The Environmental Data Acquisition Telemetry System is a versatile, flexible and economical means to accumulate data from multiple sensors at remote locations over an extended period of time; the data is normally transferred to the final destination and saved for further analysis.

This paper introduces the design and implementation of a simplified, economical and practical telemetry system to collect and transfer the environmental parameters (humidity, temperature, pressure etc.) from a remote location (Rural Area) to the processing and displaying unit.

To get a flexible and practical system, three data transfer methods (three systems) were proposed (including the design and implementation) for rural area services, the fi

The objective of this study was to assess the nutritional status of childs of nurseries in Baghdad city so that an early detection of malnutrition cases could be carried out. The results revealed that the daily consumption of food calories, protein, fat and carbohydrate were 1180.5 calories, 27.2gm, 38gm and 180gm, respectively, which were less than the RDA values and the percentages of these nutrients supplied by the food intake were 90.8, 83.7, 87.3 and 90.3%, respectively. It was also demonstrated that the highest percentages of stunting, underweight and wasting, which amounted to 32, 22.7 and 1.5%, respectively, were among those childs who obtained inadequate calories, while the percentages of the forementioned malnutrition cases amon

The research focuses on determination of best location of high elevated tank using the required head of pump as a measure for this purpose. Five types of network were used to find the effect of the variation in the discharge and the node elevation on the best location. The most weakness point was determined for each network. Preliminary tank locations were chosen for test along the primary pipe with same interval distance. For each location, the water elevation in tank and pump head was calculated at each hour depending on the pump head that required to achieve the minimum pressure at the most weakness point. Then, the sum of pump heads through the day was determined. The results proved that there is a most economical lo

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

The study examined the assessment of raw water and drinking water projects of  Diyala Governorate for the year 2017, amounting to (24) projects, The average per capita supply of potable water (0.396 m3 / day/person), which is less than the global standard for the average per capita of drinking water, and constitute water rumors within the network of water transport in the province (3%), and the water of raw and drinking value within the limits allowed to be used by Iraq and the global indicators of {Total acidity, alkaline, acidic function, chlorides, magnesium, Electrical conductivity, total soluble salts, sodium, potassium, sulfates, turbidity other than (raw water)}. While the index of calcium only a value higher than the limits

    This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find  that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.

Polypyrrole (PPy) nanocomposites were prepared using chemical oxidation and were combined with manganese oxide (MnO2) nanoparticles. The PPY-MnO2 nanocomposite was synthesized by integrating PPy nanofibers with varying volume ratio percentages of MnO2 dopant (10, 30, and 50% vol. ratio). The structural features of the PPy and PPy-MnO2 nanocomposite were investigated using X-ray diffraction (XRD).  Fourier transfor infrared (FTIR) spectroscopy was used to demonstrate the molecular structures of primary materials and the final product of PPy, MnO2, and PPy- MnO2 nanocomposites. Field Emission Scanning Electron Microscopy (FESEM) showed that the morphology of PPy consisted of a network of nanofibers. Increasing the volume ratios of ma

In this research, the methods of Kernel estimator (nonparametric density estimator) were relied upon in estimating the two-response logistic regression, where the comparison was used between the method of Nadaraya-Watson and the method of Local Scoring algorithm, and optimal Smoothing parameter λ was estimated by the methods of Cross-validation and generalized Cross-validation, bandwidth optimal λ has a clear effect in the estimation process. It also has a key role in smoothing the curve as it approaches the real curve, and the goal of using the Kernel estimator is to modify the observations so that we can obtain estimators with characteristics close to the properties of real parameters, and based on medical data for patients with chro