Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing the Sowing Date and Irrigation Strategy to Improve Maize Yield by Using CERES (Crop Estimation through Resource and Environment Synthesis)-Maize Model

Summer maize (Zea mays L.) is a widely cultivated crop in the arid and semi-arid Guanzhong region of China. However, due to the spatial and temporal variation in rainfall, the seasonal maize yield varies substantially and occasionally is not economical for poor farmers to produce. Recent water-saving agricultural practices were developed by the government to make it possible to apply supplementary irrigation at optimum sowing dates to maximize maize production under limited rainfall in the region. CERES (Crop Estimation through Resource and Environment Synthesis)-maize model was used to identify the appropriate irrigation strategies, crop growth stages and sowing dates for sustainable maize production. Model calibration process were carried out for full irrigation treatments of four growing seasons, (2012–2015). The data used for calibration included: Crop phenology, grain yield, aboveground biomass and leaf area index. The calibration phase model showed good agreement between simulated and observed values, with normalized root mean square error (nRMSE) ranging from 4.51% to 14.5%. The performance of the calibrated model was evaluated using the field data of grain yield, aboveground biomass, leaf area index and water use efficiency. The performance of the model during evaluation was satisfactory with acceptable nRMSE error ranging from 7% to 10%. Soil moisture content was evaluated for full irrigation treatments for both 2012 and 2013 seasons. With results showing that soil moisture content below 35 cm layer was well simulated with nRMSE, 0.57 to 0.86 respectively. Appropriate simulated sowing dates for higher production and water productivity were from 14 to 24 June. The proper amount and timing of irrigation water application was 100 mm at the flowering stage, and 100 mm at the grain filling stage respectively. Summer maize yield can be improved by adjusting the sowing date and applying supplementary irrigation when precipitation cannot meet the crop water demand in the Guanzhong Plain.
FREQUENCY OF TYPHOID FEVER IN HEALTHY PEOPLE OF DODA REGION OF JAMMU AND KASHMIR, INDIA: FIRST REPORT FROM AREA

: Typhoid fever (or enteric fever) remains a deadly disease in developing countries, particularly in India. Although, the paediatric population is mainly affected by this disease, however, the disease is one of the main causes of morbidity and mortality in adult populations as well. Typhoid fever is an orally transmitted infectious disease caused by the Gram negative bacterium, Salmonella typhi . The aim of the study was to examine pathogens that cause typhoid fever among healthy people in the Doda region of Jammu and Kashmir, India. Blood was collected from 150 healthy people for testing. A total of 85 (56.7%) healthy people showed positive results that they had typhoid fever based on a clinical examination and serological test, while 65 (43.3%) showed negative results of the total of 150 patients. The Widal test was found to be suitable test for enteric fever. Typhoid fever remains common in the Doda region, even among those with a high level of education. The study conducted during March 2020 to May 2020, is the first of its kind in the Doda region of Jammu and Kashmir.
Wi-Fi RTT Ranging Performance Characterization and Positioning System Design

The aim of this research is to implement a precise Wi-Fi indoor positioning system (IPS) or localization system based upon the IEEE 802.11mc fine-timing measurement (FTM) scheme also known as the Wi-Fi round trip time (RTT) ranging technique, where ranging refers to a sub-process of positioning that determines the distance between a transmitter and receiver. Our system and its algorithms were implemented using a COTS (Commercial-Off-The-Shelf) smartphone and Wi-Fi access points. Experiments were conducted in several real-life indoor environments. This paper presents the detailed Wi-Fi RTT ranging performance of these devices in different system configurations and characterizes the systematic biases and noise model to improve the ranging accuracy. A novel three-step-positioning method is proposed to overcome the issues of no or multiple intersect points in trilateration due to ranging errors to improve positioning accuracy. This consists of the following: 1) systematic bias determination and removal; 2) clustering-based trilateration (CbT) supported by weighted concentric circle generation (WCCG), namely CbT & WCCG; 3) positioning result and trajectory optimization using a Kalman filter. As a result, the evaluation experiments gave a position accuracy of ±1.2 m in 2D static positioning and ±1.3 m for dynamic motion tracking. Also, our CbT & WCCG method demonstrate good tolerance against ranging errors. Moreover, the computational cost and positioning accuracy of CbT & WCCG methods are compared with least square (LS) and recursive least square (RLS) methods and the accuracy standard deviation of our algorithm is the closest to the Cramer–Rao bound (CRB).
Virtual Reality Simulation of a Quadrotor to Monitor Dependent People at Home

Unmanned aerial vehicles (UAVs) represent an assistance solution for home care of dependent persons. These aircraft can cover the home, accompany the person, and position themselves to take photographs that can be analyzed to determine the person’s mood and the assistance needed. In this context, this work principally aims to design a tool to aid in the development and validation of the navigation algorithms of an autonomous vision-based UAV for monitoring dependent people. For that, a distributed architecture has been proposed based on the real-time communication of two modules, one of them in charge of the dynamics of the UAV, the trajectory planning and the control algorithms, and the other devoted to visualizing the simulation in an immersive virtual environment. Thus, a system has been developed that allows the evaluation of the behavior of the assistant UAV from a technological point of view, as well as to carry out studies from the assisted person’s viewpoint. An initial validation of a quadrotor model monitoring a virtual character demonstrates the advantages of the proposed system, which is an effective, safe and adaptable tool for the development of vision-based UAVs to help dependents at home.
Comprehensive Designs of Innovate Secure Hardware Devices against Machine Learning Attacks and Power Analysis Attacks

COMPREHENSIVE DESIGNS OF INNOVATE SECURE HARDWARE DEVICES AGAINST MACHINE LEARNING ATTACKS AND POWER ANALYSIS ATTACKS Yiming Wen Old Dominion University, 2020 Director: Dr. Weize Yu Hardware security is an innovate subject oriented from growing demands of cybersecurity and new information vulnerabilities from physical leakages on hardware devices. However, the mainstream of hardware manufacturing industry is still taking benefits of products and the performance of chips as priority, restricting the design of hardware secure countermeasures under a compromise to a finite expense of overheads. Consider the development trend of hardware industries and state-of-the-art researches of architecture designs, this dissertation proposes some new physical unclonable function (PUF) designs as countermeasures to side-channel attacks (SCA) and machine learning (ML) attacks simultaneously. Except for the joint consideration of hardware and software vulnerabilities, those designs also take efficiencies and overhead problems into consideration, making the new-style of PUF more possible to be merged into current chips as well as their design concepts. While the growth of artificial intelligence and machine-learning techniques dominate the researching trends of Internet of things (IoT) industry, some mainstream architectures of neural networks are implemented as hypothetical attacking model, whose results are used as references for further lifting the performance, the security level, and the efficiency in lateral studies. In addition, a study of implementation of neural networks on hardware designs is proposed, this realized the initial attempt to introduce AI techniques to the designs of voltage regulation (VR). All aforementioned works are demonstrated to be of robustness to threats with corresponding power attack tests or ML attack tests. Some conceptional models are proposed in the last of the dissertation as future plans so as to realize secure on-chip ML models and hardware countermeasures to hybrid threats.
Improving future occupational health practitioners’ competences for the management of techno-stress and excellence

In times of steadily increasing numbers of burnout in European workplaces, we propose in the frame of the IMPRESS project (Project reference: 588315-EPP-1-2017-1-ES-EPPKA2-KA) a common assessment and intervention program for HEI students in occupational psychology focusing on excellent stress management. The program is based on results of an online survey that found similar work-related stress factors in the four participating countries. Following a scientist-practitioner model, HEIs as well as practitioners of these countries developed a training offering assessment, intervention and excellence-related competences for stress-management using online tools. A first pilot was carried out in the Bachelor of Psychology, subject Organizational Behavior (UB) with 18 bachelor and 10 Master students using an online assessment tool, seminars and case studies. Evaluation of the competences acquired, and the seminars and case studies showed satisfactory results.
Experimental studies and multi-response optimisation of duplex turning parameters using grey relational analysis with entropy measurement

: In present work, the effect of turning parameters like cutting velocity, feed rate, primary depth of cut (DOC) and secondary-DOC on responses like primary cutting force (Fp), secondary cutting force (Fs) and surface roughness (Ra) using duplex turning process are observed. The preliminary experiments and entropy-grey relational analysis (GRA) has been utilised to plan the experiment. Analysis of variance (ANOVA) analyses the influence of each parameter on the responses. It is observed that feed rate has more effect as compared to other parameters. The confirmation experiment at GRA optimal condition shows the improvement in all responses as Fp = 15.34%, Fs = 17.20% and Ra = 10.14% positively.
A Broadband Wide-Scanning Planar Phased Array Antenna With Equivalent Circuit Analysis

A broadband wide-scanning planar phased array is studied in this letter. An accurate equivalent circuit model is used and studied to provide more insights into the working principle of the proposed antenna element. Surface wave suppression is achieved by introducing an air gap, which also improves the active voltage standing wave ratio (VSWR) in H-plane as a wide-angle matching layer. The infinite array cell in simulation achieves nearly 65.2% bandwidth (6.3–12.4 GHz) with active VSWR < 2 when scanning up to 60° in all azimuth planes. A prototype array is fabricated to verify this design and the experimental result achieves nearly 68.5% bandwidth (6–12.26 GHz) under a criterion of VSWR < 2 at broadside and VSWR < 3 at 60° scan in E- and H-plane. Scanning patterns are measured and show good agreements with simulated results.
Distributed Game Strategy for Formation Flying of Multiple Spacecraft With Disturbance Rejection

This article investigates a distributed game strategy for formation control of multispacecraft subjected to nonlinear dynamics and $J_2$ perturbations. In the proposed problem, each spacecraft is devoted to minimize its own performance cost using only local information, whereas the overall formation system attempts to seek an optimized decision based on communication topology. Therefore, in our scheme, the formation control problem can be treated using a Nash strategy. A worst case Nash strategy is proposed against the disturbance defined as a player, and we prove rigorously that an open-loop Nash equilibrium exists in the underlying problem. Then, a distributed terminal state observer is introduced to facilitate the local implementation of the proposed Nash strategy. Simulation results verified the performance of the proposed scheme.
A METHOD FOR PLANAR PHASED ARRAY CALIBRATION

A method is proposed to calibrate a planar phased array by reconstructing its aperture distribution, in which the aperture distribution is superposed within the physical range of radiating element. Consequently, the calibration coefficients are solved for the linear relationship between the superposed aperture distribution and elements’ excitations. The calibration accuracy that is influenced by resolution of aperture distribution is also discussed in this paper. In practice, the reconstruction procedure of aperture distribution is based on the plane wave spectrum (PWS) theory, utilizing FFT and IFFT techniques. This method turns out to be valid by experiment.
Hierarchical Decomposition-Based Distributed Full States Tracking Consensus for High-Order Nonlinear Multiagent Systems

This article studies the distributed adaptive leader-following control for high-order time-varying nonlinear multiagent systems (MASs) with uncertain parameters. The state feedback protocol and output feedback protocol are proposed, respectively, to render all states consensus errors to converge to zero asymptotically. First, the hierarchical decomposition algorithm is used to construct a refreshed communication graph to address the mutual dependence problem of controllers. Then, by introducing a local neighborhood consensus errors-based transformation, the leader-following consensus problem is converted into the stabilization problem for the consensus error system. Using the backstepping method and tuning function technique, the distributed adaptive state feedback controller is designed to render all followers’ states to track the leader’s ones. Further, by constructing the reduced-order dynamic gain k-filter to estimate unmeasured states, a distributed adaptive output feedback controller is designed. In both controller design methods, the traditional Lipschitz condition need not be satisfied any more for all time-varying nonlinear functions, and different from most of the existing results on the high-order nonlinear MASs, full states consensus can be obtained. Finally, a general numerical example is given to illustrate the effectiveness of the proposed methods.
Comparison Between Graphene and GaAs Quantized Hall Devices With a Dual Probe

A graphene quantized Hall resistance (QHR) device fabricated at the National Institute of Standards and Technology, Gaithersburg, MD, USA, was measured alongside a GaAs QHR device fabricated by the National Research Council of Canada, Ottawa, ON, Canada, by comparing them to a 1- $\text{k}\Omega $ standard resistor using a cryogenic current comparator. The two devices were mounted in a custom developed dual probe that was then assessed for its viability as a suitable apparatus for precision measurements. The charge carrier density of the graphene device exhibited controllable tunability when annealed after Cr(CO)3 functionalization. These initial measurement results suggest that making resistance comparisons is possible with a single- probe wired for two types of quantum standards—GaAs, the established material, and graphene - the newer material that may promote the development of more user-friendly equipment.
Genome wide analysis of NAC transcription factors and their expression pattern during high temperature and drought stress in groundnut

NAC (NAM, ATAF1/2 and CUC2) is a prime plant specific transcription factor, which plays a pivotal role in stress signaling. Excavating a relatively large number of NAC TFs under complex environmental cues and understanding their molecular basis, remains a challenge. The objective of this study was to analyse a total of 76 NAC transcription factors of which 38 were from Arachis duranensis (AdNAC) and Arachis ipaensis (AiNAC) for phylogeny, chromosomal location, conserved motif identification including membrane bound NTLs (NAC trans-membrane like), promoter analysis and expression profiles under high temperature and drought stress. The study led to the identification of eight membrane bound NTLs, such as AdNAC26, AdNAC36, AiNAC16, AiNAC17, AiNAC37, AdNAC14, AiNAC12, and AiNAC29, and revealed that majority of NAC proteins had four NAC domain- containing conserved motifs and were localised at the nucleus. The study also reveals AdNAC21 and AiNAC3 as positive regulators under both stress conditions. Our results provide a basis for selection of promising stress- responsive NAC candidates for further functional analysis, leading to development of transgenics with improved productivity of groundnut varieties under drought and high temperature. Keywords : Conserved motifs, NTL, phylogenetic tree, RT- qPCR
Balanced Diplexer Based on Substrate Integrated Waveguide Dual-Mode Resonator

This article presents a novel balanced diplexer based on substrate integrated waveguide (SIW) dual-mode resonator. The six-port model has been introduced in this article to achieve the conversion of S-parameters between balanced and unbalanced devices. The SIW dual-mode resonator with common-mode (CM) rejection capability is able to restrain CM signal in the passband of the diplexer. Moreover, the CM rejection performance is improved by etching the slotline on the surface of SIW without changing the transmission of the differential-mode (DM) signal. A diplexer with lower and higher channels centered at 8.8 and 9.4 GHz, with a 3-dB FBW of 4% and 4.8%, respectively, is designed and fabricated to verify the proposed concept. The measured results show that the CM rejection is greater than 42/45 dB and the DM isolation between the lower and higher channels is greater than 35 dB in passband, which shows good agreements with simulations.
Fast Localization With Unknown Transmit Power and Path-Loss Exponent in WSNs Based on RSS Measurements

Unlike most studies assuming exact knowledge of the transmit power and path-loss exponent, we address the localization problem under a more practical assumption that the exact values of the transmit power and/or path-loss exponent are unavailable. We propose an algorithm based on the differential evolution, opposition based learning, and adaptive redirection that jointly estimates the position of the target node and the parameters. Results from simulation and indoor experiments show that the proposed algorithm provides higher localization accuracy and requires less computational time than conventional algorithms especially when the exact values of the transmit power and path-loss exponent are unavailable simultaneously.
Experimental Study on Mechanical Properties of Shear-type Mild Steel Damper

Because of its good energy dissipation capacity and stable performance, the mild steel damper is widely applied in energy dissipation structure. The theoretical model of shear type metal damper was analyzed and calculation formula of the main mechanical parameters was established. Material test of domestic steel BLY160 and Q235 was conducted. On the basis of theoretical analysis and material performance, two groups of dampers with the same dimension but different energy dissipation materials were designed and made. Pseudo-static test on the two groups of specimens was carried out. The test results show that the hysteretic curves of mild steel dampers were full and mechanical properties were stable. Yield strength, yield displacement and other mechanical parameters showed small dispersion. Under Low cycle fatigue loading with ±20mm displacement, the performance of damper with BLY160 was better than that made by Q235.
Wideband Widebeam Dual Circularly Polarized Magnetoelectric Dipole Antenna/Array With Meta-Columns Loading for 5G and Beyond

A dual circularly polarized (CP) magnetoelectric dipole antenna is presented in this article. The dual-CP antenna was devised to form a circular ring shape and fabricated using 3-D printing technology. To overcome the conflict between high (broadside) gain and wide (half-power) beamwidth, a new beamwidth broadening technique was proposed. Twelve meta-columns were placed evenly along the circumference close to the ring-shaped dipole. A design approach is elaborated, where the number and size of meta-columns were decided according to the design curves. Symmetrical beamwidth of 108° in orthogonal planes with a broadside gain of 6 dBic was achieved across a wide effective bandwidth from 3.2 to 5.4 GHz (51%), sufficiently covering the 5G new radio (NR) bands: <inline-formula> <tex-math notation="LaTeX">$n77, n78, n79$ </tex-math></inline-formula>. The antenna owns a compact size of <inline-formula> <tex-math notation="LaTeX">$0.83 \times 0.83 \times 0.18\lambda ^{3}$ </tex-math></inline-formula> at 4.15 GHz. A planar subarray composed of four dual-CP elements was also investigated and compared with the existing arrays.
Single and Ensemble Classification for Predicting User’s Restaurant Preference

Classification is one of the most attractive and powerful data mining functionalities. Classification algorithms are applied to real-world problems to produce intelligent prediction models. Two main categories of classification algorithms can be adopted for generating prediction models: Single and Ensemble classification algorithms. In this paper, both categories are utilized to generate a novel prediction model to predict restaurant category preferences. More specifically, the central idea espoused in this paper is to construct an effective prediction model, using Single and Ensemble classification algorithms, to assist people to determine the best relevant place to go based on their demographic data, income level and place preferences. Therefore, this paper introduces a new application of classification task. According to the reported experimental results, an effective Restaurant Category Preferences Prediction Model (RCPPM) could be generated using classification algorithms. In addition, Bagging Homogeneous Ensemble classification produced the most effective RCPPM.
CaIAuth: Context-Aware Implicit Authentication When the Screen Is Awake

Relieving users from the burden of remembering and inputting authentication information explicitly, such as passwords/PINs and lock patterns, implicit authentication mechanisms have gained an increasing concern. When providing authentication, the existing implicit methods only depend on a specific behavior, such as typing on the screen, performing gestures, or taking a walk. However, in real applications, a user’s behavioral characteristics are also decided by the context where behavior is performed. Thus, those existing methods show limited authentication accuracy and usability. To address these issues, we propose CaIAuth, a reliable context-aware implicit authentication framework, which profiles users’ behavior and context characteristics in a holistic fashion. It observes the states of context-sensing entities for different smartphone usage patterns and builds a context-aware model to distinguish between legitimate users and illegal ones. We conducted extensive experiments to evaluate system performance with a large data set collected from 142 subjects. The experimental results show that our system achieves a low equal error rate (EER) (e.g., less 7%) and is resilient against common threats, including zero-effect attack and mimicry attack. In addition, CaIAuth achieves a low authentication delay and overhead.