An impressed current cathodic protection system (ICCP) requires measurements of extremely low-level quantities of its electrical characteristics. The current experimental work utilized the Adafruit INA219 sensor module for acquiring the values for voltage, current, and power of a default load, which consumes quite low power and simulates an ICCP system. The main problem is the adaptation of the INA219 sensor to the LabVIEW environment due to the absence of the library of this sensor. This work is devoted to the adaptation of the Adafruit INA219 sensor module in the LabVIEW environment through creating, developing, and successfully testing a Sub VI to be ready for employment in an ICCP system. The sensor output was monitored with an Arduino Uno microcontroller and the LabVIEW Linx firmware toolkit. Pulse Width Modulation (PWM) technique, which ranges from 0% to 100%, was applied by the Arduino to supply the l298N voltage driver in order to regulate the voltage input to the load. A moving average filter was employed to measure the ripple voltage averaging, and a median filter was utilized to stabilize the readings. A passive low-pass filter circuit smoothed the PWM voltage before supplying the load. The results from the MATLAB-Simulink environment showed a cut-off frequency of 2.33 Hz, ripple voltage peak to peak was 41.1 mV and a settling time of 0.157 seconds. The calibrated results of the INA219 module sensor showed an absolute voltage inaccuracy of around 2.3% at full scale. In addition, an absolute error in the current of 2.2% at 25 mA shows a gradual increase as the current increases to 7% at 43 mA, while the highest absolute error for the full scale of power was at 5.8%. The obtained measurements were highly precise, and the values of the coefficient of variation were 0.36 %, 0.28% and 0.17% for the voltage, current, and power, respectively.
Malware represents one of the dangerous threats to computer security. Dynamic analysis has difficulties in detecting unknown malware. This paper developed an integrated multi – layer detection approach to provide more accuracy in detecting malware. User interface integrated with Virus Total was designed as a first layer which represented a warning system for malware infection, Malware data base within malware samples as a second layer, Cuckoo as a third layer, Bull guard as a fourth layer and IDA pro as a fifth layer. The results showed that the use of fifth layers was better than the use of a single detector without merging. For example, the efficiency of the proposed approach is 100% compared with 18% and 63% of Virus Total and Bel
... Show MoreThin films of (CuO)x(ZnO)1-x composite were prepared by pulsed laser deposition technique and x ratio of 0≤ x ≤ 0.8 on clean corning glass substrate at room temperatures (RT) and annealed at 373 and 473K. The X-ray diffraction (XRD) analysis indicated that all prepared films have polycrystalline nature and the phase change from ZnO hexagonal wurtzite to CuO monoclinic structure with increasing x ratio. The deposited films were optically characterized by UV-VIS spectroscopy. The optical measurements showed that (CuO)x(ZnO)1-x films have direct energy gap. The energy band gaps of prepared thin films
Abstract 20 patients with osteoarthritis of the knee joint were treated by electrical stimulation in the form of 6 sessions every other day each sessions of diphase fixe (DF) for 4 minutes followed by rest for 4 minutes then treated with a monophase fixe (MF) for 2 minutes. By clinical & statistical analysis ( P value < 0.05) we conclude that the electrical stimulation is effective as one method in the treatment of osteoarthritis.
Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal.
In this study, the four tests employed for non-linear dependence which is Engle (1982), McLeod &Li (1983), Tsay (1986), and Hinich & Patterson (1995). To test the null hypothesis that the time series is a serially independent and identical distribution process .The linear structure is removed from the data which is represent the sales of State Company for Electrical Industries, through a pre-whitening model, AR (p) model .From The results for tests to the data is not so clear.
Superconducting compound Bi2Sr2-xYxCa2Cu3O10+δ were Synthesized by method of solid state reaction, at 1033 K for 160 hours temperature of the sintering at normal atmospheric pressure where substitutions Yttrium oxide with Strontium. When Y2O3 concentration (0.0, 0.1, 0.2, 0.3, 0.4 and 0.5). All specimens of Bi2Sr2Ca2Cu3O10+δ superconducting compounds were examined. The resistivity of electrical was checked by the four point probe technique, It was found th
Electrochemical oxidation in the presence of sodium chloride used for removal of phenol and any other organic by products formed during the electrolysis by using MnO2/graphite electrode. The performance of the electrode was evaluated in terms fraction of phenol and the formed organic by products removed during the electrolysis process. The results showed that the electrochemical oxidation process was very effective in the removal of phenol and the other organics, where the removal percentage of phenol was 97.33%, and the final value of TOC was 6.985 ppm after 4 hours and by using a speed of rotation of the MnO2 electrode equal to 200 rpm.