<span>With the advancement of the internet, individuals are becoming more reliant on online applications to meet most of their needs. In the meantime, they have very little spare time to devote to the selection and decision-making process. As a result, the need for recommender systems to help tackle this problem is expanding. Recommender systems successfully provide consumers with individualized recommendations on a variety of goods, simplifying their duties. The goal of this research is to create a recommender system for farmers based on tree data structures. Recommender system has become interesting research by simplifying and saving time in the decision-making process of users. We conducted although a lot of research in various fields, there are insufficient in the agriculture sector. This issue is more necessary for farmers in Quangnam-Danang or all Vietnam countries by severe climate features. Storm from that, this research designs a system based on tree data structures. The proposed model combines the you only look once (YOLO) algorithm in a convolutional neural network (CNN) model with a similarity tree in computing similarity. By experiments on 400 samples and evaluating precision, accuracy, and the value of the predictive test as determined by its positive predictive value (PPV), the research proves that the proposed model is feasible and gain better results compared with other state-of-the-art models.</span>

Aircraft wings are generally designed and optimized to give the best possible performance for cruise flight conditions. Using conventional control surfaces such as flaps, ailerons, variable wing sweep and spoilers, the structure of aircraft wings is changed for other flight conditions. With the introduction of wing morphing, the flow over an aircraft's wings can be modified locally to improve the overall wing and aircraft performance during the different flight steps. The goal of this research work is to develop an actuation control principle using a grid consisting of four similar miniature electromechanical actuators for a new morphing wing mechanism. The actuators modify the flexible upper surface of the wing so that the upper flow is modified and consequently the transition point from laminar to turbulence is delayed. The flexible upper wing surface is closed to the wing tip, while the skin is made of composite materials. The first actuation line is located at 32% and the second actuation line is at 48% of the chord. The actuators are fixed on the wing ribs and the top is attached to the flexible skin with screws. A database that relates the actuator displacements and the optimized skin is tailored for different flight conditions. A smart controller based fuzzy logic is designed to control the position of the actuator in real time so that the desired optimized skin corresponding to the desired displacements is obtained and maintained during the flight tests. The feasibility and the effectiveness of the control method are demonstrated experimentally. Nomenclature M = Mach number AoA = Angle of attack β = Deflection angle

To optimize the aerodynamic performance of the aircraft, its wing design is considered as one of the promising approaches. Unlike the conventional control surface technologies such as flaps, variable wing sweep and spoilers, where the wings' structures are changed for different flight conditions, the morphing wing technology has been introduced as another potential approach. In this technology, the aircraft wing surfaces' shape are changed to adapt to flight conditions by using four electrical actuators. They are attached inside the wing to adjust its upper surface's shape, so that the transition point between laminar and turbulent zone is moved closer to the trailing edge of the wing. An adaptive neuro-fuzzy inference system, which is a combination of fuzzy, neural network and adaptive controls, is applied for controlling these actuators. The proposed control method takes advantage of the fuzzy inference system and the self-learning abilities of the neural networks, and of the adaptive control. The experimental and simulation results are obtained using Maxon drives, National Instrument (NI) Veristand and MATLAB/Simulink software. The results show a promising idea of applying artificial intelligent control methods in improving performance of electronic devices and morphing wing technology.

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Background: One of the most common diseases in free-range ducks in the Mekong Delta is “botulism”. Botulism is a poultry disease caused by botulinum exotoxin of Clostridium botulinum. Aim: The purpose of the investigation was to evaluate the prevalence of botulism in free-range ducks in the Mekong Delta and the risk of infection by determining the presence of Clostridium botulinum in the farming environment. Methods: Research on 200 duck flocks with 187050 individuals raised freely in the fields in the provinces of the Mekong Delta including An Giang, Can Tho, Hau Giang, and Kien Giang. The ducks were diagnosed with botulism based on clinical symptoms. To demonstrate the presence of botulinum neurotoxins and identify serotype, samples of serum and/or gut were analyzed by mouse bioassay. Samples of soil (n=600), water (n=600), crabs (n=216), and snails (n=400) were taken from the grazing regions for Clostridium botulinum analysis by PCR assay. Results: There were 1.19% (2235/187050) free-range ducks in the Mekong Delta positive for botulism. Clinical symptoms of botulism including limberneck, drooping eyelids - enlarged pupils, and leg paralysis were prevalent across free-range ducks, with the frequency of 87.92% (1965/2235), 90.07% (2013/2235), and 79.78% (1783/2235), respectively. The lesions of pulmonary edema – hemorrhage, hemorrhagic liver, and gas-producing intestines were common, accounting for 86.19% (362/420), 95.48% (401/420), and 92.14% (387/420), respectively. Botulin toxin type C was found in a considerable number of serum samples, accounting for 40.48% (51/126). Meanwhile, the percentage of serum samples containing botulin toxin types E and D was 28.57% (36/126) and 25.40% (32/126), respectively. Clostridium botulinum was detected in the farming environment specifically 17.5% (105/600) in soil, 19.67% (118/600) in water, 8.33% (18/216) in crabs, and 3.00% (12/400) in snails. Conclusion: The free-range ducks in the Mekong Delta were at high risk of botulism because of the latent presence of Clostridium botulinum in the farming environment.