Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural network based integral sliding mode control of systems with time-varying state constraints

In this paper, we propose a novel neural network based state constrained integral sliding mode (NN-SCISM) control algorithm for nonlinear system with partially unknown dynamics in presence of time-varying constraints. In particular, the drift term characterizing the system dynamics is estimated by using a two-layer neural network, whose weights are adjusted according to adaptation laws designed relying on stability analysis. Thanks to a sliding variable which varies depending on the minimum distance between the system state and the current closest constraint, the control algorithm is able to drive the system state to a desired target state, while avoiding the forbidden states contained in the time-varying set delimited by the constraints. The proposal has been theoretical analysed and assessed in simulation.
Electrostatic Shield to Mitigate the High Frequency Circulating Bearing Current - A Study for Design Guidelines

In a previous work, the authors addressed electrostatic shielding to reduce the bearing discharge currents (Electrostatic discharge machining currents - EDM). In order to expand the application of such a shielding device, this paper presents an analysis of its use to reduce the inverter-induced circulating bearing currents on induction machines. Employing finite element analysis (FEA), 2D and 3D models were developed to clarify the tradeoff between the shield effectiveness and the associated additional heat losses and motor efficiency reduction, considering different geometric arrangements and materials for the shielding device construction. The results provide very good guidelines for the shield design, contributing to its practical application viability. It is shown that it is possible to design a shielding configuration that achieves a high mitigating level with a negligible impact on the motor efficiency and developed torque. Furthermore, comparing calculation models of different complexities, the paper also shows the importance of representing all capacitive couplings inside the motor and the non-uniform current distribution in the shield to determine its effectiveness. Since a large fraction of the motor failures are caused by bearing currents, this paper can provide benefits to key topics for industry, such as equipment reliability and availability.
Support Vector Machine for Color Classification of RNA

The fast developments in artificial intelligence have allowed scientists to use it for the high-throughput analysis of medical data to assist clinicians in diagnosis and health monitoring tasks. Machine learning has the potential to complement point-of-care diagnosis when coupled with readout techniques, such as colorimetry. Here, a support vector machine (SVM) is used for the rapid analysis of colorimetric images, readout to a point-of-care viral RNA detection device. We used a paradigm of viral respiratory infection, Covid-19, to illustrate SVM capabilities for diagnosis. In the test set, the SVM achieves a 94% success rate in its classification of healthy vs patients after 10 minutes. This point-of-care system would help to prevent the fast spread of infectious diseases through rapid screening operations.
Efficiency and Output Power Sensitivity to Control Parameter Variations in an LCC-Series Wireless Power Transfer System

In wireless power transfer (WPT) systems, output power <tex>$(P_{out})$</tex> can be controlled through input parameters such as, input voltage <tex>$(V_{in})$</tex>, duty cycle <tex>$(d)$</tex>, and switching frequency <tex>$(f_{sw})$</tex>. The impact of these control parameters on the overall system efficiency has not been explored in previous studies. This paper focuses on the efficiency <tex>$(\eta)$</tex> and <tex>$P_{out}$</tex> sensitivity to these control parameter variations in an LCC-Series tuned WPT system. There are multiple combinations of <tex>$V_{in},\ d$</tex>, and <tex>$f_{sw}$</tex> that can achieve a specified target <tex>$P_{out}$</tex>. However, it is important to determine the optimal combination of these control variables that will yield the maximum <tex>$\eta$</tex> for a target <tex>$P_{out}$</tex>. A MATLAB/Simulink model is built to calculate and measure <tex>$\eta$</tex> and <tex>$P_{out}$</tex>. In order to achieve this result, several simulations are run where <tex>$V_{in},d$</tex>, and <tex>$f_{sw}$</tex> are swept across a wide range to cover all possible combinations. MATLAB's Sensitivity Analysis toolbox is used to evaluate how the parameters influence the model's output. Finally, an experimental prototype is implemented. The optimal values acquired using the sensitivity analysis is then plugged into the hardware prototype and compared with the simulation. The results obtained confirm the validity of the proposed method.
The effect of an empathy-eliciting intervention on the perception of telepresence robot users *

Telepresence robots can be used in different contexts with different goals; for example, to help remote individuals virtually attend classes and meetings, or to allow healthcare workers and patients in different locations to remain in touch. Although these robots bring about different advantages to mediated communication, telepresence pilots have been found to be perceived less favorably than people who are physically present in a communicative context [1]. Thus, in the current work, to mitigate the negative effects of using a telepresence robot, we examine whether an intervention to elicit empathy can influence the way remote participants are perceived. To this end, in a within-subject design, we asked participants (N=30) to follow text-based instructions to do a language learning activity in groups of three, in which one of the participants used a GoBe telepresence robot to join other co-situated group members. We embedded an intervention designed to create empathy with the telepresence operator in the last section of the activity and used two questionnaires, one before and one after the intervention, to collect participants' subjective evaluations of each other. Findings suggest that after the empathy-eliciting question, participants found the telepresence robot user significantly more trustworthy, reliable, and fascinated by art, music, or literature. Results indicate that the empathy-eliciting intervention has a positive effect on the way collocated participants perceive telepresence users.
An Overview of the Understanding and Use of Assessment Methods in Benefits Management

Evidence suggests that benefits management is critical for enabling greater value and for enhancing the positive impact of programs, projects, and portfolios. However, many organizations only focus their efforts on identifying the intended benefits, without conducting a proper follow-up through ongoing assessment or evaluation to ensure benefits realization. For this reason, this study aims to obtain an overview of the actual use of the assessment methods in benefits management, through a compilation and analysis of the literature following the Systematic Mapping Study methodology. The results and findings obtained show a significant gap in the interplay between the fields of assessment methods and benefits management. Based on this, we suggest opportunities for improvement, such as developing audit guides and frameworks for enhancing the monitoring of the benefits, strengthening the focus on external benefits of organizations, and for adapting benefits assessment to the changed perceptions of intended benefits, in line with continuous improvement.
Going Dark: A Software “Light Switch” for Internet Servers

To fight global warming, carbon emissions must urgently be reduced. In this paper, we look at opportunities to do so by diminishing the operational energy usage of an important always-on element of the Internet: server systems. Our measurements from a server host indicate that there is probably not much to be gained by making a significant software change - but, depending on the system, a simple, easily overlooked configuration update may make a difference at no performance cost. This difference is small per server (in the order of an LED light bulb). Given the multitude of permanently operational servers in the world, it may however be significant at scale.
Investigation of a semi-closed cycle small gas turbine for high altitude UAV propulsion

Current unmanned aerial vehicles (UAVs) are limited in operating altitude and endurance by the maximum attainable performance of small gas turbine engines. While improvements in the cycle thermal efficiency can be obtained through the introduction of heat exchangers, the consequent increase in engine weight partially offsets the benefits gained in specific fuel consumption (SFC). Conceptual studies on semi-closed cycles, where part of the engine mass flow rate is recirculated through the engine core, have shown that a significant reduction in engine weight can be obtained in comparison with equivalent open cycle solutions. This thesis presents a preliminary design and optimization study of semi-closed cycle engines for high altitude UAV applications. A detailed thermodynamic and mechanical model has been created to correlate component performance and weight variation as function of thermodynamic design parameters. The model has been coupled with a multi-objective optimization algorithm to optimize various engine cycles and to assess the trade-off between minimum SFC and minimum engine weight. Results have shown that a considerable degree of compactness can be obtained with this novel configuration, leading to an overall engine weight approximately two time lower than conventional open cycles.
Index-Based Biclique Percolation Communities Search on Bipartite Graphs

Biclique percolation community (BPC) search is a fundamental problem in bipartite graph analysis and have many applications. Existing online approach has to enumerate all the maximal bicliques and compute the results based on these bicliques. Considering the large number of maximal bicliques in real graphs and the high frequency of BPC search requests issued in real applications, existing approach is cost prohibitive to obtain the result. Motivated by this, we devise an index-based (BPC-Index) approach to address the problem. Based on the index, we can obtain the result in near-optimal time with well-bounded index space. We further devise an efficient index construction algorithm. Moreover, we also extend our indexing method to address the personalized BPC search problem, which is one of the most common variants of BPC search. We conduct extensive experiments on 10 real bipartite graphs, and the experimental results demonstrate the effectiveness of the BPC model, and the efficiency of our BPC search algorithms and index construction algorithms. Remarkably, our approach can achieve up to 8 orders of magnitude speedup compared to the existing online approach.
Reduced Complexity Multicast Beamforming and User Grouping for Multi-Antenna Coded Caching

A new user-grouping method for multi antenna coded caching (CC) is proposed, able to simultaneously exploit spatial multiplexing, multicasting, and global caching gains. The proposed scheme achieves the theoretical optimal sum degrees of freedom (DoF) and can be applied to networks with any number of users K, transmit antennas L, and global CC gain t. The proposed scheme comprises both multicast and unicast transmissions wherein a suitable combination of messages is chosen exploiting a tree diagram structure thus guaranteeing symmetric transmission of data for any given set of network parameters. The same structure also removes the successive interference cancellation requirement at the receivers, thus enabling a simple linear design for optimized beamformers. Moreover, even though the proposed scheme in general requires a larger subpacketization than the original single antenna CC scheme, for the particular case of $\frac{t+L}{t+1}\in \mathbb{N}$, it works with exactly the same subpacketization value. Finally, the achievability of the proposed scheme is proven, and in the simulations, it is demonstrated that the complexity of the transmitter and receiver implementations can be greatly reduced with only a modest performance loss.
Interação não-linear entre ondas atmosféricas: um possível mecanismo para a conexão trópicos-extratrópicos em baixa-frequência

The asymptotic method of multiple time-scales is used to investigate the nonlinear interactions among equatorial waves in an equatorial β-plane adiabatic primitive equation atmospheric model in isobaric coordinates. The equatorial Rossby, mixed Rossby-gravity, Kelvin and inertio-gravity waves, with several vertical structures, are obtained as the leadingorder solution. From the solvability condition of the problem, a reduced model governing the weakly nonlinear interaction of the waves in a particular resonant triad was obtained. The total energy conservation of the leading-order solution of the original model equations implies that the sum of the coupling coefficients in any resonant triad must be zero. Using a graphical approach, we determined some resonant triads involving equatorially trapped baroclinic waves and barotropic Rossby waves having large mid-latitude amplitude. Two particular interactions deserve special attention because of their strong coupling and their possible relation to observed features in the atmospheric circulation. One is characterized by a first baroclinic mode structure mixed Rossby-gravity wave interacting with a barotropic Rossby wave with the second gravest meridional mode, both having the same wavenumber, through a zonally symmetric geostrophic mode with the same vertical structure as the Yanai wave and having the n = 1 meridional mode. The other triad is composed of a zonal wavenumber-1 Kelvin wave, a zonal wavenumber-2 mixed Rossby-gravity wave, both with the first baroclinic mode vertical structure, and a barotropic zonal wavenumber-3 Rossby wave having the second gravest meridional mode. The barotropic Rossby waves in these two triad interactions have significant projection onto middle and higher latitudes. The integration of the triad equations for these particular interactions shows that, for the initial mode amplitudes characterizing typical magnitudes of atmospheric flow perturbations, the modes in the first triad usually exchange energy on intraseasonal time-scales, while the modes in the second triad exchange energy on either intraseasonal or semi-annual time-scale, depending on the initial condition. The implications of the results for the dynamics of tropics-extratropics interaction on low-frequency time-scale are discussed.
Raspberry Pi Based Computing Prototypes: Design, Implementation and Performance Analysis

Nowadays, in Internet of Things (IoT) applications, IoT devices generate and gather data. These data can be handled in different ways. They can be processed by IoT devices directly, by the Cloud, or by the edge servers. In recent years, Raspberry Pi has been developed as a small IoT device for many applications. In this paper, we design and implement various computing models, i.e., Cloud Computing, Edge Computing, and computing on IoT devices, using Raspberry Pis as prototypes. We deploy multiple applications, run hands-on experiments, and analyze the results accordingly. We also compare the performances of these different computing paradigms, and take advantage of the parallel processing capability of Raspberry Pi devices to demonstrate the effectiveness of improving the prototype performance.
REDE: Exploring Relay Transportation for Efficient Last-mile Delivery

Last-mile delivery from delivery stations to customers’ places is now mainly finished by dedicated couriers. In practice, each courier generally collects orders destined for one delivery area at the delivery station and delivers orders to customers. However, the long distance between the delivery station and the delivery area due to practical reasons, e.g., expensive delivery station rental fee in the downtown area, increases the delivery courier’s travel time and decreases the efficiency of the state-of-the-practice last-mile delivery scheme. In this paper, we solve the problem with relay transportation, where a relay courier collects orders at the delivery station and sends them to delivery couriers, and delivery couriers focus on the order delivery at corresponding delivery areas. We design a real-time relay courier scheduling system called REDE to minimize the average relay order delivery time (ARODT) considering the relay and delivery couriers’ mobility and the order destination distribution. First, a heterogeneous task aware route prediction algorithm is proposed to characterize the delivery courier’s mobility. Then a distance-aware greedy algorithm and an ARODT-constrained exchange algorithm are designed to generate the relay route, which is updated with real-time order pickup requests. Extensive evaluation results with real-world logistics data from 100 delivery stations in 38 cities show that REDE reduces ARODT by up to 8.4% compared to baseline methods. The online A/B tests show that compared to the state-of-the-practice method, REDE improves the delivery courier’s working efficiency and the daily number of pickup orders by 20.13% and 4.51%, respectively.
Hybridization of Fuzzy Clustering and Hierarchical Method for Link Discovery

Clustering is an active research topic in data mining and different methods have been proposed in the literature. Most of these methods are based on numerical attributes. Recently, there have been several proposals to develop clustering methods that support mixed attributes. There are three basic groups of clustering methods: partitional methods, hierarchical methods and densitybased methods. This paper proposes a hybrid clustering algorithm that combines the advantages of hierarchical clustering and fuzzy clustering techniques and considers mixed attributes. The proposed algorithms improve the fuzzy algorithm by making it less dependent on the initial parameters such as randomly chosen initial cluster centers, and it can determine the number of clusters based on the complexity of cluster structure. Our approach is organized in two phases: first, the division of data in two clusters; then the determination of the worst cluster and splitting. The number of clusters is unknown, but our algorithms can find this parameter based on the complexity of cluster structure. We demonstrate the effectiveness of the clustering approach by evaluating datasets of linked data. We applied the proposed algorithms on three different datasets. Experimental results the proposed algorithm is suitable for link discovery between datasets of linked data. Clustering can decrease the number of comparisons before link discovery.
Ontology-based reasoning to reconFigure industrial processes for energy efficiency

Modern factories collect and process a large volume of different types of industrial process data. These data are used to develop metrics and Key Performance Indicators to monitor and improve productivity and the efficiency of a factory. Improving the efficiency of an industrial process, however, This work develops an ontology-based framework that semantically describes an industrial process, and in particular it describes the elements of physical connectivity, industrial behaviour, and KPIs. Using a notion of sub-process hierarchy, a Decision Support System explores and suggests options for reconfiguring the elements of the industrial process, to improve efficiency. A proof-of-concept use-case from the KIOS Water System Testbed is presented. The pumping station (connectivity, behaviour and energy efficiency KPIs) of the Testbed is semantically modelled, whereas the DSS suggests reconfiguration options for improving its overall energy efficiency.
Efficient Cross Dynamic Task Assignment in Spatial Crowdsourcing

As a novel intelligent sensing paradigm, spatial crowdsourcing has received extensive attention. Task assignment is a key issue in spatial crowdsourcing. In practice, tasks are unevenly distributed in time and space. Accordingly, the problem of cross task assignment attracts growing attention in both industry and academia. Although there has been a research on this problem, it focuses only on maximizing total revenues for inner platforms. Therefore, it can also be improved to bring a multi-win situation for outer workers and task requesters as well as the inner platform. Inspired by this, we first formulate a new cross dynamic task assignment (CDTA) problem by introducing the reputation scores of workers, and prove it to be NP-hard. For the CDTA problem, a hybrid batch-based framework is presented on the basis of a new cross-platform incentive mechanism and a hybrid batch processing strategy, which are efficient in solving the problem of uneven spatial and time distribution of tasks, respectively. After that, a KM-based algorithm and a density-aware greedy algorithm are proposed to gain an accurate assignment result of tasks in each batch and good performance, respectively. Furthermore, the CDTA problem is modeled as a potential game that is proven to have at least a pure Nash Equilibrium theoretically. Last but not least, a game-theoretic approach is developed to maximize the revenues of the inner platform and outer workers at the same time. Extensive experiments on both real and synthetic datasets are conducted to demonstrate the effectiveness and efficiency of the proposed algorithms.
Bi-Directional Human-Robot Handover Using a Novel Supernumerary Robotic System

Cooperative human-robot systems are the key technology to improve efficiency in agile production. In this work, a novel on-shoulder supernumerary robotic limb (SRL) is developed for human-robot collaboration. The SRL system is mainly composed of a 6-degree-of-freedom (DoF) lightweight robotic arm and a wearable and adjustable base, which allows different users to regulate the arm installation position to fit their physical dimensions and expand their workspace. As the SRL is close to the human head, nullspace-based collision avoidance is designed to achieve safe motion planning. Meanwhile, a Kalman filter is designed to actively predict human hand position and yield anticipatory motion control of our SRL in handover tasks. Furthermore, we conduct a bi-directional handover case study to verify the capability of the SRL system and the effectiveness of the proposed collaborative handover. The result shows that our control method can guarantee intuitive and natural handover behavior.