Traffic flow prediction is the upstream problem of path planning, intelligent transportation system, and other tasks. Many studies have been carried out on the traffic flow prediction of the spatio-temporal network, but the effects of spatio-temporal flexibility (historical data of the same type of time intervals in the same location will change flexibly) and spatio-temporal correlation (different road conditions have different effects at different times) have not been considered at the same time. We propose the Deep Spatio-temporal Adaptive 3D Convolution Neural Network (ST-A3DNet), which is a new scheme to solve both spatio-temporal correlation and flexibility, and consider spatio-temporal complexity (complex external factors, such as weather and holidays). Different from other traffic forecasting models, ST-A3DNet captures the spatio-temporal relationship at the same time through the Adaptive 3D convolution module, assigns different weights flexibly according to the influence of historical data, and obtains the impact of external factors on the flow through the ex-mask module. Considering the holidays and weather conditions, we train our model for experiments in Xi’an and Chengdu. We evaluate the ST-A3DNet and the results show that we have better results than the other 11 baselines.
Solar photovoltaic (SPV) systems are a renewable source of energy that are environmentally friendly and recyclable nature. When the solar panel is connected directly to the load, the power delivered to the load is not the optimal power. It is therefore important to obtain maximum power from SPV systems for enhancing efficiency. Various maximum power point tracking (MPPT) techniques of SPV systems were proposed. Traditional MPPT techniques are commonly limited to uniform weather conditions. This paper presents a study of MPPT for photovoltaic (PV) systems. The study includes a discussion of different MPPT techniques and performs comparison for the performance of the two MPPT techniques, the P&O algorithm, and salp swarm optimization (SSO) algorithm. MATLAB simulations are performed under step changes in irradiation. The results of SSO show that the search time of maximum power point (MPP) is significantly decreased and the MPP is obtained in the shortest time with high accuracy and minimum oscillations in the generated power when compared with P&O.
Modern greenhouses are intensive farming systems designed to achieve high efficiency and productivity. Plants are produced year-round in greenhouses by maintaining the environment at or near optimum levels regardless of extreme weather conditions. Many scientific discoveries and technological advancements that happened in the past two centuries paved the way for current state-of-the-art greenhouses. These include, but are not limited to, advancements in climate-specific structural designs and glazing materials, and temperature control, artificial lighting, and hydroponic production systems. Greenhouse structures can be broadly grouped into four distinct designs, including tall Venlo greenhouses of the Netherlands, passive solar greenhouses of China, low-cost Parral greenhouses of the Mediterranean region, and gutter-connected polyethylene houses of India and African countries. These designs were developed to suit local climatic conditions and maximize the return on investment. Although glass and rigid plastic options are available for glazing, the development of low-cost and lightweight plastic glazing materials (e.g., polyethylene) enabled widespread growth of the greenhouse industry in the developing world. For temperate regions, supplemental lighting technology is crucial for year-round production. This heavily relies on advancements in electro-lighting during the 19th and 20th centuries. The development of hydroponic production systems for the controlled delivery of nutrients further enhanced crop productivity. This article addresses important historical events, scientific discoveries, and technological improvements related to advancements in these areas.
Realization of the yield potential depends on the biological characteristics of the variety, cultivation technology and weather conditions. The article presents the results of studies carried out in 2018-2021. on the productivity of various varieties of winter rye in dryland conditions of the central zone of the Republic of Kalmykia. The fresh yield of winter rye harvested for fodder depended on the variety. Its highest index was obtained for the Saratovskaya 4 variety and amounted to 17.7 ... 26.9 t / ha. The analysis of the productivity of winter rye harvested for green fodder showed that the studied varieties provided the yield of dry matter at the level of 5.4 ... 7.1 t / ha on average for three years. All varieties have good winter hardiness. Keywords: WINTER RYE, VARIETY, NAKED FALLOW, PLANT HEIGHT, GREEN MASS, FRESH YIELD, CROP PRODUCTIVITY, DRY MATTER
Climate change is one of the most crucial challenges identified in this century for the Pacific Region, such as Fiji, Samoa, Solomon Islands and many more. Citizens of Fiji have gone through peculiarly climatic and weather conditions over the past years like globalization, which had led to many consequences, especially in the agricultural sector which is the main income of many livelihoods not only in Fiji but in other Pacific countries as well. Climatic conditions have been changing adversely from past decades, such as temperature, rise in the sea level, precipitation changes, atmospheric composition changes, flooding, and tropical cyclones. These changes have led to alterations in the environment, thus, affecting crop and livestock production in the agricultural system. For instance, crops that require specific soil and temperature situations are vastly influenced when the temperature level changes suddenly, making the crops vulnerable to adapt to the alterations and therefore, the crops eventually die. Likewise, animal species also get affected by temperature changes, such as heat stress which specifically affects the fertility of male and female livestock. Due to these events, Fiji’s economies have also been affected since agriculture plays a vital role in boosting our economy through local market sales and exporting. Thereby, this review illustrates the impacts of climate change and ways to move forward/ solutions, for example, FAO (Food and Agriculture Organization) and Pacific Islands Climate Change Assistance Program (PICCAP) have supported Fiji in bringing adaptation programs for preparing farmers and all other individuals on the upcoming climatic conditions such as adapting tolerant crops that can handle droughts and other adverse weather conditions.
The state-of-the-art technique to control slug pests in agriculture is the spreading of slug pellets. This method has some downsides, because slug pellets also harm beneficials and often fail because their efficiency depends on the prevailing weather conditions. This study is part of a research project which is developing a pest control robot to monitor the field, detect slugs, and eliminate them. Robots represent a promising alternative to slug pellets. They work independent of weather conditions and can distinguish between pests and beneficials. As a prerequisite, a robot must be able to reliably identify slugs irrespective of the characteristics of the surrounding conditions. In this context, the utilization of computer vision and image analysis methods are challenging, because slugs look very similar to the soil, particularly in color images. Therefore, the goal of this study was to develop an optical filter-based system that distinguishes between slugs and soil. In this context, the spectral characteristics of both slugs and soil in the visible and visible near-infrared (VNIR) wavebands were measured. Conspicuous maxima followed by conspicuous local minima were found for the reflection spectra of slugs in the near infrared range from 850 nm to 990 nm]. Thus, this enabled differentiation between slugs and soils; soils showed a monotonic increase in the intensity of the relative reflection for this wavelength. The extrema determined in the reflection spectra of slugs were used to develop and set up a slug detector device consisting of a monochromatic camera, a filter changer and two narrow bandpass filters with nominal wavelengths of 925 nm and 975 nm. The developed optical system takes two photographs of the target area at night. By subtracting the pixel values of the images, the slugs are highlighted, and the soil is removed in the image due to the properties of the reflection spectra of soils and slugs. In the resulting image, the pixels of slugs were, on average, 12.4 times brighter than pixels of soil. This enabled the detection of slugs by a threshold method.
Protection of the natural environment is a key activity driving development in the transport discipline today. The use of simulators to train civil aviation pilots provides an excellent opportunity to maintain the balance between efficiency and limit the negative impact of transport on the environment. Therefore, we decided to determine the impact of selected simulations of air operations on energy consumption. The aim of the research was to determine the energy consumption of the flight simulator depending on the type of flight operation and configuration used. We also decided to compare the obtained result with the energy consumption of an aircraft of a similar class, performing a similar aviation operation and other means of transport. In order to obtain the results, a research plan was proposed consisting of 12 scenarios differing in the simulated aircraft model, weather conditions and the use of the simulator motion platform. In each of the scenarios, energy consumption was measured, taking into account the individual components of the simulator. The research showed that the use of a flight simulator has a much smaller negative impact on the natural environment than flying in a traditional plane. Use of a motion platform indicated a change in energy consumption of approximately 40% (in general, flight simulator configuration can change energy consumption by up to 50%). The deterioration of weather conditions during the simulation caused an increase in energy consumption of 14% when motion was disabled and 18% when motion was enabled. Energy consumption in the initial stages of pilot training can be reduced by 97% by using flight simulators compared to aircraft training.