Development of an empirical dust storm attenuation prediction model for microwave links in arid area – a proposed framework

Wireless communication service providers are currently facing challenges due to the congested frequencies spectrum which has imposed the use of higher and higher frequencies. However, higher frequency bands are more sensitive to weather condition and the microwave signal attenuation due to atmospheric particles increases rapidly at higher frequency bands. Consequently dust storms and other phenomena cause signal attenuation which can limit the performance of wireless communication systems for the frequencies above 10GHz in arid area. The paper aim is to show that real dust storm is a complex phenomena which is difficult to be described by the theoretical physical or mathematical models. An empirical dust storm prediction model based on the long term statistical observations of dust storm properties and its corresponding microwave signal levels will be a step forward to provide microwave link designers with a precise tool to rely on. This paper has proposed a research framework to collect necessary data from Khartoum, Sudan and develop an empirical attenuation prediction model

Development of duststorm attenuation model for microwave links

Duststorms are significant meteorological phenomenon occur for a significant percentage of time in arid and semi arid areas especially at African Sahara and Middle East. Measurements at existing microwave links show that the duststorms can potentially result in serious attenuation in signal level especially at Ku band and higher frequencies with direct impact on telecommunications system performance. Very limited research has been done to predict the attenuation even the scarcity of measured data forces the researcher to work for the duststorm prediction modeling

Air born dust particles effects on microwave propagation in arid-area

Dust storms can degrade visibility and increase atmospheric attenuation. Therefore, microwave (MW) propagation is severely affected by dust storms in many parts of the world. Air-born dust particles may affect electromagnetic waves during a dust storm. In this paper air- born dust particles effects are studied based on measured visibility. Recent analytical and numerical models results are compared to the measured at 14 GHz. Consequently, measured attenuation is significantly greater than the predicted using recent analytical and numerical models. Dust storms can degrade visibility and increase atmospheric attenuation. Therefore, microwave (MW) propagation is severely affected by dust storms in many parts of the world. Air-born dust particles may affect electromagnetic waves during a dust storm. In this paper air- born dust particles effects are studied based on measured visibility. Recent analytical and numerical models results are compared to the measured at 14 GHz. Consequently, measured attenuation is significantly greater than the predicted using recent analytical and numerical models

Effects of humidity on sand and dust storm attenuation predictions based on 14 GHz measurement

Several models were proposed to predict the attenuation of microwave signals due to sand and dust storms. Those models were developed based on theoretical assumptions like Rayleigh approximation, Mie equations or numerical methods. This paper presents a comparison between attenuation predicted by three different theoretical models with measured attenuation at 14 GHz. Dielectric constant of dust particles is one of the important parameter in prediction models. This constant is estimated from measured dust samples and is utilized for predictions. All models are found largely underestimating the measurement. Humidity is also monitored and has been observed higher during dust storm. Hence dielectric constants are re-estimated with relative humidity conditions using available conversion model. The prediction has a great impact of humidity and predicted attenuations are found much higher in humid than dry dust condition. However, all models underestimate the measurement even considering 100% of relative humidity. Hence it is recommended to investigate the models by considering humidity and other environmental factors that change during dust storm

2D omni‐directional wireless power transfer modeling for unmanned aerial vehicles with noncollaborative charging system control

Wireless power transfer (WPT) has been extensively studied from various aspects such as far field and near field, operating frequency, coil design, matched capacitance values, misaligned locations of transmitting and receiving coils, distance variance between them, target loads in the specific locations, environment, and operating conditions. This is due to the usefulness of WPT technology in many applications, including the revolutionary method of auto-recharging of unmanned aerial vehicles (UAVs). This paper presents analytical modeling of a WPT-link with two orthogonal transmitting coils arranged to produce an omnidirectional magnetic field suitable for charging a moving rotating load, maximizing energy transfer without any feedback from the receiving end. To achieve a suitable 2D WPT simulation system, as well as an accurate control design, the mutual coupling values in terms of receiver angular rotation are simulated using Ansys software. Power transfer is maximized by using extremum seeking control (ESC), making use of the input power as an objective function with specific parameter values that represent the WPT model to obtain the results. The results shown are those of the input power transmitted by the transmitting-end coils to a load of an orbiting mobile UAV. Based on the simulation results, the controller can achieve maximum power transfer in 100 µs of duration when the speed of the UAV is close to 314 rad/s

Dust storm attenuation modeling based on measurements in Sudan

Microwave (MW) and millimeter-wave (MMW) propagation are severely affected by dust storms and sand storms in arid and semi-arid areas. Electromagnetic waves may suffer from attenuation due to suspended particles during a dust storm. This paper proposes an empirical model to predict the attenuation due to dust storms based on a one-year measurement of visibility, humidity and their effects on microwave links in Sudan. Signal strength variations on two operational microwave links at 14 GHz and 22 GHz as well as visibility were monitored simultaneously. The model is developed empirically using measured attenuation and measured storm characteristics (e.g., visibility, dielectric constant, frequency and moisture content). The predicted attenuation from the proposed empirical model is compared with the attenuation at frequencies ranging from 7.5 GHz to 40 GHz measured at different locations, and good agreement is found. Additionally, this method is characterized by simplicity and capability to predict reliable dust storm attenuation for a wide range of frequencies and moisture levels

Seasonal variations of hydrographic parameters off the Sudanese coast of the Red Sea, 2009–2015

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Regional Studies in Marine Science 18 (2018): 1-10, doi:10.1016/j.rsma.2017.12.004.The variations of temperature and salinity in the Sudanese coastal zone of the Red Sea are studied for the first time using measurements acquired from survey cruises during 2009–2013 and from a mooring during 2014–2015. The measurements show that temperature and salinity variability above the permanent pycnocline is dominated by seasonal signals, similar in character to seasonal temperature and salinity oscillations observed further north on the eastern side of the Red Sea. Using estimates of heat flux, circulation and horizontal temperature/salinity gradients derived from a number of sources, we determined that the observed seasonal signals of temperature and salinity are not the product of local heat and mass flux alone, but are also due to alongshore advection of waters with spatially varying temperature and salinity. As the temperature and salinity gradients, characterized by warmer and less saline water to the south, exhibit little seasonal variation, the seasonal salinity and temperature variations are closely linked to an observed seasonal oscillation in the along-shore flow, which also has a mean northward component. We find that the inclusion of the advection terms in the heat and mass balance has two principal effects on the computed temperature and salinity series. One is that the steady influx of warmer and less saline water from the south counteracts the long-term trend of declining temperatures and rising salinities computed with only the local surface flux terms, and produces a long-term steady state in temperature and salinity. The second effect is produced by the seasonal alongshore velocity oscillation and most profoundly affects the computed salinity, which shows no seasonal signal without the inclusion of the advective term. In both the observations and computed results, the seasonal salinity signal lags that of temperature by roughly 3 months.The SPS surveys were funded by the Norwegian Norad’s Program for Master Studies and organized by IMR–RSU in Port Sudan. The central Red Sea mooring data were acquired as part of a WHOI–KAUST collaboration funded by Award Nos. USA00001, USA00002, and KSA00011 to the WHOI by the KAUST in the Kingdom of Saudi Arabia. The work of I. Skjelvan and A.M. Omar was partly supported by the Research Council of Norway through the MIMT Center for Research-based Innovation. This work is part of a Ph.D. project at GFI–UiB funded by the Norwegian Quota program

Effect of dust storm intensity variations on total path attenuation prediction

This paper proposes a novel dust-storm total path attenuation prediction model. This model is formulated as a function of specific attenuation (dB/km) and the effective distance, which considers the non-uniform dust storm intensity variations throughout the link. The effective distance is obtained as a combination of the total link distance and the reduction factor. The reduction factor is developed based on the modeled 2-D structure of the observed dust storm characteristics. A measurement campaign of atmospheric characteristics, their properties, and effects on several microwave links operated in Khartoum-Sudan was conducted. In an earlier report, an empirical dust storm attenuation prediction model was proposed based on short-distance links by assuming uniform dust storm intensity variations. However, it was observed that the dust intensity varies with the distance, which affects total attenuation, and this issue is not addressed yet. One year measurement on the 6.2 km and 7.6 km long microwave links operating at 21.2 GHz and 14.5 GHz are used to validate the proposed dust storm total path attenuation model

Thermal-based early breast cancer detection using inception V3, inception V4 and modified inception MV4

Breast cancer is one of the most significant causes of death for women around the world. Breast thermography supported by deep convolutional neural networks is expected to contribute significantly to early detection and facilitate treatment at an early stage. The goal of this study is to investigate the behavior of different recent deep learning methods for identifying breast disorders. To evaluate our proposal, we built classifiers based on deep convolutional neural networks modelling inception V3, inception V4, and a modified version of the latter called inception MV4. MV4 was introduced to maintain the computational cost across all layers by making the resultant number of features and the number of pixel positions equal. DMR database was used for these deep learning models in classifying thermal images of healthy and sick patients. A set of epochs 3–30 were used in conjunction with learning rates 1 9 10–3, 1 9 10–4 and 1 9 10–5, Minibatch 10 and different optimization methods. The training results showed that inception V4 and MV4 with color images, a learning rate of 1 9 10–4, and SGDM optimization method, reached very high accuracy, verified through several experimental repetitions. With grayscale images, inception V3 outperforms V4 and MV4 by a considerable accuracy margin, for any optimization methods. In fact, the inception V3 (grayscale) performance is almost comparable to inception V4 and MV4 (color) performance but only after 20–30 epochs. inception MV4 achieved 7% faster classification response time compared to V4. The use of MV4 model is found to contribute to saving energy consumed and fluidity in arithmetic operations for the graphic processor. The results also indicate that increasing the number of layers may not necessarily be useful in improving the performance

Influence of tissue thermophysical characteristics and situ-cooling on the detection of breast cancer

This article presents a numerical simulation model using COMSOL software to study breast thermophysical properties. It analyzes tumor heat at different locations within the breast, records breast surface temperatures, investigates the effects of factors such as blood perfusion, size, depth, and thermal conductivity on breast size, and applies Pennes’ bioheat formula to illustrate thermal distribution on the breast skin surface. An analysis was conducted to examine how changes in tumor location depth, size, metabolism, blood flow, and heat conductivity affect breast skin surface temperature. The simulation model results showed that the highest variations in skin temperatures for breasts with tumors and without tumors can range from 2.58 °C to 0.274 °C. Further, large breast size with a large surface area consistently reduces the temperature variations on the skin and might have difficulty in yielding observable temperature contrast. For small breast sizes, however, heat from tumor sizes below 0.5 cm might be quite difficult to detect, while tumors located deep within the breast layers could not produce observable temperature variations. Motivated by the above interesting results, an emulation experiment was conducted to enhance the observable heat and temperature background contrast, using situ-cooling gel applied to silicon breasts, while the tumor source was emulated using LEDs. The experiment was used to evaluate the effectiveness of adding situ-cooling to the breast surface area, and to study the modulated effect of tumor size and depth. Experimental results showed that situ-cooling enhances thermal contrast in breast thermal images. For example, for a tumor location at a depth of 10 cm, a difference of 6 °C can still be achieved with situ-cooling gel applied, a feat that was not possible in the simulation model. Furthermore, changes in tumor size and location depth significantly impacted surface temperature distribution