Always Best Connected Mobile Sensor Network to Support High Accuracy Internet of Farming

The Internet of Farming be dependent on data gathered from sensor of Wireless Sensor Network (WSN). The WSN requires a reliable connectivity to provide accurate prediction data of the farming system. This paper introduces a mechanism that gives always best connectivity (ABC). The mechanism considers all stakeholders (mobile node, corresponding node and users) attributes. An empirical simulation shows that the proposed mechanism provides an acceptable ABC to the mobile sensors in the WSN

A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia

An energy producer must determine optimal energy investment strategies in order to maximize the value of its energy portfolio. Determining optimal investment strategies is challenging. One of the main challenges is the large uncertainty in many of the parameters involved in the optimization process. Existing large-scale energy models are mostly deterministic and thus have limited capability for assessing uncertainty. Modelers usually use scenario analysis to address model input uncertainty. In this research, I developed a probabilistic model for optimizing energy investments and policies from an energy producer’s perspective. The model uses a top-down approach to probabilistically forecast primary energy demand. Distributions rather than static values are used to model uncertainty in the input variables. The model can be applied to a country-level energy system. It maximizes the portfolio expected net present value (ENPV) while ensuring energy sustainability. The model was built in MSExcel® using the @RISK Palisade add-in, which is capable of modeling uncertain parameters and performing stochastic simulation optimization. The model was applied to Saudi Arabia to determine its optimum energy investment strategy, determine the value of investing in alternative energy sources, and compare deterministic and probabilistic modeling approaches. The model, given its assumptions and limitations, suggests that Saudi Arabia should keep its oil production capacity at 12.5 million barrels per day, especially in the short term. It also suggests that most of the future power-generation (electricity) demand in Saudi Arabia should be met using alternative-energy sources (nuclear, solar, and wind). Otherwise, large gas production is required to meet such demand. In addition, comparing probabilistic to deterministic model results shows that deterministic models may overestimate total portfolio ENPV and underestimate future investments needed to meet projected power demand. A primary contribution of this work is rigorously addressing uncertainty quantification in energy modeling. Building probabilistic energy models is one of the challenges facing the industry today. The model is also the first, to the best of my knowledge, that attempts to optimize Saudi Arabia’s energy portfolio using a probabilistic approach and addressing the value of investing in alternative energy sources

Transferencia electrónica homogénea de clorofila y su derivado clorofilina en un electrodo de oro

Introduction: Chlorophyll is a light harvesting pigment, which absorbs light in the visible spectrum of sunlight and promotes electron transfer, Chlorophyllin (CHL) is One of the most important derivative molecules of chlorophyll. Nowadays, chlorophyll pigment and its derivatives are utilised in organic photosynthetic solar cells for their desirable photovoltaic properties. Cyclic voltammetry (CV) is an essential technique. It is extensively used to study electroactive species to interpret the intermediates of reactions, supply information about the thermodynamics of oxidation-reduction reactions and elucidate the kinetics of electron transfer reactions. Materials and Methods: Prior to the electrochemical study, the working gold (Au) electrode surface was prepared by immersing it in the various concentrations of chlorophyllin for a period time. The electrolyte was degassed by using N2 for approximately 30 minutes inside a Faraday cage before any electrochemical experiment was performed. A three electrode system was used with, Ag/AgCl as a reference electrode, graphiteas a counter and the working electrode (Au). Results and Discussion: As a route to develop new chemical systems for artificial photosynthesis, this work reports the effectiveness of different parameters in transferring electrons between chlorophyllin (CHL) pigment and the working electrode surface (gold). These parameters such as the adsorption time, the electrolyte nature and concentration and chlorophyllin concentration are investigated. The use of chlorophyllin as a redox mediator is examined, with a gold electrode being employed. The importance of gold electrode surface preparation in determining the mechanism of redox is described, and the environment of adsorption process of the different concentrations of chlorophyllin on the surface of the gold electrode has been elucidated in this study. Conclusiones: The electrochemical method showed that the cyclic voltammetry responses of studied adsorption chlorophyllin pigment on the gold electrode were more efficient. In addition, the redox reaction was successful electrochemically in aqueous solution thanthe organic solution. It was suggested that electrons reduce to the chlorophyllin pigment by adding active species in the bulk solution homogeneous transfer. Finally, detections of chl on spinach leaves using various methods are reported

Awareness of using Radiology in Diagnosing COVID-19 among Radiological Students

The coronavirus (COVID-2019) has spread very rapidly over many countries around the world, producing an outbreak of acute infectious pneumonia. Medical imaging devices play a vital role in early diagnosis, evaluating severity and disease prognosis of confirmed patients with COVID-19. The aim of the study is to evaluate the awareness level of radiology students about COVID-19 and their understanding of the role of radiology devices in diagnosing COVID-19. An online cross-sectional questionnaire was conducted. Seventy-one students participated in this study. This study showed that students were properly aware of the basic knowledge of the COVID-19, 87 % of the students believed that radiology had an important role in diagnosing COVID-19. In addition, 50% of the students believed that CT was the most important modality in diagnosing COVID-19 and 32.35% believed that x-ray was the most important one. Lack of knowledge was found regarding the biomarkers that appear in radiological images in patients with COVID-19. 66.18 % of the students acquired the knowledge from their study in the radiology field and from social media (Twitter). The level of awareness among radiology students is high. There were two main reasons for this high level of awareness: gained education and social media, especially Twitter. The outbreak of the COVID-19 was not only about its health effects but also how the population persevered this pandemic. However, this level of awareness tended to be lower when discussing detailed findings of radiological images such as detailed biomarkers

Performance Analysis of Sensing-based Semi-Persistent Scheduling (SB-SPS) MAC Protocol for C-V2X

Sensing-based Semi-Persistent Scheduling (SB-SPS) MAC protocol is proposed as part of the latest cellular vehicle to everything (C-V2X) standard for medium access between vehicles. As C-V2X uses LTE based frame structure, mode 4 of the C-V2X standard uses SB-SPS to allocate resource blocks effectively. C-V2X shows great potential for the future as it brings many improvements such as enhanced range, reliability, and the ability to support and evolve with emerging technologies such as 5G. In this article, the SB-SPS protocol’s performance was analyzed in different scenarios using OMNET++, SUMO, and Veins simulator. Different vehicle speeds and densities were used to observe the effect on packet loss and throughput. It was found that as packet loss decreased, throughput increased when the mobility of vehicles decreased. The effects of changing some important parameters of SB-SPS were also observed. The results showed that while parameters such as increasing the number of subchannels increased the packet delivery ratio (PDR), the change in the probability of resource reselection parameter did not affect the PDR

A Triple-Porosity Model for Fractured Horizontal Wells

Fractured reservoirs have been traditionally idealized using dual-porosity models. In these models, all matrix and fractures systems have identical properties. However, it is not uncommon for naturally fractured reservoirs to have orthogonal fractures with different properties. In addition, for hydraulically fractured reservoirs that have preexisting natural fractures such as shale gas reservoirs, it is almost certain that these types of fractures are present. Therefore, a triple-porosity (dual-fracture) model is developed in this work for characterizing fractured reservoirs with different fractures properties. The model consists of three contiguous porous media: the matrix, less permeable micro-fractures and more permeable macro-fractures. Only the macro-fractures produce to the well while they are fed by the micro-fractures only. Consequently, the matrix feeds the micro-fractures only. Therefore, the flow is sequential from one medium to the other. Four sub-models are derived based on the interporosity flow assumption between adjacent media, i.e., pseudosteady state or transient flow assumption. These are fully transient flow model (Model 1), fully pseudosteady state flow model (Model 4) and two mixed flow models (Model 2 and 3). The solutions were mainly derived for linear flow which makes this model the first triple-porosity model for linear reservoirs. In addition, the Laplace domain solutions are also new and have not been presented in the literature before in this form. Model 1 is used to analyze fractured shale gas horizontal wells. Non-linear regression using least absolute value method is used to match field data, mainly gas rate. Once a match is achieved, the well model is completely described. Consequently, original gas in place (OGIP) can be estimated and well future performance can be forecasted