Miracle-dz/UniFAR-FTUs huggingface dataset:
Global Distributed Attitude Tracking Control of Multiple Rigid Bodies via Quaternion-Based Hybrid Feedback

This article investigates the leader-following attitude tracking control problem of multiple rigid body systems in the presence of uncertain parameters and disturbances. The communication constraint is considered that only a subset of followers have access to the leader, and a quaternion-based nonlinear hybrid distributed observer is first proposed to estimate the leader's trajectory for each follower. In particular, the proposed distributed attitude observer always evolves on the 3-D unit sphere $\mathbb {S}^{3}$. This property guarantees the feasibility of the observer-based distributed control scheme, since the separation principle is satisfied. By incorporating a hysteresis-based switch of a binary logic variable for each pair of neighboring rigid bodies, the proposed hybrid distributed observer achieves the global asymptotic stability for any initial attitude and avoids the unwinding phenomenon. Next, an observer-based attitude tracking control law is developed by combining adaptive technique and hybrid theory, which does not require precise model information and has good robustness to the disturbances. In addition, it is shown that the attitude tracking errors converge to the origin globally asymptotically. Finally, simulation results are provided to validate the theoretical results.
Static-Output-Feedback Based Robust Fuzzy Wheelbase Preview Control for Uncertain Active Suspensions With Time Delay and Finite Frequency Constraint

This paper proposes a static-output-feedback based robust fuzzy wheelbase preview control algorithm for uncertain active suspensions with time delay and finite frequency constraint. Firstly, a Takagi-Sugeno (T-S) fuzzy augmented model is established to formulate the half-car active suspension system with consideration of time delay, sprung mass variation and wheelbase preview information. Secondly, in view of the resonation between human's organs and vertical vibrations in the frequency range of 4-8 Hz, a finite frequency control criterion in terms of $H_{\infty}$ norm is developed to improve ride comfort. Meanwhile, other mechanical constraints are also considered and satisfied via generalized $H_{2}$ norm. Thirdly, in order to maintain the feasibility of the controller despite of some state variables are not online-measured, a two stage approach is adopted to derive a static output feedback controller. Finally, numerical simulation results illustrate the excellent performance of the proposed controller.
Study on Direct Torque Control Methods of a Doubly Fed Induction Machine Working as a Stand-Alone DC Voltage Generator

The article presents a comparison of different Direct Torque Control methods of a Stand-Alone Doubly Fed Induction DC-Voltage Generator, with classic field oriented control used as a benchmark. The system consists of a doubly fed induction generator the stator circuit of which is connected to the DC-bus with a diode rectifier, and the rotor circuit converter is connected to the same DC bus. The main problem of this power generation system are large torque oscillations caused by a nonlinear diode rectifier connected to the stator. Three direct torque control algorithms are described as a means of reduction of this drawback with simultaneous control of DC bus voltage and stator voltage frequency. The methods differ by the second variable used for control in parallel to the torque control path. The selected second variable is the d component of the rotor current vector, the d component of the stator flux or the stator flux module.
Understanding system features through information visualisations to improve product development: An exploratory study with data analysts

Information visualisations, such as diagrams and charts, support analysis of large amounts of information. While there exist various information visualisations for decision support in product development, they are often being created in an ad-hoc manner. In this paper, we examine whether certain types of information visualisations facilitate understanding of characteristic features of systems, such as hierarchy, relationships, patterns and processes. Results from our study suggest that information visualisations are recognised as representing the aforementioned characteristic system features.
Design of ₌׀₌ Shape Stub-Based Negative Group Delay Circuit

Editor’s note: This article presents a type of negative group delay (NGD) circuit based on transmission line resonators. To obtain the circuit’s S-parameters, this article uses a combination of ABCD and Z-parameters. Analytical design equations are presented, which are verified using circuit simulations. —Binoy Ravindran, Virginia Tech
A Novel Strain Sensor Using a Fiber Taper Cascaded With an Air Bubble Based on Fabry–Perot Interferometer

A novel optical fiber strain sensor based on a Fabry–Perot Interferometer (FPI) is proposed and experimentally demonstrated. The FPI is fabricated by splicing a single mode fiber (SMF) taper and an air micro-bubble formed by using repeated discharging on the hollow core fiber (HCF). By doing this, the sensitivity of the proposed configuration to strain is greatly increased comparing with that of other FPIs. Experimental results show that the sensitivity of the sensor to strain can reach 41.5 pm/<inline-formula> <tex-math notation="LaTeX">$\mu \varepsilon $ </tex-math></inline-formula>, 42.56 pm/<inline-formula> <tex-math notation="LaTeX">$\mu \varepsilon $ </tex-math></inline-formula> and 41.02 pm/<inline-formula> <tex-math notation="LaTeX">$\mu \varepsilon $ </tex-math></inline-formula> at the dips of 1525.9721 nm, 1646.3134 nm and 1567.1797 nm, respectively with negligible power fluctuation. And average sensitivity at three resonance peaks to temperature is 2.04 pm/°C resulting the temperature cross sensitivity of <inline-formula> <tex-math notation="LaTeX">$0.0489~\mu \varepsilon / ^{\circ }\text{C}$ </tex-math></inline-formula>. In addition, the proposed sensor shows good performances in the repeatability and stability, which can be potentially used in the many fields such as medical treatment and structural health monitoring.
Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors

In the recent Internet-of-Things (IoT) era where biomedical applications require continuous monitoring of relevant data, edge computing keeps gaining more and more importance. These new architectures for edge computing include multi-core and parallel computing capabilities that can enable prevention diagnosis and treatment of diseases in ambulatory or home-based setups. In this article, we explore the benefits of the parallelization capabilities and computing heterogeneity of new wearable sensors in the context of a personalized online atrial fibrillation (AF) prediction method for daily monitoring. First, we apply optimizations to a single-core design to reduce energy, based on patient-specific training models. Second, we explore multi-core and memory banks configuration changes to adapt the computation and storage requirements to the characteristics of each patient. We evaluate our methodology on the Physionet Prediction Challenge (2001) publicly available database, and assess the energy consumption of single-core (ARM Cortex-M3 based) and new ultra-low power multi-core architectures (open-source RISC-V based) for next-generation of wearable platforms. Overall, our exploration at the application level highlights that a parallelization approach for personalized AF in multi-core wearable sensors enables energy savings up to 24% with respect to single-core sensors. Moreover, including the adaptation of the memory subsystem (size and number of memory banks), in combination with deep sleep energy saving modes, can overall provide total energy savings up to 34%, depending on the specific patient.
Adaptive silviculture for climate change network

The Adaptive Silviculture for Climate Change (ASCC) project is a collaborative effort that has established a series of experimental silvicultural trials across a network of different forest ecosystem types throughout North America. Scientists, land managers, and a variety of partners have co-developed a series of experimental sites as part of this multiregion study to research long-term ecosystem responses to a range of climate change adaptation approaches (Swanston et al. 2016). Silvicultural treatments at each study site were developed by using a modified process from Swanston et al. (2016). The treatments represent three general climate adaptation options: (1) resistance—maintaining relatively unchanged conditions over time; (2) resilience—allowing some change in current conditions but encouraging an eventual return to reference conditions following disturbance; and (3) transition—actively facilitating change to encourage adaptive responses (definitions modified from Millar et al. 2007).
Energy Efficient Artificial Noise-Aided Precoding Designs for Secured Visible Light Communication Systems

Physical layer security (PLS) has recently gained a lot of attention in the research and development of visible light communication (VLC). In this article, we study the designs of PLS in VLC systems in the presence of multiple unauthorized users (i.e. eavesdroppers) using artificial noise (AN)-aided precoding. The design objective focuses on minimizing the total transmit power subject to specific constraints on the signal-to-interference-plus-noise ratios (SINRs) of the legitimate and unauthorized users. In particular, two design approaches are investigated considering the availability of unauthorized users’ channel state information (CSI) at the transmitter. In the case of unknown CSI, the AN is constructed to lie on the null-space of the legitimate user’s channel. The design problem is convex, thus, can be effectively solved. When the CSI is available, the design additionally imposes constraints on the maximum allowable unauthorized users’ SINRs. The design problem, in this case, is, nevertheless, non-convex. Therefore, instead of finding the optimal solution, we examine two different sub-optimal yet low-complexity approaches to solve the problem, namely: Concave-Convex Procedure (CCP) and Semidefinite Relaxation (SDR). Additionally, robust designs that take into account channel uncertainty are also investigated. Extensive numerical results are shown to demonstrate the feasibility and performance of each design with practical parameters.
Análisis de sentimientos en Twitter: desarrollo de recursos en el español rioplatense de Argentina

Rojo, V. , Pollo-Cattaneo, Ma. F; Britos, P. 1. Programa de Maestría en Ingeniería en Sistemas de Información. Facultad Regional Buenos Aires. Universidad Tecnológica Nacional. Argentina. 2. Grupo de Estudio en Metodologías de Ingeniería de Software (GEMIS). Facultad Regional Buenos Aires. Universidad Tecnológica Nacional. Argentina. 3. Universidad Nacional de Río Negro. Laboratorio de Informática Aplicada. Río Negro, Argentina. {vmrojo, flo.pollo}@gmail.com, pbritos@unrn.edu. ar
Conflict and Competition

Conflict and competition arise when involved parties’ preferences and goals collide. This chapter highlights theoretical and empirical perspectives on the emergence and manifestations of conflicts. We outline how conflicts can occur from three perspectives: considering conflicts between individual actors, considering conflicts between individuals in competing groups, and considering conflicts between individuals within their groups. We show how individual-level preferences determine actions taken in dilemma situations in which outcomes are interdependent, leading to cooperative, selfish or competitive behaviour. Further, we summarize key theoretical perspectives about the formation of conflict between groups, and highlight how individual behaviour contributes to such conflicts. We show how individuals may be at odds with other members of their group, experiencing conflict about their relationships and joint tasks. Finally, we outline how coalitions are formed when more than two parties face each other in conflicts. In sum, we consider the potential – both productive and detrimental – that conflict harbours for social exchange.
Greening the Old New Deal: Strengthening Rural Electric Cooperative Supports and Oversight to Combat Climate Change

New Deal cooperatives succeeded in electrifying rural America when for-profit utilities would not. Today, however, rural electric cooperatives are lagging behind when it comes to meeting the challenge of climate change. Cooperatives have collectively been slower to embrace the shift to low-carbon electricity than for-profit and municipal utilities and have served as a drag on state and federal clean energy and climate policies. This is partially because of the structural differences between cooperatives and other utilities, but also because of a weak and under-determined federal and state regulatory structure. A few cooperatives in Colorado and New Mexico are seeking to lead the charge to a low-carbon electricity system, but they are finding themselves stymied by their own power supply cooperative. Drawing on insights from organization, public choice, and energy regulation theories, this Article argues that institutional incentives at power supply cooperatives inhibit prudent resource planning in a time of climate change. It concludes that cooperatives need significant changes to state and federal regulatory structures to counter these factors. These changes include subjecting power supply cooperatives to rigorous integrated resource planning requirements and providing state utility commissions oversight over power supply contract buy-out fees. It also includes reconsidering the wholesale electricity rate structure between power supply and distribution cooperatives.
Batch Processing for Truss Maintenance in Large Dynamic Graphs

This article studies the batch processing of truss maintenance in large graphs. Trussness is a widely used index in graph analytics for cohesive subgraph mining. It is defined on edges to reflect the closeness of vertices connected by the edges. The trussness maintenance problem, i.e., updating trussness after edge insertions/deletions and avoiding recomputation, was proposed by Cohen (2008) with the assumption that real graphs are continuously evolving in nature and their dynamicity usually only affects few edges. Different from the existing work that mainly focuses on simple single edge/vertex insertion/deletion, we propose batch processing algorithms for truss maintenance with multiedge insertions/deletions. By presenting an edge structure called triangle disjoint set, whose insertion/deletion can make each edge change its trussness by at most 1, we tackle the difficulty in quantifying the trussness changes of the edges in batch processing. More specifically, we propose two indices, namely sustain support and pivotal support, to help measure whether the edges have the potential to change their trussness, such that the search range of the potential edges is greatly reduced. The extensive experiments on real-world graphs illustrate that compared with the single-edge processing approach, our batch processing algorithms can significantly improve the processing efficiency, and the improvement becomes more obvious when more edges are inserted/deleted.
On the Reflectivity Extraction Based on Partial Bistatic Near-Field Scattering From Microwave Blackbody

This work reports numerical investigations on the scattering from microwave blackbody, for developing a national standard facility on the emissivity determination in China. Based on the Kirchhoff’s law of thermal equilibrium, the standard facility follows a bistatic scattering measurement configuration and covers a wide frequency range. In general, the reflectivity is to be extracted based on partially collected scattering in the near-field region. The whole electromagnetic process, from the quasi-optical antenna illumination, to target scattering, and finally the aperture coupling reception, is modeled to be analyzed. It is shown in the simulation results that the Floquet scattering properties of the array-shaped blackbody can be obtained without fulfilling the far-field condition. Then, evaluations on the reflectivity extraction are performed at 54, 89, 118, and 183 GHz, addressing typical blackbody structures of coated cones and coated pyramids. The factors of referencing targets, curve integration, and the oblique incidence are discussed, as well as the case of geometry flawed blackbody. This work offers important reference and specific suggestions for achieving accurate and stable reflectivity determination in the bistatic near-field configuration.
Influence of Geomagnetic Field on the Long-Range Propagation of Relativistic Electron Beam in the Atmosphere

It is known that Earth’s atmosphere and geomagnetic field affect the propagation of an artificial electron beam; many previous studies have neglected the effect of their variation on the propagation dynamics. In this article, parameters in envelope equations were modified according to the International Geomagnetic Reference Field (IGRF) model and MSIS-90 atmosphere model; then, the model was constructed to study the propagation of artificial electron beam in the atmosphere. Calculation of the beam’s energy loss and radial expansion in propagation showed that the variation of geomagnetic field intensity can be the main reason for the radial pinch in the altitudes above 150 km, and the ambient particle density plays a dominant role in the beam’s radial expansion in altitudes below 150 km. The Monte Carlo model was used to simulate the interactions of a relativistic (1 MeV) electron beam with the atmosphere in the altitude range 100–150 km. Energy deposition density demonstrates that the geomagnetic field can limit the radial expansion of the beam. The relativistic electron beam was emitted horizontally in the atmosphere. The geomagnetic field can limit the beam’s radial expansion and cause the beam to propagate along the field line, irrespective of the direction in which the beam is emitted.
Efficient Extraction of Target Users for Package Promotion in Big Social Networks

Package promotion (or product bundling and bundle promotion) is widely adopted as an effective marketing strategy to increase sales, but the social tightness of the users significantly influences their willingness to purchase certain products. However, addressing these two factors simultaneously is not a trivial task because it is critical to properly choose a set of socially tight target users to encourage them to buy the products together (social tightness factor), and the selected users should have high preference for the package of products (preference factor). To address the aforementioned challenges, in this article, we study the research problem of promoting a package of products to a set of closely related friends. We formulate a new research problem, named package-oriented group identification (PGI), which can obtain a set of $t$ socially tight users (i.e., inducing more than $k$ edges) who have the maximum preference for a package of items. We prove that the proposed PGI problem is NP-hard, and we develop a polynomial-time algorithm named incremental solution construction with redundancy and infeasibility avoidance for PGI (ISCP) that can effectively and efficiently obtain a good solution to the PGI problem. We compare the performance of ISCP with four other baselines on a large-scale product copurchasing data set with more than 500 k products and 1.7 M copurchasing relationships. The results show that our proposed ISCP algorithm outperforms the other baselines in terms of solution quality and efficiency.
Cloud of Things (CoT): Cloud-Fog-IoT Task Offloading for Sustainable Internet of Things

With a high rise in the popularity of Internet of Things (IoT), mobile computing, and wearable devices, a huge amount of data is being generated. Running complex tasks such as that are machine learning-based with minimum energy consumption is a challenge. It requires complex algorithms to run locally such as on middleware fog within the proximity of the devices generating data, or globally in a cloud to analyze the acquired data and create robust and smart applications. However, it depends on the type of task execution policy applied at each level; local or global, to decide on energy and performance efficiency, since certain tasks are high in complexity. Hence, task execution will be hierarchically distributed among the IoT nodes, fog, and cloud. Given that, we present in this paper a three-tier IoT-fog-cloud model. We argue that with distributed task execution, we can achieve high scalability of IoT services, and manage the global energy consumption as well. As a proof-of-concept, we evaluate our three-tier architecture by taking into account computational tasks for various applications in IoT related to medical, multimedia, location-based, and text. We evaluate using real datasets, based on three scenarios: fog-only, cloud-only, and fog-cloud collaborative. Task execution policy (at fog/cloud) play a key role in efficiently processing a task (especially large tasks, such as in deep learning). Therefore, we take that into account and elaborate what types of policies suit what type of offloading environment (fog-only, cloud-only, or fog-cloud collaborative).
Selectivity of a fishing gear used in the catch of Anomalocardia flexuosa in the Northeast of Brazil

EnglishA type of dredge was introduced as fishing gear along the extractive bank of Mangue Seco - PE from which the largest annual catch of Anomalocardia flexuosa in the world is extracted. This study was carried out with the objective of estimating the selectivity of the new fishing gear and quantitatively evaluating the length classes most compromised by the catches, especially considering 20 mm as the reference value. Specimens larger than this size are most likely to be mature. For the selectivity estimation, the methodology using codends (16 or 20 mm) and small meshed cover (2 mm) was used. To estimate the selectivity parameters, a logistic regression and the Bayesian approach were used. The transition between the state in which the specimen is invulnerable to the fishing gear and vulnerable occurs between 10 and 18 mm, using a 16 mm mesh, and using a 20 mm mesh, this transition is between 14 and 20 mm. Dredgers with 16 mm and 20 mm mesh compromise a large proportion of specimens smaller than 20 mm. If the intention is to protect this part of the population, measures such as total restriction of the 16 mm mesh and use of the 20 mm mesh should be necessary only in the months of less catching incidences, or increasing the mesh to 25 mm portuguesUm tipo de draga foi introduzido como arte de pesca no banco extrativista de Mangue Seco - PE de onde se extrai a maior captura anual de Anomalocardia flexuosa do mundo. Este trabalho foi realizado com objetivo de estimar a seletividade do novo petrecho de pesca e avaliar quantitativamente quais sao as classes de comprimento mais penalizadas nas capturas, tendo especialmente como referencial o valor de 20 mm. Exemplares maiores que esse tamanho tem elevada probabilidade de estarem maturos. Para estimativa da seletividade foi utilizado o metodo com uso de saco (16 ou 20 mm) e sobresaco (2 mm). Para estimativa dos parâmetros de seletividade foi utilizada regressao logistica e abordagem bayesiana. A transicao entre o estado em que o exemplar e invulneravel a arte de pesca e em que o mesmo seria quase com certeza capturado ocorre para malha de 16 mm entre 10 e 18 mm, enquanto para malha de 20 mm essa transicao se da entre 14 e 20 mm. As dragas com malha de 16 e 20 mm penalizam uma proporcao grande de exemplares menores que 20 mm. Se a intencao e proteger essa parcela da populacao, seriam necessarias medidas como a restricao total da malha de 16 mm e uso da malha de 20 mm somente nos meses de menor incidencia de recrutamento, ou o aumento da malha para 25 mm