Weather effects on intrahabitat movements of the western green lizard, Lacerta bilineata (Daudin, 1802), at its northern distribution range border: a radio-tracking study

2000 ◽  
Vol 78 (10) ◽  
pp. 1831-1839 ◽  
Author(s):  
P Sound ◽  
M Veith
Keyword(s):  
Activity Patterns ◽  
Strong Dependence ◽  
Weather Conditions ◽  
Distribution Range ◽  
Maximum Temperature ◽  
Second Phase ◽  
Northern Distribution ◽  
Radio Transmitters ◽  
Movement Parameters ◽  
Bad Weather

Daily activity patterns of male western green lizards, Lacerta bilineata (Daudin, 1802), at the edge of their northern distribution range in western Germany after the breeding season from June to October were recorded using implanted radio transmitters. Different activity indices discriminating between stimulation, duration, and length of movement were correlated with actual weather conditions (d0) and with weather conditions on the 2 previous days (d-1 and d-2). The lizards' dependence on weather showed two different phases throughout the study period. During the first period and in the period preceding a drastic change of weather in midsummer, weather had no significant influence on movement parameters. After that event, temperatures dropped and a strong dependence on weather of all movement parameters except those indicating displacements became apparent. Thresholds for 50% activity during this second phase were a maximum temperature of 17°C and a minimum humidity of 35%. Two days after periods of bad weather, the influence of weather conditions increased again. This can be explained by physiological deficits that require compensation during the period of marginal weather conditions prior to hibernation. Displacement movements were significantly longer than home-range movements and were neither triggered nor modulated by the weather. They must therefore represent activities such as patrolling territory boundaries.

CNN-based Rain Reduction in Street View Images

2020 ◽  
Vol 2020 (1) ◽  
pp. 78-81
Author(s):  
Simone Zini ◽  
Simone Bianco ◽  
Raimondo Schettini
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
State Of The Art ◽  
Weather Conditions ◽  
Specific Interest ◽  
Optical Character ◽  
Street View ◽  
In The Wild ◽  
Bad Weather ◽  
Detection And Recognition

Rain removal from pictures taken under bad weather conditions is a challenging task that aims to improve the overall quality and visibility of a scene. The enhanced images usually constitute the input for subsequent Computer Vision tasks such as detection and classification. In this paper, we present a Convolutional Neural Network, based on the Pix2Pix model, for rain streaks removal from images, with specific interest in evaluating the results of the processing operation with respect to the Optical Character Recognition (OCR) task. In particular, we present a way to generate a rainy version of the Street View Text Dataset (R-SVTD) for "text detection and recognition" evaluation in bad weather conditions. Experimental results on this dataset show that our model is able to outperform the state of the art in terms of two commonly used image quality metrics, and that it is capable to improve the performances of an OCR model to detect and recognise text in the wild.

scholarly journals AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk
Keyword(s):  
Atmospheric Pressure ◽  
Real Life ◽  
Real Data ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Air Masses ◽  
Weather Forecasts ◽  
Life Problems ◽  
The World ◽  
The City

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.

Short-term scheduling problem in smart grid considering reliability improvement in bad weather conditions

2017 ◽  
Vol 11 (10) ◽  
pp. 2521-2533 ◽  
Author(s):  
Babak Yousefi-khangah ◽  
Saeid Ghassemzadeh ◽  
Seyed Hossein Hosseini ◽  
Behnam Mohammadi-Ivatloo
Keyword(s):  
Smart Grid ◽  
Weather Conditions ◽  
Scheduling Problem ◽  
Short Term ◽  
Reliability Improvement ◽  
Bad Weather

scholarly journals Risk Analysis and Management of Moored Ships in Ports

2018 ◽  
Author(s):  
Liliana V. Pinheiro ◽  
Conceição J. E. M. Fortes ◽  
João A. Santos
Keyword(s):  
Integrated Management ◽  
Warning System ◽  
Weather Conditions ◽  
Complete Information ◽  
Decision Makers ◽  
Modular System ◽  
Economic Losses ◽  
Sea Waves ◽  
Bad Weather ◽  
Port Areas

The risks associated with mooring of ships are a major concern for port and maritime authorities. Sea waves and extreme weather conditions can lead to excessive movements of vessels and mooring loads affecting the safety of ships, cargo, passengers, crew or port infrastructures. Normally, port activities such as ships’ approach manoeuvres and loading/unloading operations, are conditioned or suspended based solely on weather or wave forecasts, causing large economic losses. Nevertheless, it has been shown that some of the most hazardous events with moored ships happen on days with mild sea and wind conditions, being the culprit long waves and resonance phenomena. Bad weather conditions can be managed with an appropriate or reinforced mooring arrangement. A correct risk assessment must be based on the movements of the ship and on the mooring loads, taking into account all the moored ship’s system. In this paper, the development of a forecast and warning system based on the assessment of risks associated with moored ships in port areas, SWAMS ALERT, is detailed. This modular system can be scaled and adapted to any port, providing decision-makers with accurate and complete information on the behaviour of moored ships, movements and mooring loads, allowing a better planning and integrated management of port areas.

scholarly journals Sugarcane stems as larval habitat for the stable fly (Stomoxys calcitrans) in sugarcane plantations

2013 ◽  
Vol 33 (6) ◽  
pp. 741-744 ◽  
Author(s):  
Paulo H.D. Cançado ◽  
Taciany Ferreira ◽  
Eliane M. Piranda ◽  
Cleber O. Soares
Keyword(s):  
Primary Source ◽  
Weather Conditions ◽  
Larval Habitat ◽  
Stomoxys Calcitrans ◽  
Stable Fly ◽  
Mato Grosso ◽  
Larval Habitats ◽  
Control Programs ◽  
Bad Weather ◽  
Mato Grosso Do Sul

Outbreaks of stable fly, Stomoxys calcitrans, cause losses for livestock producers located near sugarcane mills in Brazil, especially in southern Mato Grosso do Sul. The sugarcane mills are often pointed by local farmers as the primary source of these outbreaks; some mills also joined the farmers in combating the flies. Brazilian beef cattle production has great economic importance in similar level to bio-fuel production as ethanol. In this context, the wide-ranging knowledge on the biology and ecology of the stable fly, including larval habitats and their reproduction sites is extremely important for further development of control programs. This paper aims to report the occurrence and development of S. calcitrans larvae inside sugarcane stems in three municipalities of Mato Grosso do Sul. The sugarcane stems give protection against bad weather conditions and insecticide application. In this way, for sustainable sugarcane growth specific research concerning this situation should be conducted.

The Effect of Curvature and Torsion on the Temperature Distribution in a Helix

1985 ◽  
Vol 52 (3) ◽  
pp. 529-532 ◽  
Author(s):  
D. D. Sayers ◽  
M. C. Potter
Keyword(s):  
Differential Equation ◽  
Finite Element Method ◽  
Partial Differential Equation ◽  
Temperature Distribution ◽  
Strong Dependence ◽  
Maximum Temperature ◽  
Nonuniform Heating ◽  
The Finite Element Method ◽  
Curvature Parameter ◽  
Curvature And Torsion

Traditional analysis treats the helix as a straight wire with the effects of nonuniform heating, torsion, and large curvature ignored. Using a helical coordinate system the governing partial differential equation including these effects is derived. The equation is then solved numerically using the finite element method. The results indicate a strong dependence of the temperature on the torsion parameter when the curvature parameter is significant. As the curvature parameter increases, the temperature distribution becomes skew-symmetric and the maximum temperature in the helix increases. Nonuniform heating influences the temperature distribution independent of the curvature and torsion.

scholarly journals SUMMARY OF NATURAL DISASTER RESPONSES BY THE ADVANCED LAND OBSERVING SATELLITE-2 (ALOS-2)

2019 ◽  
Vol XLII-3/W7 ◽  
pp. 69-72 ◽  
Author(s):  
T. Tadono ◽  
M. Ohki ◽  
T. Abe
Keyword(s):  
Natural Disasters ◽  
Weather Conditions ◽  
Forest Monitoring ◽  
Array Type ◽  
Microwave Radar ◽  
Typical Data ◽  
Disaster Monitoring ◽  
Operational Phase ◽  
Bad Weather ◽  
Area Monitoring

<p><strong>Abstract.</strong> The Advanced Land Observing Satellite-2 (ALOS-2) was launched on May 24, 2014, and it is operating very well in space more than 4.5 years. The designed mission life is five years as nominal operational phase and the target is over seven years since launch the satellite. The mission objectives of ALOS-2 are 1) disaster monitoring, 2) national land and infrastructure information, 3) cultivated area monitoring, and 4) global forest monitoring. To achieve the objectives, ALOS-2 carries on the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2), which is an active microwave radar using the 1.2 GHz frequency band and observes in day and night times even in bad weather conditions as successor PALSAR instrument onboard ALOS satellite operated from 2006 to 2011. PALSAR-2 instrument has several enhanced features from PALSAR e.g. finer spatial resolution, spotlight observing mode, dual-polarisation ScanSAR. This paper summarises an introduction of typical data analysis results for monitoring natural disasters by ALOS-2 during the operational phase. As the response natural disasters, more than 400 times of the emergency observations have been conducted to identify damages caused by volcanic activities, earthquakes, flooding etc. happened in Japan and the World.</p>

scholarly journals ROUTINE, EXTREME AND ENGINEERING METEOROLOGY ANALYSIS FOR KARACHI COASTAL AREA

2020 ◽  
Vol 4 (1) ◽  
pp. 15-22
Author(s):  
Muhammad Taqui ◽  
Jabir Hussain Syed ◽  
Ghulam Hassan Askari
Keyword(s):  
Climate Change ◽  
Coastal Area ◽  
Meteorological Parameters ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Meteorological Station ◽  
Annual Precipitation ◽  
Maximum Temperature ◽  
Intergovernmental Panel ◽  
Interdisciplinary Field

Pakistan’s largest city, Karachi, which is industrial centre and economic hub needs focus in research and development of every field of Engineering, Science and Technology. Urbanization and industrialization is resulting bad weather conditions which prolongs until a climate change. Since, Meteorology serves as interdisciplinary field of study, an analytical study of real and region-specific meteorological data is conducted which focuses on routine, extreme and engineering meteorology of metropolitan city Karachi. Results of study endorse the meteorological parameters relationship and establish the variability of those parameters for Karachi Coastal Area. The rise of temperature, decreasing trend of atmospheric pressure, increment in precipitation and fall in relative humidity depict the effects of urbanization and industrialization. The recorded extreme maximum temperature of 45.50C (on June 11, 1988) and the extreme minimum temperature of 4.5 0C(on January 1, 2007) is observed at Karachi south meteorological station. The estimated temperature rise in 32 years is 0.9 0C, which is crossing the Intergovernmental Panel on Climate Change (IPCC) predicted/estimated limit of 2oC rise per century. The maximum annual precipitation of 487.0mm appearing in 1994 and the minimum annual precipitation of 2.5mm appearing in 1987 is observed at same station which is representative meteorological station for Karachi Coast. Further Engineering meteorological parameters for heating ventilation air condition (HVAC) system design for industrial purpose are deduced as supporting data for coastal area site study for industrial as well as any follow-up engineering work in the specified region.

scholarly journals Spatial Analysis and Geographic Factors Associated with Cutaneous Leishmaniasis in Southern Iran

2020 ◽  
Author(s):  
Mehdi Sharafi ◽  
Zahra Poormotaseri ◽  
Jalal Karimi ◽  
Shahab Rezaeian ◽  
Seyedeh Leila Dehghani ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Cutaneous Leishmaniasis ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Least Square ◽  
Environmental Data ◽  
Maximum Temperature ◽  
Fars Province ◽  
Disease Pattern ◽  
And Control

Introduction: This study aimed to determine the hotspot areas for Cutaneous Leishmaniasis (CL) in Fasa city and assess the relations between the geographical factors with CL incidence using spatial analysis. Materials and Methods: This ecological study was conducted in Fasa city, data of the CL disease such as the total number of CL cases and the population at risk from 2009 to 2014. Weather conditions' data including the means of temperature, humidity, rainfall, sunny days, rainy days, and evaporation were collected from the weather forecast centers in Fars province. The disease cases' information such as the number of disease cases was collected from all healthcare centers located in Fasa City. Ordinary Least Square (OLS) and Global Moran’s Index (GMI) were used to assess the associations of the various environmental variables with CL incidence and to map clustering of CL cases across the region. Results: The cumulative incidence of CL was 16 per 10,000 populations during a six-year period. The results showed the southern area of Fasa as a hotspot area which is considered as hyperendemic foci for CL. OLS revealed a high incidence of CL in areas with maximum temperature, mean of temperature, mean of evaporation, sunny days and wind velocity. Conclusion: A spatial disease pattern was found in the present study. Hence, substantial consideration to environmental data leads to not only suitable protection against CL but also designing a suitable measure for the prevention and control of the disease.

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