Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of an Embedded System for Use in Real-Time Intelligent Traps to Detecting Fruit Fly (Diptera:Tephritidae)

Fruit flies affect direct and indirect the fruit production, causing damage and losses in a worldwide scale. The control of fruit flies is usually done in an unregulated way, using insecticides in the form of bait-toxic, without knowledge of the infecting species. This work presents the development of an embedded system based on optoeletronic sensor to be used in an McPhail intelligent trap, sending remotely the data related to the fruit flies through a wireless protocol with low power consumption and wide range.
Reduction Factor Approach to Improve the Performance of Soft Output Viterbi Algorithm in AWGN Channel

Turbo Codes are considered the paramount channel coding technique due to its significant performance with guaranteed Quality of Service (QOS) that is highly suitable for advanced wireless applications. Complexity of these codes, particularly their decoders are considered a major hindrance for practical implementation. Turbo decoder uses Maximum A posteriori Probability (MAP), Logarithmic MAP (Log-MAP) and Soft Output Viterbi Algorithm (SOVA) for decoding. The MAP decoding algorithm is optimal but computationally intense and hence they cannot be implemented in real time systems. So, simplified and sub-optimal algorithms like Log-MAP and SOVA are used for practical implementation. Sub-optimal performance of SOVA is slightly attributed to over optimistic estimation of reliability values that can be reduced by Reduction Factor (RF) approach. This paper proposes the use of two RF values corresponding to each component decoder to reduce over optimistic effect in AWGN channel. RF values giving least Bit Error Rate (BER) for each $E_{b}/{N}_{0}$ are chosen using Matlab. The proposed SOVA with RF is analyzed in AWGN channel and the results provide superior performance of proposed algorithm with low BER and nominal complexity than SOVA and MAP algorithms respectively.
Partial Offloading in Energy Harvested Mobile Edge Computing: A Direct Search Approach

In the next generation wireless communication paradigm, the number of devices are expected to increase exponentially after the concept of Internet of Things (IoT). These devices are power constrained, with limited processing capability. Therefore, in order to get the maximum advantage from these low power IoT sensing devices, it is of utmost need to empower them. Similarly, the devices are not able to process the computationally intensive applications. In this work, Wireless Power Mobile Edge Cloud (WPMEC) is considered, which is an integration of Wireless Power Transfer (WPT) and Mobile Edge Cloud (MEC) to address low power devices’ battery and computational capabilities. The WPMEC is charging the devices in the first phase using the WPT and in the second phase, the devices are offloading their computational intensive data to the MEC. Partial offloading scheme is first time introduced and analyzed with WPMEC. Performance of proposed solution is evaluated in terms of overall network computational energy efficiency. Extensive simulations have been carried out to validate the proposed solution. It is shown that the proposed partial offloading scheme with WPMEC outperforms the binary and local computational schemes.
A Comparative study of parallel CPU/GPU implementations of the K-Means Algorithm

The K-Means algorithm is one of the most sophisticated and known algorithms for data-clustering. In this study, we will show the K-Means algorithm as it relates to OpenCL, which is a widespread parallel ecosystem that is reliable for processing and mining datasets that are large in scale. Additionally, we propose a comparative study of the three most efficient K-means algorithm implementations: The Lloyd-Forgy’s sequential Method Implementation, a parallel implementation targeting the CPU using OpenMP and finally one of the most complex implementations that uses an OpenCL language. Typically, the measure of performance is done using different data sizes. For large datasets under OpenCL, when comparing the GPU-based parallel algorithm to the CPU-based serial algorithm, the results have shown a good acceleration effect. On the other hand, for small data sets, the OpenMP implementation has turned out to be the best choice.
Two-dimensional Quasi-Bessel Beam Synthesis and Frequency-scanning Leaky-wave Launchers

In this paper, a technique to synthesize a 2D frequency-scanned high order Bessel beam in a parallel plates waveguide (PPW) scenario is presented. This technique is based on a one dimensional beam launcher, rather than the more typical axicons or the more recent metasurfaces and antenna arrays for 3D Bessel beam synthesis. With this launcher, it is possible to generate a 2D Bessel beams whose direction can be controlled by changing the frequency of the feeding signal in the Ku band from 14.5 GHz to 15 GHz. It is demonstrated how this can be done by combination of two leaky waves (LW), which can be created by the same 1D structure, scanning at different angles and launched to the PPW region. The beams are generated in a triangular area, with one of its sides being the launcher itself and the other sides are defined by the direction of radiation of each of the forming leaky waves.
UAVs’ autonomous collision avoidance in urban space*

Small UAVs are seeking wide usage in urban space for its advantageous performance. However, there are crowded with static and dynamic buildings, causing serious challenges for UAVs’ safety. This paper proposes a novel autonomous collision avoidance method based on time-obstacle dynamic map. First, the state estimation and trajectory prediction are performed based on extended Kalman filtering. Second, the time-obstacle dynamic map is constructed via introducing time axis. Third, the flyable paths are searched on the basis of breadth first approach and then the optimal path can be obtained through A-Star algorithm. Finally, the simulation results have shown that the proposed collision avoidance method can avoid immobile building and moving obstacles, and making a safe path for UAVs in urban space
Haze removal Methods: A Comprehensive Review

Outdoor scenes are usually affected by air particles and water vapor in the atmosphere. Haze is such phenomena happened due to atmospheric absorption and scattering. Haze affects the visibility and causes a degradation in the images quality of outdoor scenes, which in turn affects various image processing applications. In this paper, a review of the recent haze removal methods and its applications is introduced. The haze removal methods are categorized according to the input of their algorithm into two categories: multiple images and single image. Afterward, the different strategies in each category of the haze removal techniques are discussed and their characteristics are illustrated. Eventually, the quantitative parameters that evaluate the quality of the haze removed image are presented. This review paper highlights the importance of the haze removal methods in restoring a high-quality image relative to the quality of the original haze-free image. This haze removed image is a vital key in many computer vision applications including the visual navigation and object recognition and target detection.
Multimodal Biometric Verification using the Iris and Major Finger Knuckles

The drawbacks of unimodal biometric systems such as non-universality, noisy sensor data and spoofing can be mitigated using multiple biometric traits. In this study, a novel multibiometric system to authenticate users based on their major knuckle finger patterns using four fingers (i.e., little, ring, middle, and index) and iris is proposed. A local texture descriptor namely binarized statistical image features (BSIF) has been employed to extract the features for each of the biometric traits considered in order to improve biometric-based personal verification. The comparison results on PolyU contactless hand dorsal images database and IIT Delhi-1 iris database indicate that the proposed multibiometric authentication with grouping function based score fusion outperforms the existing transformation-based fusion approaches in literature (e.g., t-norms, symmetric-sum), attaining a correct recognition rate of 95.54%.
Examples of test calculations by the acoustic mode parabolic equation with the mode interaction and the elastic bottom

In this work a mode parabolic equation method for resonantly interacting modes accounting for the weak elasticity in the bottom is developed. The proposed method is tested numerically. The test calculations carried out for the ASA wedge benchmark prove an excellent agreement with the source images method for sufficiently small values of shear waves speed that are typical for soft sediments of the sea bottom.
Buffer Based Adaptation Using Scalable Video Coding for 360-Degree Video Streaming over NDN

360-degree video streaming is an important component of virtual reality. A video streaming server stores video streams with various quality levels. These streams are fragmented into several video segments. In 360-degree video streaming, these segments are tiled into video tiles. In general, the client changes the viewport quality level based on predictions of the user’s viewport and network throughput. In named data networking (NDN), the throughput measured at the client is not always stable due to network-inherent caching. Therefore, the viewport video quality changes (referred to as quality switching) frequently in 360-degree video streaming over NDN. In this paper, we propose buffer-based adaptation using scalable video coding for 360-degree video streaming over NDN. In the proposed method, a buffer-based adaptation algorithm and the prefetching of video tiles are used to avoid video quality switching. A simple performance evaluation using computer simulations shows that the proposed method reduces the quality switching compared with that for a rate-based adaptation algorithm.
A Motion Control Scheme for a WMR Based on Input-Output Feedback Linearization and PID

This paper presents a trajectory tracking control scheme for an underactuated wheeled mobile robot (WMR). The WMR model used includes the robot kinematics and dynamics, as well as some DC motor nonlinearities. The proposed control scheme contains two loops: the inner one is a PID controller that handles the dynamics, and the outer one deals with the kinematics, using a input-output feedback linearization of the Follow the Carrot approach. Some different shapes of trajectories are devised in order to analyze the feasibility of the method.
SSSC Based Hybrid scheme for damping subsynchronous resonance

This paper proposed phase-imbalanced series capacitive $(\mathrm{C}_{\mathrm{c}})$ compensation technique and it is impressive in amplifying power system $(\mathrm{P}_{\mathrm{s}})$ dynamics. It has capability of damping the power sways in system additionally (SSR) Subsynchronous Resonance Swinging. The SCC (series capacitive compensation) technique is used for damping SSR oscillation by the use of SSSC based hybrid SCC scheme. In this scheme I have used SSSC in one phase in series with the series capacitive compensation, we called it as fix capacitor $(\mathrm{C}_{\mathrm{c}})$ and remaining duplet phases are compensated with fixed capacitor (C). Also make same comparative study analysis to know how this system works. The working and effectiveness of this particular proposed scheme evaluated on MATLAB simulation.
A Wideband Low Noise Flat Gain Amplifier for Interferometric Passive Microwave Imaging System

This paper proposes a two-stage broadband low noise amplifier for interferometric passive microwave imaging system using 0.15-μm GaAs pseudomorphic high electron mobility transistor (pHEMT) process. The first stage is designed for wideband input and noise matching using source degeneration. Frequency-controlled feedback amplifier is employed in the second stage to obtain flat gain across the bandwidth. Measurement results show that gain of the amplifier is larger than 18 dB from 3.6-9.4 GHz, and the gain flatness within 4–8 GHz is under $\pm 0.6$ dB. A minimum noise figure of 1.5 dB is obtained with input and output return loss both above 10 dB. The dimension of the chip is 1.5 $\times$ 0.8 m2.
Millimeter-Wave (MMW) Wideband Circularly Polarized Antenna Based on Gap-Waveguide

In this paper, a wideband end-fire circularly polarized (CP) antenna based on gap waveguide (GWG) is proposed for millimeter-wave (MMW) applications. The proposed CP antenna is composed of three layers of groove GWGs with two anti-symmetric triangular septum blades. The groove width is the same with WR-10, and the middle layer is used for feeding energy. The simulation results show that the antenna can achieve a 69.1% bandwidth for both axial ratio (AR)<3dB and $|{S}_{11}|$ <−10dB from 76.6GHz to 150.9GHz.
Multi-section Unequal Power Divider Using a Decomposition Method

This paper presents a multi-section unequal power divider using a decomposition method. This divider consists of a transmission line and a resistor-capacitor parallel circuit. The transmission line portion is implemented by decomposing an arbitrarily terminated transmission line into two transmission lines satisfying the power splitting ratio. These decomposed transmission lines can be divided into several transmission lines using a multi-section transmission line matching method. In addition, there is a resistor-capacitor parallel circuit to improve the matching and isolation characteristics of the output ports. To verify the feasibility of this method, we implemented a two and a three section unequal power divider with a splitting ratio of 1: 2 operating at a frequency of 2 GHz. The measured results were in good agreement with the simulated results.
Fuzzy Dynamic Gait Pattern Generation for Real-Time Push Recovery Control of a Teen-Sized Humanoid Robot

A fuzzy dynamic gait pattern generator, which allows a teen-sized humanoid robot to generate, in real-time, a suitable gait pattern when it is hit by an unexpected force, is proposed in this paper. Conventional gait pattern generators usually utilize the ideal Zero Moment Point (ZMP) to plan the trajectory of the Center of Mass (CoM), along with a cycloid to generate steps. However, pre-planned gait patterns cannot deal with unexpected situations, especially instances when the robot experiences an unknown force. Therefore, we propose a dynamic gait pattern generator that leverages the Virtual Force Linear Inverted Pendulum Model (VFLIPM) to adjust the trajectory of the CoM, and which detects balance status by estimating the trajectory of the ZMP using eight high-precision load cell pressure sensors mounted onto the robot’s soles. We integrate an accelerometer and the pressure sensors through a fuzzy controller to instantly respond to external forces and generate a suitable gait pattern. When the robot is pushed suddenly, it first adopts a pre-planned gait pattern to replace the current gait. At the same time, the fuzzy controller calculates the recovery gait, with appropriate strides and lean angles to absorb the impact. The proposed method is implemented on the teen-sized humanoid robot, David Junior II, for the Push Recovery event at RoboCup. David Junior II endured a hit with potential energy during walking, which is 1.3 times more robust than when standing.
Multi-keyword Ranked Searchable Encryption Supporting CP-ABE Test

Internet of Things (IoT) and cloud computing are promising technologies that change the way people communicate and live. As the data collected through IoT devices often involve users’ private information and the cloud is not completely trusted, users’ private data are usually encrypted before being uploaded to cloud for security purposes. Searchable encryption, allowing users to search over the encrypted data, extends data flexibility on the premise of security. In this paper, to achieve the accurate and efficient ciphertext searching, we present an efficient multi-keyword ranked searchable encryption scheme supporting ciphertext-policy attribute-based encryption (CP-ABE) test (MRSET). For efficiency, numeric hierarchy supporting ranked search is introduced to reduce the dimensions of vectors and matrices. For practicality, CP-ABE is improved to support access right test, so that only documents that the user can decrypt are returned. The security analysis shows that our proposed scheme is secure, and the experimental result demonstrates that our scheme is efficient.
Ultrasonic Phased Array Imaging Method Based On Multi - Scattering Model

With the development of ultrasonic technology, ultrasonic wave plays an increasingly important role in the field of nondestructive testing. Among all kinds of ultrasonic nondestructive testing technologie, ultrasonic phased array is widely used because of its high accuracy and flexibility. However, due to the existence of rayleigh limit, ordinary ultrasonic phased array technology cannot recover the space frequency greater than 2K, so it is impossible to achieve the resolution less than half of the wavelengthof the super-resolution. In this paper, we introduce a method to realize super resolution imaging in multi-band phased array.In this method, the damage is detected by multiple phased arrays, and the received signals are processed by specific algorithms to obtain super-resolution imaging. The signal is excited by M exciter and then received by N receiver. The total signal can form an M*N matrix. After singular valuedecomposition of the collected signal matrix,T significant eigenvalues can be obtained. The T significant eigenvalues represent the number of injuries. The singular vector after singular value decomposition contains the information of noise space. The number of eigenvalues in the signal space is the number of damage. Using the randomness of noise subspace, special algorithm can be used to restore the spatial frequency greater than 2K to achieve super-resolution imaging.The more elements in this method, the more accurate and complicated it is. As long as the smallest value of M and N is greater than the number of injuries, each injury can be successfully distinguished under super resolution. Therefore, the appropriate number of matrix elements should be selected for different damages.
Wavelet-Based Enhanced Medical Image Super Resolution

Low-resolution medical images can seriously interfere with the medical diagnosis, and poor image quality can lead to loss of detailed information. Therefore, improving the quality of medical images and accelerating the reconstruction is of particular importance for diagnosis. To solve this problem, we propose a wavelet-based mini-grid network medical image super-resolution (WMSR) method, which is similar to the three-layer hidden-layer-based super-resolution convolutional neural network (SRCNN) method. Due to the amplification characteristics of wavelets, a stationary wavelet transform (SWT) is used instead of a discrete wavelet transform (DWT). Also, due to the nature of redundant (scale-by-scale) wavelets, it is possible to retain additional information about the image and restore high-resolution images in detail. For a large amount of training data, wavelet sub-band images, including approximation and frequency subbands are combined into a predefined full-scale factor. The mapping between the wavelet sub-band image and its approximate image is then determined. In order to ensure the reproducibility of the image, a method of adding a sub-pixel layer is proposed to realize the hidden layer, and replacing the small mini-grid-network on the hidden layer is of considerable significance to speed up the image recovery speed. Experimental results on the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) show that the model has better performance.
A fault location method for aging bugs in Flight Control Software

With the increasing complexity of flight control software,it becomes very challenging to improve the reliability of flight control software. There is a kind of software aging bugs which can reduce the system memory and eventually trigger failure, which will seriously affect the reliability of flight control software. Aiming at the bugs, a context-based software aging fault location method is proposed. Thie basic idea of the proposed method is to transfer the main circulation model of the flight control software into a task tree, and then extract main cycle executions runs into a sequence of task tree. By utilizing Cox-Stuart Test, the memory attribute of the central node of the task tree is detected to find the suspicious task. Thereafter, according to the relationship among the task tree series, suspicious tasks are selected to locate defects. The function of suspicious task is the location of the defect. Finally, an experiment is implemented and the results show that the proposed method can not only locate the defect, but also show the call context.
Trajectory Tracking Control Design for UAV Based on MPC and Active Disturbance Rejection

A control strategy which consists of model predictive control and active disturbance rejection is proposed for the trajectory tracking problem of fixed-wing unmanned aerial vehicles under disturbances. Considering the longitudinal motion dynamic model, a constrained predictive controller is designed for trajectory tracking control while ADRC is designed to estimate and compensate disturbances. In this article, an augmented state-space model is established for predictive controller design and Hildreth’s Quadratic Programming Procedure is used to solve constrained problem. In terms of ADRC, the linear extended state observer (LESO) is established to deal with disturbances. The performance of the proposed control strategy is demonstrated by simulation.
A New Field Expansion Enabling the Compressive-Sensing-based Diagnosis of Realistic Planar Arrays through Phaseless Measurements

An innovative and effective approach to the diagnostics of faulty elements in planar array antennas is presented and assessed. The introduction and exploitation of a new field expansion allow casting the faulty elements' recovery problem as the determination of the actual aperture-field distribution. Notably, a number of remarkable features is provided, including the exploitation of just phaseless far-field measurements, the profitable use of the Compressive Sensing theory, and the capability of dealing with whatever kind of planar arrays (e.g., realistic radiating systems where mutual coupling and mounting-platform effects come into play). The given theory is supported by numerical experiments involving full-wave data relative to a realistic 100-elements waveguide array.
A Proposed Genetic Based Method to Solve Frequency Assignment Problem for HF Band

The Electromagnetic Compatibility (EMC) problem is considered as complex scientific problem. It obeys to knapsack problem constraints in which, it is well known, that at increasing the number of variables of the problem under consideration, the solution will become very complex.This paper provides a modeling and simulation of a proposed method to solve the EMC problem based on the genetic algorithm, relating to problem of distributing the frequencies among wireless radio stations operating in High Frequency (H.F.) Band, used in specified geographical region, and a very restricted frequency band, especially in Military applications. The paper provides a description of the Frequency Assignment Problem (FAP), and it focuses on the different interference types, that have great role in this problem.This paper discusses the performance evaluation of the proposed method via it’s comparison with the conventional method (Back Tracking Method) used in the solution of this problem, through many case studies taken from the military environments. The time taken by the proposed method is smaller than that taken by conventional method.