Miracle-dz/UniFAR-FTUs huggingface dataset:
Microgrid Frequency & Voltage Adjustment Applying Virtual Synchronous Generator

The distributed generations (DG) are linked to microgrids (MGs) by power converters regularly and the MG will be in mutual interconnection with conventional power systems. The more the participation level of the converter-based DGs in the MG, the more the stability issues are seen in the MG. Unlike conventional synchronous generators (SGs) which have considerable inertia, the converter-based DG units lack this intrinsic inertia; therefore, they potentially make the MG prone to stability issues. The idea to emulate the behavior of SGs in the control loop of interfaced converters to maintain the MGs stability is a newly-growing idea. This paper tends to propose an improved voltage and frequency control strategy for island MGs consisting several converter-based DGs. The proposed control structure uses an advanced Virtual Synchronous Generator (VSG) model and aimed at implementing the primary frequency and voltage control of MGs. The designed model considers both resistive and inductive parameters of lines in MGs. Since the suggested control structure is a local one, doesn't require communication links between DG units. The simulation results verify the potency of the recommended control structure to preserve the frequency and voltage stability of an island MG even in severe events.
Life Cycle Assessment of Locally Manufactured Small Wind Turbines and Pico-Hydro Plants

Locally manufactured small wind turbines and pico-hydro plants are a low-cost alternative for providing energy access to rural communities, but the life cycle environmental impacts of such systems have not been thoroughly investigated. In this paper, a life cycle model and inventory have been implemented to assess the environmental impacts of locally manufactured technologies in an off-grid context, based on actual data from two case studies. Variations in parameters that influence the performance and impact of these systems, such as the number of failures and the availability of wind resource in the case of small wind turbines, have also been considered in the modelling. Life cycle impacts for the two systems are presented for five impact categories. In both cases, the manufacturing of components of the electrical system, such as the batteries and the inverter, is found to have significantly higher impacts than those of the locally manufactured energy conversion units. The results are then compared with the impacts of a small generator set. Overall, the study shows that both renewable energy systems have significantly lower impacts than the small generator set, with the pico-hydro plant having the lowest impacts due to its high capacity factor, while the impacts of the small wind turbine are found to depend heavily on the average wind speed of the installation site; a parameter that proved to be more significant in terms of environmental impacts than the actual number of failures that can occur in the lifetime of a locally manufactured machine.
Polar Coding for Parallel Gaussian Channels

In this paper, we propose a polar coding scheme for parallel Gaussian channels. The encoder knows the sum capacity of the parallel channels (the capacity of each channel is assumed to be fractional) but does not know the capacity of any channel. By using the nesting property of polar codes, we design a coding/decoding scheme to achieve the sum capacity.
SN-VNE: A Virtual Network Embedding Algorithm for Satellite Networks

Network virtualization is a significant technology for the future network development. Many research results of it have already been proposed. However, almost all of these research is based on terrestrial networks to establish a network model. These terrestrial-based research cannot adapt to the extremely limited re-sources and high dynamics of satellite networks, and obviously cannot meet the demands of satellite networks for the network virtualization services. The inter-satellite link only establishes a connection when it carries a task. This establishment of inter-satellite links consumes the energy of the satellite. To reduce energy consumption of satellite network, this paper establishes a satellite network model and proposes a virtual network embedding (SN-VNE) algorithm. By considering link establishment state in node mapping and link mapping, we moderately map virtual links to the established physical connections. Our experiments prove that SN-VNE can reduce the number of link establishments in the mapping of virtual links. This reduction can save the energy consumption of satellite networks.
Semi-Automated 3D Registration for Heterogeneous Unmanned Robots Based on Scale Invariant Method

This paper addresses the problem of 3D registration of outdoor environments combining heterogeneous datasets acquired from unmanned aerial (UAV) and ground (UGV) vehicles. In order to solve this problem, we introduced a novel Scale Invariant Registration Method (SIRM) for semi-automated registration of 3D point clouds. The method is capable of coping with an arbitrary scale difference between the point clouds, without any information about their initial position and orientation. Furthermore, the SIRM does not require having a good initial overlap between two heterogeneous datasets. Our method strikes an elegant balance between the existing fully automated 3D registration systems (which often fail in the case of heterogeneous datasets and harsh outdoor environments) and fully manual registration approaches (which are labour-intensive). The experimental validation of the proposed 3D heterogeneous registration system was performed on large-scale datasets representing unstructured and harsh outdoor environments, demonstrating the potential and benefits of the proposed 3D registration system in real-world environments.
A High-Precise Arrhythmia Detection Method Based on Biorthogonal Wavelet and Fully Connected Neural Network

A novel approach for detecting feature points of ECG signals is proposed, which is based on an adaptive wavelet-threshold-slope method. Biorthogonal spline wavelet is applied for QRS complex detection. The original signals are decomposed with the equivalent filters of a biorthogonal wavelet by Mallat algorithm. In addition, threshold and slope methods are used for auxiliary monitoring of QRS complex. A fully connected neural network is proposed for arrhythmia detection, after morphological and statistics features are calculated by the position of feature points. MIT-BIH Arrhythmia Databases are used to verify the recognition accuracy of the proposed method, and comparative experiments are conducted. Experimental results demonstrated that adaptive threshold and slope detection methods are robust against noise, and the fully connected neural network has high performance for arrhythmia detection.
Operational Equivalence of Distributed Hypothesis Testing and Identification Systems

In this paper we revisit the connections of the distributed hypothesis testing against independence (HT) problem with the Wyner-Ahlswede-Korner (WAK) problem and the¨ identification systems (ID). We show that the strong converse for the WAK problem is equivalent to the strong converse for the HT problem via constructive and nonconstructive transformations of codes. As another consequence of the transformation we provide a new exponentially strong converse equivalence statement. Applying the same idea, we prove a new result that the -identification capacity of the ID problem is equal to the maximum ϵ-exponent of type II of error in the HT problem when both side compression is allowed.
Brain-Controlled Adaptive Lower Limb Exoskeleton for Rehabilitation of Post-Stroke Paralyzed

Stroke is a standout amongst the most imperative reasons of incapacity on the planet. Due to partial or full paralysis, the majority of patients are compelled to rely upon parental figures and caregivers in residual life. With post-stroke rehabilitation, different types of assistive technologies have been proposed to offer developments to the influenced body parts of the incapacitated. In a large portion of these devices, the clients neither have control over the tasks nor can get feedback concerning the status of the exoskeleton. Additionally, there is no arrangement to detect user movements or accidental fall. The proposed framework tackles these issues utilizing a brain-controlled lower limb exoskeleton (BCLLE) in which the exoskeleton movements are controlled based on user intentions. An adaptive mechanism based on sensory feedback is integrated to reduce the system false rate. The BCLLE uses a flexible design which can be customized according to the degree of disability. The exoskeleton is modeled according to the human body anatomy, which makes it a perfect fit for the affected body part. The BCLLE system also automatically identifies the status of the paralyzed person and transmits information securely using Novel-T Symmetric Encryption Algorithm (NTSA) to caregivers in case of emergencies. The exoskeleton is fitted with motors which are controlled by the brain waves of the user with an electroencephalogram (EEG) headset. The EEG headset captures the human intentions based on the signals acquired from the brain. The brain-computer interface converts these signals into digital data and is interfaced with the motors via a microcontroller. The microcontroller controls the high torque motors connected to the exoskeleton’s joints based on user intentions. Classification accuracy of more than 80% is obtained with our proposed method which is much higher compared with all existing solutions.
Assessing Social Aspects of Urban Vehicular Scenarios for Improving Message Diffusion

Message diffusion in Vehicular Networks takes place upon the establishment of ephemeral contacts among vehicles. This approach has one severe limitation: since the amount of information transmitted in a contact is limited by the transmission speed and the contact duration, large messages are not likely to be exchanged, and thus their diffusion is severely limited. In this paper, we study the impact that different social aspects have on the spreading of messages, showing that splitting a large message into smaller parts can improve its diffusion. Based on this idea, we propose an extension of the epidemic protocol called Xpread. We have developed an analytical model based on Population Processes to evaluate the impact and the efficiency of the partition scheme, showing that a fixed size partition is the best option, while also providing a simple expression to obtain the optimal size. Finally, we show that the diffusion of the messages is improved up to two times with a slight reduction in the delivery time and overhead. These results were also confirmed with simulation experiments.
OffVid: A System for Linking Off-Topic Concepts to Topically Relevant Video Lecture Segments

We present a system for automatically connecting off-topic concepts from a video lecture to appropriate and topically relevant video lecture segments. The linked video lectures are expected to provide more detailed account of the corresponding off-topic concept. The system is realized with three modules: off-topic identification, topic base generation and segment linking. We modelled the problem of finding off-topic concept identification task as a community structure analysis in concept similarity graph. Word embedding-based technique has been used to generate topic specific video segments that act as the targets of off-topic concept connection candidates. The segmented videos are indexed using extracted topic by Solr search engine and are retrieved against queries formulated from offtopic concepts. The system has been evaluated on video lecture picked up from NPTEL MOOC platform. User study on the quality of recommendation has been found to be promising.
Experimental validation of an equivalent dynamic model for active distribution networks

In this paper a real-time laboratorial experiment is presented, intended to validate a “grey-box” equivalent model for medium voltage active distribution networks with high presence of converter-connected generation, considering the latest European grid codes requirements, in response to severe faults at the transmission network side. A hybrid setup was implemented at INESC TEC's laboratory (Porto, Portugal), relying on a real-time digital simulator to provide the interface between simulation and physical assets available at the laboratory, in a power-hardware-in-the-loop configuration. The study considered the laboratory's internal network to be operating (virtually) as a medium voltage distribution network with converter-connected generation (fault ride through compliant), connected to a fully-detailed transmission network model. The aggregated reactive power response of the laboratory's network was fitted by the dynamic equivalent model, recurring to an evolutionary particle swarm optimization algorithm. The methodology adopted, testing conditions and respective results are presented.
Combining Sequential and Aggregated Data for Churn Prediction in Casual Freemium Games

In freemium games, the revenue from a player comes from the in-app purchases made and the advertisement to which that player is exposed. The longer a player is playing the game, the higher will be the chances that he or she will generate a revenue within the game. Within this scenario, it is extremely important to be able to detect promptly when a player is about to quit playing (churn) in order to react and attempt to retain the player within the game, thus prolonging his or her game lifetime. In this article we investigate how to improve the current state-of-the-art in churn prediction by combining sequential and aggregate data using different neural network architectures. The results of the comparative analysis show that the combination of the two data types grants an improvement in the prediction accuracy over predictors based on either purely sequential or purely aggregated data.
Distributed TDMA Scheduling Using Topological Ordering in Wireless Sensor Networks

TDMA protocols can provide a reliable, collision-free data-transferring mechanism for wireless sensor networks. However, it requires an effective scheduling (time slot assignment)algorithm, which is a challenging issue, especially in wireless multi-hop networks due to random-based competition. In this paper, we propose DSTO, a distributed TDMA scheduling algorithm using Topological Ordering (TO). DSTO aims to reduce conflict of scheduling time among neighbor nodes by creating a Topological Order with local neighborhood size as the main priority factor. We implemented DSTO on OPNET Network Simulator and proved its effectiveness compared to DRAND in terms of running time and message overheads.
Parallel Nested Rollout Policy Adaptation

Nested Rollout Policy Adaptation (NRPA) is a Monte Carlo tree search algorithm that excels in the domain of single agent optimization problems. It was applied to a wide class of problems, including vehicle routing, DNA alignment, 3D packing, travelling salesman problem, combinatorial puzzles and more.We develop a parallel version of NRPA that replicates results of the sequential version. The parallelization allows us to run deeper calculations. The experimental data shows that depth of the calculation is a deciding factor in the result quality. Earlier parallelization attempts used parallel architecture to run wider, but not deeper, calculations.We applied the parallel version to the Morpion Solitaire benchmark. To aid parallelization, we used a different best result replacement rule. Using the new rule, on a distributed architecture with 768 cores we obtained an average speedup over a single core computation by a factor 547.48. For the first time a level 6 NRPA computation with 80 iterations per level was finished. It was completed in less than 20 hours of wall-clock time. The different replacement rule was effective. In each run, the record 178-move sequence was found.
“Coworking Is About Community”: But What Is “Community” in Coworking?

Coworking spaces are shared working environments in which independent knowledge workers gather. Coworking is consistently described in terms of community and collaboration—yet these terms are defined inconsistently in the coworking literature. This study reviews the literature on coworking to better examine how community relates to collaboration. To anchor a more systematic analysis of community in coworking, the authors introduce Adler and Heckscher’s typology of communities; apply it to a study of six coworking spaces in the United States, Italy, and Serbia; and develop the typology to better understand coworking.
An Active Thermal Control Method for AC-DC Power Converter with Sequence-based Control Approach

With the heightened development of semiconductor technology, power electronic devices have had a crucial role in power systems. They are employed in a different variety of applications, including but not limited to energy conversation and grid connection for renewable energy sources, motor drive systems in electric vehicles and industrial systems, and AC/DC power conversion in the ship power system (SPS). Especially, medium voltage DC (MVDC) distribution systems are highly interested in future ship power systems, therefore, power converter devices and their control systems will be commonly used in the ship system. Due to the limitation of weight and size of the power converter and its cooling system, a well-designed control system may reduce the required cooling system and improve the overall system performance. In this paper, we propose an active thermal management for power converter using model predictive control approach.
Resolving Simultaneity Bias: Using Features to Estimate Causal Effects in Competitive Games

In this paper, we walk through an application of the instrumental variables (IV) and control function approach (CF) estimators to identify the causal effect of in-game features on the probability of winning. Without use of IV or CF, typical methods of identifying the effect of in-game features (like player performance) will be strongly biased. Practical uses of unbiased estimates include predictive game balance when introducing new heroes and features, enhanced estimation of player rankings, and better interpretation of individual player statistics.
Effect of chronic stress on cardiovascular and ventilatory responses activated by both chemoreflex and baroreflex in rats

ABSTRACT Chronic stress results in physiological and somatic changes. It has been recognized as a risk factor for several types of cardiovascular dysfunction and changes in autonomic mechanisms, such as baroreflex and chemoreflex activity. However, the effects of different types of chronic stress on these mechanisms are still poorly understood. Therefore, in the present study, we investigated, in adult male rats, the effect of repeated restraint stress (RRS) or chronic variable stress (CVS) on baroreflex, chemoreflex and heart rate variability in a protocol of 14 days of stress sessions. Exposure to RRS and CVS indicated no changes in the basal level of either arterial pressure or heart rate. However, RRS and CVS were able to attenuate sympathovagal modulation and spontaneous baroreflex gain. Additionally, only RRS was able to increase the power of the low-frequency band of the systolic blood pressure spectrum, as well as the slope of linear regression of baroreflex bradycardic and tachycardic responses induced by vasoactive compounds. Additionally, our study is one of the first to show that exposure to RRS and CVS decreases the magnitude of the pressor response and potentiates respiratory responses to chemoreflex activation, which can trigger cardiovascular and respiratory pathologies. Furthermore, the basal respiratory parameters, such as minute ventilation and tidal volume, were significantly decreased by both protocols of chronic stress. However, only CVS increased the basal respiratory frequency. In this way, the findings of the present study demonstrate the impact of chronic stress in terms of not only depressive-like behavior but also alterations of the autonomic baroreflex responses and cardiocirculatory variability (systolic blood pressure and pulse interval). Our results provide evidence that chronic stress promotes autonomic dysregulation, and impairment of baroreflex, chemoreflex and heart rate variability. Summary: Our results provide evidence that autonomic changes may reflect important mechanisms in the etiology of cardiovascular diseases associated with exposure to chronic stress.
Long-term impact of giving antibiotics before skin incision versus after cord clamping on children born by caesarean section: protocol for a longitudinal study based on UK electronic health records

Introduction In the UK, about a quarter of women give birth by caesarean section (CS) and are offered prophylactic broad-spectrum antibiotics to reduce the risk of maternal postpartum infection. In 2011, national guidance was changed from recommending antibiotics after the umbilical cord was cut to giving antibiotics prior to skin incision based on evidence that earlier administration reduces maternal infectious morbidity. Although antibiotics cross the placenta, there are no known short-term harms to the baby. This study aims to address the research gap on longer term impact of these antibiotics on child health. Methods and analysis A controlled interrupted time series study will use anonymised mother-baby linked routine electronic health records for children born during 2006–2018 recorded in UK primary care (The Health Improvement Network, THIN and Clinical Practice Research Datalink, CPRD) and secondary care (Hospital Episode Statistics, HES) databases. The primary outcomes of interest are asthma and eczema, two common allergy-related diseases in childhood. In-utero exposure to antibiotics immediately prior to CS will be compared with no exposure when given after cord clamping. The risk of outcomes in children delivered by CS will also be compared with a control cohort delivered vaginally to account for time effects. We will use all available data from THIN, CPRD and HES with estimated power of 80% and 90% to detect relative increase in risk of asthma of 16% and 18%, respectively at the 5% significance level. Ethics and dissemination Ethical approval has been obtained from the University of Birmingham Ethical Review Committee with scientific approvals obtained from the independent scientific advisory committees from the Medicines and Healthcare products Regulatory Agency for CPRD and the data provider, IQVIA for THIN. The results will be published in peer-reviewed journals, presented at national and international conferences and disseminated to stakeholders.