Miracle-dz/UniFAR-FTUs huggingface dataset:
A Powerful Equalizer Based on Modified SVM Classifier Without Nonlinear Kernel Enabled 100-Gb/s NG-EPON System With 10-G Class

For the future high-speed next-generation Ethernet passive optical network (NG-EPON) system, the low-cost system could be kept by adopting low bandwidth devices. To compensate for the signal distortion and improve the performance of high-speed bandwidth limited system, we propose a special feature vector construction to achieve a new equalizer scheme based on support vector machines (SVM) classifier. For the first time, we mathematically analyze the model of the bandwidth-limited optical transmission system and theoretically derive the linear separability of the proposed feature vector formed linear hyperplane in 100-Gb/s NG-EPON system. Furthermore, <inline-formula> <tex-math notation="LaTeX">$4\times 25$ </tex-math></inline-formula>-Gb/s non-return to zero (NRZ) and <inline-formula> <tex-math notation="LaTeX">$2\times 50$ </tex-math></inline-formula>-Gb/s four-level pulse amplitude modulation (PAM-4) per wavelength transmission experiments with 10-G class optics system are demonstrated to prove the feasibility of our scheme. The experimental results show that, for 25-Gb/s/<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> NRZ transmission, compared to the decision feedback equalizer (DFE) and feed-forward equalizer (FFE), the receiver sensitivity achieved by our scheme can be improved by about 0.5-dB @BER=3.8e-3 with limited training sequence. For the 50-Gb/s/<inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> PAM-4 case, the SVM-based equalization method improves the receiver sensitivity for about 1-dB.
A Hybrid Transmission Based Data Collection Scheme With Delay and Reliability Guaranteed for Lossy WSNs

Mobile computing provides new ways of data collection on the Internet of Things (IoT). The sensed environment information by various sensing devices could make access to a wireless sensor network (WSN) through access points and vice versa. Improving the energy efficiency for a prolonged network lifetime while meeting the adaptive performance requirements under the guarantees of transport delay and reliability is an important problem to be solved in data collection for lossy and large-scale wireless sensor networks (WSN). Although many previous studies devoted to improving the energy efficiency, reliability, or network delay, they mainly focus on one of the performance metrics of the WSN. In this paper, a hybrid transmission scheme integrating the packet reproduction (PR) and Hop-by-Hop Automatic Repeat-reQuest (HBH ARQ) schemes are proposed to improve energy efficiency and reduce delay under guarantee of reliability for the lossy WSN. In the proposed scheme, the network is divided into two parts by a hybrid boundary where the location information is used to help determine the routing changes between the PR and HBH ARQ schemes. Some key parameters involved in the scheme are discussed and analyzed. The effectiveness of the proposed scheme is evaluated via extensive simulation results.
Selection of CTV-tolerant citrus hybrids for ornamental use

Introduction. Ornamental citrus is well established in Europe and North America, but is still incipient in Brazil, despite the fact that the country is among the world’s leading citrus fruit producers. However, the potential for innovation in this agribusiness segment is increasingly recognized. The Citrus Breeding Program of Embrapa Cassava & Fruits, among other objectives, aims to create plants suitable for ornamental use. Materials and methods. Ten hybrids were characterized by application of 39 morphological descriptors to identify their ornamental potential and to classify them in use categories. Additionally, these hybrids were evaluated regarding their susceptibility to the citrus tristeza virus (CTV). Results and discussion. The hybrids [(RPL x YMCT-005) × MCP-011], [(RPL × YMCT-005) × MCP-015], [GLINL × MCP-002], [GLINL × FTNL-001], [RPL × MCSH-002] and [CSM × MCP-002] can be recommended for use as potted plants, minifruit, landscaping and hedges; [(RPL × YMCT-005) × MCP-016], [CSM × MCP-003] are suitable as potted plants, landscaping and hedges; [(RPL × YMCT-005) × SMM-014] fits in the potted plant, landscaping and ornamental minifruit; and [(RPL × YMCT-005) × GLINL-001] is suitable for use as potted plants and in landscaping. According to the results on the reaction to the CVT pathogen, four hybrids were classified as resistant, four were classified as highly tolerant and two were classified as highly intolerant, indicating the need for their protection with weak CTV strains. Conclusion. The hybrids evaluated presented substantial morphological variability that distinguished them from each other. Their traits qualify them for use as ornamental plants.
Economic analysis of environmental benefits of integrated pest management: a Philippine case study

Health and environmental concerns associated with pesticide use have motivated the development of integrated pest management (IPM) programs around the world. Little empirical work has been completed to estimate the value of the environmental benefits of IPM. This paper provides an approach to evaluate a broad set of such benefits for a vegetable program in the Philippines. Assessments were made of (1) IPM-induced reduction in environmental risks posed by pesticides in onion production in the Central Luzon and (2) willingness to pay to reduce those risks. The latter was based on a contingent valuation (CV) interview survey of 176 farmers. Risks to humans, birds, aquatic species, beneficial insects, and other animals were considered. IPM practices on onions reduced the use of specific pesticides from 25 to 65%, depending on the practice, and the projected adoption ofiPM practices varied from 36 to 94%. Estimated economic benefits varied from 231 to 305 pesos per person per cropping season (40 pesos = 1 US$). The aggregate value of environmental benefits for the five villages where the IPM research program was centred was estimated at 150,000 US$ for the 4600 local residents. Assessment of environmental benefits can help in designing public policies and regulations, and in justifying support for publicly funded IPM programs. © 2001 Elsevier Science B.V. All rights reserved.
Color Constancy for Uniform and Non-Uniform Illuminant Using Image Texture

Color constancy is the capability to observe the true color of a scene from its image regardless of the scene’s illuminant. It is a significant part of the digital image processing pipeline and is utilized when the true color of an object is required. Most existing color constancy methods assume a uniform illuminant across the whole scene of the image, which is not always the case. Hence, their performances are influenced by the presence of multiple light sources. This paper presents a color constancy adjustment technique that uses the texture of the image pixels to select pixels with sufficient color variation to be used for image color correction. The proposed technique applies a histogram-based algorithm to determine the appropriate number of segments to efficiently split the image into its key color variation areas. The K-means++ algorithm is then used to divide the input image into the pre-determined number of segments. The proposed algorithm identifies pixels with sufficient color variation in each segment using the entropies of the pixels, which represent the segment’s texture. Then, the algorithm calculates the initial color constancy adjustment factors for each segment by applying an existing statistics-based color constancy algorithm on the selected pixels. Finally, the proposed method computes color adjustment factors per pixel within the image by fusing the initial color adjustment factors of all segments, which are regulated by the Euclidian distances of each pixel from the centers of gravity of the segments. The experimental results on benchmark single- and multiple-illuminant image datasets show that the images that are obtained using the proposed algorithm have significantly higher subjective and very competitive objective qualities compared to those that are obtained with the state-of-the-art techniques.
Realtime Face-Detection and Emotion Recognition Using MTCNN and miniShuffleNet V2

In this paper, the problem of facial expression is addressed, which contains two different stages: 1. Face detection, 2. Emotion Recognition. For the first stage, an MTCNN (Multi-Task Convolutional Neural Network) has been employed to accurately detect the boundaries of the face, with minimum residual margins. The second stage, leverages a ShuffleNet V2 architecture which can tradeoff between the accuracy and the speed of model running, based on the users’ conditions. The experimental results clearly Shows that our proposed model outperforms the state-of-the-art on FER 2013 dataset which has been provided by Kaggle.
Judgments of Size Change Trends in Static and Animated Graduated Circle Displays

Despite the abundance of research on the perception of information presented as graduated or proportional circles on static maps, such experiments have been rare for animated map displays. However, such experimental results might be beneficial for selecting optimal methods for depicting temporal change on graduated circle maps. In the present experiment, participants judged whether a greater number of circles in an n x n array increased or decreased during a 1500-millisecond (ms) observation interval. The variable n represented values of 6, 8, and 10,and all circles changed size (some larger, some smaller) from a common starting size either in a discrete shift (static condition) in the middle of the observation interval, or in a smooth, apparently continuous shift (animated condition) over the same interval. In addition, the size changes were relatively small, moderate, or large. The proportion of “more bigger” judgments, plotted against the actual proportions of enlarged circles, produced an ogive function (a cumulative normal) with similar slopes in all conditions. However, the bias towards “bigger” judgments increased with the size discrepancies between the initial and final circle diameters, and the bias towards “bigger” judgments was greater for animated than for static circle diameter changes. The results are interpreted in terms of attentional precedence for larger items and also for those that appear to be continuously increasing in size (looming). These results have implications for the presentation of information on static and animated graduated circle maps.
The Drive Circuit Design for Paralleling Operation of Enhancement GaN HEMT in an Isolated DC-DC converter

For current limitation of a single low voltage enhancement mode GaN HEMT, paralleling of GaN HEMT are essential in high current and low voltage applications. Through parallel GaN HEMT, the converter will increase the power handling capability and realize high efficiency. Driving paralleled operation GaN HEMT needs special care on parameters design of both driving circuit and power device layout, because the low gate-to-source maximum voltage (Vgs) rating and low gate threshold voltage (Vth) raise some strict constrains and challenges. This paper presents the driving challenges in paralleling of GaN devices in an isolated dc-dc converter. The design rules for gate driver and PCB layout are concluded based on the analysis of parasitic. The hardware prototype of a 300W flyback forward isolated converter with paralleling of GaN devices is implemented and presented in this paper.
Control of Quad-rotor in Cooperation with an Attached 3-DOF Manipulator

Autonomous quad-rotor flight systems have grabbed considerable attention for varied missions in rescue, inspection devices, and so forth. Accordingly, various control methods have been employed for hovering these devices. Recently, in order to extend the applications of quad-rotors, including, among the others, the pick-and-place, a robotic arm has been attached, which requires the analysis of both dynamic equations and control procedures. However, considering the coupled system as a case of robot-robot interaction, these state-of-the-art flight systems have rarely received attention due to much higher complexity of dynamic equations. Moreover, flight time expense is revealed as another critical issue in the flight systems with the attached arm, which requires effective solution due to excessive arm loads and power source limitations. To this end, in this paper, the dynamic equations of quad-rotor with a 3-link arm are obtained in order to be employed in designing suitable control methods. In this regard, by stabilizing the quad-rotor in desired coordinations and tracking desired paths for robotic arm, the dynamic interaction as the main challenge of the robot-robot interaction is successfully handled. Thereafter, a Linear Quadratic Regulator (LQR) is proposed to tackle the flight time issue in which by assigning optimal values to the state input weighting matrix, the motion of arm links reduced and as the result, the flight time effectively increases. In order to demonstrate the superiority of the proposed method, two well-known control approaches, namely, Sliding Mode Control (SMC) and Pole Placement are implemented in the same conditions. In simulation with Matlab software, the performance of the forgoing methods is compared by employing different indices, where it is inferred that despite presence of an external force resembling windy condition, the proposed LQR decreases the motion index by 24.14% in compare with SMC and Pole Placement methods, with approximately similar tracking index to them.
Speed Accuracy in Motor Performance and Risk-Taking Characteristics

Past research has led to the conclusion, through studies of the speed-accuracy trade-off, that there is a natural covariance between speed and accuracy within individuals on movement tasks (Adam, 1992). In this study, we investigated the relationship between the speed-accuracy continuum and risk-taking personality characteristics. In order to investigate the hypotheses, the study used a Fitts’ cyclical aiming task in which participants moved a mouse between two targets that were at various widths and amplitudes. The various widths and amplitudes included 15 unique combinations of movement measurements, which were compared to two measures of risk-taking. These were the Investment Risk Tolerance Quiz (IRTQ), which is a questionnaire that measures an individual’s risk-tolerance with regard to financial investment, and the Personality Inventory of the DSM-5 (PID-5), which is an overarching method of testing personality characteristics, including risk-taking. We used a linear regression between risktaking and measures of motor performance (movement time, accuracy, and variability) to assess if there is a relationship between the two. With this analysis, we were interested if variability along one dimension predicted the variability along the other dimension. The first prediction, that as movement time (MT) increases risk taking should decline, did not yield significant results. The second prediction, that as accuracy increases, with regard to target hits and misses, risk taking should decline was also found not to be significant. Last, the prediction that variability increases, with regard to the standard deviation of movement amplitude, as risk taking increases was found not to be significant also. These predictions were not significant and this
An Effective Corrective Remedial Action Algorithm to Prevent Voltage Instability

The objective of this paper is to propose a fast and efficient corrective remedial action algorithm to prevent mid-term and long term voltage instability. In this method, voltage control areas (VCAs) are determined using electrical distance based partitioning algorithm and an improved line stability index has been proposed to assess the stability status of VCAs. Since those line stability indices proposed in the literature cannot assess the stability in real power systems (which have more than two buses), in this paper, an improved line stability index is proposed which can accurately determine the voltage stability stiffness. Then, considering the stability status of VCAs, a simple and effective corrective remedial action will be proposed to inhibit voltage instability. The performance of the proposed approach has been validated through several scenarios which are performed using DIgSILENT PowerFactory software in IEEE 39-bus test system.
A Fully Integrated C-Band GaN MMIC Doherty Power Amplifier With High Efficiency and Compact Size for 5G Application

This paper presents a fully integrated C-band Doherty power amplifier (DPA) based on a 0.25- $\mu \text{m}$ GaN-HEMT process for the 5G massive MIMO application. The performance degradation caused by nonlinear output capacitance is analyzed, and a novel compensation technique is proposed. A low-Q output network is employed to broaden the bandwidth, and its insertion loss in the back-off region is demonstrated to be mainly decided by the Q-factor of the drain bias inductor of the main PA. Hence, by adopting on-chip transmission lines with high Q-factors for drain biasing, a full integration, and a low loss can be achieved simultaneously. Reversed uneven power splitting and back-off input matching are proposed for gain enhancement. The fabricated DPA demonstrates a small-signal gain of 8.6–11.6 dB, an output power of 40.4–41.2 dBm, a 6-dB back-off drain efficiency (DE) of 47% – 50%, and a saturation DE of 55%–63% across a wide bandwidth from 4.5 to 5.2 GHz, with an ultra-compact size of 2.2 $\text {mm} \times 2.1$ mm. Using a 40-MHz LTE signal with a 7.7-dB peak-to-average power ratio at the carrier frequency of 4.9 GHz, the measured average output power and efficiency are 33 dBm and 43%, respectively. The raw adjacent channel power ratio is −29 dBc and is improved to −46 dBc by applying digital predistortion.
Adaptation of a Commercially Available Laser Raman Spectrometer for Underwater Chemical Sensing

To achieve in situ underwater chemical sensing, a commercially available Raman spectroscopy system was adapted for underwater operation. Using off-the-shelf laser unit, optical probe, spectrometer, and power/communications module, the system was integrated into a custom designed pressure housing. This instrument was deployed on the FITS (Fiber-optical Instrumentation Towed System) developed by the National Sun Yat-sen University for experiments. Measurements of Raman spectra were successfully performed with the instrument at 500 m depth. Power supply, instrument control, and data collection were provided through the FITS, which was connected to the research vessel with a cable containing copper conductors and fiber optic cables. Raman signal of sea water was successfully obtained from the measurements. Evidence of possible detection of methane was also recorded in the measurements.
Measuring Determinants and Effects of Firms’ Financial Structure in a Deleverage Setting: Evidence From Italy

Since 2011, after ten year of growth, Italian non-financial firms have heavily reduced their bank debt. Indeed, the ratio between bank credit to non-financial sector and the Italian GDP decreased from 92.5% to 83.5% in the last five years. This paper examines the determinants of this reduction using an OLS regression model performed on a sample of 12,974 Italian firms. In addition, we analyse the effect of this change in the capital structure on profitability and on debt-service. Results show that Growth, Size, Tangibility and Profitability are associated with leverage, consistently with the previous literature. Furthermore, we found that firm reduced their return on equity but improved their cash flow to debt ratio.
An Inverse Robust Optimisation Approach for a Class of Vehicle Routing Problems under Uncertainty

There is a trade-off between the total penalty paid to customers (TPC) and the total transportation cost (TTC) in depot for vehicle routing problems under uncertainty (VRPU). The trade-off refers to the fact that the TTC in depot inevitably increases when the TPC decreases and vice versa. With respect to this issue, the vehicle routing problem (VRP) with uncertain customer demand and travel time was studied to optimise the TPC and the TTC in depot. In addition, an inverse robust optimisation approach was proposed to solve this kind of VRPU by combining the ideas of inverse optimisation and robust optimisation so as to improve both the TPC and the TTC in depot. The method aimed to improve the corresponding TTC of the robust optimisation solution under the minimum TPC through minimising the adjustment of benchmark road transportation cost. According to the characteristics of the inverse robust optimisation model, a genetic algorithm (GA) and column generation algorithm are combined to solve the problem. Moreover, 39 test problems are solved by using an inverse robust optimisation approach: the results show that both the TPC and TTC obtained by using the inverse robust optimisation approach are less than those calculated using a robust optimisation approach.
Adaptive Gabor Convolutional Neural Networks for Finger-Vein Recognition

Finger-vein recognition has become an important branch in the field of biometrics. Convolutional neural networks (CNNs) have achieved remarkable success in finger-vein recognition, but their models have many problems, such as high complexity, large parameters, running time slowly and so on. To solve these problems, we proposed adaptive Gabor convolutional neural networks (AGCNN). We replaced the normal convolution layer of CNNs with Gabor convolution layer, and systematically investigate comparative performance using AGCNN and CNNs in the raw image and region of interest (ROI) image of finger vein database respectively. Experimental results show that the parameter complexity of AGCNN is significantly less than that of CNNs with slight performance decrease. And the experimental results of the raw image database show that the processing speed has been greatly improved.
The benefits of comparing solution methods in solving equations

This study, which was experimental, investigated the benefits of comparing multiple solution methods in solving one and two-steps linear equations. The participants were 64 students from a private secondary school in the metropolitan area of Bauchi, Bauchi State of Nigeria. The students were randomly assigned to experimental and control groups. After pretest administration, there was an intervention for three days and on the fourth day the posttest was administered. The students learnt about solving equations either by comparing and contrasting solution methods or by reflecting on the same solution methods one at a time. The study revealed that students in the experimental group benefited more than those in the control group. At posttest, students in the experimental group had greater gains in procedural knowledge and flexibility knowledge than those in the control group. The findings of the study suggest that the method of comparing and contrasting solution methods can be an effective method in the mathematics classroom.