Miracle-dz/UniFAR-FTUs huggingface dataset:
Queuing Model Based Edge Placement for Work Offloading in Mobile Cloud Networks

Recently, many useful services have been provided through wireless mobile devices. One of the critical issues is that mobile devices are generally built with limited computing capability, and thus may not be able to handle the complexity of many advanced services. This problem can be mitigated by offloading certain jobs from the mobile devices to the edge or cloud servers. However, the locations of the edge servers and the allocation of the offloading jobs to the edge servers can significantly affect the traffic generated in the network. Accordingly, this study conducts an investigation into the edge server placement and work allocation strategy with a focus on minimizing the total traffic load so as to achieve green communications in the mobile cloud networks. Mobile devices are assumed to be attached to the nearby node and they may send work offloading requests to the attached nodes. Meanwhile, edge servers are deployed at carefully selected nodes. The offloading jobs received by a node are assigned to a selected edge server. If the edge server is busy, the work will be forwarded to the central cloud server. Otherwise, it is processed locally in the edge server. A queuing model is adopted to evaluate the job forwarding probability at the edge servers. The problem is formulated as an integer programming problem. Two novel heuristic schemes are proposed, namely the Set-by-Set algorithm and the $K$ -clustering algorithm. The simulation results showed that the $K$ -clustering algorithm consistently outperforms both the Set-by-Set algorithm and the Density-Based-Clustering (DBC) algorithm presented in the literature in terms of a lower total traffic load within the network.
Design of a Microstrip Diplexing Filtering Power Divider

A diplexing filtering divider is proposed by using arbitrary even-order Butterworth-type filtering transformers and two extra matching lines. The matching design is similar to that of the T-junction design of a conventional diplexer. Therefore, the required matching conditions can be easily achieved by designing two properly 50-Ω lines. The proposed circuit has been carefully examined for a diplexing 2nd-order filtering divider.
Microwave Confocal Imaging by Antenna Grouping Method for Medical Application

This paper introduces an antenna grouping method based on the principle of confocal imaging method. In view of the fact that traditional multistatic array confocal imaging method requires high computation time which hinder its application in rapid diagnosis, the proposed antenna grouping methods only uses the multistatic data among antennas within each group. The data between the antennas from different groups are not considered, which is more efficient to reconstruct the image. The effectiveness of the proposed method is verified by computer simulation and experiment.
Syntax-aware Transformer Encoder for Neural Machine Translation

Syntax has been shown a helpful clue in various natural language processing tasks including previous statistical machine translation and recurrent neural network based machine translation. However, since the state-of-the-art neural machine translation (NMT) has to be built on the Transformer based encoder, few attempts are found on such a syntax enhancement. Thus in this paper, we explore effective ways to introduce syntax into Transformer for better machine translation. We empirically compare two ways, positional encoding and input embedding, to exploit syntactic clues from dependency tree over source sentence. Our proposed methods have a merit keeping the architecture of Transformer unchanged, thus the efficiency of Transformer can be kept. The experimental results on IWSLT’ 14 German-to-English and WMT14 English-to-German show that our method can yield advanced results over strong Transformer baselines.
A Hybrid 3D Printed K-Band Focal-Shifted Two-Dimensional Beam Scanning Lens Antenna with Non-Uniform Feed

A K-band (18-26.5 GHz) lens antenna that scans two-dimensionally is introduced. The novelties lie in three aspects: (a) The two-dimensional beam scannability is achieved by deploying the feed in a focal-shifted manner. (b) Feed of nonuniform aperture is applied to compensate the gain loss due to aperture tapering from the lens. (c) It takes the form of a fully 3D printed lens antenna, in which the metallic and dielectric 3D printing technologies are used for the lens and feed fabrication respectively. The antenna features high gain, good matching and two-dimensional beamscanability.
Design of Bi-Level-Microstrip Quadrature Directional Couplers with Indirectly Coupled Lines

In the paper the design of coupled-line directional couplers is presented in which the lines are not directly coupled. Instead an additional conductor is utilized to provide the coupling between the two transmission lines. The proposed realization technique is easily applicable in practical designs and the design procedure does not require advanced analysis of multi-conductor coupled lines, instead a simple calculator for single microstrip line is required.
The Dependence of the Fibrillation Cycle Fraction on which the Defibrillation Pulse is Effective on the Pulse Energy

Based on the data of modeling the response of a cardiomyocyte in a state of simulated fibrillation to rectangular defibrillation pulses, diagrams of the dependence on the energy of the defibrillation pulse of the fraction of the fibrillation cycle were constructed, on which the defibrillation pulse causes a long-term extension of the refractory period of cardiomyocytes (defibrillation completeness index). The constructed diagrams showed that the long-term extension of the refractory period of cardiomyocytes on a part of the fibrillation cycle is achieved at a pulse energy lower than the excitation energy. Presumably, such pulses provide safe low-energy defibrillation. The defibrillation completeness index of safe low-energy defibrillation pulses increases with increasing pulse duration. Guaranteed defibrillation is achieved when the defibrillation pulse causes the extension of the current refractory period of cardiomyocytes to a value of the pulse repetition period of fibrillation and more. The energetically optimal pulse duration of guaranteed defibrillation is approximately 2 times higher than the energetically optimal pulse duration of the excitation. The relative threshold energy of the pulses providing guaranteed defibrillation at pulse durations shorter than the optimum significantly exceeds the values corresponding to the Hoorweg–Weiss–Lapicque law.
Convergence of Recommender Systems and Edge Computing: A Comprehensive Survey

Under the explosive growth of information available on the Web, recommender systems have been used as an effective technology to filter useless information and attempt to recommend the most useful items. The proliferation of smart phones, smart wearable devices and other Internet of Thing (IoT) devices has gradually driven many novel emerging services which are latency-sensitive and computation-intensive with a higher quality-of-service. Under such circumstances, the data sources contain four key characteristics (i.e., sparsity, heterogeneity, mobility, volatility). The conventional recommender systems based on cloud computing are incapable of digging the information of user demands. Mobile edge computing is a novel computing paradigm via pushing computation/storage resource from the remote cloud servers to the network edge servers to provide more intelligent and personalized service. This paper comprehensively reviews the state of the art literature on the convergence of recommender systems and edge computing, and identify the future directions along this dimension. This paper can provide an array of new perspectives on the convergence for researchers, practitioners, and tap into the richness of this interdisciplinary research area.
Guaranteed Cost Consensus for Fuzzy Multi-Agent Systems With Switching Topologies

This paper concentrates on guaranteed cost consensus problem for nonlinear multi-agent systems (MASs) under directed switching topologies. First, a novel polynomial fuzzy model is constructed for describing the nonlinear error MASs that are formulated by follower agents and a leader agent. Then, a consensus tracking protocol is devised to ensure that the MASs with changing topologies can achieve agreement. For the established fuzzy MASs, guaranteed cost function is introduced based on error states and control inputs. By the multiple polynomial Lyapunov function, we present relaxed sufficient condition to reach consensus with a guaranteed cost for the fuzzy MASs. Moreover, the designed consensus protocol can realize guaranteed cost by the upper bound for any initial error state. The obtained condition is converted to sum of squares and solved numerically. Finally, an example is given to illustrate the validity of the proposed consensus technique.
Practical Homotopy Methods for Finding the Best Minimum-Fuel Transfer in the Circular Restricted Three-Body Problem

Finding a solution to a low-thrust minimum-fuel transfer trajectory optimization problem in the circular restricted three-body problem (CRTBP) is already known to be extremely difficult due to the strong nonlinearity and the discontinuous bang-bang control structure. What is less commonly known is that such a problem can have many local solutions that satisfy all the first-order necessary conditions of optimality. In this paper, the existence of multiple solutions in the CRTBP is fully demonstrated, and a practical technique that involves multiple homotopy procedures is proposed, which can robustly search as many as desired local solutions to determine the best solution with the optimal performance index. Due to the common failure of the general homotopy method in tracking a homotopy path, the parameter bounding fixed-point (PBFB) homotopy is coupled to construct the double-homotopy, which can overcome the difficulties by tracking the discontinuous homotopy path. Furthermore, the PBFB homotopy is capable to achieve multiple solutions that lie on separate homotopy path branches. The minimum-time problem is first solved by the double-homotopy on the thrust magnitude to infer a reasonable transfer time. Then the auxiliary problem is solved by the double-homotopy and the PBFP homotopy, and multiple local solutions with smooth control profiles are obtained. By tracking homotopy paths starting from these solution points, multiple solutions to the minimum-fuel problem are obtained, and the best solution is eventually identified. Numerical demonstration of the minimum-fuel transfers from a GEO to an Earth-Moon $L_{1}$ halo orbit is presented to substantiate the effectiveness of the technique.
Predicting Dropout Using High School and First-semester Academic Achievement Measures

Due to the big data accumulated in educational administrative systems and due to the advance of machine learning techniques, a new scientific discipline has emerged in the last few years, namely educational data science. An important research objective of this field is to predict dropout and improve graduation rates, in particular in STEM higher education.The goal of this study is to identify students at risk of dropping out at a large Hungarian technical university using predictive analytical tools. We use data of 10,196 students who finished their undergraduate studies (either by graduation or dropping out) between 2013 and 2018. We analyze dropout predictability in two main scenarios: first using data available at the time of enrollment, e.g. pre-enrollment achievement measures, and personal details, then in another scenario we supplement this feature set with first-semester performance indicators and use this richer set of attributes for further analysis. We apply artificial neural networks and boosting algorithms for prediction, and examine how the predictive power can be improved by the additional information. In other words, we study the incremental predictive validity of the early university performance indicators on graduation over the pre-enrollment achievement measures and vice versa.
Wideband Dipole Antenna and Array Based on Liquid Crystal Polymer for 5G Applications

In this paper, a wideband end-fire dipole antenna and array based on liquid crystal polymer (LCP) is proposed for fifth-generation (5G) applications. Meandered or bent arm is adopted in the dipole antenna design to reduce its size. Meanwhile, a director is added in front of the dipole, which not only improves the gain, but also generates a new resonance to expand the bandwidth. The simulated results show a wide bandwidth from 22.5 GHz to 30.2GHz with end-fire radiation and good beam steering characteristic. Two antenna prototypes, including an antenna element and an array are fabricated and the experimental results demonstrate good agreement with the simulated ones.
Linear Quadratic Gaussian Control of a Quadrotor with an Unknown Suspended Payload

The task of a quadrotor carrying an unknown suspended payload is difficult, as the payload has a considerable effect on the flight dynamics of the vehicle, the payload parameters are unknown and the payload state is not available for measurement. Linear Quadratic Gaussian control is considered to address the problem. The payload parameters are first estimated using Recursive Least Squares to estimate the payload mass and estimating the cable length from the oscillating frequency obtained with the Fast-Fourier Transform. These estimated parameters are used to design the Linear Quadratic Gaussian controller to simultaneously estimate the swing angle of the payload and apply full-state feedback control. These techniques are found to reduce the oscillations caused by the payload, even in the presence of sensor noise and external disturbances, which practical systems suffer from.
Comparison of DC voltage Control Strategies for Multi-terminal HVDC Network during AC Faults

Multi-terminal HVDC grid is one of the promising solutions of the electrical power network configuration that ensures the reliability of power supply and economy of the power generated from numerous renewable sources. The benefits of using HVDC grids are the possibilities of trading energy in different AC systems and transporting large scale of power over long distances. This paper will be showing the importance of DC voltage control strategies in a multi-terminal VSC-HDVC system following a system disturbance caused by an asymmetrical three-phase fault. Conventional and Droop methods are the two control strategies that will be compared in this paper. MATLAB/Simulink software simulator will be used to evaluate the response of a DC grid when a three-phase to ground AC fault occurs. The results show that droop-controlled DC grids are highly reliable during abnormal operating conditions compared to the conventional method.
Moving Objects Segmentation Method for Flight Vision Systems

In matters of ensuring the safety of the aircraft operations, it is especially important to provide the crew with the information about the runway condition and obstacles presence. The paper covers the objects segmentation method proposed for use on moving obstacles on the runway. The results of this work are relevant to the tasks of avionics, computer vision and image processing
A Tractable Approximation Approach to Deal with the Binary Nature of Shiftable Loads in Multi-Period Optimal Power Flow

Distribution systems are currently in a transitional phase, as they transform from passive to active. In the coming years, customer participation is expected to drastically increase, as an additional option for maintaining reliable operation of distribution systems and for supporting the distribution and transmission system operators' growing needs. Amongst the available customer-side technologies, the shiftable load (SL) has one of the highest electricity demands and complexity levels; modelling its operation requires a multi-period optimal power flow (MP-OPF) approach. The SL is traditionally modelled in a mixed-integer nonlinear programming (MINLP) setting using many binary variables. However, for larger problem sizes, the MINLP approach lacks tractability. This work proposes a novel NLP approximation of the classic MINLP SL modelling that accurately mimics a SL at the optimum. The proposed approach is validated in a day-ahead deterministic multi-period OPF on two small distribution networks. It is demonstrated that when convergence is achieved, it occurs much faster than for the original formulation. The approach's sensitivity to the chosen level of accuracy and the initialization point are also explored in order to determine the best way to further complement it.
Bone Mineral Density and Biomarkers of Bone Turnover in Young-Adult Females with and without Cognitive Eating Restraint

55 Introduction. 56 Subjects and Methods . 57 Results . 61 Discussion. 67 References . 71 BONE MINERAL MEASURES AND MARKERS OF BONE TURNOVER DO NOT DIFFER BETWEEN WOMEN WITH LOW AND HIGH COGNITIVE EATING RESTRAINT SCORES . 75 Abstract . 76 Introduction. 77 Experimental Subjects. 77 Materials and Methods . 78 Results . 82 Discussion. 97 Acknowledgements. 114 References . 114 A PROSPECTIVE EVALUATION OF DIETARY INTAKE, BONE MINERAL, AND MARKERS OF BONE METABOLISM IN WOMEN WITH HIGH AND LOW COGNITIVE EATING RESTRAINT . 124. 76 Introduction. 77 Experimental Subjects. 77 Materials and Methods . 78 Results . 82 Discussion. 97 Acknowledgements. 114 References . 114 A PROSPECTIVE EVALUATION OF DIETARY INTAKE, BONE MINERAL, AND MARKERS OF BONE METABOLISM IN WOMEN WITH HIGH AND LOW COGNITIVE EATING RESTRAINT . 124 MicroAbstract . 125 Abstract . 125 Introduction. 127 Materials and Methods . 127 Results . 132 References . 171 SUMMARY AND FUTURE DIRECTIONS. 179 APPENDIX. 182 REPEATED MEASURES ANALYSIS OF VARIANCE TABLES . 182 VITA. 188
X-band Absorber Integrated with A Low-frequency Transmission Performance

The design of an X-band absorber with a low-frequency transmission window is proposed. The structure is composed of an absorbing layer and a bandpass layer separated by dielectric substrates. The absorbing layer consisting of indium tin oxide film in the shape of square rings and the bandpass layer is a modified Jerusalem cross structured slot-type metallic patch. The proposed absorber is simulated and fabricated. Both fullwave simulation and measurement results show that the designed absorber exhibits a broadband absorption over the entire X-band frequency range with a transparency window in S-band under wide incidence angle. The proposed structure presents a promising prospect in novel absorber applications.
A Convolutional Attention Residual Network for Stereo Matching

Deep learning based on convolutional neural network (CNN) has been successfully applied to stereo matching, which has achieved greater improvement in speed and accuracy compared with traditional methods. However, existing CNN-based stereo matching frameworks frequently encounter two problems. First, the existing stereo matching network has a large number of parameters, which results in too long matching running time since excessive network width and excessive number of convolution kernels. Second, in some areas where reflection, refraction and fine structure may lead to ill-posed problems, the disparity estimation errors can be occurred. In this paper, we proposed a lightweight network, convolution attention residual network (CAR-Net), which can balance the real-time matching and matching accuracy for stereo matching. Besides, a multi-scale residual network called CBAM-ResNeXt, which combines attention, was proposed for features extraction. With an aim is to simplify the parameters of the network model by reducing the size of filters and to extract the semantic features such as categories and locations from the image through convolutional block attention module (CBAM). Here, the CBAM consists of channel attention module and spatial attention module, where the semantic information of the feature map can be fully maintained after the parameters were simplified. Moreover, we proposed a dimension-extended 3D-CBAM, which is connected to 3DCNN for cost aggregation. By combining these two sub-modules of attention, the network is guided to selectively focus on the foreground or background regions, so as to improve the disparity accuracy in the ill-posed regions. The experimental results showed that our proposed method generated high accuracy and optimized the velocity compared to the state-of-the-art benchmark on KITTI 2012, KITTI 2015 and Scene Flow.
A Comparative Study of License Plate Detection and Recognition Techniques

This paper reviews several works on license plate detection and recognition (LPDR) techniques. LPDR system detects license plates from images and recognizes what is written in the license plate. The importance of LPDR system is increasing day by day. Starting from imposing traffic rules to security measures, everywhere in traffic management system, automation is one of the most important tasks. Some most recent approaches of LPDR system have been discussed and their relative performances have been analyzed in this paper. The applications, advantages and limitations are also discussed based on the approaches. A comparative study is shown based on their suitability on several aspects such as performance, detecting capability of multiple license plates, detecting capability of oblique license plate, scale adaptiveness and sensitivity to noise.
Clustering-Based Emotion Recognition Micro-Service Cloud Framework for Mobile Computing

In a situation where life becomes more stressful and challenging, people feel compelled to be more concerned about their mental situation. Different emotional statuses are external reactions to different mental states. Therefore, researchers always identify people’s mental situation by monitoring their real-time emotions. At the same time, due to the availability of built-in sensors in a smartphone, applications that can identify real-time emotions of mobile users are constantly emerging. However, compared to most emotion recognition algorithms, computing resources and battery life in mobile phones are always limited. This makes accuracy and latency of these applications are unsatisfactory. In this paper, we propose a micro-service platform for mobile emotion recognition application developers (MSPMERAD) which can supply high performance. First, a classifier fusion emotion recognition algorithm is proposed by using a dynamic adaptive fusion strategy. Second, this new algorithm is encapsulated into a micro-service. With other affiliated micro-services such as data uploading, preprocessing, etc., developers can ignore the implementation of the emotion recognition algorithm and just focus on how to collect sensor data and interact with users. The accuracy and latency of one application based on the MSPMERAD are compared with another application that is implemented using a locale emotion recognition algorithm. Experiments based on the daily behavior data of 50 student volunteers show that the application based on our platform has higher recognition accuracy with a more reasonable time.
Gain Enhancement of Flexible Power Transfer Antenna using Frequency Compensation

This research is on an antenna gain enhancement of a flexible antenna for electromagnetic wave based power transfer system. Especially, it is about the change of the center frequency and the compensation method when the flexible antenna is bent. For this purpose, a patch antenna was designed using Polydimethylsiloxane(PDMS), which is a representative flexible substrate, and the variation of center frequency according to the degree of bending was measured. As a result, it was confirmed that when the antenna is bent outward, the inductance increases and the center frequency increases. To improve this, a capacitor was added to compensate the frequency. In conclusion, we could compensate the shifted frequency with the initial center frequency and improve the antenna gain up to 1.7dBi.