This study aims to improve the quality of satellites signals in addition to increase accuracy level delivered from handheld GPS data by building up a program to read and decode data of handheld GPS. Where, the NMEA protocol file, which stands for the National Marine Electronics Association, was generated from handheld GPS receivers in real time using in-house design program. The NMEA protocol file provides ability to choose points positions with best status level of satellites such as number of visible satellite, satellite geometry, and GPS mode, which are defined as accuracy factors. In addition to fix signal quality, least squares technique was adopted in this study to minimize the residuals of GPS observations and enh

In recent years, English language teaching and second language acquisition has demonstrated a significant accentuation upon basic reasoning abilities improvement in the language capability advancement. Encouraging a point of view of duty to training basic intuition aptitudes in accordance with the English language courses, this paper gives an account of an investigation directed at theoretical meanings of basic deduction, drifts about the centrality of basic speculation for language educating and associations between critical thinking and language learning. The educators have the focal pretended by basic intuition in successful language teaching method, identified to Ennis’ (2011) critical thinking categories. The skill of thinking critic

Carbides or nitrides thin films present materials with good mechanical properties for industrial applications as they can be coatings at low temperatures serve temperature sensitive surfaces. In this work the effect of the C percentage on the mechanical properties represented by the Young modulus (E) of combinatorial magnetron sputtered TiC_x (34%x˂65%) has been studied. The structure of the produced films is TiC independent on the C concentration. The mechanical properties are increased with increasing the C concentration up to 50%, and then decreasing with further C % increasing. These results can be explained by considering the resultant residual stresses.

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n

In this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method  and the least squares method and that using the method of simulation model  first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that

This work dealt with separation of naphthenic hydrocarbons from non-naphthenic hydrocarbons and in particular concerns an improved process for increasing the naphthenes concentration in naphtha, The separation was examined using adsorption by Y and  B zeolite in a fixed bed process. The concentration of naphthenes in the influent and effluent streams was determined using PONA classification. The effect of different operating variables such as feed flow rate (2- 4 L/hr); bed length (50 - 80 cm) on the adsorption capacity of Y and  zeolite was studied. Increasing the bed length lead to increase the naphthenes concentration, and increasing the flow rate lead to decrease in the concentration of naphthenes, It was found that the decrease