Applying computer vision for detection of diseases in plants

Early detection and quantification of diseases in food plants are critical to agriculture industry and national food security. However, limitation in technology and cost has limited the success of applying Computer Vision in Plant Science. This research builds on the recent advance of Machine Learning, GPU and smartphones to tackle the problem of fast and low cost diagnosis of plant disease. In particular, we choose soybean as the subject for applying automatic disease detection. The reason is because soybean is an important crop for the state of Iowa and an important source of food for America. The plant is however, highly vulnerable to several type of diseases. This thesis consists of two sub-analyses of soybean diseases, which are: First, detection of a single disease in soybean, particularly Sudden Death Syndrome (SDS) with high detail (including location and severity). Second, detection of multiple diseases in soybean, using mobile phones which are resource- constraine

Nonlinear Optics in Waveguide Arrays and Photonic Nanowires

In this paper we review our works in the field of nonlinear optics in waveguide arrays (WAs) and photonic nanowires. We first focus on the new equation governing light propagation in optical fibers with sub-wavelength cores which simultaneously takes into account (i) the vector nature of the electromagnetic modes inside fibers, (ii) the strong dispersion of the nonlinearity inside the spectral body of the pulse, (iii) and the full variations of the vector mode profiles with frequency. From this equation we have shown that a new kind of nonlinearity emerges in subwavelength-core fibers which can suppress the Raman self-frequency shift of solitons. We then discuss some nonlinear phenomena in WAs such as the emission of the diffractive resonant radiation from spatial discrete solitons and the anomalous recoil effect. Finally, we review our works on the optical analogues of Dirac solitons in quantum relativistic physics in binary waveguide arrays (BWAs) for both fundamental and higher-order solitons, and its interaction.

A New Linear Printed Vivaldi Antenna Array with Low Side Lobe Level and High Gain for the Band 3.5 GHz

This paper proposes a new design of low sidelobe level (SLL) and high gain linear printed Vivaldi antenna array. The array composes of two parts, which are a linear Vivaldi antenna array and a back reflector. The array consists of 10 single Vivaldi antennas and a series-fed network, those are based on Roger RO4003C substrate (ε = 3.55) with the dimension of 140 x 450 x 1.524 mm3. A new Bat algorithm with the amplitude-only control technique has been applied to optimize the output coefficients of the series-fed network for gaining a low SLL. The simulation results indicate that the proposed antenna provides a low SLL of -29.2 dB in E-plane with a high gain of 16.5 dBi at the frequency of 3500 MHz. A prototype of the proposed antenna array has been fabricated. The measured data has a good agreement with the simulated data

Factors Affecting Lecturer’s Commitment to Non-Public University: A Study in Ho Chi Minh City, Vietnam

By using SPSS 22.0 software to analyze the reliability through Cronbach’s alpha, EFA and AMOS 20.0 to modify the scale through CFA tool, test model through SEM, the study aimed to identify factors affecting lecture’s commitment to non-public university – a study in Ho Chi Minh city. Through  the offical survey with 510  samples,  the result showed the factors affecting lecture’s commitment including: satisfaction,  leadership and partnership.The satisfaction is the strongest factor. In other hand, the study identified that job satisfaction is affected by training, promotion, income.  Based on that, researcher raised some recommends to enhance the lecture’s commitment in  non-public  university. Keywords: non-public uinversity, commitment, lecture, job satisfactio

Periodic solutions for Boussinesq systems in weak-Morrey spaces

We prove the existence and polynomial stability of periodic mild solutions for Boussinesq systems in critical weak-Morrey spaces for dimension $n\geqslant3$. Those systems are derived via the Boussinesq approximation and describe the movement of an incompressible viscous fluid under natural convection filling the whole space $\mathbb{R}^{n}$. Using certain dispersive and smoothing properties of heat semigroups on Morrey-Lorentz spaces as well as Yamazaki-type estimate on block spaces, we prove the existence of bounded mild solutions for the linear equations corresponding to the Boussinesq system. Then, we establish a Massera-type theorem to obtain the existence and uniqueness of periodic solutions to corresponding linear equations on the half-line by using a mean-ergodic method. Next, using fixed point arguments, we can pass from linear equations to prove the existence uniqueness and polynomial stability of such solutions for Boussinesq systems. Finally, we apply the results to Navier-Stokes equations.Comment: 18 page

Improvement of Step Tracking Algorithm Used for Mobile Receiver System via Satellite

In the mobile communication via satellite, received systems are mounted on the mobile device such as ship, train, car or airplane. In order to receive continuous signals, received antenna system must be steered in both the azimuthal and elevation angle to track a satellite. This paper proposes the improved step-tracking algorithm using for mobile receiver system via satellite Vinasat I. This paper also presents the results of study, design and manufacture of the discrete-time controller system for the fast tracking of a satellite by applying an improved step tracking algorithm with fuzzy proportional integral derivative proportional integral derivative controller. Simulated and experimental results indicate that the system performances obtain from applying the improved step tracking algorithm and the fuzzy controller was better than traditional control systems

On stability problem for the stationary Boussinesq system in Morrey-type spaces

In this paper we establish the asymptotic stability of steady solutions for the Boussinesq systems in the framework of Cartesian product of critical weak-Morrey spaces on $\mathbb{R}^n$, where $n \geqslant 3$. In our strategy, we first establish the continuity for the long time of the bilinear terms associated with the mild solutions of the Boussinesq systems, i.e., the bilinear estimates by using only the norm of the present spaces. As a direct consequence, we obtain the existence of global small mild solutions and asymptotic stability of steady solutions of the Boussinesq systems in the class of continuous functions from $[0, \infty)$ to the Cartesian product of critical weak-Morrey spaces. Our techniques consist interpolation of operators, duality, heat semigroup estimates , Holder and Young inequalities in block spaces (based on Lorentz spaces) that are preduals of Morrey-Lorentz spaces. Our results are generalized the previous ones of the steady Boussinesq systems in weak-$L^p$ spaces obtained by Hishida [T. Hishida, {\it On a class of Stable Steady flow to the Exterior Convection Problem}, Journal of Differential Equations, Vol. 141, Iss. 1 (1997), pages 54-85] and Ferreira et al. [L.C.F. Ferreira and E.J. Villamizar-Roa, {\it On the stability problem for the Boussinesq equations in weak-$L^p$ spaces}, Commun. Pure Appl. Anal. (2010), Vol. 9, No. 3, pages 667-684] and of the Navier-Stokes equations in Morrey spaces obtained by Kozono et al. [H. Kozono and M. Yamazaki, {\it The stability of small stationary solutions in Morrey Spaces of the Navier-Stokes equation}, Indiana University Mathematics Journal, Vol. 44, No. 4 (1995), pages 1307-1336].Comment: 17 page

Multimodal Graph Learning for Modeling Emerging Pandemics with Big Data

Accurate forecasting and analysis of emerging pandemics play a crucial role in effective public health management and decision-making. Traditional approaches primarily rely on epidemiological data, overlooking other valuable sources of information that could act as sensors or indicators of pandemic patterns. In this paper, we propose a novel framework called MGL4MEP that integrates temporal graph neural networks and multi-modal data for learning and forecasting. We incorporate big data sources, including social media content, by utilizing specific pre-trained language models and discovering the underlying graph structure among users. This integration provides rich indicators of pandemic dynamics through learning with temporal graph neural networks. Extensive experiments demonstrate the effectiveness of our framework in pandemic forecasting and analysis, outperforming baseline methods across different areas, pandemic situations, and prediction horizons. The fusion of temporal graph learning and multi-modal data enables a comprehensive understanding of the pandemic landscape with less time lag, cheap cost, and more potential information indicators

First occurrence of the little-known genus Noteriades (Hymenoptera, Megachilidae) from Vietnam: discovery of a new species and a key to the Southeast Asian fauna

The little-known megachiline genus Noteriades Cockerell, 1931 is recorded from Vietnam for the first time. A new species, Noteriades hangkia Tran, Engel & Nguyen sp. nov. is described and figured based on a series of females collected from the provinces of the northern and central highlands of Vietnam. The genus is briefly discussed and a new subtribe is established, Noteriadina Engel, Tran & Nguyen subtrib. nov. of Megachilini. Lastly, an identification key and distribution map are provided for those species occurring in Southeast Asia