Good Weather Conditions Research Articles

Style Optimization Networks for real-time semantic segmentation of rainy and foggy weather

Semantic segmentation is an essential task in the field of computer vision. Existing semantic segmentation models can achieve good results under good weather and lighting conditions. However, when the external environment changes, the effectiveness of these models are seriously affected. Therefore, we focus on the task of semantic segmentation in rainy and foggy weather. Fog is a common phenomenon in rainy weather conditions and has a negative impact on image visibility. Besides, to make the algorithm satisfy the application requirements of mobile devices, the computational cost and the real-time requirement of the model have become one of the major points of our research. In this paper, we propose a novel Style Optimization Network (SONet) architecture, containing a Style Optimization Module (SOM) that can dynamically learn style information, and a Key information Extraction Module (KEM) that extracts important spatial and contextual information. This can improve the learning ability and robustness of the model for rainy and foggy conditions. Meanwhile, we achieve real-time performance by using lightweight modules and a backbone network with low computational complexity. To validate the effectiveness of our SONet, we synthesized CityScapes dataset for rainy and foggy weather and evaluated the accuracy and complexity of our model. Our model achieves a segmentation accuracy of 75.29% MIoU and 83.62% MPA on a NVIDIA TITAN Xp GPU. Several comparative experiments have shown that our SONet can achieve good performance in semantic segmentation tasks under rainy and foggy weather, and due to the lightweight design of the model we have a good advantage in both accuracy and model complexity.

RTDOD: A large-scale RGB-thermal domain-incremental object detection dataset for UAVs

Recently, visual understanding using unmanned aerial vehicles (UAVs) has gained significant attention due to its wide range of applications, including delivery, security investigation and surveillance. However, most existing UAV-based datasets only capture color images under ideal illumination and weather conditions, typically sunny days. This limitation fails to account for the complexity of real-world scenarios, such as cloudy or foggy weather, and nighttime conditions. Deep learning methods trained on color images with good lighting and weather conditions struggle to adapt to the complex visual scenes in these scenarios. Moreover, color images may not provide sufficient visual information under the complex visual scenes. To bridge this gap and meet the demands of real-world applications, we propose a large-scale RGB-Thermal Domain-incremental Object Detection (RTDOD) dataset in this paper. Our dataset includes RGB and thermal videos synchronously captured using calibrated color thermal cameras mounted on UAVs. It covers various weather conditions, from sunny to foggy to rainy, and spans from day to night. We sample and obtain approximately 16,200 pairs of images, and manually label dense annotations, including object bounding boxes and object categories. With the proposed dataset, we introduce a challenging domain-incremental object detection task. We also present a baseline approach that uses task-related gates to filter features for knowledge distillation to reduce forgetting. Experimental results on the RTDOD dataset demonstrate the effectiveness of our proposed method in domain-incremental object detection. To facilitate future research and development in domain-incremental object detection tasks on aerial images, the RTDOD dataset and our baseline model are made available at https://github.com/fenght96/RTDOD.ARTICLE INFO.

Subjective and Objective Evaluation of Driving Behaviour in Depression

Abstract Introduction Road traffic collisions and related casualties are a major issue for public health and society. Depression is characterized by mental, emotional and executive dysfunction, which may have an impact on driving behaviour. Among its symptoms sleep disturbance is very common. Objectives The current study examined behaviour and attitude towards driving in a group of patients with depression and a group of controls, considering sleep disturbances. Methods Participants (patients N = 39 and controls N = 30) were asked to complete the Driver Stress Inventory (DSI) and Driver Behavior Questionnaire (DBQ). Afterwards, they were asked to drive on a driving simulator in a motorway scenario, and in urban and rural scenarios under low and high traffic load, all in good weather conditions. Driving simulator data included speed, lateral position (LP) and safety distance from the preceding vehicle. Results Gender, age and, to a lesser extent, body mass index influenced almost all variables. Patients with depression did not differ from the controls regarding driving behaviour as assessed through the DSI and DBQ questionnaires. Subjective fatigue was found to be positively correlated with aggression (β = 0.027, p = 0.005), dislike of driving (β = 0.036, p = 0.006), hazard monitoring (β = 0.046, p = 0.001) and traffic violations (β = 0.010, p = 0.020). On the driving simulator, patients maintained a longer distance from the preceding vehicle. Epworth Sleepiness Scale and Athens Insomnia Scale scores were positively associated with safety distance and with the Standard Deviation of LP, denoting lower ability to keep a stable vehicle track (β = 2.108, p = 0.003 and β = 0.047, p = 0.004 respectively). Conclusions It seems that although certain symptoms of depression (insomnia, fatigue and somnolence) may affect driving performance, this effect is lessened by patients driving more carefully. There are parameters (age and sex) which influence driving behaviour and attitude similarly for both groups. Key messages • Patients with depression did not differ from controls regarding driving behaviour and attitude. • Patients seem to realize the effects of symptoms of depression on their driving ability and, consequently, drive more carefully.

Investigating the temporal differences among bike-sharing users through comparative analysis based on count, time series, and data mining models

Bike-sharing services provide easy access to environmentally-friendly mobility reducing congestion in urban areas. Increasing demand requires highly service planning methods based on bike-sharing user behavior. Negative Binomial, Poisson Regression, and Time Series models were elaborated considering the weather to reveal the differences between the members, occasional users, and visitor bike-sharing user groups. The negative Binomial approach is found to be superior to Poisson. Weather effects were varied in their influence on bike-sharing user classifications. In general, good weather conditions lead to more usage of bike-sharing. Weekends attract more occasional users and visitors than weekdays. In time series models, the seasonal trend of bike-sharing trips conducted by members was predicted without weather impact. According to the comparison, Random Forest performed better than SARIMA when the number of observations was low. Visitors are more influenced by temperature, wind and type of day. Occasional users are more subjected to precipitation. For members, it is found that the temperature, type of day are the most significant factors. The least factors for all are varied as well: precipitation for visitors, humidity for occasional users, precipitation and wind for members. The results help decision-makers predict the daily usage of bike-sharing for various user groups.

Adaptive Image Dehazing and Object Tracking in UAV Videos Based on the Template Updating Siamese Network

Visual object tracking for unmanned aerial vehicles (UAVs) is extensively used in civil and military applications such as intelligent transportation, disaster rescue, and military reconnaissance. However, when a UAV encounters haze weather, its tracking performance deteriorates greatly because of problems such as blurring and quality degradation of the collected images. Most trackers are designed to operate in good weather conditions, this greatly limits the robustness of UAV tracking in haze weather. To solve this problem, this paper proposes an adaptive dehazing Siamese network, which consists of an adaptive dehazing module, a dynamic template update branch, and feature extraction and bounding box prediction subnetworks. The dehazing module yields haze-free images and preserves the edge information of the object, so that the tracker can extract the object features with better characterization. Subsequently, to mitigate the risk of tracking drift caused by the changing appearance of the object, the dynamic template update branch dynamically selects more reliable template images during tracking. In addition, to solve the problem of insufficient UAV object tracking testing datasets in haze scenes, a haze testing dataset for UAV video object tracking is obtained through artificial synthesis and data collection in real-world haze scenes. Furthermore, experiments are conducte on haze testing datasets, namely UAV123-AH, UAV20L-AH, UAVDT-AH, DTB70-AH, and UAVhaze; the results verified that the proposed tracker yields more competitive performance and more robustness in haze scenes compared with the existing algorithms.

The Influence of Ambient Weather Conditions on Stated Preferences for Ecosystem Services Management

One of the assumptions in stated preference studies is the stability of respondents’ preferences. This assumption might be violated in situations of context dependence, i.e., when the contingent situation influences respondents’ choices. Ambient weather conditions (AWCs) are one element of the context that may influence stated preferences. The literature suggests that AWCs affect people’s emotions, behaviors, and decision-making processes; however, the potential AWCs impact in environmental preference studies has not yet been investigated. This aspect is of high importance because context-dependent choices return biased willingness to pay estimates and affect the subsequent welfare analysis that informs public policy. To shed light on this important aspect of non-market valuation studies, we explore the effect of AWCs on preferences elicited with a Discrete Choice Experiment for ecosystem services management of a Nature Park. Results of a generalized mixed logit model evidenced a significant effect of AWCs on respondents’ choices, with good weather conditions leading to higher preferences and willingness to pay for ecosystem services management. This result, which is consistent with previous psychological studies, raises the issue of sampling design and reveals the importance of a sensitivity analysis of WTP. As this issue is still unexplored in stated preference studies, we also encourage undertaking similar studies to add a priori knowledge for more accurate ex-post calibration of WTP estimates.

Exploring the Environmental Tourism Potentials in Mubi Town, Adamawa State Nigeria

The study aims to assess the environmental tourism potentials of Mubi Town Adamawa state, Nigeria with the view to make recommendations. The study employed both spatial and quantitative data. The spatial data involves the geographical information system Arc GIS 10.3, and remote sensing used for location map generation. The quantitative data was generated from one hundred structured questionnaires administered to the sampled populations. A systematic random sampling technique was employed for the questionnaire administration. This is because it allows all individual members to be chosen for the administration. Observation and photographing were conducted as part of the data collection. Descriptive statistics were utilized for correlating Environmental Tourism Potential (ETP) and Physical Tourism Potential (PTP). The correlation analysis between Environmental Tourism Potentials (ETP) indicates a strong correlation indicated a significant perfect and positive correlation of 0.01 at 2 Tailed. Additionally, the respondents' perceptions regarding the environmental tourism potentials were ranked according to a score point to get the results of the prioritized environmental tourism products. The findings demonstrate that the mountains and the hills give a good scenario as the first in the raking; good and conducive weather conditions as the second. At the same time, the attractive natural landscape is the third. Conclusively, if the potentials are appropriately planned, developed, and managed, it will attract both local and foreign tourists to come to Mubi town. Two recommendations are proposed development plan preparation and preservation and conservation of the identified environmental tourism potentials.

Identification of factors increasing the risk of pedestrian death in road accidents involving a pedestrian with a motor vehicle

Walking is a basic form of activity for every human being and has many advantages, including health, economic and environmental benefits. Every journey made using various means of transport begins and ends on foot. As is well known, the group of road users particularly exposed to the risk of serious injury in road accidents, apart from cyclists, also includes pedestrians. These are the so-called vulnerable road users. Pedestrians are a group of road users that is often deprecated by many drivers of motor vehicles, but very important in road traffic. Pedestrian injuries and pedestrian fatalities have enormous social and economic consequences. The problem of high pedes-trian risk on Polish roads is well known and has been widely described in the scientific literature last few years. However, the reasons for this state of affairs have not been fully explained, as evidenced by the statistics of road traffic incidents. Despite many studies in this area, the causes indicated in the research often differ depending on the area of analysis, the environment in which the incident took place, location, participants of the incident, environmental conditions, behaviorism and many other features. Therefore, the main goal of the article was to determine the factors influencing the formation of fatalities in road traffic accidents among pedestrians in acci-dents involving pedestrians and motor vehicles in the Silesian Voivodeship (Poland) in 2016-2021. The logit model presented in the article allowed for the conclusion that the main attributes influencing the increasing the risk of pedestrian death in road accidents involving a pedestrian with a motor vehicle include such features as driving under the influence of alcohol by the driver, exceeding the speed limit by the vehicle driver, when the road incident involves a heavy vehicle (truck, bus), a pedestrian is a male, pedestrian is over 60 years old, is under the influence of alcohol, the incident took place outside built-up area, at night, i.e. from 10:00 p.m. up to 6:00 a.m, in other than good weather conditions. The obtained results can be used in various activities, campaigns aimed at improving the safety of pedestrian traffic in the area of the analysis.

Analysis of the PV system sizing and economic feasibility study in a grid-connected PV system

UAE has good weather conditions for the integration of renewable energies in utility grid, especially photovoltaic solar energy, as it is one of the countries with the highest rate of solar radiation in the world, thus being able to contribute to policies to reduce greenhouse gas emissions. This article presents a study on how to control the variability that the production of electricity from solar energy presents and how to improve the integration of this type of production for self-consumption in an installation. Thus, in addition to a survey on the legislation that regulates the activity of self-consumption, topics such as energy storage, photovoltaic production and the optimization of the dimensioning of production systems with storage were addressed. The dimensioning process of a photovoltaic system connected to the grid is based on the choice and suitability of the module and DC/AC inverter and other peripheral equipment. The inverter sizing factor is the relationship between the inverter power and the PV generator power, and your choice depends on several factors. In addition, this work aims to in addition to presenting a study regarding economic feasibility so that it is possible to assess the profitability of this technology for the selected building.

Photosynthetic performance of Chlamydopodium (Chlorophyta) cultures grown in outdoor bioreactors.

The microalga Chlamydopodium fusiforme MACC-430 was cultured in two types of outdoor pilot cultivation units-a thin-layer cascade (TLC) and a raceway pond (RWP) placed in a greenhouse. This case study aimed to test their potential suitability for cultivation scale-up to produce biomass for agriculture purposes (e.g., as biofertilizer or biostimulant). The culture response to the alteration of environmental conditions was evaluated in "exemplary" situations of good and bad weather conditions using several photosynthesis measuring techniques, namely oxygen production, and chlorophyll (Chl) fluorescence. Validation of their suitability for online monitoring in large-scale plants has been one of the objectives of the trials. Both techniques were found fast and robust reliable to monitor microalgae activity in large-scale cultivation units. In both bioreactors, Chlamydopodium cultures grew well in the semi-continuous regime using daily dilution (0.20-0.25 day-1). The biomass productivity calculated per volume was significantly (about 5 times) higher in the RWPs compared to the TLCs. The measured photosynthesis variables showed that the build-up of dissolved oxygen concentration in the TLC was higher, up to 125-150% of saturation (%sat) as compared to the RWP (102-104%sat). As only ambient CO2 was available, its shortage was indicated by a pH increase due to photosynthetic activity in the thin-layer bioreactor at higher irradiance intensities. In this setup, the RWP was considered more suitable for scale-up due to higher areal productivity, lower construction and maintenance costs, the smaller land area required to maintain large culture volumes, as well as lower carbon depletion and dissolved oxygen build-up. KEY POINTS: • Chlamydopodium was grown in both raceways and thin-layer cascades in pilot-scale. • Various photosynthesis techniques were validated for growth monitoring. • In general, raceway ponds were evaluated as more suitable for cultivation scale-up.

AGRICULTURAL IRRIGATION – INNOVATIVE SOLUTIONS

Bulgaria's good soil and weather conditions increase the potential of agriculture and provide good opportunities for quality and sustainable food production. These can be expanded and further improved through the use of innovation in all agricultural activities. Farm irrigation is essential for the food supply and economic development of many countries. Innovative solutions are needed to improve the efficiency and sustainability of agricultural practices. Innovations in agricultural irrigation are essential for sustainable farm development and reducing water stress in the world. They help farmers to improve their harvests and preserve water resources for future generations. Integrating different water sources such as groundwater, surface water, rainwater and wastewater can provide a more sustainable and reliable source of water for farms. Innovations in agricultural irrigation require training and education for farmers to understand how to use new technologies and methods. Governments and financial institutions can provide support and incentives to invest in innovative irrigation solutions. In recent years, aquaponics has become an innovative study of the aquaculture industry. Aquaponics is an innovation in modern farming, a sustainable micro ecosystem with a controlled environment, combining aquaculture with hydroponics. It is developing at a rapid pace as the need for sustainable food production grows and freshwater and phosphorus supplies decline. Another innovative method to tackle the problem of farm irrigation is aeroponics. It is defined as an aerial water culture system or the science of growing plants without soil or substrate culture. The plant grows in the air with the help of artificial support and no soil or substrate is required to sustain the plant. The roots of the plant are suspended in a closed container in the dark and exposed to the open air to receive nutrient-rich water dispersed through atomizers. The modernisation, rehabilitation and renewal of irrigation systems provides an opportunity to reduce the use of pesticides and fertilisers in line with the Green Deal. It also provides an opportunity for Bulgarian farmers to be competitive with their counterparts in other countries. The effect could be strongest for permanent crops, fruit and vegetable production and livestock farming. The goal of the report is to focus on solutions to the problem of farm irrigation in the country by implementing innovative solutions. Key words: technology, agriculture, environment, innovation, irrigating JEL: O3, Q1, Q5, Q16.

CAGE17-1-Leg1 Cruise Report: Water column observation from CTD and water samples west of Prins Karls Forland, Svalbard

From the afternoon of May 15th to the afternoon of May 19th, CAGE-Centre for Arctic Gas Hydrate, Climate and Environment, the Department of Geoscience UiT, the Arctic University of Norway, arranged a scientific cruise to survey offshore Prins Karls Forland, Svalbard to perform CTD measurements and water sampling on R/V “Helmer Hanssen”. The purpose is to study the variations in methane release and its dependence on oceanographic changes. The area has been continuously surveyed for the last three years for methane concentration, and methane consumption by bacteria and other related data. Because of the good weather conditions time allowed survey of the outer part of the shelf west of Prins Karls Forland – the socalled ‘Masox area’. Here three CTD’s were taken and the area surveyed by echosounding (EK60), chirp and multibeam for combined flare survey (EK60) and geological recording of sedimentary environments (chirp and multibeam). A total of 69 CTD (conductivity-temperature-depth) casts were performed with 12 water bottles sampled for each CTD station. The cruise may be known as: CAGE17_1_leg1

Polar cod connectivity cruise 2022

The Nansen Legacy Polar Cod Connectivity cruise aimed at unravelling polar cod and capelin population connectivity and relation to the physical and chemical environment in Svalbard’s fjords. The main focus areas were Isfjorden, Kongsfjorden, Storfjorden and the South-East of Svalbard. A total of 36 stations were visited to collect of information on polar cod and capelin vertical and horizontal distribution (using echosounder, pelagic and bottom trawls), their population, life cycle and size structure (observation of maturity, otoliths reading and genetic sampling), as well as their diet (stomachs content, sampling of benthic/planktonic prey). Other studies were conducted in link with the objectives of the research foci RF2 The Human Impacts and RF3 The Living Barents Sea. The cruise was also an opportunity to visit well-known monitoring stations to complete already long time series and investigate seasonal variability. 
 The cruise started November 12th in Longyearbyen and ended in Tromsø on November 22nd, 2022. The first two days and a half were spent on multidisciplinary sampling in thirteen stations distributed in contrasted areas inside Isfjorden. A rockhopper gear strapping was installed after the first bottom trawl to avoid mud and rocks and kept for the whole cruise. There were some difficulties also with the grab which did not always close. It was possible to spend one day sampling Kongsfjorden, thanks to relatively good weather and low sea-ice conditions. However, the presence of cables on the seafloor and irregular and unsuitable bottom types in that fjord did not allow for bottom trawling to sample demersal and benthic communities. After approximately one day of steaming south in good weather conditions, the sampling continued in Storfjorden. However, the shallowest stations north of Storfjorden and on the way out of the fjord towards the South-East of the archipelago could not be sampled due to time constraints and difficult navigational access. Finally, five multidisciplinary stations could be sampled in the South-East of Svalbard before the two-days transit to Tromsø. Overall, most stations were visited. Polar cod largest fish were maturing, but not mature. Further analyses of the samples should unveil potential genetic differences across the fjords, and image analyses of plankton net samples will be able to detect if there were already eggs in the water column at the beginning of the dark season. There was very little signal on the echosounder during most of the cruise, but the extractive sampling revealed a diversity of communities in the different fjords.

Mumbai - An Engine for Atmanirbhar Bharat

Mumbai city is an island city which has a history starting from the 18th century when the Hornby vellard project reclaimed some areas from the seven islands from the sea. This transformed the area into a major seaport after development work like roads and railways was completed undertaken in the land in 1845. In 1960 the new state of Maharashtra was formed with its capital as Bombay, which was re-christened as Mumbai in 1995. It has steadily grown to be the economic hub and capital of India, with the help of its nature and inherent advantages. This paper attempts to give a comprehensive picture and a rational understanding of what defines Mumbai financially, its infrastructure and how improving this will impact positively its economy. Optimising the use of resources in one city (Mumbai) can actually impact the whole state and the nation as a whole. Building resilience requires long-term coordination and cooperation between cities decision-makers, communities, businesses and other stakeholders to reduce disaster risk, both through specific risk reduction policies and investments, and by improving infrastructure and the provision of services (UNISDR, 2012). The researcher has used suitable statistical techniques like correlation, charts histograms, trend lines, time series, scatter plot charts, polynomial lines and line graphs to illustrate points significant to the study and recommendations thereof. London, Zurich, Singapore, New York, Hong Kong, Chicago, Tokyo, Frankfurt, Shanghai etc. are major financial capitals of the world. Mumbai features as one among these financial hubs. Government and policy makers should ensure that the city is kept in the race. Using the Indian demographic advantage, good weather conditions as a leverage to project Mumbai as a global city is necessary. Use of smart technology in infrastructure, transportation, and housing helps corporations to work together with citizens toward better and citizen-centric cities.

Weather myths: how attractive is good weather really for same-day visits to outdoor recreation destinations?

ABSTRACT From a short-term (e.g. daily) perspective, visitor numbers to an outdoor recreation destination are strongly influenced by good or bad weather conditions. However, to date, a large body of literature has focused on tourists’ responses to climate change or weather conditions over a longer temporal scale, such as a year. Using data for Mount Rigi, a Swiss outdoor recreation destination, we specify a regression model to explain the variation in daily visitor numbers. Our findings confirm the strong weather and seasonal sensitivity that are often found in previous studies. However, we also found that the effect of the weather on daily visitors is not homogeneous but decreases with the number of previous sunny days within a given tourist season. Our finding is that, contrary to popular belief, the impact of weather on tourist service providers and destinations is less pronounced when viewed seasonally. We provide some possible explanations for these observations based on the destination’s characteristics, its visitor segment(s) and the theory of planned behaviour in tourism.

Arrival flight efficiency in pre- and post-Covid-19 pandemics

Covid-19 pandemic affected aviation severely, resulting in unprecedented reduction of air traffic. While aviation is slowly re-gaining traffic volumes, we use the opportunity to study the arrival performance in the Terminal Maneuvering Area (TMA) in non-congested scenarios.Applying flight efficiency and environmental performance indicators (PIs) to the historical data of arrivals to Stockholm Arlanda and Gothenburg Landvetter airports, we discover noticeable inefficiencies, despite significant reduction of traffic intensity. We analyze the impact of such factors as weather and traffic intensity on arrival efficiency in isolated scenarios when only one factor dominates: isolated scenario with low traffic and isolated scenario with good weather conditions. Our analysis uncovers that weather has a stronger influence than traffic intensity on the vertical efficiency, while traffic intensity has stronger effect on the lateral efficiency. Impact of traffic intensity on the lateral efficiency might be explained by frequent hold-on patterns and flight trajectory extensions due to vectoring in high traffic conditions. Further investigation is needed to explain weather and vertical/lateral efficiency correlations, the conclusions might be country-specific.

On the Spatio-Temporal Dependence of Anomalies in the Atmospheric Electric Field Just around the Time of Earthquakes

In this study, we report atmospheric electric field (AEF) anomalies observed around the time of earthquakes (EQs) in Japan. Using a newly developed AEF observation network with three spatially separated stations in Japan (Chofu, Kakioka, and Iwaki), we conducted a study for two EQs that occurred within a few 100 km from the EQ epicenter under relatively good local weather conditions as shown by a local all-sky camera and weather information. Time series and wavelet analyses of the AEF indicate that fluctuation anomalies in the AEF with periods of 10–60 min and larger than 70 min were observed from a few hours before up to a few hours after the occurrence of the EQs. The lag in the onset time increased with increasing distance from the EQ epicenter to the field site. The above-mentioned characteristics of these AEF fluctuation anomalies were similar among the three stations, and therefore the observed AEF anomalies were considered to be an imminent precursor of EQs. The observed AEF anomalies were likely to be caused by internal gravity waves (IGWs) generated around the EQ epicenter a few hours before the EQ, passing over the field site while changing the AEF by changing the space charge density in the surface layer of the atmosphere.

Joint Semantic Intelligent Detection of Vehicle Color under Rainy Conditions

Color is an important feature of vehicles, and it plays a key role in intelligent traffic management and criminal investigation. Existing algorithms for vehicle color recognition are typically trained on data under good weather conditions and have poor robustness for outdoor visual tasks. Fine vehicle color recognition under rainy conditions is still a challenging problem. In this paper, an algorithm for jointly deraining and recognizing vehicle color, (JADAR), is proposed, where three layers of UNet are embedded into RetinaNet-50 to obtain joint semantic fusion information. More precisely, the UNet subnet is used for deraining, and the feature maps of the recovered clean image and the extracted feature maps of the input image are cascaded into the Feature Pyramid Net (FPN) module to achieve joint semantic learning. The joint feature maps are then fed into the class and box subnets to classify and locate objects. The RainVehicleColor-24 dataset is used to train the JADAR for vehicle color recognition under rainy conditions, and extensive experiments are conducted. Since the deraining and detecting modules share the feature extraction layers, our algorithm maintains the test time of RetinaNet-50 while improving its robustness. Testing on self-built and public real datasets, the mean average precision (mAP) of vehicle color recognition reaches 72.07%, which beats both sate-of-the-art algorithms for vehicle color recognition and popular target detection algorithms.

Environmental DNA (eDNA) for monitoring marine mammals: Challenges and opportunities

Monitoring marine mammal populations is essential to permit assessment of population status as required by both national and international legislation. Traditional monitoring methods often rely on visual and/or acoustic detections from vessels and aircraft, but limitations including cost, errors in the detection of some species and dependence on taxonomic expertise, as well as good weather and visibility conditions often limit the temporal and spatial scale of effective, long-term monitoring programs. In recent years, environmental DNA (eDNA) has emerged as a revolutionary tool for cost-effective, sensitive, non-invasive species monitoring in both terrestrial and aquatic realms. eDNA is a rapidly developing field and a growing number of studies have successfully implemented this approach for the detection and identification of marine mammals. Here, we review 21 studies published between 2012 and 2021 that employed eDNA for marine mammal monitoring including single species detection, biodiversity assessment and genetic characterization. eDNA has successfully been used to infer species presence (especially useful for rare, elusive or threatened species) and to characterize the population genetic structure, although additional research is needed to support the interpretation of non-detections. Finally, we discuss the challenges and the opportunities that eDNA could bring to marine mammal monitoring as a complementary tool to support visual and acoustic methods.

Improved one-dimensional dilation-based top-hat algorithm for star segmentation under complicated background conditions.

The white top-hat transformation has been widely used in small bright target extraction. It usually applies an erosion operation to remove the target and then a dilation operation to recover the intensity of the processed image. A bright target will be extracted by subtracting the opening operation (erosion followed by dilation) from the raw image. The drawback of this method is that its denoising ability is poor because the estimated background threshold by an opening operation is smaller than the raw image. This study puts forward the viewpoint that by use of a proposed one-dimensional (1D) symmetrical line-shaped structuring element a bright target can also be removed by the dilation operation. Consequently, the white top-hat transformation can be implemented by subtracting only the dilation operation from the raw image. To the best knowledge of the authors, it is the first time to use this method to achieve the top-hat transformation. The simulation experiment shows that the proposed 1D top-hat algorithm has excellent performance in denoising ability and detection ability. Moreover, real night experiments demonstrate that our proposed algorithm can work reliably under both complicated background conditions and good weather conditions. It is noticeable that the performance of computational efficiency and resource consumption have been considerably improved because a 1D structuring element is employed and the erosion operation is not included.