ALBERT

Description: In this paper, a hybrid bat optimization algorithm based on variable neighbourhood structure and two learning strategies is proposed to solve a three-stage distributed assembly permutation flowshop scheduling problem to minimize the makespan. The algorithm is firstly designed to increase the population diversity by classifying the populations, which solves the difficult trade-off between convergence and diversity of the bat algorithm. Secondly, a selection mechanism is used to update the bat’s velocity and location, solving the difficulty of the algorithm to trade-off exploration and mining capacity. Finally, the Gaussian learning strategy and elite learning strategy assist the whole population to jump out of the local optimal frontier. The simulation results demonstrate that the algorithm proposed in this paper can well solve the DAPFSP. In addition, compared with other metaheuristic algorithms, IHBA has better performance and gives full play to its advantage of finding optimal solutions.

Description: In Europe, the qualification of injection anchors in masonry under static and quasi-static actions is based on an assessment of tests performed in undamaged masonry. Nevertheless, in seismic prone countries like Italy the influences deriving from earthquake actions cannot be disregarded. Masonry elements are very sensitive to cyclic/seismic action and research on the behavior of anchors in damaged masonry is rather limited. The paper presents the results of an experimental campaign aimed at evaluating the residual tensile strength of adhesive anchors installed into undamaged walls that were subsequently subjected to cyclic in-plane loading to simulate seismic actions before. Consequently, the anchors experienced different stresses depending on their location within the walls. Overall, 29 tests were performed with anchors placed both, in undamaged and damaged areas. The results showed that there is a correlation between residual tensile strength and masonry initial conditions, and therefore the installation of anchors in masonry elements should be carefully planned avoiding areas that could be heavily damaged during seismic events or considering redundant connections in critical areas. In particular, it seems that the width of the crack (created by cyclic actions) that passes nearby/into the anchor borehole is the main parameter that affects the ultimate resistance of the anchors.

Description: Sowing time, as an element, is important to improving the adaptation of cultivars to environmental conditions and to achieving high seed yields. The field experiment was conducted from 2018–2019 at the Experimental Station of Vytautas Magnus University Agriculture Academy. The experimental design included treatments with different sowing dates: eight sowing dates in 2018 and 10 sowing dates in 2019. The first sowing of spring rapeseed was carried out when the soil reached its physical maturity, i.e., it did not stick to agricultural implements and it crumbled well. The other sowing dates were every seven subsequent days. From 2018–2019, the rapeseed emerged as best in early May (3 and 4 May), and later sowing reduced the emergence of rapeseed. In 2018, most pods were formed on one plant when the rapeseed was sown (on 1 June), compared to other sowings, on average 2.8 times more. In 2019, most pods were formed by the latest-sown rapeseed (7 June), from 1.4 to 2.7 times more compared to previously sown crops. In 2018, the sowing time of spring rapeseed did not have a significant effect on the number of seeds in one pod. In 2019, it was found that the rapeseed formed most of the seeds in the pod at a similar time as in 2018: the sowings of 19 April and 7 June. The average number of seeds in the pod was significantly reduced by early sowing (5 April). In 2019, the highest 1000-seed weight was found at the earliest-sown crop (5 April), which was on average 18.0% higher compared to the later sowings. The 1000-seed weight of the last-sown rapeseed (7 June) was the lowest. In 2018, the yields of early-sown (20 April) spring rapeseed were the highest. Later sowing significantly reduced the yields by 20.7 to 48.2%. In 2019, the highest seed yield was obtained after sowing spring rapeseed in late April (26 April); it was significant, on average, 1.9 times higher than the yields of spring rapeseed sown from 3 May to 7 June. Meteorological conditions had a stronger effect on the field emergence and yield components of spring rapeseed than the sowing date.

Description: Dynamic behavior modeling and parameter optimization of the spray boom based on multi-body vibration were developed to study the influence of the boom sprayer’s motion in a complex working environment on the dynamic behavior of the spray boom. First, a geometric continuous model of spray boom vibration was established considering the influence of the boom sprayer body and boom suspension. Then, the dynamic behavior of the spray boom under step excitation was studied on a SWAN3WP-500 self-propelled boom spray experimental platform. The time-domain response of spray boom movement was characterized using a multi-channel dynamic test system, and the simulation results of the geometric continuous model were verified. The correlation coefficient between the simulated and experimental results is 0.917, and the maximum relative error is 12.16%. Finally, the effects of boom sprayer speed, spray boom length, and spray boom cross-section shape on spray boom vibration were analyzed through the geometric continuous model. (1) The amplitude and period of vibration at the extremity of the spray boom gradually decline with a rise in boom sprayer speed. (2) The amplitude and period of vibration at the extremity of the spray boom gradually increase when the unilateral spray boom is shorter than 5 m but slowly decrease when it is longer than 5 m. To avoid excessive static elastic deformation of the spray boom, the length of the unilateral spray boom should be controlled within 6 m. (3) A reasonable cross-sectional shape can improve the spray boom vibration, and the spray boom with a type B cross-section can better inhibit the vertical vibration of the spray boom under the same cross-sectional area.

Description: Mycotoxins are toxic secondary metabolites produced by fungi on agricultural produce. Mycotoxins can be cytotoxic, genotoxic, mutagenic, and teratogenic, and they are persistent threats to human and animal health. Consumption of mycotoxin-contaminated maize can cause cancer and even sudden death. Health hazards can also occur from consuming products from animals fed with mycotoxin-contaminated feed or forage. The main mode of spread of mycotoxigenic fungi is through air-borne spores originating from soil or plant debris, although some fungi can also spread through infected seed-to-seedling transmission, ultimately followed by contamination of the harvestable product. This perspective assesses opportunities to prevent mycotoxigenic fungal infection in maize seeds produced for sowing as an important starting point of crop contamination. A case study of Nigeria showed infection in all tested farmer-produced, seed company, and foundation seed samples. A schematic overview of the formal and informal seed systems is presented to analyze their contribution to fungal infection and mycotoxin contamination in the maize value chain, as well as to set criteria for successful control. We recommend an integrated approach to control mycotoxigenic fungal infection, including resistant varieties and other control methods during seed production, grain production, and grain storage, with an important role in maintaining seed health.

Description: The cross-flow rotating packed bed (RPB) has attracted wide attention in recent years because of its advantages of large gas capacity, low pressure drop and lack of flooding limitation. However, the complex structure of the packing makes it difficult to obtain the gas flow characteristics in the cross-flow RPB by experiments. In this study, the dry pressure drop in the cross-flow RPB was investigated by computational fluid dynamics (CFD). The packing was modeled by the porous media model and the rotation of the packing was simulated by the sliding mesh model. The simulation results obtained by three turbulence models were compared with experimental results, and the RNG k-ε model was found to best describe the turbulence behaviors in the cross-flow RPB. Then, the effects of gas flow rate and rotating speed on dry pressure drop in different parts of the cross-flow RPB were analyzed. The results of this study can provide important insights into the design and scale-up of cross-flow RPB.

Description: This paper analyses the construction time and advance rate of a 3 km long drill and blast tunnel under various geological conditions using an upgraded NTNU drill and blast prediction model. The analysis was carried out for the five types of Korean tunnel supports according to the rock mass quality (from Type 1, meaning a very good rock mass quality; to Type 5, meaning a very poor rock mass quality). Four kinds of rock properties, as well as the rock mass quality, for each tunnel support type were applied to simulate different geological conditions based on previous studies and the NTNU model. The construction time was classified into five categories: basic, standard, gross, tunnel and total, according to the operation characteristics to more effectively analyse the time. In addition, to consider the actual geological conditions in tunnelling, the construction times for the three mixed geological cases were analysed. It was found that total construction time of a tunnel covering all the operations and site preparations with a very poor rock mass quality was more than twice that of a tunnel with a very good rock mass quality for the same tunnel length. It is thought that this study can be a useful approach to estimating the construction time and advance rate in the planning or design stage of a drill and blast tunnel.

Description: As more and more fields utilize deep learning, there is an increasing demand to make suitable training data for each field. The existing interactive object segmentation models can easily make the mask label data because these can accurately segment the area of the target object through user interaction. However, it is difficult to accurately segment the target part in the object using the existing models. We propose a method to increase the accuracy of part segmentation by using the proposed interactive object segmentation model trained only with edge images instead of color images. The results evaluated with the PASCAL VOC Part dataset show that the proposed method can accurately segment the target part compared to the existing interactive object segmentation model and the semantic part-segmentation model.

Description: Nowadays, the demand for personalized goods is increasing, with small batches of customized products. Companies are asked to cope with this need to be more competitive; thus, it is crucial to optimally set up the production process to cope with the demand. Among the products composed of several parts, sales kits occupy a significant role. Sales kits are sets of different components, supplied as a single unit. Automation is usually used to reduce the unit direct production costs for assembled products, and this is especially true for kitting since it has minimum added value, compared to other technologies. The wide range of components leads to frequent reconfiguration of the feeding devices between different products, increasing the setup time. The aim of this work is to provide a model that minimizes the setup times of automatic kitting systems when working with a high variety of products. To reach this goal, we propose to apply the traveling salesman problem (TSP) to the production process by integrating a multi-clustering model, thus increasing its appeal to several applications. This method is applied both to simulations and to a real case study, and proves to be able to provide a good solution in a reasonable time.

Description: With the advantages of high resolution, structural simplicity, reliability, compact size, and high sensitivity, inductive sensors have been widely used in nanopositioning systems. However, the measuring range of traditional inductive sensors are usually limited to 0.2 mm. A novel analysis and design methodology of the miniaturized inductive sensor with large measuring range and nanoscale resolution is proposed. Firstly, an accurate leakage inductance model is established. Secondly, a design rule of armature size is proposed by considering the fringing effect. Then, the error terms introduced by the measurement circuit of differential inductive sensors are analyzed and the corresponding error suppression methods are illustrated. Moreover, A design rule of selecting the optimal excitation frequency is proposed to meet the requirements of high Q value and high bandwidth, and to minimize the impact of core loss resistance on the performance of the sensor. Validated by the experiments, the proposed analysis and design method can effectively guide the design of the miniaturized inductive sensor with nanoscale resolution in the measuring range of ±0.5‍ mm. The overall size of the fabricated sensor prototypes is less than 6 mm × 6 mm × 3 mm. Combined with large range, high resolution and ideal miniaturization, this inductive sensor can be well suitable for compact and large stroke nanopositioning systems.