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From data to decision: How wearable plant sensors help improving proactive irrigation strategies and water use efficiency
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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.

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Publication Date
Sun Jan 04 2015
Journal Name
Journal Of Educational And Psychological Researches
Effectiveness of the self-questioning strategy in the achievement of the third stage Institutes of teacher preparation and decision - making in Chemistry
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This research aims to find out "the effectiveness of the self-questioning strategy in the achievement of students Phase III institutes of teacher preparation and decision-making in chemistry." The researcher follows approach quasi-experimental with a post-test, and the sample consisted of (27) from " Teachers Training Institute-AL-Byaa "in Directorate of Education Baghdad Karkh / 2 students divided into two unequal groups: experimental its number (14) students studied using reciprocal teaching strategy and control its number (13) students have studied in the usual way.The two groups were equivalent extraneous variables.

The researcher was prepare achievement test consist of 40 items was the adoption of a measure of decision-makin

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Strategic orientation and its reflection on the Learning organization: Survey study of a sample of Makers decision the Iraqi Ministry of Communications
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The current research focuses on the extent to which the strategic orientation(entrepreneurial orientation, customer orientation, technology orientation, learning orientation, and investment orientation) affects the learning organization (building common vision, systemic thinking, personal dominance, mental models, team learning)The first hypothesis to test the connection relation between research variables and The second hypothesis was to test the relationship between these variables. In order to ascertain the validity of the hypotheses, the research was based on a questionnaire questionnaire prepared according to a number of In addition to building a fifth sub-variable for the strategic orientation (investment orientation) based

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Publication Date
Fri Mar 15 2019
Journal Name
Alustath Journal For Human And Social Sciences
A Developmental-Longitudinal Study of Request External Modifiers in Authentic and Elicited Data
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Publication Date
Wed Jul 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Fast and robust approach for data security in communication channel using pascal matrix
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This paper present the fast and robust approach of English text encryption and decryption based on Pascal matrix. The technique of encryption the Arabic or English text or both and show the result when apply this method on plain text (original message) and how will form the intelligible plain text to be unintelligible plain text in order to secure information from unauthorized access and from steel information, an encryption scheme usually uses a pseudo-random enecryption key generated by an algorithm. All this done by using Pascal matrix. Encryption and decryption are done by using MATLAB as programming language and notepad ++to write the input text.This paper present the fast and robust approach of English text encryption and decryption b

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Publication Date
Wed Jan 01 2020
Journal Name
Advances In Science, Technology And Engineering Systems Journal
Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Fri Jun 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Correlation for fitting multicomponent vapor-liquid equilibria data and prediction of azeotropic behavior
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Correlation equations for expressing the boiling temperature as direct function of liquid composition have been tested successfully and applied for predicting azeotropic behavior of multicomponent mixtures and the kind of azeotrope (minimum, maximum and saddle type) using modified correlation of Gibbs-Konovalov theorem. Also, the binary and ternary azeotropic point have been detected experimentally using graphical determination on the basis of experimental binary and ternary vapor-liquid equilibrium data.

            In this study, isobaric vapor-liquid equilibrium for two ternary systems: “1-Propanol – Hexane – Benzene” and its binaries “1-Propanol –

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Publication Date
Sun Jan 01 2023
Journal Name
Petroleum And Coal
Analyzing of Production Data Using Combination of empirical Methods and Advanced Analytical Techniques
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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Semi parametric Estimators for Quantile Model via LASSO and SCAD with Missing Data
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In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

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Publication Date
Fri Feb 28 2025
Journal Name
The Iraqi Geological Journal
Structural Interpretation of Najaf Basin Using the Magnetic and Gravity Data, Central Iraq
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Potential data interpretation is significant for subsurface structure characterization. The current study is an attempt to explore the magnetic low lying between Najaf and Diwaniyah Cities, In central Iraq. It aims to understand the subsurface structures that may result from this anomaly and submit a better subsurface structural image of the region. The study area is situated in the transition zone, known as the Abu Jir Fault Zone. This tectonic boundary is an inherited basement weak zone extending towards the NW-SE direction. Gravity and magnetic data processing and enhancement techniques; Total Horizontal Gradient, Tilt Angle, Fast Sigmoid Edge Detection, Improved Logistic, and Theta Map filters highlight source boundaries and the

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