Miracle-dz/UniFAR-FTUs huggingface dataset:
A Modified DistFlow for Distributed Generation Planning Problems in Radial Grids

This paper focuses on a simplified expression of the load flow constraints for the optimal planning of distributed generation (DG) in radial grids. The proposed approach lies on the conventional DistFlow equations improved with the consideration of linearized bi-directional losses and their impact on the voltage profiles. The method is validated on various radial test cases and allows to run time coupled power flows in order to consider dynamic constraints (e.g. battery state of chare) in short computational times. With the help of the proposed method, a DG placement problem is solved in less than 2 minutes with an exhaustive search over a 69 buses system and the operation is simulated along a single representative day. A scalability test is finally performed with longer time horizons and greater numbers of connected DG. The developed approach allows to run the operation of a 69 buses system over 2 months and with 20 connected DGs in less than 5 minutes.
Fast-Model Predictive Control for a Grid-Tie Photovoltaic System

This paper proposes a hybrid control scheme based upon both a linear and a predictive control approach for a grid-tie inverter for photovoltaic applications. The proposed strategy uses the complex representation of the switching states and splits them choosing the best one without using an iterative loop. The resulting algorithm, in terms of the dynamic and static response, performs like the traditional Finite Set Model Predictive Control (FS-MPC). However, the proposed scheme is easy to implement, it does not need to tune parameters nor need a cost function and nor require iterating all the possible states to choose the best. Over the abovementioned advantages, it has the capability to operate the photovoltaic module at the maximum power point (MPP) and the ability to impose a sinusoidal current at the grid side with a unitary displacement power factor. Preliminary results are presented to validate the proposed control method.
Routing Optimization of Time-Triggered Ethernet Based on Genetic Algorithm

The development of avionics systems has promoted the introduction of the time-triggered concept. The Time-triggered Ethernet (TTE) is a deterministic, synchronous, conflict-free network protocol based on the IEEE 802.3 Ethernet standards and is compatible with ARINC 664p7 protocol. It supports real-time application of mixed-criticality by providing three types of traffic: time-triggered (TT) traffic, which has low jitter and bounded end-to-end delay; rate-constrained (RC) traffic, which has bounded end-to-end delay; and best-effort (BE) traffic, which cannot ensure end-to-end delay. Carrying out offline routing and scheduling configuration on TT traffic ensures the conflict-free of TT traffic in the transmission link. Since the priority of TT traffic is higher than that of RC traffic, ignoring RC traffic in the process of configuring TT traffic routing may make the RC traffic transmission delay very large, exceeding the scope of network design requirements. The issue of concern in this paper is the routing configuration for TT traffic and RC traffic in the TTE network. Under the premise of ensuring the schedulability of TT traffic, the transmission path of TT and RC traffic is configured and optimized, and the end-to-end delay of RC traffic is reduced. Through the network topology information and network traffic information, a load balancing strategy based on the genetic algorithm is used in this paper to configure TT traffic routing, and a path cost strategy is used to configure RC traffic routing. Experimental results from multiple use cases show that routing configuration for TT traffic has a great effect on the end-to-end delay of RC traffic.
Extension to Symmetrical and Asymmetrical n-Phase AC Drives of Simple Carrier-Based PWM for Prolonged High DC-Link Utilization

Recently, it was proposed to combine circulating-current (x-y) filters with a carrier-based pulsewidth-modulation (PWM) method, which injects harmonics in no-torque x-y subspaces (attenuated by the filter) of five-phase motors to achieve high dc-link utilization (DLU). The filter allows prolonged high DLU without overheating. Unlike square-wave switching, no torque ripple is introduced by the PWM. Compared with other PWM techniques capable of high-DLU operation (often called overmodulation), the one proposed for said filters is especially convenient because of its simplicity. However, it is unclear if this PWM method can be extended to machines of any phase number n and winding arrangement (symmetrical or asymmetrical). This paper extends this simple carrier-based PWM strategy to n-phase (symmetrical or asymmetrical) drives, and evaluates its behavior in terms of DLU. The improvement in DLU, compared with conventional PWM with zero-sequence injection, is considerable in most cases. Current distortion is negligible with suitable filter, and no torque ripple (unlike square-wave switching) is generated.
Functional traits and phenotypic plasticity modulate species coexistence across contrasting environments

Functional traits are expected to modulate plant competitive dynamics. However, how traits and their plasticity in response to contrasting environments connect with the mechanisms determining species coexistence remains poorly understood. Here, we coupled field experiments under two contrasted climatic conditions to a plant population model describing competitive dynamics between 10 annual plant species in order to evaluate the associations of niche and fitness differences with 19 functional traits covering physiological, morphological and reproductive characteristics. We found a rich diversity of univariate and multidimensional relationships, in which outstand the primary role of traits related to water- and light-use-efficiency in modulating the determinants of competitive outcomes. Importantly, such traits and their plasticity promoted species coexistence across climatic conditions by enhancing stabilizing niche differences and by generating competitive trade-offs between species. Our study represents a significant advance showing how leading dimensions of plant form and function connect to the mechanisms determining the maintenance of biodiversity.
A Survey: Resource Allocation Technology Based on Edge Computing in IIoT

With the proposal of industry 4.0, the industrial automation of “Human-Machine-Things” based on environmental perception is gradually stepping into the higher exploration field. Based on a large amount of edge computing architecture technology research and application scenarios, this paper summarizes the development status of edge computing and edge resource allocation technology in the emerging stage. It also proposes the idea of combining Industrial Internet of Things(IIoT) and resource allocation in edge computing, so as to provide the technical reference and research direction for the key strategy of resource allocation in industrial edge computing.
Non-Interactive Dealer-Free Dynamic Threshold Secret Sharing Based on Standard Shamir’s SS for 5G Networks

Wireless group communications and mobile computing have demonstrated its potential capacity in the next generation of mobile communication networks and wireless systems (5G), where devices have the particularity of being heterogeneous and so have different capabilities in terms of storage, computing, communication and energy. Conventional protocols are not suitable for 5G networks since this environment needs more flexible and simple protocols for secure group communications. Hence, how to realize the dynamical security is a big challenge for 5G networks. In data security management, the longer the system runs, the greater the attacker’s capabilities become. A threshold changeable secret sharing scheme (TCSS) in which shares of a <inline-formula> <tex-math notation="LaTeX">$(t,n)$ </tex-math></inline-formula> SS generated by the dealer initially can be used to reconstruct the secret but having a larger threshold <inline-formula> <tex-math notation="LaTeX">$j$ </tex-math></inline-formula>, (i.e., <inline-formula> <tex-math notation="LaTeX">$t< j\le n$ </tex-math></inline-formula>), is a secure way to protect the secret for a longer period of time. A straightforward approach to design a non-interactive dealer-free TCSS is to let the dealer follow Shamir’s SS to generate multiple shares for different thresholds, <inline-formula> <tex-math notation="LaTeX">$i$ </tex-math></inline-formula>, for <inline-formula> <tex-math notation="LaTeX">$i=t,t+1,\cdots,n$ </tex-math></inline-formula>. Using this approach, each shareholder needs to store <inline-formula> <tex-math notation="LaTeX">$n-t+1$ </tex-math></inline-formula> shares. In this article, we propose a non-interactive dealer-free TCSS in which each shareholder only needs to store <inline-formula> <tex-math notation="LaTeX">$\left \lceil{ \frac {n-1}{t} }\right \rceil $ </tex-math></inline-formula> shares. Our proposed TCSS can support standard Shamir’s <inline-formula> <tex-math notation="LaTeX">$(t,n)$ </tex-math></inline-formula> SS. Our technique can thus be applied to existing Shamir schemes even if they were set up without consideration to future threshold increases. It is unconditionally secure and simpler than most of the existing schemes.
Lossless Current Sensing Approach for Backpack Energy Harvester

The backpack energy harvester not only harvests energy to charge portable device but also reduces the risk of orthopaedic and muscular injury. In this paper, a lossless current sensing approach for backpack energy harvester is present in swop fly-back converter. The swop fly-back converter is reconstructed by the input capacitor and transformer in fly-back converter. It is controlled with constant on time algorithm and is switching in boundary mode strategy. The measured digital data is transmitted to smart phone by Bluetooth. And then, as a portable base station, the smartphone sent to the cloud. In the previous test, the linearity between time to digital converter output and output current is good as the reason that the correlation coefficients is 0.9772. The average output current is 0.1686 A for striding and 0.4242 A for jogging. The maximum output current is 0.9972 A for striding and 2.16 A for jogging.
On the efficacy of in-probe pre-amplifiers for piezoelectric 2D arrays

Transducer arrays for 3D imaging are characterized by elements distributed over a 2D surface. The dimensions of each element are typically one half-wavelength in both x- and y-directions. Such small elements inherently have a high electrical impedance. When the elements are connected to a probe cable, the high cable capacitance decimates the delivered voltage and results in a poor Signal to Noise Ratio (SNR). This may have dramatic effects, especially in sparse arrays, where a small number of elements contributes to the beamformed signal. In this paper we demonstrate that the use of in-probe preamplifiers in a sparse PZT probe is valuable to significantly increase the SNR.
On the Vulnerability of Random Access Channels in Aeronautical Communications

In the last years, digitization of wireless communication has reached the field of aviation. New manned aircraft require advanced communication services to operate efficiently, while unmanned aircraft depend on communication to operate at all. The absence of a crew on board of unmanned aircraft makes reliable data communication between the remote pilot and the air vehicle a requirement for safe operation. One critical part of digital aeronautical communication systems is the initial login of new users. In many digital systems, this is realized by a random access channel, that aircraft use to establish communication with the network. Since failing to log in would make communication with the network impossible, the random access channel is an attractive target for an attacker. In this paper, we analyze the effect of targeted jamming attacks on the random access channel on the login performance of a terrestrial aeronautical communication system. Using computer simulations we show that pulsed jammers with very low duty cycle can achieve similar jamming performances as continuous wave jammers while being far more energy efficent and thus more feasible. We quantize our findings with the network login time and success rate under jamming and conclude that aeronautical communication can be effectively blocked by attacking the random access channel in practical ways. We conclude with the discussion of possible countermeasures.
OLED-Based Visible Light Communication System Using Universal Filtered Multi-Carrier

Universal filtered multi-carrier (UFMC), which is a modification of orthogonal frequency-division multiplexing (OFDM), is one of the proposed modulation methods for next generation wireless communication systems. To the best of our knowledge, the UFMC modulation method has not been implemented on visible light communication (VLC) systems using organic light emitting diodes (OLED), which have been rigorously researched for next generation indoor and short-range wireless communications. In this paper, for the first time, we presented in details the implementation process and experimental demonstration of UFMC modulation techniques for a VLC system using a commercial OLED. In our initial experimental results, UFMC could be support an aggregated bit rate of 3.1738 Mbps in a OLED-based VLC system with 325 kHz bandwidth.
Improving the prediction of potato productivity: APSIM-Potato model parameterization and evaluation in Tasmania, Australia

Crop growth models are required to be extensively evaluated against actual data from field grown plants in order to have confidence in their prediction of crop productivity under various management options or a future changed climate. We evaluated the ability of the APSIM-potato model to predict production, phenology, and Nuptake of potato (Solanum tuberosum L.) under Tasmanian conditions. On-farm monitoring plots were established in north-west Tasmania within four different well-managed potato fields grown during the 2012/13 cropping season. Detailed soil and crop data sets measured in the on-farm plots planted with two potato cultivars, 'Russet Burbank' and 'Moonlight' were used to parameterise and evaluate the model. The model ealistically reproduced the observed tuber yield with high precision (a mean N-RMSE of 15.4% and modelling efficiency of 1.0 for both cultivars). Measured mean tuber yield was 17 t ha-1 for 'Russet Burbank' with a simulated yield of 20 t ha-1. For 'Moonlight' simulated tuber yield was 16.0 t ha-1 compared to measured yield of 15.1 t ha-1. The simulation results provide insight on the model performance under Tasmanian conditions. The results suggest that the model has potential to be used for purposes such as simulating productivity under various management options and climate change impact studies. Additional experiments are however required to improve cultivar specific input parameters such as phenology, leaf area and leaf duration and other functions that needs further refinement to improve model ability to simulate plant organs beside the tuber
Design and Analysis of Boost Converter Using Sliding Mode Approach

DC-DC converters play an extensive role in power electronics industries. These converters are prone to inherent errors, as a consequence these errors affect the functioning where constant output voltage operation is a must, regardless of the changes in load up to certain extent. Sliding Mode Control can handle huge non-linearities in the systems and ensures stability with respect to load and source variations as well. Despite having exceptional error reduction calibre, these controllers have least behavioural interference in the characteristics of the system on which these controllers are deployed upon. This paper focuses on the small signal (small ac disturbance) analysis of the boost converter for the continuous conduction mode(CCM) and the close loop controlling of the boost converter using sliding mode control(SMC). With these controllers in effect an authentic study has been done for output voltage and current of the converter under different load and source variations. Effects of changes in ESR (effective series resistance i.e rC) on these controllers is also brought into light in this paper and the results are recognised to be evident and substantial using MATLAB as testing platform.
Effects of post-annealing on texture evolution of sputtered ScAlN films

The piezoelectric response of the sputtered scandium aluminum nitride (ScAlN) film are highly dependent on its crystallinity. The film texture continues to develop during the post-annealing process at high temperatures. In this work, the annealing experiments at temperatures up to 1000 °C were conducted on the sputtered ScAlN/Mo film stacks. Temperature dependences of the crystal structure and the stress were evaluated and discussed. The interface between the ScAlN film and the bottom Mo electrode is also inspected to assess the thermal stability. Our results would contribute to the robust piezoelectric device development.
Ethnobotanical Appraisal and Conservation Status of Medicinal Plants in Hindukush Range, District Swat, Pakistan

ABSTRACT This study documented ethnobotanical information of medicinal plants and their conservation status in Chail Valley, Dabargai, Shinko and Bishigram areas in Hindukush range, District Swat, Pakistan during 2012–2016. A total of 174 plants were recorded as ethno-medicinally important. The area represented 167 species of angiosperms (95.97%) and 7 species of gymnosperms (4.02%). Family importance value (FIV) indicated that Lamiaceae (97.94) was the leading family that contributed the largest number of species, followed by Rosaceae (91.09), Solanaceae (83.13), Asteraceae (76.02), Moraceae (70.54), Apiaceae (67.12), and Polygonaceae (60.95). Local inhabitants used them in treating digestive disorders, as tonics, to relieve fever, and to expel worms from the abdomen. The ethnoflora was found to be under severe biotic and abiotic stresses. The data of conservation status revealed that most of the medicinal plants were rare (107 spp.), followed by vulnerable (42 spp.), infrequent (24 spp.) and Melia azedarach as endangered species.
Experimental Validation of a New Method for 3-D Vector Flow Imaging in the Frequency Domain

Current 3-D Vector Flow Imaging (VFI) techniques are typically limited by either low temporal resolution and/or high computational cost. In this work, we illustrate a 3-D high frame rate VFI method, which efficiently splits the 3-D (x, y, z) displacement estimation in two separate 2-D VFI estimations operated in the frequency domain. The echo-data received after the transmission of plane waves are beamformed and high-pass filtered before being VFI processed. The new method was experimentally tested by using the ULA-OP 256 research system connected to a 3 MHz, 256-element, 2-D spiral array. Phantom experiments were conducted in steady laminar flow conditions for different probe-to-flow angles. For the tested conditions, the mean relative bias was 11.5% with a standard deviation of 10.9%. The 2-step approach applied to the 2-D VFI technique makes the new 3-D VFI method accurate and computationally efficient.
Axial Super-Resolution Study for Optical Coherence Tomography Images Via Deep Learning

Optical coherence tomography (OCT) is a noninvasive, high resolution, and real-time imaging technology that has been used in ophthalmology and other medical fields. Limited by the point spread function of OCT system, it is difficult to optimize its spatial resolution only based on hardware. Digital image processing methods, especially deep learning, provide great potential in super-resolving images. In this paper, the matched axial low resolution (LR) and high resolution OCT image pairs from actual OCT imaging are collected to generate the dataset by our home-made spectral domain OCT (SD-OCT) system. Several methods are selected to super-resolve LR OCT images. It is shown from the experimental results that the residual-in-residual dense block network (RRDBNet) trained with different loss functions performs the best super-resolution for OCT images, and it is demonstrated from the preliminary results that deep learning methods have good generalization and robustness between OCT systems. We believe deep learning methods have broad prospects in improving the quality of OCT images.
Machine learning for drone operations: challenge accepted

Machine learning is among the top research topics of the last decade in terms of practicality and popularity. Though often unnoticed, machine learning guides many aspects of our lives since its introduction via the big tech companies. Its abilities rise, defeating 9-dan Go professional, their accuracy increase, enabling smooth voice recognition, adding intelligence to our daily lives. However, its development is mostly supported by high tech companies for now rather than the public, or regulations, who show increasing concern about its usage. Despite some reluctance, machine learning has started to appear in aviation as well. Operational improvements were among the first applications. In this paper, we offer to present an introduction to machine learning, compare it with well known modeling techniques by giving an example from aviation and question their fitness for certification. We discuss the enablers and try to understand the limitations that might result or prevent the use of machine learning on certified safety systems. Similar considerations are held for systems that do not require certification, but need to be taken into account in risk analysis methods. The ultimate purpose of this paper is to highlight the existing challenges which prevent machine learning algorithms from having a wider role in drone avionics, and more generally in aviation.
Stability Control Design for TAB-Based Three-Port Bidirectional DC/DC Converters in PV-Battery Grid-Connected Applications

As affected by climate conditions, e.g. solar irradiation and temperature, the output power of photovoltaic (PV) generation is generally random and intermittent. Energy storage devices like batteries are thus necessary to be incorporated in a PV system to smooth the output power. In order to connect the PV-battery to the DC grid, a three-port bidirectional DC/DC converter based on the triple-active-bridge (TAB) topology is a superior choice. Such three-port converter is a strongly coupled system, which demands decoupling control methods to obtain independent control of input/output power in each port. However, the conventional control strategy with decoupling control cannot suppress the filter resonance in DC-grid-port effectively and could lead to the converter output current instability. Therefore, a stability control design for TAB-based three-port bidirectional DC/DC converters is proposed in this paper. It can manage the power flow among the ports with reliability and maintain the system stable operation. Simulation results are finally presented to verify the proposed control design.