Miracle-dz/UniFAR-FTUs huggingface dataset:
A remote sensing image target recognition method based on improved Mask-RCNN model

As an important branch in the field of machine vision, target detection and recognition technology have important applications in various fields. In view of the fact that the general target detection and recognition model does not perform well in remote sensing images, and there’re large amount of different size targets need to be recognized. On the basis of Mask R-CNN model, one of the classic target detection and recognition model, this paper proposes A target recognition and detection method that integrates data enhancement processing and improves the Mask R-CNN backbone network FPN to RFP. When inputting image data, perform random enhancement processing on the data, randomly cut the image, and randomly merge; when extracting features, improve the FPN in the original Mask R-CNN model to RFP to make the extracted features better Reflecting the original picture information, experiments have shown that this model has a good performance in fine-grained target recognition in remote sensing images. On the same data set, its evaluation indicators are superior to other comparison algorithms in all aspects.
Spectrum Sharing Incentive for Legitimate Wireless Information Surveillance

In this paper, spectrum sharing incentive for legitimate wireless information surveillance at the physical layer is investigated. The concept behind this is that authorized government agencies want to eavesdrop the communication between a suspicious source-destination pair, and stimulate the help of another source-destination pair (referred to as secondary users) looking for transmission opportunities. We thus propose to let the secondary receiver act as a monitor to eavesdrop the suspicious communication and let the secondary transmitter act as a friendly jammer to improve the eavesdropping performance, such that they are granted to share the spectrum of the suspicious users, as a reward. To guarantee the eavesdropping performance, the successful eavesdropping probability is required to be larger than that with passive eavesdropping. The problems of jointly optimizing the transmit power of the secondary transmitter and the successive interference cancellation (SIC) decoding order at the secondary receiver to maximize the average secondary transmission rate and minimize the secondary transmission outage probability are investigated. Two scenarios are considered for the availability of the channel state information (CSI). The first scenario assumes perfect CSI, and the optimal strategies for the transmit power control and the SIC decoding ordering are derived. The second scenario assumes partial CSI, where the instantaneous CSI of the secondary transmission link and the statistical CSI of the links related to the suspicious communication are available, and the optimal strategies for maximizing an approximate average secondary transmission rate and minimizing an approximate secondary transmission outage probability are proposed. Extensive simulation results validate the effectiveness of the proposed strategies.
Study of the Complex Permittivity of a Polyurethane Matrix Modified by Nanoparticles

This study presents the influence of various types of nanoparticle (NP) fillers incorporated into a polyurethane (PU) (VUKOL 022) matrix and its subsequent changes in complex permittivity. Two types of surface modification of SiO<sub>2</sub> fillers were investigated. The frequency dependence of the real and imaginary parts of complex permittivity was measured within the frequency range of 1 mHz to 1 MHz using the capacitance method. The 1 wt. % NPs in PU caused an increase (MgO, TiO<sub>2</sub>, n-SiO<sub>2</sub>, and f-SiO<sub>2</sub>) or a decrease (d-SiO<sub>2</sub>) in the real permittivity. The <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>-relaxation and intermediate dipolar effect were observed at the temperature dependence of the imaginary permittivity. The change in permittivity by various surface modifications of SiO<sub>2</sub> and other nanofillers was discussed based on the multi-core model. Moreover, the NPs caused a shift in the local maximum of the permittivity, which was a result of the interfacial polarisation and a charge multiplication of the <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>-relaxation process.
Optimal Massive-MIMO-Aided Clustered Base-Station Coordination

A large-scale clustered massive MIMO network is proposed for improving the spectral efficiency of the next-generation wireless infrastructure by maximizing its sum-rate. Our solution combines the advantages of the centralized processing architecture and massive MIMO. Explicitly, the network is divided into multiple clusters; each cluster is handled by a centralized processing unit, which connects to a certain number of massive MIMO-aided BSs, where only limited information is exchanged among the clusters; each user of a cluster can be served by several nearby BSs in a user-centric way. We analyze the maximum sum-rate of the network with multiple antennas at BSs and UEs, relying on the optimal transmit precoder matrix of each BS configured for each user, and on the optimal frequency-domain power sharing scheme of each cluster. The optimizations are conceived for multiple coordination schemes that were widely studied in literature, namely the coherent-joint-transmission (CJT) scheme, the non-coherent-joint-transmission (NCJT) scheme and the coordinated-beamfoming/scheduling (CBF/CS) scheme. Our simulations show that the optimal CJT achieves 2.2 – 4.5 times higher average sum-rate than its non-cooperative massive MIMO network counterpart, while the optimal NCJT and the optimal CBF/CS achieve at most a factor 1.3 average sum-rate gain. The popular signal-to-leakage-and-noise-ratio (SLNR) scheme is also extended to the multi-antenna UE scenario and achieves a factor 1.1 – 1.2 gain.
Visual Heading Estimation for UAVs in Indoor Environments

Recently, The UAV (Unmanned Aerial Vehicle) industry is getting a lot of attention, especially for very small drones that could fly indoors. Such a small drone can help perform rescue tasks such as investigating gas leaks or emergency situation that imposes risk on human intervention. Additionally, the UAVs can be utilized for indoor inspection and 3D mapping. The indoor environment is very challenging for the UAVs since the Global Navigation Satellite System (GNSS) cannot be reliably accessed to help UAV to locate itself. Various sensors could be mounted on UAVs to help the surveillance and navigation aspects of the operation. Range sensors such as 2D Lasers and LIDAR are very useful for providing valuable measurements towards reliable localization algorithms. Including such sensors will typically raise the system cost and limit the flight time due to increased power consumption. This research aims to assess the potential of using the typically installed UAV main camera to help estimate the UAV heading. The typical indoor environment includes many challenging situations such as monochrome surfaces and identical repeated patterns, especially in the ground surface. The research investigates the performance of different heading estimation approaches using a minimum cost configuration (without laser scanners). The proposed integration between the drone forward camera and the downward camera enhanced the navigation result compared to the other individual solutions using the downward camera only, forward camera only, or magnetometer. The performance of the investigated approaches in a real indoor flight is presented and discussed.
Research on Invasive Insect Image Recognition Based on Artificial Intelligence

The problem of invasive insect image accuracy identification is diffcult when the proportion of right samples is small and the quality of image is not very high. This article proposes a TRML (Transfer-Residual-network-Maximumentropy-Learning) model that can effectively identify invasive insects in a large amount of information. It compensates for the small proportion of invasive samples and low sample quality that often exist in actual intrusion problems. This article takes the Asian Hornet invasion of North America as an experiment, it show that the accuracy of the model test reaches 94.25%, and it indicates that the accuracy of the sample can be significantly improved. It also provides a new solution for solving this kind of feedback identification problem.
MCTA: Multi-UAV Collaborative Target Allocation to Monitor Targets with Dynamic Importance

With the development of mechanical manufacturing, wireless communication, and other related technologies, unmanned aerial vehicle (UAV) has become a typical paradigm of IoTs. The emergence of multi-UAV collaboration technology is expected to compensate for the shortcomings of a single UAV, which has become an important research point of IoT applications. The collaboration of multi-UAV is generally driven by scenarios, so we firstly abstract these scenarios into the target allocation problem. Then, we model the constraint of geographic space as an undirected weighted graph. Through a series of rigorous mathematical derivation and theoretical proof, the multi-UAV collaborative target allocation is modeled as a variable scale assignment problem, whose objective is to minimize the battery consumption. Based on that, a heuristic task scheduling algorithm named MCTA is proposed. Through the simulation experiments, the performance of MCTA is effectively evaluated. Compared with three comparison algorithms, MCTA shows many advantages in terms of effectiveness, energy saving, and overall balance.
A Capacitive Microwave Sensor With Guard Electrodes for Biological Cell Characterization

Parallel plate capacitor configurations are common for permittivity measurements. Depending on the exact geometry of the plates, the contribution of the usually unwanted fringing fields can be significant. At low frequencies, this effect can be simply avoided by means of properly driven guard electrodes. This way, only the approximately homogeneous field beneath the main electrode is measured. This paper proposes a microwave implementation of such a sensor and a simple method based on scattering parameter measurements for permittivity extraction. The intended application is the size independent assessment of biological cell properties in a microfluidic setup. The paper presents simulation results for a parallel plate cell sensor without and with a guard electrode. Experimental verification is provided with a scaled version realized in printed circuit board technology. The measurements are performed on a dielectric slab at different positions.
Channel Estimation for Millimeter Wave Massive MIMO Systems Using Separable Compressive Sensing

Channel estimation is a fundamental problem for downlink transmission in millimeter wave (mmWave) multiple input multiple output (MIMO) systems. This paper proposes a channel estimation algorithm by exploiting the separable structured sparsity of mmWave massive MIMO channel. The mmWave downlink channel is firstly formulated as a two dimensional (2D) separable compressive sensing (CS) model according to the sparsity structure of the channel in angle of arrivals (AoAs) and angle of departures (AoDs) domains. Then a separable compressive sampling match pursuit (SCoSaMP) algorithm is proposed to solve the separable CS recovery problem for channel estimation. Based on the separable sparsity structure of the channel, we design the precoding and combining matrices under the metric of mutual information to further improve the performance of channel estimation. Simulations demonstrate the advantages of the proposed algorithm over the traditional CS-based channel estimation methods.
Investigating Effect of Students' and Coaches' emotional intelligence on academic achievement with mediation of sport success

This research aims to study the effect of students’ and coaches’ emotional intelligence (EI) on academic achievement (AA) with mediation of sport success (SS). This is a causative research and it is applied research in terms of the purpose. The population consists of second grade students and their coaches. For sampling, 33 sport teams were identified that had 347 second grade students, and the research questionnaires were distributed among them. The results showed that EI of students and coaches have significant effect on SS. In addition, students’ EI have a significant effect on AA. Also, the EI of students and coaches have indirect effect on AA through SS. Finally, considering the importance of EI, coaches and students should perceive the EI functions and aspects to utilize it in different situation.
COMBINING ELECTROSPUN FIBER MATS AND BIOACTIVE COATINGS FOR USE IN VASCULAR GRAFT PROSTHESES

École Polytechnique de Montréal, Montreal, QC, Canada (1Institute of Biomedical Engineering, 3Department of Chemical Engineering, 5Department of Engineering Physics) 2 Laboratory of Endovascular Biomaterials (LBeV), Research Centre, Centre Hospitalier de l’Université de Montreal (CRCHUM), Montreal, QC, Canada 4 Department of Mechanical Engineering, École de technologie supérieure, Montreal, QC, Canada
Navigating through hydrogen

However, production of hydrogen in the EU is currently emissions intensive. Hydrogen supply could be decarbonised if produced via electrolysis based on electricity from renewable sources, or produced from natural gas with carbon, capture, and storage. The theoretical production potential of low-carbon hydrogen is virtually unlimited and production volumes will thus depend only on demand and supply cost.
The Mortgage Piggy Bank: Building Wealth through Amortization

Mortgage amortization schedules are among the largest savings plans in the world (ex. U.S. households contribute hundreds of billions of dollars annually to these “mortgage piggy banks”). However, little is known about their effects on wealth accumulation. Ex-ante, the effect is unclear. It depends on the fungibility of home equity and other savings, and households’ willingness to adjust consumption or leisure. Empirically, effects are difficult to identify since amortization and other savings choices are typically co-determined. We overcome this challenge by utilizing a 2013 Dutch reform that increased amortization requirements for new mortgages. Using detailed administrative data, we compare savings decisions for home-buyers right before or after the reform. We use plausibly exogenous variation in the timing of home purchase coming from life-events (ex. birth of a child) to address selection concerns. We find that marginal wealth-building from amortization (MWA) is substantial. Remarkably, households leave non-mortgage savings untouched and cut consumption and leisure instead, implying a near 1-for-1 rise in net-worth. Results hold five years out when the additional amortization-induced home equity is larger than the stock of liquid savings, suggesting substantial amounts of amortization-driven wealth-building over a typical business cycle. Effects are ubiquitous and hold for unconstrained households, who could easily offset the additional amortization by reducing non-mortgage savings, and movers, suggesting a broad applicability of our results. Overall, our results highlight the critical importance of mortgage amortization for household wealth-building and macroprudential policies.
The Effects of Mixed Vitamins, Minerals, Fatty Acids and Amino Acids Supplementation into Drinking Water on Broiler Chickens Performance and Carcass Traits

1 Animal Science Study Program, Faculty of Agriculture and Animal Science, State Islamic University of Sultan Syarif Kasim, Pekanbaru, Riau 28293, Indonesia 2 Graduate School of Nutrition and Feed Science, Faculty of Animal Science, IPB University, Bogor, Indonesia 3 Animal Science Study Program, Faculty of Agriculture, Universitas Tanjungpura, Pontianak 78115, Indonesia 4 Department of Pathology, Faculty of Veterinary Medicine, Universitas Wijaya Kusuma Surabaya, Surabaya 60225, Indonesia 5 Research Unit for Natural Products Technology (BPTBA), Indonesia Institute of Sciences, Yogyakarta, Indonesia 6 Vocational School, Universitas Sebelas Maret, Surakarta 57126, Indonesia *Corresponding author's Email: sadarman@uin-suska.ac.id ; ORCID: 0000-0002-9632-8478 **Corresponding author's Email: a.irawan@staff.uns. ac.id ; ORCID: 0000-0003-1179-0469 Received: 02 Jan. 2021 Accepted: 16 Feb. 2021 ABSTRACT
An Approach to Analyze Quality of Service

: In this paper, we review the basic of Quality of Service. The key idea is to decouple congestion measure from performance measures such as loss, queue length or delay. The resources that network needs to manage are buffer and bandwidth. Specifically, paper starts by introducing the services in QoS, buffer management scheme and scheduling. Scheduling mainly used to distinguish between the packets that selected by the scheduler for further processing. Its main goal is to improve the QoS. Buffer management used to control traffic fairly and efficiently. Also, includes two QoS framework. Integrated services (intserv) and differentiated services (diffserv). IntServ uses RSVP to reserve resources whereas DiffServ controls network traffic. Congestion in network occurs due to exceed in demand as compared to the capacity of the resources. At the end, an effort has been made to judge the performance of Drop Tail and RED. The RED introduces randomness to overcome the problem of global synchronization.
Khamuliak N. V. MULTIFACETED TEACHERS’ ROLE FOR INCREASING STUDENTS’ MOTIVATION

The purpose of this article is to explore the role of teachers in promoting students’ motivation and its in uence on students’ overall success. Due to the recent increase in popularity of distance learning, abundancy of various online courses and availability of easily accessed information the role of teachers in the learning process is being diminished. However, a close study of the factors which motivate students’ learning proves that teachers’ role is crucial for both academic and social success. The research also identi es the main types of motivation such as intrinsic and extrinsic with the former being of greater importance for students’ success as it causes the desire to learn without any external pressure or rewards. This motivation may be in uenced for the bene ts of the students by means of adequate teacher’s guidance.
Corticospinal excitability remains unchanged in the presence of residual force enhancement and does not contribute to increased torque production

Background Following stretch of an active muscle, muscle force is enhanced, which is known as residual force enhancement (rFE). As earlier studies found apparent corticospinal excitability modulations in the presence of rFE, this study aimed to test whether corticospinal excitability modulations contribute to rFE. Methods Fourteen participants performed submaximal plantar flexion stretch-hold and fixed-end contractions at 30% of their maximal voluntary soleus muscle activity in a dynamometer. During the steady state of the contractions, participants either received subthreshold or suprathreshold transcranial magnetic stimulation (TMS) of their motor cortex, while triceps surae muscle responses to stimulation were obtained via electromyography (EMG), and net ankle joint torque was recorded. B-mode ultrasound imaging was used to confirm muscle fascicle stretch during stretch-hold contractions in a subset of participants. Results Following stretch of the plantar flexors, an average rFE of 7% and 11% was observed for contractions with subthreshold and suprathreshold TMS, respectively. 41–46 ms following subthreshold TMS, triceps surae muscle activity was suppressed by 19–25%, but suppression was not significantly different between stretch-hold and fixed-end contractions. Similarly, the reduction in plantar flexion torque following subthreshold TMS was not significantly different between contraction conditions. Motor evoked potentials, silent periods and superimposed twitches following suprathreshold TMS were also not significantly different between contraction conditions. Discussion As TMS of the motor cortex did not result in any differences between stretch-hold and fixed-end contractions, we conclude that rFE is not linked to changes in corticospinal excitability.
THE ESTIMATION OF CONTROL SYSTEMS STABILITY BOUNDARIES BY THE DESCRIBING FUNCTION METHOD BY EXAMPLE OF AIRCRAFT

In this paper, the conditions for periodic modes formation in the closed-loop pilot-vehicle system in the compensatory control mode are established. The case of high gain pilot task is considered under the conditions of a sudden disturbance, as well as under the influence of the system nonlinearities, such as actuator position and rate limit. Sinusoidal input describing function method and parametric resonance equation were used to determine the onset conditions for self-oscillations and forced oscillations. The case when this methods lead to erroneous results is established. The numerical limits of permissible pilot gain, time delay and reference signal at which unstable periodic modes do not arise are calculated.
Reconstruction of brown bear population dynamics in Slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data

Reliable data and methods for assessing changes in wildlife population size over time are necessary for management and conservation. For most species, assessing abundance is an expensive and labor-intensive task that is not affordable on a frequent basis. We present a novel approach to reconstructing brown bear population dynamics in Slovenia in the period 1998-2019, based on the combination of two CMR non-invasive genetic estimates (in 2007 and 2015) and long-term mortality records, to show how the latter can help the study of population dynamics in combination with point-in-time estimates. The spring (i.e. including newborn cubs) population size estimate was 383 (CI: 336-432) bears in 1998 and 971 (CI: 825-1161) bears in 2019. In this period, the average annual population growth rate was 4.5 %. The predicted population size differed by just 7 % from the non-invasive genetic size estimate after eight years, suggesting that the method is reliable. It can predict the evolution of the population size under different management scenarios and provide information on key parameters, e.g. background mortality and the sex- and age-structure of the population. Our approach can be used for several other wildlife species, but it requires reliable mortality data over time.
237-364 Tourism 2020 03ENG.indd

Th e purpose of the present study is to test a holistic destination loyalty model using the case of Budva in Montenegro. Th e model combines the following six variables: tourist satisfaction, loyalty and preferences, destination performance, perceived value and destination image. Th e structural equation modelling (SEM) approach is adopted. Model tests confi rm good fi t of the data to the proposed model and it is recommended to further validate the model using other destination settings.