Reliable Integrated Satellite Terrestrial Communications using MIMO for Mitigation of Microwave Absorption by Earths Oxygen

Microwaves are used to communicate with satellite and terrestrial communication networks. But as microwaves pass through the Earth’s atmosphere, the oxygen gas absorbs microwave. In this 5G era, when the whole world is moving towards high data-rates and reliable communications, this absorption affects the data transmission in Integrated Satellite/Terrestrial Communication (ISTC) systems, which leads to degradation of the system performance. The multiple-input-multiple-output (MIMO) technology has become a boon for modern wireless communication systems to achieve the necessities of higher data-rates and communication reliability. The paper analyses the MIMO effect on block error rate (BLER), error vector magnitude (EVM) and throughput performance of the data transmission with different MIMO configurations. The paper establishes that better data-rates as well as reliable data communication is achieved with higher order MIMO configurations. MIMO 8×1 provides 5, 20 and 42.5 times improved performance to BLER; 5.26%, 25% and 81.82% in throughput; and 10.34%, 23.07% and 28% in EVM calculations as comparable to MIMO 4×1, MIMO 2×1 and SISO 1×1, respectively at 15 dB signal-to-noise ratio (SNR). The authors also give a new concept of multi-cellular layers based mobile communication network, useful for future smart cities

Closed-form Distribution and Analysis of a Combined Nakagami-lognormal Shadowing and Unshadowing Fading Channel , Journal of Telecommunications and Information Technology, 2016, nr 4

The realistic wireless channels face combined (time shared) Nakagami-lognormal shadowing and unshadowing fading because of time varying nature of radio channel and mobile user. These channels can be modeled as time-shared sum of multipath-shadowing and unshadowing Rician distributions. These fading create severe problems in long distance wireless systems where multipath fading is superimposed on shadowing fading (called multipath-shadowing fading). The multipath effect can be modeled using Rayleigh, Rician, Nakagami-m or Weibull distribution and shadowing effect is modeled using lognormal distribution. In this paper, authors present a new closed-form probability distribution function of a Nakagami-lognormal fading channel. Using this result, the closed-form expression of combined Nakagamilognormal shadowing and unshadowing fading is presented. The obtained closed-form result facilitates to derive the important performance metrics of a communication system such as amount of fading, outage probability, and average channel capacity in closed-form expressions

Investigations on RF Behavior of a V-Band Second Harmonic Gyrotron for 100/200 kW Operation

This article presents the investigations on RF-behavioral aspects for the possible operation of a V -band, continuous wave (CW) second harmonic gyrotron for plasma diagnostic application. Keeping in view the design goals and constraints, initial design studies for the mode selection and the computation of starting currents are carried out. From these studies, two possible modes, namely, TE 7,3 and TE 8,3 are considered for the second harmonic operation. Later, the cold cavity design and self-consistent calculations are carried out for the selected operating modes. All the computations are performed using the latest version of our in-house code Gyrotron Design Studio Second Harmonic Version 2020 (GDS2H-2020) with Glidcop as the cavity material. The RF behavior studies confirm the feasible operation of such a second harmonic gyrotron with power levels in excess of 115.52/217.64 kW with the chosen modes of operation

“Surveying Oral Health: A Comprehensive Analysis Of Disparity In Methods Of Tooth Brushing”

Aim: This study aimed to explore variations in tooth brushing techniques, frequency, additional mouth rinses, and the usage of toothpaste, daatun, electric toothbrushes, and charcoal among individuals aged 15 and above. Objectives: The primary objective of this research was to identify and analyse patterns of oral hygiene practices across different age groups, investigating potential disparities in methods employed for maintaining oral health. Materials & Methods:A comprehensive questionnaire consisting of 10 questions was designed and administered through Google Forms to collect data on oral hygiene practices. Participants aged 15 and above were randomly sampled, ensuring a diverse representation. The questionnaire focused on aspects such as tooth brushing techniques, frequency, usage of additional oral care products, and preferred oral hygiene tools. Data collection was conducted through online responses. Results: The survey results, obtained through Google Forms, revealed intriguing disparities in oral hygiene practices across age groups. Variations were observed in the choice of tooth brushing techniques, frequency of brushing, and the use of additional products such as mouth rinses, daatun, electric toothbrushes, and charcoal-based oral care items. Conclusion: In conclusion, this study, utilizing Google Forms for data collection, highlighted diverse oral hygiene practices among individuals aged 15 and above. Recognizing these variations is crucial for tailoring oral health education programs and interventions to address the specific needs of different age groups. The findings underscore the importance of personalized oral care approaches to promote optimal oral health across the populatio

Unveiling the combined effect of nano fertilizers and conventional fertilizers on crop productivity, profitability, and soil well-being

It is widely accepted that deficiency of macro (nitrogen) and micronutrients (zinc, copper etc.) affects the plant growth and development which cause a significant threat to crop production and food security. The Indian Farmers Fertilizer Cooperative (IFFCO) developed nano-urea (nano-N), nano-zinc (nano-Zn), and nano-copper (nano-Cu) liquid fertilizer formulations to enhance the crop yields, simultaneously addressing the nutrient deficiency, without causing toxicity. Therefore, this study was formulated to evaluate the effectiveness of nano-N (nano-urea), nano-Zn, and nano-Cu at varying N levels [0, 50, 75, and 100% of the recommended rates of nitrogen (RRN)] on maize-wheat and pearl millet-mustard systems during 2019–20 and 2020–21. The results exhibited that the application of nano-N + nano-Zn with 100% RRN exhibited significantly higher grain yields in maize (66.2–68.8%), wheat (62.6–61.9%), pearl millet (57.1–65.4%), and mustard (47.2–69.0%), respectively, over absolute control plots and combinations of three nano-fertilizers like nano-N + nano-Zn + nano-Cu applied plots. This was mainly attributed to the higher N and Zn uptake by the crops. However, 75% RRN with nano-N + nano-Zn also produced comparable yields. Thus, applying nano-N and nano-Zn via foliar applications, in conjunction with conventional urea, has the potential to reduce the required nitrogen fertilizer amount by up to 25%, while simultaneously maintaining equivalent yield levels. Similarly, 100% RRN and 75% RRN + nano-N + nano-Zn registered comparable profitability, soil mineral N, dehydrogenase activity (DHA), and soil microbial biomass carbon (SMBC), during both the study years. However, further research and field trials on nano fertilizers alone or in combination with conventional fertilizers are essential to fully unlock its benefits and ascertain its long-term effects which may offer a pathway to more efficient and eco-friendly crop nourishment

Nutritionally Enhanced Staple Food Crops

Crop biofortification is a sustainable and cost-effective strategy to address malnutrition in developing countries. This review synthesizes the progress toward developing seed micronutrient-dense cereals and legumes cultivars by exploiting natural genetic variation using conventional breeding and/or transgenic technology, and discusses the associated issues to strengthen crop biofortification research and development. Some major QTL for seed iron and zinc, seed phosphorus, and seed phytate in common bean, rice,J;md wheat have been mapped. An iron reductase QTL associated with seed-iron ~QTL is found in common bean where the genes coding for candidate enzymes involved in phytic acid synthesis have also been mapped. Candidate genes for Ipa co segregate with mutant phenotypes identified in rice and soybean. The Gpe-B1 locus in wild emmer wheat accelerates senescence and increases nutrient remobilization from leaves to developing seeds, and another gene named TtNAM-B1 affecting these traits has been cloned. Seed iron-dense common bean and rice in Latin America; seed iron-dense common bean in eastern and southern Africa;....

Artificial neural networks for modeling and digital predistortion for software defined transmitters

Bibliography: p. 139-151Some pages are in colour.Includes copy of copyright permissions. Original copies with original Partial Copyright Licence.The overall objective of this thesis is to develop and analyze efficient and robust artificial neural network methodologies and distiibuted structures for complete transmitter modeling and its practical use as digital compensation solution for nonlinearity and hardware impainnents in wireless transmitters for software defined radio Applications. A suitable feedforward topology namely real valued focused time delay neural network is proposed and various nonlinear optimization algorithms are implemented to achieve best perfonnance in the presence of different power amplifiers and signals. While conventional digital predistortion (DPD) techniques focus mostly on power amplifiers and are dependent on signal statistics, the proposed linearization is more robust to signal statistics and generic in the sense that it adapts to any change in the input data even in the presence of modulator gain/ phase imbalances and DC offsets. Although highly robust, back propagation based feedforward neural network solutions have shortcomings such as high number of parameters to be stored leading to higher digital processing cost. Therefore, as an alternative cost cutting solution, this thesis ventures to modify conventional memory polynomial by applying layered structure similar to neural networks. With experimental results of different PAs, it is established that proposed three-layered-biased-memory-polynomial model enjoys better numerical stability and lower dispersion of coefficients which eventually helps in decreasing processing load on DSP and therefore can replace conventional memory polynomials providing similar performance. Above stated DPD techniques works in batch mode and when PA characteristics cannot be assumed constant over long time and constant adaptation of coefficients is needed, they may still lead to higher processing time therefore thesis further analyzes spatially distributed or lattice neural networks for adaptive digital compensation. It is reported that with its spatially distributed structure total processing cost is even lower than previously reported conventional adaptive nonlinear filters with reasonable performance especially in case of highly nonlinear PAs

Comparison of climate change impact on rainfed maize yield in Kansas using statistical and process-based models

Master of ScienceDepartment of Biological & Agricultural EngineeringVaishali ShardaChanging climate and the projected increase in variability and frequency of extreme events make an accurate prediction of crop yield critically important for addressing emerging challenges in food security. Precise and timely prediction of crop yield can provide valuable information to agronomists, producers, and decision-makers. Even without considering climate change, several factors including environment, management, and genetics and their complex interactions make the prediction of crop yield challenging. In this study a statistical-based Multiple Linear Regression (MLR) model was developed to predict rainfed maize yield in Kansas and compared with yield predictions of the DSSAT process-based model to assess the impact of synthetic climate change scenarios of 1 and 2 °C temperature rise. Historic weather, soils, and crop management data were collected and converted to model-compatible formats to simulate and compare maize yield using both models. It was found that DSSAT had a large Root Mean Square Error (RMSE) compared to the MLR model whereas the correlation coefficients (r) were 0.93 and 0.70 for MLR and DSSAT, respectively. These results indicated that predicted yields from the MLR model had a stronger association with the observed yields than the simulated yields from DSSAT. Analysis of climate change impact showed that the reduction in rainfed maize yield predicted by DSSAT was 8.7% and 18.3% for the synthetic scenarios of 1 and 2 °C temperature rise respectively. Reduction in rainfed maize yield predicted by the MLR model was nearly 6% in both scenarios. Due to the extreme heat effect, predicted impacts under uniform climate change scenarios were considerably more severe for the process-based model than for the statistical-based model