Search results for: weather variation

Authors: Odejayi Adedayo Olugbenga, Aina Adebisi

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Weather variables (rainfall and temperature) affect the diversity and abundance of both fauna and flora species. This study compared the weather variables with spider abundance in two ecological zones of Ogun State, Nigeria namely Ago-iwoye (Rainforest) in the Ijebu axis and Aiyetoro (Derived Savannah) in the Yewa axis. Seven study sites chosen by Simple Random Sampling in each ecosystem were used for the study. In each sampling area, a 60 m x 120 m land area was marked and sampled, spider collection techniques were; hand picking, use of sweep netting, and Pitfall trap. Adult spiders were identified to the species level. Species richness was estimated by a non-parametric species estimator while the diversity of spider species was assessed by Simpson Diversity Index and Species Richness by One-way Analysis of Variance. Results revealed that spiders were more abundant in rainforest zones than in derived savannah ecosystems. However, the pattern of spider abundance in rainforest zone and residential areas were similar. During high temperatures, the activities of spiders tended to increase according to this study. In contrast, results showed that there was a negative correlation between rainfall and spider species abundance in addition to a negative and weak correlation between rainfall and species richness. It was concluded that heavy downpour has lethal effects on both immature and sometimes matured spiders, which could lead to the extinction of some unknown species of spiders. Tree planting should be encouraged, as this shelters the spider.

Keywords: spider, abundance, species richness, species diversity

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Authors: Krismonika Khoirunnisa

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This research article aims to describe the variation of the Javanese lexicon "Sleep " and its distribution in the Jombang area, East Java. The objectives of this study were (1) to classify the variation of the "Sleep" lexicon in the Jombang area and (2) to design the fish rips for the variation of the "Sleep" lexicon according to their distribution. This type of research is a qualitative descriptive study using the method of leading proficiency, namely conducting interviews with speakers without directly meeting the speakers (interviews via WhatsApp and email as the media). This research article uses techniques record as support and tools for mapping and classifying data, collecting data in this study conducted at four points, namely the Kaliwungu village (Jombang City), Banjardowo village (District of Jombang), Mayangan Village (Subdistrict Jogoroto), and Karobelah village (Subdistrict Mojoagung) as a target investigators to conduct the interview. This study uses the dialectology theory as a basis for analyzing the data obtained. The results of this study found that the Javanese language variation "Sleep" has many different linguals, meanings, and forms even though they are in the same area (Jombang).

Keywords: geographical dialectology, lexicon variations, jombangan dialect, sssavanese language

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Authors: Sepehr Moradi

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This study investigates the contribution of individual Australian Superfine Merino Wool (ASFW) and Inner Mongolia Cashmere (IMC) fibres strength behaviour to the breaking force variation (CVBF) and minimum fibre diameter (CVₘFD) induced by actual single fibre lengths and the combination of length and diameter groups. Mid-side samples were selected for the ASFW (n = 919) and IMC (n = 691) since it is assumed to represent the average of the whole fleece. The average (LₘFD) varied for ASFW and IMC by 36.6 % and 33.3 % from shortest to longest actual single fibre length and -21.2 % and -21.7 % between longest-coarsest and shortest-finest groups, respectively. The tensile properties of single animal fibres were characterised using Single Fibre Analyser (SIFAN 4). After normalising for diversity in fibre diameter at the position of breakage, the parameters, which explain the strength behaviour within actual fibre lengths and combination of length-diameter groups, were the Intrinsic Fibre Strength (IFS) (MPa), Min IFS (MPa), Max IFS (MPa) and Breaking force (BF) (cN). The average strength of single fibres varied extensively within actual length groups and within a combination of length-diameter groups. IFS ranged for ASFW and IMC from 419 to 355 MPa (-15.2 % range) and 353 to 319 (-9.6 % range) and BF from 2.2 to 3.6 (63.6 % range) and 3.2 to 5.3 cN (65.6 % range) from shortest to longest groups, respectively. Single fibre properties showed no differences within actual length groups and within a combination of length-diameter groups, or was there a strong interaction between the strength of single fibre (P > 0.05) within remaining and removing length-diameter groups. Longer-coarser fibre fractionation had a significant effect on BF and IFS and all of the length groups showed a considerable variance in single fibre strength that is accounted for by diversity in the diameter variation along the fibre. There are many concepts for the improvement of the stress-strain properties of animal fibres as a means of raising a single fibre strength by simultaneous changes in fibre length and diameter. Fibre fractionation over a given length directly for single fibre strength or using the variation traits of fibre diameter is an important process used to increase the strength of the single fibre.

Keywords: single animal fibre fractionation, actual length groups, strength variation, length-diameter groups, diameter variation along fibre

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Authors: Carla Idely Palencia-Aguilar

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Artificial wetlands play an important role at Guasca Municipality in Colombia, not only because they are used for the agroindustry, but also because more than 45 species were found, some of which are endemic and migratory birds. Remote sensing was used to determine the changes in the area occupied by water of artificial wetlands by means of Aster and Modis images for different time periods. Evapotranspiration was also determined by three methods: Surface Energy Balance System-Su (SEBS) algorithm, Surface Energy Balance- Bastiaanssen (SEBAL) algorithm, and Potential Evapotranspiration- FAO. Empirical equations were also developed to determine the relationship between Normalized Difference Vegetation Index (NDVI) versus net radiation, ambient temperature and rain with an obtained R2 of 0.83. Groundwater level fluctuations on a daily basis were studied as well. Data from a piezometer placed next to the wetland were fitted with rain changes (with two weather stations located at the proximities of the wetlands) by means of multiple regression and time series analysis, the R2 from the calculated and measured values resulted was higher than 0.98. Information from nearby weather stations provided information for ordinary kriging as well as the results for the Digital Elevation Model (DEM) developed by using PCI software. Standard models (exponential, spherical, circular, gaussian, linear) to describe spatial variation were tested. Ordinary Cokriging between height and rain variables were also tested, to determine if the accuracy of the interpolation would increase. The results showed no significant differences giving the fact that the mean result of the spherical function for the rain samples after ordinary kriging was 58.06 and a standard deviation of 18.06. The cokriging using for the variable rain, a spherical function; for height variable, the power function and for the cross variable (rain and height), the spherical function had a mean of 57.58 and a standard deviation of 18.36. Threatens of eutrophication were also studied, given the unconsciousness of neighbours and government deficiency. Water quality was determined over the years; different parameters were studied to determine the chemical characteristics of water. In addition, 600 pesticides were studied by gas and liquid chromatography. Results showed that coliforms, nitrogen, phosphorous and prochloraz were the most significant contaminants.

Keywords: DEM, evapotranspiration, geostatistics, NDVI

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Authors: Parvin Ghafarian, Mohammadreza Mohammadpur Panchah, Mehri Fallahi

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Synoptic patterns from surface up to tropopause are very important for forecasting the weather and atmospheric conditions. There are many tools to prepare and analyze these maps. Reanalysis data and the outputs of numerical weather prediction models, satellite images, meteorological radar, and weather station data are used in world forecasting centers to predict the weather. The forecasting extreme precipitating on the southern coast of the Caspian Sea (CS) is the main issue due to complex topography. Also, there are different types of climate in these areas. In this research, we used two reanalysis data such as ECMWF Reanalysis 5th Generation Description (ERA5) and National Centers for Environmental Prediction /National Center for Atmospheric Research (NCEP/NCAR) for verification of the numerical model. ERA5 is the latest version of ECMWF. The temporal resolution of ERA5 is hourly, and the NCEP/NCAR is every six hours. Some atmospheric parameters such as mean sea level pressure, geopotential height, relative humidity, wind speed and direction, sea surface temperature, etc. were selected and analyzed. Some different type of precipitation (rain and snow) was selected. The results showed that the NCEP/NCAR has more ability to demonstrate the intensity of the atmospheric system. The ERA5 is suitable for extract the value of parameters for specific point. Also, ERA5 is appropriate to analyze the snowfall events over CS (snow cover and snow depth). Sea surface temperature has the main role to generate instability over CS, especially when the cold air pass from the CS. Sea surface temperature of NCEP/NCAR product has low resolution near coast. However, both data were able to detect meteorological synoptic patterns that led to heavy rainfall over CS. However, due to the time lag, they are not suitable for forecast centers. The application of these two data is for research and verification of meteorological models. Finally, ERA5 has a better resolution, respect to NCEP/NCAR reanalysis data, but NCEP/NCAR data is available from 1948 and appropriate for long term research.

Keywords: synoptic patterns, heavy precipitation, reanalysis data, snow

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Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

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The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events

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Authors: Ridha Fethi Mechlouch, Ahlem Ayadi, Ammar Ben Brahim

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Given the importance of the preservation of polyphenols and carotenoids during thermal processing, we attempted in this study to investigate the variation of these two parameters in faba beans during microwave treatment using different power densities (1; 2; and 3W/g), then to perform a mathematical modeling by using non-linear regression analysis to evaluate the models constants. The variation of the carotenoids and polyphenols ratio of faba beans and the models are tested to validate the experimental results. Exponential models were found to be suitable to describe the variation of caratenoid ratio (R²= 0.945, 0.927 and 0.946) for power densities (1; 2; and 3W/g) respectively, and polyphenol ratio (R²= 0.931, 0.989 and 0.982) for power densities (1; 2; and 3W/g) respectively. The effect of microwave power density Pd(W/g) on the coefficient k of models were also investigated. The coefficient is highly correlated (R² = 1) and can be expressed as a polynomial function.

Keywords: microwave treatment, power density, carotenoid, polyphenol, modeling

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: Thapasya J., Rajesh Kumar

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Language plays complex roles in society. The previous studies on language and society explain their interconnected, complementary and complex interactions and, those studies were primarily focused on the variations in the language. Variation being the fundamental nature of languages, the question of personal and social identity navigated through language variation and established that there is an interconnection between language variation and identity. This paper analyses the sociolinguistic variation in language at the lexical level and how the lexical choice of the speaker(s) affects in shaping their identity. It obtains primary data from the lexicon of the Mappila dialect of Malayalam spoken by the members of Mappila (Muslim) community of Kerala. The variation in the lexical choice is analysed by collecting data from the speech samples of 15 minutes from four different age groups of Mappila dialect speakers. Various contexts were analysed and the frequency of borrowed words in each instance is calculated to reach a conclusion on how the variation is happening in the speech community. The paper shows how the lexical choice of the speakers could be socially motivated and involve in shaping and changing identities. Lexical items or vocabulary clearly signal the group identity and personal identity. Mappila dialect of Malayalam was rich in frequent use of borrowed words from Arabic, Persian and Urdu. There was a deliberate attempt to show their identity as a Mappila community member, which was derived from the socio-political situation during those days. This made a clear variation between the Mappila dialect and other dialects of Malayalam at the surface level, which was motivated to create and establish the identity of a person as the member of Mappila community. Historically, these kinds of linguistic variation were highly motivated because of the socio-political factors and, intertwined with the historical facts about the origin and spread of Islamism in the region; people from the Mappila community highly motivated to project their identity as a Mappila because of the social insecurities they had to face before accepting that religion. Thus the deliberate inclusion of Arabic, Persian and Urdu words in their speech helped in showing their identity. However, the socio-political situations and factors at the origin of Mappila community have been changed over a period of time. The social motivation for indicating their identity as a Mappila no longer exist and thus the frequency of borrowed words from Arabic, Persian and Urdu have been reduced from their speech. Apart from the religious terms, the borrowed words from these languages are very few at present. The analysis is carried out by the changes in the language of the people according to their age and found to have significant variations between generations and literacy plays a major role in this variation process. The need of projecting a specific identity of an individual would vary according to the change in the socio-political scenario and a variation in language can shape the identity in order to go with the varying socio-political situation in any language.

Keywords: borrowings, dialect, identity, lexical choice, literacy, variation

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Authors: Kristine Nore, Alexander Severnisen, Petter Arnestad, Dimitris Kraniotis, Roy Rossebø

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Natural materials like wood, absorb and release moisture. Thus wood can buffer indoor climate. When used wisely, this buffer potential can be used to counteract the outer climate influence on the building. The mass of moisture used in the buffer is defined as the potential hygrothermal mass, which can be an energy storage in a building. This works like a natural heat pump, where the moisture is active in damping the diurnal changes. In Norway, the ability of wood as a material used for climate buffering is tested in several buildings with the extensive use of wood, including supermarkets. This paper defines the potential of hygrothermal mass in a supermarket building. This includes the chosen ventilation strategy, and how the climate impact of the building is reduced. The building is located above the arctic circle, 50m from the coastline, in Valnesfjord. It was built in 2015, has a shopping area, including toilet and entrance, of 975 m². The climate of the area is polar according to the Köppen classification, but the supermarket still needs cooling on hot summer days. In order to contribute to the total energy balance, wood needs dynamic influence to activate its hygrothermal mass. Drying and moistening of the wood are energy intensive, and this energy potential can be exploited. Examples are to use solar heat for drying instead of heating the indoor air, and raw air with high enthalpy that allow dry wooden surfaces to absorb moisture and release latent heat. Weather forecasts are used to define the need for future cooling or heating. Thus, the potential energy buffering of the wood can be optimized with intelligent ventilation control. The ventilation control in Valnesfjord includes the weather forecast and historical data. That is a five-day forecast and a two-day history. This is to prevent adjustments to smaller weather changes. The ventilation control has three zones. During summer, the moisture is retained to dampen for solar radiation through drying. In the winter time, moist air let into the shopping area to contribute to the heating. When letting the temperature down during the night, the moisture absorbed in the wood slow down the cooling. The ventilation system is shut down during closing hours of the supermarket in this period. During the autumn and spring, a regime of either storing the moisture or drying out to according to the weather prognoses is defined. To ensure indoor climate quality, measurements of CO₂ and VOC overrule the low energy control if needed. Verified simulations of the Valnesfjord building will build a basic model for investigating wood as a climate regulating material also in other climates. Future knowledge on hygrothermal mass potential in materials is promising. When including the time-dependent buffer capacity of materials, building operators can achieve optimal efficiency of their ventilation systems. The use of wood as a climate regulating material, through its potential hygrothermal mass and connected to weather prognoses, may provide up to 25% energy savings related to heating, cooling, and ventilation of a building.

Keywords: climate buffer, energy, hygrothermal mass, ventilation, wood, weather forecast

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Authors: Shailaja Grover, Purvi Tiwari, Vigneshwaran S. R., U. Dinesh Kumar

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In India, grapes are one of the most important horticulture crops. Grapes are most vulnerable to downy mildew, which is one of the most devasting diseases. In the absence of a precise weather-based advisory system, farmers spray pesticides on their crops extensively. There are two main challenges associated with using these pesticides. Firstly, most of these sprays were panic sprays, which could have been avoided. Second, farmers use more expensive "Preventive and Eradicate" chemicals than "Systemic, Curative and Anti-sporulate" chemicals. When these chemicals are used indiscriminately, they can enter the fruit and cause health problems such as cancer. This paper utilizes decision trees and predictive modeling techniques to provide grape farmers with customized advice on grape disease management. This model is expected to reduce the overall use of chemicals by approximately 50% and the cost by around 70%. Most of the grapes produced will have relatively low residue levels of pesticides, i.e., below the permissible level.

Keywords: analytics in agriculture, downy mildew, weather based advisory, decision tree, predictive modelling

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Authors: M. T. Amina, A. A. Alazba, U. Manzoor

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Solar disinfection (SODIS) is a viable method for household water treatment and is recommended by the World Health Organization as cost effective approach that can be used without special skills. The efficiency of both SODIS and solar collector disinfection (SOCODIS) system was evaluated using four different sources of water including stored rainwater, storm water, ground water and treated sewage. Samples with naturally occurring microorganisms were exposed to sunlight for about 8-9 hours in 2-L polyethylene terephthalate bottles under similar experimental conditions. Total coliform (TC), Escherichia coli (E. coli) and heterotrophic plate counts (HPC) were used as microbial water quality indicators for evaluating the disinfection efficiency at different sunlight intensities categorized as weak, mild and strong weathers. Heterotrophic bacteria showed lower inactivation rates compared to E. coli and TC in both SODIS and SOCODIS system. The SOCODIS system at strong weather was the strongest disinfection system in this study and the complete inactivation of HPC was observed after 8-9 hours of exposure with SODIS being ineffective for HPC. At moderate weathers, however, the SOCODIS system did not show complete inactivation of HPC due to very high concentrations (up to 5x10^7 CFU/ml) in both storm water and treated sewage. SODIS even remained ineffective for the complete inactivation of E. coli due to its high concentrations of about 2.5x10^5 in treated sewage compared with other waters even after 8-9 hours of exposure. At weak weather, SODIS was not effective at all while SOCODIS system, though incomplete, showed good disinfection efficiency except for HPC and to some extent for high E. coli concentrations in storm water. Largest reduction of >5 log occurred for TC when used stored rainwater even after 6 hours of exposure in the case of SOCODIS system at strong weather. The lowest E. coli and HPC reduction of ~2 log was observed in SODIS system at weak weather. Further tests with varying pH and turbidity are required to understand the effects of reaction parameters that could be a step forward towards maximizing the disinfection efficiency of such systems for the complete inactivation of naturally occurring E. coli or HPC at moderate or even at weak weathers.

Keywords: efficiency, microbial, SODIS, SOCODIS, weathers

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Authors: Md. Jahoor Alam

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Recent studies suggest that Glucose controls several lifesaving pathways. Glucose molecule is reported to be responsible for the production of ROS (reactive oxygen species). In the present work, a p53-MDM2-Glucose model is developed in order to study spatiotemporal properties of the p53 pathway. The systematic model is mathematically described. The model is numerically simulated using high computational facility. It is observed that the variation in glucose concentration level triggers the system at different states, namely, oscillation death (stabilized), sustain and damped oscillations which correspond to various cellular states. The transition of these states induced by glucose is phase transition-like behaviour. Further, the amplitude of p53 dynamics with the variation of glucose concentration level follows power law behaviour, As(k) ~ kϒ, where, ϒ is a constant. Further Stochastic approach is needed for understanding of realistic behaviour of the model. The present model predicts the variation of p53 states under the influence of glucose molecule which is also supported by experimental facts reported by various research articles.

Keywords: oscillation, temporal behavior, p53, glucose

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Authors: Siphat Lim

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The result of the study revealed that the interaction between money, exchange rate, and price level was mainly derived from the policy-induced by the central bank. Furthermore, the variation of inflation was explained weakly by exchange rate and money supply. In the period of twelfth-month, the variation of inflation which caused by exchange rate and money supply were not more than 1.78 percent and 9.77 percent, respectively.

Keywords: money supply, exchange rate, price level, VAR model

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Authors: M. Yousefi, N. Nasirzadeh

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In this paper, behavior of an oscillator under injection of another signal has been investigated. Also, variation of output signal amplitude versus injected signal phase variation, the effect of varying the amplitude of injected signal and quality factor of the oscillator has been investigated. The results show that the locking time depends on phase and the best locking time happens at 180-degrees phase. Also, the effect of injected lock has been discussed. Simulations show that the locking time decreases with signal injection to bulk. Locking time has been investigated versus various phase differences. The effect of phase and amplitude changes on locking time of a typical LC oscillator in 180 nm technology has been investigated.

Keywords: analysis, oscillator, injection-lock oscillator, phase modulation

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Authors: Hoyoung Lee, Dong-Kyu Kim, Seung-Young Kho, R. Eddie Wilson

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This study quantifies a decrement in freeway capacity during rainfall. Traffic and rainfall data were gathered from Highway Agencies and Wunderground weather service. Three inter-urban freeway sections and its nearest weather stations were selected as experimental sites. Capacity analysis found reductions of maximum and mean pre-breakdown flow rates due to rainfall. The Kruskal-Wallis test also provided some evidence to suggest that the variance in the pre-breakdown flow rate is statistically insignificant. Potential application of this study lies in the operation of real time traffic management schemes such as Variable Speed Limits (VSL), Hard Shoulder Running (HSR), and Ramp Metering System (RMS), where speed or flow limits could be set based on a number of factors, including rainfall events and their intensities.

Keywords: capacity randomness, flow breakdown, freeway capacity, rainfall

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Authors: Said Ettaieb, Kamel Hamrouni, Su Ruan

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This paper presents a new method based both on Active Shape Model and a priori knowledge about the spatio-temporal shape variation for tracking deformable structures in medical imaging. The main idea is to exploit the a priori knowledge of shape that exists in ASM and introduce new knowledge about the shape variation over time. The aim is to define a new more stable method, allowing the reliable detection of structures whose shape changes considerably in time. This method can also be used for the three-dimensional segmentation by replacing the temporal component by the third spatial axis (z). The proposed method is applied for the functional and morphological study of the heart pump. The functional aspect was studied through temporal sequences of scintigraphic images and morphology was studied through MRI volumes. The obtained results are encouraging and show the performance of the proposed method.

Keywords: active shape model, a priori knowledge, spatiotemporal shape variation, deformable structures, medical images

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Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

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The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

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Authors: F. B. Masok, S. S Songdeg, R. R. Dawam

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Vision is an important process for learning and communication as man depends greatly on vision to sense his environment. Prevalence and variation of refractive errors conducted between December 2010 and May 2011 in Jos, revealed that 735 (77.50%) out 950 subjects examined for refractive error had various refractive errors. Myopia was observed in 373 (49.79%) of the subjects, the error in the right eyes was 263 (55.60%) while the error in the left was 210(44.39%). The mean myopic error was found to be -1.54± 3.32. Hyperopia was observed in 385 (40.53%) of the sampled population comprising 203(52.73%) of the right eyes and 182(47.27%). The mean hyperopic error was found to be +1.74± 3.13. Astigmatism accounted for 359 (38.84%) of the subjects, out of which 193(53.76%) were in the right eyes while 168(46.79%) were in the left eyes. Presbyopia was found in 404(42.53%) of the subjects, of this figure, 164(40.59%) were in the right eyes while 240(59.41%) were in left eyes. The number of right eyes and left eyes with refractive errors was observed in some age groups to increase with age and later had its peak within 60 – 69 age groups. This pattern of refractive errors could be attributed to exposure to various forms of light particularly the ultraviolet rays (e.g rays from television and computer screen). There was no remarkable differences between the mean Myopic error and mean Hyperopic error in the right eyes and in the left eyes which suggest the right eye and the left eye are similar.

Keywords: left eye, refractive errors, right eye, variation

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Authors: I. Szer, J. Szer, M. Pieńko, A. Robak, P. Jamińska-Gadomska

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Work at height, such as construction works on scaffoldings, is associated with a considerable risk. Scaffolding workers are usually exposed to changing weather conditions what can additionally increase the risk of dangerous situations. Therefore, it is very important to foresee the risk of adverse conditions to which the worker may be exposed. The data from meteorological stations may be used to asses this risk. However, the dependency between weather conditions on a scaffolding and in the vicinity of meteorological station, should be determined. The paper presents an analysis of two selected environmental parameters which have influence on the behavior of workers – air temperature and wind speed. Measurements of these parameters were made between April and November of 2016 on ten scaffoldings located in different parts of Poland. They were compared with the results taken from the meteorological stations located closest to the studied scaffolding. The results gathered from the construction sites and meteorological stations were not the same, but statistical analyses have shown that they were correlated.

Keywords: scaffolding, health and safety at work, temperature, wind velocity

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Authors: Betty Makena, Tsegaye Tadesse, Mark Svoboda

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Global warming has intensified the frequency and intensity of extreme climate disasters and led to unpredictable weather conditions. Consequently, rapid shifts between drought and floods, known as Drought-Flood Abrupt Alteration (DFAA), have become increasingly common. DFAA results in superimposed impacts of drought and floods within a short period, exacerbating the effects of the floods or drought event. Current disaster management plans often overlook DFAA events, as they primarily focus on either floods or drought. Therefore, effectively identifying DFAA events is crucial for developing effective mitigation strategies. This study aims to identify historical DFAA events in Kenya using the Long Cycle Drought-Flood Abrupt Alteration Index (LDFAI). The research will analyze the spatial distribution, temporal variation, and intensity of DFAA events from 1990 to 2023, as well as their socio-economic impacts. Understanding these events is important to develop more effective strategies to address the impacts of DFAA events. Findings from this study will inform decision making to develop coping strategies to mitigate the adverse effects of DFAA in Kenya.

Keywords: abrupt, alteration, drought, floods

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Authors: Bandreddy Anand Babu, Srinivasa Rao Mandadi, C. Pradeep Reddy, N. Ramesh Babu

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In this paper quickly illustrate the correlation investigation of Auto-Regressive Integrated Moving and Average (ARIMA) and daptive Network Based Fuzzy Inference System (ANFIS) models done by climate estimating. The climate determining is taken from University of Waterloo. The information is taken as Relative Humidity, Ambient Air Temperature, Barometric Pressure and Wind Direction utilized within this paper. The paper is carried out by analyzing the exhibitions are seen by demonstrating of ARIMA and ANIFIS model like with Sum of average of errors. Versatile Network Based Fuzzy Inference System (ANFIS) demonstrating is carried out by Mat lab programming and Auto-Regressive Integrated Moving and Average (ARIMA) displaying is produced by utilizing XLSTAT programming. ANFIS is carried out in Fuzzy Logic Toolbox in Mat Lab programming.

Keywords: ARIMA, ANFIS, fuzzy surmising tool stash, weather forecasting, MATLAB

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Authors: Chatrabhuti Pipop, Visessri Supattra, Charinpanitkul Tawatchai

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Durian is one of the top agricultural products exported by Thailand. There is the massive market potential for the durian industry. While the global demand for Thai durians, especially the demand from China, is very high, Thailand's durian supply is far from satisfying strong demand. Poor agricultural practices result in low yields and poor quality of fruit. Most irrigation systems currently used by the farmers are fixed schedule or fixed rates that ignore actual weather conditions and crop water requirements. In addition, the technologies emerging are too difficult and complex and prices are too high for the farmers to adopt and afford. Many farmers leave the durian trees to grow naturally. With improper irrigation and nutrient management system, durians are vulnerable to a variety of issues, including stunted growth, not flowering, diseases, and death. Technical development or research for durian is much needed to support the wellbeing of the farmers and the economic development of the country. However, there are a limited number of studies or development projects for durian because durian is a perennial crop requiring a long time to obtain the results to report. This study, therefore, aims to address the problem of durian production by developing an autonomous and precision irrigation system. The system is designed and equipped with an industrial programmable controller, a weather station, and a digital flow meter. Daily water requirements are computed based on weather data such as rainfall and evapotranspiration for daily irrigation with variable flow rates. A prediction model is also designed as a part of the system to enhance the irrigation schedule. Before the system was installed in the field, a simulation model was built and tested in a laboratory setting to ensure its accuracy. Water consumption was measured daily before and after the experiment for further analysis. With this system, the crop water requirement is precisely estimated and optimized based on the data from the weather station. Durian will be irrigated at the right amount and at the right time, offering the opportunity for higher yield and higher income to the farmers.

Keywords: Durian, precision irrigation, precision agriculture, smart farm

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Authors: Patience Muchini, Electdom Matandiroya, Emmanuel Mashonjowa

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A ground-end manifestation of space weather phenomena is known as geomagnetically induced currents (GICs). GICs flow along the electric power transmission cables connecting the transformers and between the grounding points of power transformers during significant geomagnetic storms. Geomagnetically induced currents have been studied in other regions and have been noted to affect the power grid network. In Zimbabwe, grid failures have been experienced, but it is yet to be proven if these failures have been due to GICs. The purpose of this paper is to characterize geomagnetically induced currents with a power grid network. This paper analyses data collected, which is geomagnetic data, which includes the Kp index, DST index, and the G-Scale from geomagnetic storms and also analyses power grid data, which includes reactive power, relay tripping, and alarms from high voltage substations and then correlates the data. This research analysis was first theoretically analyzed by studying geomagnetic parameters and then experimented upon. To correlate, MATLAB was used as the basic software to analyze the data. Latitudes of the substations were also brought into scrutiny to note if they were an impact due to the location as low latitudes areas like most parts of Zimbabwe, there are less severe geomagnetic variations. Based on theoretical and graphical analysis, it has been proven that there is a slight relationship between power system failures and GICs. Further analyses can be done by implementing measuring instruments to measure any currents in the grounding of high-voltage transformers when geomagnetic storms occur. Mitigation measures can then be developed to minimize the susceptibility of the power network to GICs.

Keywords: adverse space weather, DST index, geomagnetically induced currents, KP index, reactive power

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Authors: Mohammad Reza Farzami Pour

Abstract:

Determination of genetic variation is useful for plant breeding and hence production of more efficient plant species under different conditions, like drought stress. In this study, a sample of 28 recombinant inbred lines (RILs) of wheat developed from the cross of Norstar and Zagross varieties, together with their parents, were evaluated for two years (2010-2012) under normal and water stress conditions using split plot design with three replications. Main plots included two irrigation treatments of 70 and 140 mm evaporation from Class A pan and sub-plots consisted of 30 genotypes. The effect of genotypes and interaction of genotypes with years and water regimes were significant for all characters. Significant genotypic effect implies the existence of genetic variation among the lines under study. Heritability estimates were high for 1000 grain weight (0.87). Biomass and grain yield showed the lowest heritability values (0.42 and 0.50, respectively). Highest genotypic and phenotypic coefficients of variation (GCV and PCV) belonged to harvest index. Moderate genetic advance for most of the traits suggested the feasibility of selection among the RILs under investigation. Some RILs were higher yielding than either parent at both environments.

Keywords: wheat, genetic gain, heritability, recombinant inbred lines

Procedia PDF Downloads 291

Authors: Nihit Madireddi, P. A. Mahanwar

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We have aimed to produce a self-cleaning transparent polymer coating with polyurethane (PU) matrix as the latter is highly solvent, chemical and weather resistant having good mechanical properties. Nano-silica modified by 1H, 1H, 2H, 2H-perflurooctyltriethoxysilane was incorporated into the PU matrix for attaining self-cleaning ability through hydrophobicity. The modification was confirmed by particle size analysis and scanning electron microscopy (SEM). Thermo-gravimetric (TGA) studies were carried to ascertain the grafting of silane onto the silica. Several coating formulations were prepared by varying the silica loading content and compared to a commercial equivalent. The effect of dispersion and the morphology of the coated films were assessed by SEM analysis. All coating standardized tests like solvent resistance, adhesion, flexibility, acid, alkali, gloss etc. have been performed as per ASTM standards. Water contact angle studies were conducted to analyze the hydrophobic character of the coating. In addition, the coatings were also subjected to salt spray and accelerated weather testing to analyze the durability of the coating.

Keywords: FAS, nano-silica, PU clear coat, self-cleaning

Procedia PDF Downloads 285

Authors: Aminu Yakubu Umar

Abstract:

X-ray is the major contributor to the effective dose of both the patient and the personnel. Because of the radiological risks involved, it is usually recommended that dose to patient from X-ray be kept as low as reasonably achievable (ALARA) with adequate image quality. The implementation of quality assurance in diagnostic radiology can help greatly in achieving that, as it is a technique designed to reduce X-ray doses to patients undergoing radiological examination. In this study, quality control was carried out in six hospitals, which involved KVp test, evaluation of total filtration, test for constancy of radiation output, and check for mA linearity. Equipment used include KVp meter, Rad-check meter, aluminum sheets (0.1–1.0 mm) etc. The results of this study indicate that, the age of the X-ray machines in the hospitals ranges from 3-13 years, GHI and GH2 being the oldest and FMC being the newest. In the evaluation of total filtration, the HVL of the X-ray machines in the hospitals varied, ranging from 2.3-5.2 mm. The HVL was found to be highest in AHC (5.2 mm), while it was lowest in GH3 (2.3 mm). All HVL measurements were done at 80 KVp. The variation in voltage accuracy in the hospitals ranges from 0.3%-127.5%. It was only in GH1 that the % variation was below the allowed limit. The test for constancy of radiation output showed that, the coefficient of variation ranges from 0.005–0.550. In GH3, FMC and AHC, the coefficient of linearity were less than the allowed limit, while in GH1, GH2 and GH4 the coefficient of linearity had exceeded the allowed limit. As regard to mA linearity, FMC and AHC had their coefficients of linearity as 0.12 and 0.10 respectively, which were within the accepted limit, while GH1, GH3 and GH4 had their coefficients as 0.16, 0.69 and 0.98 respectively, which exceeded the allowed limit.

Keywords: radiation, X-ray output, quality control, half-value layer, mA linearity, KVp variation

Procedia PDF Downloads 590

Authors: Arefeh Lotfi, Mahdi Babaei, Ayda Mashhadizadeh, Samira Nikpour, Morteza Bagheri

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The main objective of this study is to investigate the key factors in accidents’ severity at rail-road level crossings. The data required for this study is obtained from both accident and inventory database of Iran Railways during 2009-2015. The Ordered Probit model is developed using SPSS software to identify the significant factors in the accident severity at rail-road level crossings. The results show that 'train speed', 'vehicle type' and 'weather' are the most important factors affecting the severity of the accident. The results of these studies assist to allocate resources in the right place. This paper suggests mandating the regulations to reduce train speed at rail-road level crossings in bad weather conditions to improve the safety of rail-road level crossings.

Keywords: rail-road level crossing, ordered probit model, accidents’ severity, significant factors

Procedia PDF Downloads 121

Authors: Amira Balaska, Ali Tahri, Amine Boudghene Stambouli, Takashi Oozeki

Abstract:

This paper is dealing with the evaluation of photovoltaic modules as part of the Sahara Solar Breeder project (SSB), five different photovoltaic module technologies which are: m-si, CIS, HIT, Back Contact, a-si_μc -si and a weather station recently installed at the University of Saida (Tahar Moulay) in Saida city located at the gate of the great southern Algeria’s Sahara. The objective of the present work is the study of solar photovoltaic capacity and performance parameters of each PV module technology. The goal of the study is to compare the five different PV technologies in order to find which technologies are suitable for the climate conditions of Algeria’s desert. Measurements of various parameters as irradiance, temperature, humidity and so on by the weather station and I-V curves were performed outdoors at the location without shadow. Finally performance parameters as performance ratio, energy yield and temperature losses are given and analyzed.

Keywords: photovoltaic modules, performance ratio, energy yield, sahara solar breeder, outdoor conditions

Procedia PDF Downloads 637

Authors: Hung-Shuo Wu, Huan-Chieh Chiu, Xiang-Yao Zheng, Yu-Cheng Yang, Chien-Hao Wang, Jen-Cheng Wang, Chwan-Lu Tseng, Joe-Air Jiang

Abstract:

Dynamic Thermal Rating (DTR) provides crucial information by estimating the ampacity of transmission lines to improve power dispatching efficiency. To perform the DTR, it is necessary to install on-line thermal sensors to monitor conductor temperature and weather variables. A simple and intuitive strategy is to allocate a thermal sensor to every span of transmission lines, but the cost of sensors might be too high to bear. To deal with the cost issue, a thermal sensor placement problem must be solved. This research proposes and implements a hybrid algorithm which combines proper orthogonal decomposition (POD) with particle swarm optimization (PSO) methods. The proposed hybrid algorithm solves a multi-objective optimization problem that concludes the minimum number of sensors and the minimum error on conductor temperature, and the optimal sensor placement is determined simultaneously. The data of 345 kV transmission lines and the hourly weather data from the Taiwan Power Company and Central Weather Bureau (CWB), respectively, are used by the proposed method. The simulated results indicate that the number of sensors could be reduced using the optimal placement method proposed by the study and an acceptable error on conductor temperature could be achieved. This study provides power companies with a reliable reference for efficiently monitoring and managing their power grids.

Keywords: dynamic thermal rating, proper orthogonal decomposition, particle swarm optimization, sensor placement, smart grid

Procedia PDF Downloads 405