “guessing” the values of the hidden variables and to re-estimate the parameters by assuming that the guessed values are the true values. The EM algorithm is a hill-climbing approach, thus it can only be guanranteed to reach a local maxima. When there are multiple maximas, whether we will actually reach the global maxima clearly depends on where we start; if we start at the “right hill”, we will be able to find a global maxima. When there are multiple local maximas, it is often hard to identify the “right hill”. There are two commonly used strategies to solving this problem. The first is that we try many different initial values and choose the solution that has the highest converged likelihood value. The second uses a much simpler model (ideally one with a unique global maxima) to determine an initial value for more complex models. The idea is that a simpler model can hopefully help locate a rough region where the global optima exists, and we start from a value in that region to search for a more accurate optima using a more complex model. There are many good tutorials on the EM algorithm (e.g., [2, 5, 1, 4, 3]). In this note, we introduce the EM algorithm through a specific problem – estimating a simple mixture model.
Vehicle-to-grid transactions and shunt active filtering capability of SmartParks equipped with modified ICosФ controller

This paper discusses about vehicle-to-grid (V2G) services such as reactive power compensation and harmonic elimination by employing the converters used in electric vehicle charging stations (Smartparks) as shunt active filters (SAF). Batteries can be charged using the bidirectional converters during off peak hours. The parks can supply stored energy to the grid if they have excess solar energy for charging and also support the grid by providing compensation. By incorporating modified ICosΦ algorithm the complete simulation of hysteresis current controlled voltage source converter (VSC) acting as a Smartpark is presented. For inductive and non-linear loads simulations have been performed in Matlab under steady state and transient conditions. The feasibility of this simple and efficient controller to be used as SAF is demonstrated by the simulation results.
Curriculum and curriculum access issues for students with special educational needs in post-primary settings: an international review

(From the Executive Summary.) Introduction This report presents the findings of an evidence review designed to summarise what is known about good practice concerning the content of, and access to, the school curriculum for students with special educational needs. The review focused on post-primary settings where the issue is particularly pertinent; the focus of education shifts from being student-centred at primary level to being much more subject-focused in post-primary settings. The research team delivered two literature reviews: one national, one international. Each was designed to draw out key issues around curriculum and access to the curriculum for students with special educational needs – including gaps and trends in the evidence base – to help the National Council for Special Education (NCSE) plan its future research agenda. The project aims to: * deliver a narrative review of research from the Republic of Ireland and Northern Ireland to identify key issues and themes within the area of curriculum and/or curriculum access at post-primary level for students with special educational needs relevant to the Irish context * deliver a systematic review of the international literature on these priority themes for students with special educational needs at post-primary level * summarise key findings from the reviews to enhance understanding of curriculum issues in order to assist the NCSE to plan further empirical research as necessary, and to formulate policy advice on the matter to the Minister.
Differential effects of specific carotenoids on oxidative damage and immune response of gull chicks

Micronutrients are essential for normal metabolic processes during early development. Specifically, it has been suggested that diet-derived carotenoids can play a key role in physiological functions because of their antioxidant and immunostimulant properties. However, their role as antioxidants remains controversial. Additionally, it is also unclear whether oxidative stress mediates their immunostimulatory effects. In this field study, we separately supplemented yellow-legged gull (Larus michahellis) chicks with two carotenoids (lutein and β-carotene) with different molecular structures and different transformation pathways into other oxidative forms of carotenoids. We quantified their effect on the oxidative status and the immune response of chicks before and after an oxidative challenge with paraquat, a pro-oxidant molecule. Prior to oxidative challenge, none of the carotenoid treatments affected the oxidative status of chicks, but they enhanced the inflammatory response to an antigen compared with controls. The oxidative challenge enhanced plasma vitamin E levels (but not in β-carotene-supplemented chicks) and the antioxidant capacity in the short term. Interestingly, lutein-supplemented chicks showed lower oxidative damage to proteins than non-lutein-supplemented chicks. After the oxidative challenge, the positive effect of carotenoid supplementation on the immune response disappeared. Thus, these results suggest differential effects of two carotenoids with different molecular structures on the oxidative status. Lutein but not β-carotene helps to combat oxidative damage after a free-radical exposure. Additionally, the results indicate that the immunostimulatory effects of carotenoids are linked to oxidative status during early life.
Invariant Descriptor for RGB-D Images

Traditional local features already achieve resistance toward changes in illumination, translation, rotation, and scale variance, thus play an important role in visual content retrieval. However, they are not stable to 3D rotation or viewpoint changes. This report aims to solve this problem by introducing depth sensor, a new kind of sensor which can capture depth with regular optical information, in this problem and proposing a novel descriptor to achieve viewpoint invariance. We first transform input RGB-Depth images to 3D point cloud in Cartesian space, estimate normal vector and calibrate viewpoint for each local patch, and then project the cloud to 2D plane and calculate the descriptors. Some preliminary experiment results also support the effectiveness of our descriptor.
Radio Network Planning with Combinatorial Optimization Algorithms

Future UMTS radio planning engineers will face difficult problems due to the complexity of the system and the size of these networks. In the STORMS project, a software for the optimisation of the radio network is under development. Two mathematical models of the radio planning problem are proposed. Two software prototypes based on these models are described with the first experimental and comparative results.
Six-minute stepper test: a valid clinical exercise tolerance test for COPD patients

Introduction Exercise tolerance testing is an integral part of the pulmonary rehabilitation (PR) management of patients with chronic obstructive pulmonary disease (COPD). The 6-minute stepper test (6MST) is a new, well-tolerated, reproducible exercise test, which can be performed without any spatial constraints. Objective The aim of this study was to compare the results of the 6MST to those obtained during a 6-minute walk test (6MWT) and cardiopulmonary exercise testing (CPET) in a cohort of COPD patients. Methods Ninety-one COPD patients managed by outpatient PR and assessed by 6MST, 6MWT, and CPET were retrospectively included in this study. Correlations between the number of steps on the 6MST, the distance covered on the 6MWT, oxygen consumption, and power at the ventilatory threshold and at maximum effort during CPET were analyzed before starting PR, and the improvement on the 6MST and 6MWT was compared after PR. Results The number of steps on the 6MST was significantly correlated with the distance covered on the 6MWT (r=0.56; P<0.0001), the power at maximum effort (r=0.46; P<0.0001), and oxygen consumption at maximum effort (r=0.39; P<0.005). Performances on the 6MST and 6MWT were significantly improved after PR (570 vs 488 steps, P=0.001 and 448 vs 406 m, respectively; P<0.0001). Improvements of the 6MST and 6MWT after PR were significantly correlated (r=0.34; P=0.03). Conclusion The results of this study show that the 6MST is a valid test to evaluate exercise tolerance in COPD patients. The use of this test in clinical practice appears to be particularly relevant for the assessment of patients managed by home PR.
Effects of membrane surface charge and calcium on the gating of rat brain sodium channels in planar bilayers [published erratum appears in J Gen Physiol 1989 Apr;93(4):following 760]

The voltage-dependent gating of single, batrachotoxin-activated Na channels from rat brain was studied in planar lipid bilayers composed of negatively charged or neutral phospholipids. The relationship between the probability of finding the Na channel in the open state and the membrane potential (Po vs. Vm) was determined in symmetrical NaCl, both in the absence of free Ca2+ and after the addition of Ca2+ to the extracellular side of the channel, the intracellular side, or both. In the absence of Ca2+, neither the midpoint (V0.5) of the Po vs. Vm relation, nor the steepness of the gating curve, was affected by the charge on the bilayer lipid. The addition of 7.5 mM Ca2+ to the external side caused a depolarizing shift in V0.5. This depolarizing shift was approximately 17 mV in neutral bilayers and approximately 25 mV in negatively charged bilayers. The addition of the same concentration of Ca2+ to only the intracellular side caused hyperpolarizing shifts in V0.5 of approximately 7 mV (neutral bilayers) and approximately 14 mV (negatively charged bilayers). The symmetrical addition of Ca2+ caused a small depolarizing shift in Po vs. Vm. We conclude that: (a) the Na channel protein possesses negatively charged groups on both its inner and outer surfaces. Charges on both surfaces affect channel gating but those on the outer surface exert a stronger influence. (b) Negative surface charges on the membrane phospholipid are close enough to the channel's gating machinery to substantially affect its operation. Charges on the inner and outer surfaces of the membrane lipid affect gating symmetrically. (c) Effects on steady-state Na channel activation are consistent with a simple superposition of contributions to the local electrostatic potential from charges on the channel protein and the membrane lipid.
The KR System dlv: Progress Report, Comparisons and Benchmarks

dlv is a knowledge representation system, based on disjunctive logic programming, which ooers front-ends to several advanced KR formalisms. The system has been developed since one year at the Technical University of Vienna in an ongoing project funded by the Austrian Science Funds. After a report on the current state of the art in the implementation of dlv and of its application front-ends, the paper compares dlv with other knowledge representation systems. Both a qualitative and a quantitative comparison are carried out. The rst compares the representational power of the systems (intended as the ability to represent problems in a natural and simple fashion). The latter compares the performances of the systems. The dlv system turns out to be very powerful from the knowledge representation side and, on the other hand, quite good also in computational power.
Understanding the linkage between agricultural productivity and nutrient consumption: Evidence from Uganda

The prevalence of malnutrition across a predominantly agrarian country like Uganda and its potential economic implications indicate the importance of understanding the link between agricultural productivity and nutrient consumption. Such an understanding will highlight the importance of different nutrients (and foods) available across Uganda, thus guiding policymakers in prioritizing and developing appropriate programs to tackle malnutrition and improve agricultural productivity. This study contributes to the more recent literature on the linkage between nutrition and productivity by exploring the impact of various micronutrients, in addition to caloric intake, on agricultural productivity in Uganda. Using a structural equations model (SEM), estimation results clearly reveal the bidirectional relationship between productivity and nutrient intake. Labor productivity elasticity with respect to nutrient intake varies between 0.04 for vitamin B12 and 0.01 for Iron. Our findings suggest that labor productivity increases agricultural income as one would expect. We also find that nutrient intake as well as labor productivity positively affect agricultural income in Uganda. Overall, results indicate that agricultural productivity in Uganda is likely to be enhanced if nutrients intake is significantly increased.
Growth Inhibition of Sulfate-Reducing Bacteria in Produced Water from the Petroleum Industry Using Essential Oils

Strategies for the control of sulfate-reducing bacteria (SRB) in the oil industry involve the use of high concentrations of biocides, but these may induce bacterial resistance and/or be harmful to public health and the environment. Essential oils (EO) produced by plants inhibit the growth of different microorganisms and are a possible alternative for controlling SRB. We aimed to characterize the bacterial community of produced water obtained from a Brazilian petroleum facility using molecular methods, as well as to evaluate the antimicrobial activity of EO from different plants and their major components against Desulfovibrio alaskensis NCIMB 13491 and against SRB growth directly in the produced water. Denaturing gradient gel electrophoresis revealed the presence of the genera Pelobacter and Marinobacterium, Geotoga petraea, and the SRB Desulfoplanes formicivorans in our produced water samples. Sequencing of dsrA insert-containing clones confirmed the presence of sequences related to D. formicivorans. EO obtained from Citrus aurantifolia, Lippia alba LA44 and Cymbopogon citratus, as well as citral, linalool, eugenol and geraniol, greatly inhibited (minimum inhibitory concentration (MIC) = 78 µg/mL) the growth of D. alaskensis in a liquid medium. The same MIC was obtained directly in the produced water with EO from L. alba LA44 (containing 82% citral) and with pure citral. These findings may help to control detrimental bacteria in the oil industry.
Dynamic Resource Arrangement in Cloud Federation

Cloud Federation is one of the ideal solutions tothis random burst traffic problem. It focuses on 'borrowing'computing resources from foreign Clouds when home Cloud isabout to overloaded and 'leasing' resources to foreign Cloudswhen home Cloud is free. Considering crucial importance ofbusiness value for a Cloud provider, we need to perform somedynamic, reasonable and simple rules or mechanisms to helpCloud provider making better billing decisions and improvingthe overall performance in a federation scope. Cloud Federationis implemented by network connections, so in common situationthe best candidate Cloud to be federated enjoys a higher speedof connection to the home Cloud. This remains a problem thatseveral Clouds located in a subnet have a high possibility to befederated with each other, thus complicated dependency relationsamong them will appear. In this paper, we have carried out aseries of mechanisms involving dynamic resource arrangement inestablishment and deconstruction of a Cloud Federation, in orderto sort out these dependency relations which are the potentialrisk factors to the overall performance.
Power system restoration planning with standing phase angle and voltage difference constraints

This paper considers the restoration of a transmission system after a significant disruption such as a natural disaster. It considers the Restoration Order Problem (ROP) that jointly considers generator dispatch, load pickups, and restoration prioritization to minimize the size of the blackout while satisfying the network operational constraints. The paper examines transient effects in power restoration and generalizes the ROP formulation with standing phase angle and voltage difference constraints in order to minimize rotor swings. Case studies indicated that the novel ROP-SPASVD formulation reduces rotor swings of synchronous generators by over 50%, while having a negligible impact on the blackout size (i.e., <; 1.5% increase), which is still optimized holistically.
Genetic algorithm in time series fatigue analysis

This paper is described the analysis of fatigue road loading using the genetic algorithm approaches. This approach is based on a partitional clustering. A new method for temporal pattern matching of a time series is developed using pattern wavelets and genetic algorithms. This method is used to clustering the data into a sequence of a nested partition. Fatigue damage cumulating is a random variable in essence. It is caused by variable amplitude loading. The randomness comes from the loading process and fatigue resistance of material. This modulation is developed as a mathematical method that can be implemented directly into existing evolutionary algorithms without writing special operators and changing the program loop. This article is presented in order to solve some theoretical and practical issues in evolutionary algorithms like numerical bounded variables, dynamic focalized search, dynamic control of diversity and feasible region analysis. Finally it is suggested that the genetic algorithm approach provided a good platform for analyzing the time series in the aspect of the durability research.
Thickness analysis and reconstruction of trabecular bone and bone substitute microstructure based on fuzzy distance map using both ridge and thinning skeletonization

The accurate geometric analysis of microstructured biological porous media is crucial for an understanding of the geometric changes that result from diseases such as osteoporosis and for the design of bone substitutes for the treatment of cancer patients. This paper presents a methodological development designed to improve the description of the average pore size and thickness of a micro structure's biological media. Specifically, the paper introduces a new skeletonization method based on a ridge skeleton combined with fuzzy distance transform (FDT), which has recently been used in the literature and has shown some advantages compared to the traditional distance transform. The new skeletonization method is applied to trabecular bone excised from healthy and osteoporotic vertebrae, as well as to bone substitutes with small and large pores. These samples are scanned by a micro-computed tomography scanner. The new skeletonization method has been implemented successfully, and an exact algorithm for implementation and reconstruction has been developed. The results show that, compared to widely used thinning methods, the new FDT ridge skeleton generates measurements that are more representative of the microstructure of the examined media. It is concluded that the new method can find the ridges of the FDT and produce topologically accurate skeletons, leading to accurate measurement and reconstruction of the microstructured porous media.
Uniform Solution Sampling Using a Constraint Solver As an Oracle

We consider the problem of sampling from solutions defined by a set of hard constraints on a combinatorial space. We propose a new sampling technique that, while enforcing a uniform exploration of the search space, leverages the reasoning power of a systematic constraint solver in a black-box scheme. We present a series of challenging domains, such as energy barriers and highly asymmetric spaces, that reveal the difficulties introduced by hard constraints. We demonstrate that standard approaches such as Simulated Annealing and Gibbs Sampling are greatly affected, while our new technique can overcome many of these difficulties. Finally, we show that our sampling scheme naturally defines a new approximate model counting technique, which we empirically show to be very accurate on a range of benchmark problems.