Wearable sensors are a revolutionary tool in agriculture because they collect accurate data on plant environmental conditions that affect plant growth in real-time. Moreover, this technology is crucial in increasing agricultural sustainability and productivity by improving irrigation strategies and water resource management. This review examines the role of wearable sensors in measuring plant water content, leaf and air humidity, stem flow, plant and air temperature, light, and soil moisture sensors. Wearable sensors are designed to monitor various plant physiological parameters in real-time. These data, obtained through wearable sensors, provide information on plant water use and physiology, making our agricultural choices more informed and accurate. Internet of Things (IoT) technologies can improve irrigation strategies and reduce water consumption by analyzing data from wearable sensors and adapting it to automate the irrigation system. The review also highlights the importance of using Artificial Intelligence (AI) to predict plant water needs accurately. This review concludes that wearable sensors provide accurate and real-time data on the stress state of plants and their surroundings, improving water management efficiency and agricultural production sustainability. These IOT and AI-enabled technologies are a crucial milestone toward smart and sustainable agriculture, which shows the importance of innovation in responding to enhanced climate threats.
The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h
... Show MoreForecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti
... Show MoreThe wide use of pesticides in recent years leads to rapid distribution of these pollutants in the environment (air, water and soil).They were transported by means of air or water to biological ecosystems. They become more toxic through the processes of biological magnification while some of them persist for along period.The aim of this work is to show the negative effect that chemical pesticides causes, and in the same to show their side effect on the environment and health in Iraq. We could conclude that the bad use of these chemicals could cause an urgent impact now or in the future. Governmental offices dealing with these materials should take the right measures to minimize the danger and the misuse of these chemicals by seeking alternat
... Show MoreThe application of low order panel method with the Dirichlet boundary condition on complex aircraft configuration have been studied in high subsonic and transonic speeds. Low order panel method has been used to solve the case of the steady, inviscid and compressible flow on a forward swept wing – canard configuration with cylindrical fuselage and a vertical stabilizer with symmetrical cross section. The aerodynamic coefficients for the forward swept wing aircraft were calculated using measured wake shape from an experimental work on same model configuration. The study showed that the application of low order panel method can be used with acceptable results
The integration of arti cial intelligence (AI), whether through devices or software, has become a critical tool in analyzing and evaluating technical performance. AI signi cantly contributes to enhancing athletic performance by enabling accurate data analysis and supporting educators in developing effective training programs and interactive curricula. This study addresses a noticeable gap in the literature regarding the attitudes and inclinations of educators toward AI in physical education and sport sciences—a gap often attributed to limited awareness and lack of access to moderntechnologies.Theprimaryaimofthestudyistoexaminethetendenciesandperceptionsoffemaleinstructorsin physical education and sport sciences toward the use of AI
... Show MoreBackground: A noninvasive method of determining the severity of coronary artery disease (CAD) is the use of cardiac biomarkers. This study aimed to investigate the use of serum levels of high-sensitivity cardiac troponin I (hs-cTnI) and N-terminal pro–B-type natriuretic peptide (NT-proBNP) in determining CAD severity.Methods: This cross-sectional study included 125 participants categorized by coronary angiographic results into 3 groups: group I (no or < 50% stenosis), group II (1 or 2 vessels with ≥ 50% stenosis), and group III (left main stem or ≥ 3 vessels with ≥ 50% obstruction). Serum hs-cTnI and NT-proBNP levels were measured by enzyme-linked immunosorbent assay. Data were analyzed using SPSS version 25.0 and described as pe
... Show MoreThis study included isolation of some active materials from Curcuma longa such as tannins, saponins and volatile oils with percentage of 59%, 31%, and 9% respectively. Also the study included the determination of minerals in Curcuma longa such as " Na, Ca and K" using Flame photometer. The concentrations of these minerals were (14 ppm),(10 ppm) and )76 ppm) respectively. The anti-bacterial activity study was performed for the active materials isolated from Curcuma longa against two genus of pathogenic bacteria, Escherichia Coli and Staphylococcus aurous by using agar-well diffusion method. It appeared from this study that all of the extraction have inhibitory effect on bacteria was used. The inhibition zone diameter varies with
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