Iman Morsi

A surface acoustic wave (SAW) gas sensor allows propagation of the wave through its surface piezoelectric materials. SAW devices are now frequently utilized. In a variety of fields due to their benefits characteristics such as a simple design, low cost, and superb performance, they may also be used in challenging environmental circumstances. The aim of this paper is to create a mass-sensitive transducer that works with metal oxide semiconductors to be integrated. An examination of the SAW gas sensor's materials, architecture design, and analysis of the SAW gas sensor are proposed in this paper. SAW devices were fabricated in commercial MEMS processes using piezoelectrical material such as Zinc oxide (ZnO), Tin Oxide (SnO2), and Barium titanate (BaTiO3) in the form of polycrystalline material. This paper represents a comparative study of a SAW gas sensor with two different designs of interdigitated transducers (IDT) using different piezoelectric materials as a substrate with a sensing layer based on COMSOL Multiphysics 5.5 software to maximize its output. The first design has the shape rectangular (IDT) while the second design has the shape of an ellipse.

Accelerometers are inertial sensors that detect acceleration and forces along three orthogonal axes; the readings are then produced as a digital or analog signal and used in various applications. Microelectromechanical systems (MEMS) have recently been utilized to perform inertial sensing techniques on an integrated circuit (IC) at micro size. Due to the various characteristics of MEMS materials and how they affect the sensitivity of the MEMS accelerometer with these variations. In this paper, a MEMS accelerometer model was created using the COMSOL © software. The design was then applied to polycrystalline Silicon (Si), Gallium Arsenide (GaAs) and Germanium (Ge) and the sensing voltage of the accelerometer was determined using each material to compare the performance these materials. It was found that the gallium arsenide material is the best, as the output, if used, is 50% higher than that of polysilicon and 7% higher than that of germanium, using the same parameters and at a constant temperature.

Theoretically speaking, within the track of photothermal therapy, heat impacts to cancer cells localization is overspreading strategy for confronting cancer. It helps in decreasing the side impacts on cells close to tumors, enhances the quality of life of affected people, and by and large, and consequently, the hyperthermia impact is upgraded. The nanoparticles optical features are based on their form and size. The main objective of our work is a trial to upgrade the photo-thermal features some noble metal nanostructures by enhancing the absorption characteristics. This is accomplished by utilizing unused shapes in addition to some modern geometrical forms of nanoparticles self-similar clusters. The significance is of this work is its use in treating tumors, through distributed heating, especially caused by cancer and destroying the injured cells, while keeping the other cells safe. The nano-rod single element is used, achieving absorption of-31.8 dB at 613.5 THz. Also, the proposed nano-sphere shape results in an optimum performance that exceeds literature reported results, achieving absorption of-42.5 dB at 1035 THz.

Commercial string photovoltaic systems exhibit performance degradation due to partial shading and/or irradiance mismatch as a result of missing global maximum power point. Several artificial intelligence based maximum power point tracking (MPPT) techniques tackle this problem and commonly suffer performance versus computational burden trade-off. In this paper, an efficient partial-shadingtolerant MPPT technique is proposed offering simple implementation, dead-beat like performance, minimal oscillation and reduce computational burden.

This paper introduces a real-time autonomous navigation system (ANS) utilizing reduced expense hardware gadgets with considerable itinerary accuracy. This framework could be essentially constructed inside any vehicle to empower its self-driving development. The proposed ANS is actualized through an open loop decentralized loosely integration approach of an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS). The GPS receiver is chosen to be the Skylab SKM53 module. Due to its modularity and smaller filter size, the 6 degree of freedom (DOF) MPU6050 breakout board is utilized to be the IMU in the framework. Proper ongoing route precision levels are acquired through the rectification of Position and Velocity (PV) readings coming out from the GPS. Two Extended Kalman Filters (EKFs) are utilized to give the adjusted PV readings. The filters are built through two state machines that are running instantaneously on an Atmel ATmega16 microcontroller which is the principal regulator of the proposed ANS. The framework additionally incorporates 3DRobotics 915 MHz remote telemetry module to handle the real-time processing of the route information. The framework's accuracy is approved on an actual vehicular direction. The Root Mean Square Error (RMSE) values for the actualized ANS in ENU headings have reached 0.254, 0.337, and 0.462 meters individually _ which is remarkably significant with other recent related work.

In photo-thermal therapy, the localization of heat effects to cancer cells is an over growing approach in cancer treatment. This potentially reduces the side effects on tumor neighboring cells, improves the quality of life of the patient, and generally enhances the effectiveness of the hyperthermia. The optical properties of the nanoparticles depend mainly on their shape and size. The aim of this work is to enhance the photo thermal properties of noble metal nanostructures through improving their absorption characteristics. This is achieved using new shapes as well as new geometrical configurations of selfsimilar arrays of nanoparticles.

Carbon NanoTube Field Effect Transistor (CNTFET) is the new alternative and promising nano-scaled device for the implementation of high performance, and low power circuits. In this paper, comparison of CNTFET devices with MOSFET devices in the application of operational transconductance amplifier (OTA) in the GM-C filter is analyzed. The effect of capacitance with channel length, number of tubes, and chirality at frequency 5MHz is studied. The MOSFET filter uses 16 pF capacitors with the OTAs, whereas in the CNTFET filter only 0.8 pF capacitance is needed to achieve the same frequency response while preserving the same levels of total harmonic distortion. The proposed design of GM-C filter using CNTFET makes a reduction up to 95% of the capacitance needed over the MOSFET one, and also a reduction up to 95% in the bias current needed. Both are major benefits in the chip size, IC fabrication, and power consumption aspects.

This paper proposes a hybrid electro-mechanical maximum power point tracking (MPPT) technique for recently evolved photovoltaic (PV) based innovative solar trees. The presented technique incorporates (i) a single axis digitally controlled mechanical sun tracker in addition to (ii) a modified variable step Perturb and Observe (P&O) electrical MPPT algorithm. The proposed system enhanced performance is attested using MATLAB/SIMULINK based model in addition to experimental verification.

Accidents could happen by leaking flammable and toxic gases. It is necessary for preventing a serious accident to implement a reliable detector system which can monitor these gases. In this paper, an inexpensive with high accuracy system based on the Internet of Things (IoT) and artificial intelligence techniques is used to monitor important environment parameters. The designed system used three different sensors; two metal oxide(MOX) gas sensors (MQ-2 and MQ-5) which are used to detect different concentration of Liquefied Petroleum Gas (LPG) at (200,400,700,1000 ppm) and carbon monoxide (CO) at (50,100,200,500 ppm). These measurements are based on the threshold value of gas concentration of Occupational Safety and Health Administration organization OSHA (1000ppm for LPG and 50ppm for CO), and one sensor DHT11 for temperature (T), relative humidity (RH%). All sensors are connected to the microcontroller ATmega328P to continuously sense the environment parameters. A Wi-Fi Module based on an ESP8266 chip is used to send the data to an android mobile phone application in real time. This paper provides the calibration techniques for each gas sensor while comparing the measurements with actual value sensitivity curve using variation in load resistance 0.5 KΩ, 1 KΩ, 1.5 KΩ, and 2 KΩ at T: 25℃ and RH: 33%. It is found that the average accuracy of gas sensors is in the range 80-90%; MQ-5 is more accurate than MQ-2 for LPG while MQ-2 is more accurate than MQ-5 for CO. The main impact comes from temperature and humidity. To compensate the impact of ambient temperature and humidity on gas accuracy artificial neural network (ANN) and Fuzzy logic techniques are used. The results of the ANN and Fuzzy logic are shown to provide gas identification concentration according to variation in different parameters, such as gas sensor sensitivity, temperature, and humidity which improves the system average accuracy in the range of 97%-99%.

Steam boiler is one of the most widely used industrial systems. The boiler is used in many industrial applications. It produces steam and is used for many purposes, for example as a heat exchanger used in the refining and separation of oil and is used in electricity production also. Like any combustion system, boilers burn fossil fuels to generate steam. Emissions from fuel include carbon monoxide and nitrogen oxides. Incomplete combustion increases these emissions. The way to reduce these emissions is the control of combustion to make complete combustion by monitoring exhaust components like (NOx, CO2, CO and O2). Steam boilers are usually controlled for steam pressure only without including the exhaust components in the control loop. In this paper, a limiter for exhaust components will be included in the control loop beside the steam pressure control. This paper outlines the various stages of operation involved in the conversion of a manually operated boiler towards a fully automated one. Over the years, the demand for high quality, greater efficiency and automated machines has increased. The first part of the paper focuses on passing the inputs to the boiler at a required temperature, so as to constantly maintain a particular temperature in the boiler. The air preheater and economizer help in this process. The paper mainly focuses on level, pressure and flow control at the various stages of the boiler plant. The temperature in the boiler is constantly monitored. The automation is further enhanced by constant monitoring using a Supervisory Control and Data Acquisition system (SCADA) screen which is connected to the PLC by means of a communication cable. This paper describes the construction of SCADA and the corresponding Human Machine Interface (HMI) for a steam boiler plant. This last consists of the water drum, the air heaters and the main boiler. The control system of the plant is implemented using Siemens SIMATIC S7 PLC with ladder programming and WINCC to create the SCADA/ HMI system.

Photovoltaic (PV) cell/modules mathematical modelling is a mandatory aspect in recent renewable energy based systems. Several PV mathematical modelling techniques have been recently presented that vary in complexity and accuracy. In addition, the study of PV modules performance under partial shading conditions adds more complexity due to the presence of multiple local maxima/minima. In this paper, an enhanced PV array model is proposed with extended capabilities like: (i) graphical user interface (GUI) environment, (ii) open source structure, (iii) applicability on cell/array/module configuration, (iv) individual irradiance/temperature input per cell, and (v) accurate determination of local/global maxima/minimums points due to partial shading. The effectiveness of the proposed model is illustrated via rigorous simulation results in addition to a comparison between the proposed model and several recent references that are concerned with partial shading conditions.

In this research we describe the use of cyclic voltammetry concept in order to determine the level of Ascorbic Acid in orange juice. The proposed method consists of an open-source poteniostat and screen printed electrodes. The Current result from the chemical reaction is proportional to the concentration of the Ascorbic Acid. This method was applied to different commercial samples of orange juice and the results were used to determine which one has the most preservation of Ascorbic Acid.

This paper is a practical implementation of data acquisition system based on navigational devices. The data are extracted from different ship sensors on board. The objective of this paper is to build a navigation system based on sensors to simulate the original system. This system is implemented by collecting data from different sensors which are connected to microcontrollers PIC 16F628A & P16F886 then these data is transmitted wireless using Serial UART wireless module (200M Range-433 Mhz) to a computer station which enable continuous tracking for the all ship's sensor which indicate the situation in receiving site located at another place .The simulated system is built by using Lab View version (13). The ROM cost of the system around (220$).

Radio Frequency Identification (RFID) that enables tracking of people and objects indoor. 3-D LANDMARC has many problems but the 3-D Virtual LANDMARC can overcome the draw backs of 3-D LANDMARC like additional cost , improve the Localization accuracy , the problem of Radio Signal , the effect of reference Tags and without additional real Tags and Readers. Numerical Simulation Result show that the proposal algorithm is very simple and it gives higher location accuracy showed that enhances the precision of indoor localization the new k-nearest algorithm can provide better performance than the old one used in 3-D LANDMARC.

Water quality standards usually changes from application to another. For industrial application high water quality is required for boilers and turbines protection. Habitual desalinated planets water is used, but by the time it creates some problems because of salts and silica concentrations. Some important parameters have been studied for desalinated water which are Sodium (Na), Calcium (Ca), Magnesium (Mg), Potassium (k), Sulfate (So), Silica (Sio2), Chloride (Cl), and Fluoride (F-); in addition to PH and conductivity. The linear regression model, based on these parameters, is extracted and its coefficients and error are calculated using Regstat method. The principle component analysis (PCA) is applied for clustering water parameters according to the value of measured parameters; the result indicates that it is important to follow the desalination process by another purification process to improve water quality. The demineralization process can decrease ionic impurities significantly, so it is recommended to be used to protect industrial component from deposits and corrosion.

Water quality is measured based on the study of several parameters for different water sources. Three different sources of water are studied in Alexandria (Egypt): Mediterranean Sea, Mariot Lake, and mineral water. The measured parameters are: Sodium (Na), Magnesium (Mg), Calcium (Ca), Nickel (Ni), in addition to pH, conductivity and temperature. The measured values are compared with the standard of water parameters given by the World Health Organization (WHO). Different devices and sensors are used in measurements which are:ICP-7500 sequential plasma Spectroscopy SHIMADZU, ASTM D1126-02, ASTM D5708-11, ASTM D4191-08, ASTM D1125-95, ASTM D4191-08, ASTM D1293-99, in addition to colorimetric and potentiometric sensors. The linear regression model based on these parameters is extracted, and the coefficients are calculated by using three statistical analysis methods namely: regstat, roubustfit, and curve fitting. The predicted values of the concentrations from the linear regression models are compared with the measured values, and the root mean square error (RMS) is calculated. The principal component analysis (PCA) method is applied for clustering the three sources of water according to the values of measured parameters. The results indicate that, Mediterranean Sea is recommended as an alternative source. Mariot Lake is contaminated to a high degree.

Healthcare sector quality demands are exponentially rising to design expert systems for medical diagnosis. Likewise there is growing capture of biological, clinical, administrative data and integration of distributed and heterogeneous databases. Those previous mentioned branches create a completely new base for medical quality and cost management. In this paper fuzzy logic model is designed and practically tested. A group of 105 patients is use to develop this model and another group of same count patients was used to test it. All results are compared using fuzzy logic model in MATLB.

Gas identification represents a big challenge for improving detection and pattern recognition of each gas by using inexpensive gas sensor. This paper presents a gas detector system which is built to monitor, and measure gas pollutant emissions in the air and also used to detect different gases. The pollutants are ethane (C2H6) and methane (CH4) which are located beside the fertilizer factories in Alexandria Egypt and some other gases as hydrogen (H2), propane (C3H8) and isobutane (C4H10).The gas sensors TGS-2611, TGS-816, TGS-2620 and TGS-823 from Figaro Engineering Inc. are used to build agas detector system and it is located in the site of measurements. The data of each sensor is transmitted and received wirelessly using XBee module (DigiXBee 802.15.4) and microcontroller PIC 18F4620. The system is controlled and monitored by using programmable logic controllerPLC Step 7-200 from Siemens and Supervisory Control and Data Acquisition SCADA systems respectively. The principal component analysis PCA method is applied for clustering and distinguishing among different gases. The results indicate thatmethane can be detected using TGS-2611 better than other sensors.Isobutane can be detected by using TGS-2620 and TGS-2611 better than others. Propane can be detected by using TGS-816 and TGS-823 better than others. Hydrogen can be detected using TGS-2620, TGS-816 and TGS-823 better than others.

In oil refinery there is a variety of physical parameters such as pressure, flow rate and level that need to be measured. A microcontroller system is built based on PIC 16F877A, piezoresistive differential pressure DP sensor (24PC series) and strain gauge DP sensor (IDP-10) with ranges from 0 to 15psi. The results of the microcontroller system showed that; the percentage error for piezoresistive sensor in pressure from 0.43808% to 8.613 %, in flow rate from 0.21929% to 20.340%, and in level from 0.43808% to 2.5789%. While the percentage error for strain gauge sensor from 0.846% to 1.946% for pressure measurement, from 0.1% to 0.4% for flow rate measurement and from 0% to 0.64% for level measurement. The percentage error of the piezoresistive sensor is more than the percentage error of the strain gauge sensor: for pressure measurement by about 6.667%, for flow rate measurement by about 19.94% and for level measurement by about 1.9389%. Fuzzy logic is used to predict the output surface of pressure, flow rate, and level measurements.

In recent years, polymer-ceramic nanocomposite materials have been given great attention due to the possibility of their use in piezoelectric and pyroelectric transducers. Nanocomposite of polyvinylidene fluoride (PVDF) and barium titnate (BaTiO 3) is prepared using cast technique. When infrared spectra were used, it is concluded that pure PVDF and their composite with BaTiO 3 exist in the unpoled state (αphase). It is found that incorporation of BaTiO 3 into PVDF has destroyd the spherulite structure and has dispersed in the PVDF matrix with nanosize particles. It is observed that nanocomposite of 30 wt. % of PVDF has the highest pyroelectric coefficient of 1.00 nC/cm 2 / o C.

CulnS 2 thin films were electrodeposited onto indium tin oxide substrate by the electrodeposition technique. Cyclic voltammetry and chronoamperometry were carried out to determine the optimum pH and the amount of sodium thiosulfate for electroplating CuInS 2 compound. The composition, crystallinity and optical properties of the compounds synthesized were studied by energy dispersive X-ray (EDX), (SEM), X-ray diffraction and UV-Visible spectra. It was found that the increasing pH shifts the electrodepositions voltage toward more negative and lowers the deposition current. Increasing the amount of sodium thiosulfate also decreases the deposition current but it has no effect on the deposition potential. It was concluded that CuInS 2 with atomic stoichiometric ratio was prepared at pH equals 1 and 150 ml of 0.1 M sodium thiosulfate, 5 ml of 0.1 M indium chloride and 5 ml of 0.1 M cupper acetate. The energy gaps were calculated to be 1.6, 1.7 and 1.75 eV for CuInS 2 prepared at 1, 1.5 and 2 of pH, respectively. It was indicated that the amount of the sodium thiosulfate has a slight effect on the energy gap.

Voyage data recorders (VDR) enable accident investigators to review procedures and instructions before an
incident and help to identify the cause of any accident. The Future data recording should be capable of recording data
audio and video during day and night. The recording should be of high integrity, digital as well as independent of ship
supplies. Voyage data recorder, popular name black- box, is used for recording all kinds of navigation information.
VDR is a data recording system designed for all vessels required to comply with the International Maritime
Organization IMO's and International Convention safety of life at sea SOLAS requirements (IMO). Data from various
sensors on board the vessel is collected, digitized, compressed and then stored in an externally mounted protective
storage unit. The protective storage unit is a tamper-proof unit designed to with stand the extreme shock impact,
pressure and heat, which could be associated with a marine incident (fire, explosion, collision, sinking, etc). This
research realizes the importance of obtaining these stored data for accident analysis. This paper considers a real case
accident, by downloading and replaying the data of real black box for a sunken ship in the red sea. Eventually, video
recorded data of the accident will be more helpful to the investigation

Copper indium disulfide (CulnS 2) has direct band-gap energy of about 1.5 eV and a large absorption coefficient, which are well suited to the photovoltaic conversion of solar energy. In this task a novel florin doped tin oxide (FTO)/CuInS 2 / polyaniline base/ZnO/FTO hetrojunction solar cell was fabricated. CulnS 2 thin films were electrodeposited onto fluorine doped tin oxide substrate by the electrodeposition technique. Current-voltage characteristic curves were measured under darkness and illumination. It found that Jsc, Voc, and η are 3.2x10-6 A/cm 2 , 0.714 V and 1.92x10-3 % for FTO/CuInS 2 /ZnO/ITO herterojunction solar cell while Jsc, Voc, and η are 3.25x10-6 A/cm 2 , 0.724 V and 1.8x10-3 % for FTO/CuInS 2 /polyaniline base ZnO/ITO herterojunction solar cell.

The desalination plant is a project that needs to control and monitor the operation sequence This paper describes the construction of a Supervisory Control and Data Acquisition system (SCADA) and the corresponding Human-Machine Interface (HMI) for a multi-stage flash Brine Recirculation (BR) desalination plant. It consists of eight main cycles: the sea water cycle, the brine recirculation cycle, the brine heater cycle, the distillation cycle, the brine blow down cycle, the steam cycle, the condensate cycle and the pressure reduction cycle with a large number of inputs and outputs signals. The relay matrix is used to minimize the number of signals connected to the S7-3000(PLC) Siemens controller and connect it with (WINCC) software to show the application running under control. To maintain healthy system in case of main server failure we must create a redundant server connected with the main server by Ethernet and connected with the main control loop by Multi Point Interface (MPI). In this paper the SCADA/HMI main control loop is MPI because it is faster than Ethernet connection while MPI the control speed is 185kbps but the control speed in Ethernet is only 10/100kbps.

This paper introduces an efficient security system that, not only prevents intruders from being in unauthorized places, but also evaluates the performance of the employees by monitoring their movements in the facility and analyzing their behavior using the fuzzy logic theory. Rules were constructed using Mamdani fuzzy modeling and the design is made using the MATLAB fuzzy logic tool. The security system is extended to include employee performance evaluation. This paper was made for a machining workshop and the approach was setup using the data submitted from that workshop to determine the effective working hours that a worker actually makes. The salary is paid for the time the employee spends in his department working under the supervision of his supervisor. The employee is paid also to work in other departments for some time according to his work credibility and the relation of this department with his original department. The access of the employee to any department is monitored by IR and RFID sensors for security reasons and for the fuzzy evaluation of his performance. The base station is provided by a microcontroller to analyze the data obtained from the related stations. Fuzzy logic is used to determine for each employee the allowed time he can spend outside his original department.

Electronic noses are intelligent designs that are able to classify and quantify different gases/ odors. This concept permits us to easily provide remote connectivity, large data storage and complex signal processing by using commercial sensors. In this paper a case study is presented for examining the use of sensor grid system concerning urban air pollution monitoring for carbon monoxide, carbon dioxide (CO, CO2) gases for three different regions in Alexandria-Egypt along the Corniche and 2 different traffic roads. This is based on the integration of distributed sensors, data integration and developing a simple air pollutant model. The analysis and the characterization of environmental data are acquired by building a prototype of multi-sensors monitoring system (electronic nose), which are TGS 822, TGS 2442, TGS 813, TGS 4160, TGS 2600, temperature sensor, humidity sensor and wind speed measurements. All sensors are connected to the microcontroller (Pic 16F 628A) and PC to visualize and analyze data. Quadratic surface regression method is used to find possible correlations exisistance between some pollutants, elaborated by Matlab software and statistical analysis. The influence of meteorological quantities is taken into account to improve the model as well as different factors including weather conditions, topography and local situation. To investigate the performance of quadratic model, the interpolation quadrate function obtained is compared using the reduced data set after eliminating data in a random way with the results obtained using the original data set, then the mean square error (mse) is calculated. Analysis of variance (ANOVA) is used to detect the significant factors in the final quadrate equation and understanding the functional relationship between a set of independent factors.

One of the most important and crucial problems in the gas detection field is that there is a strong demand to detect Butane and Propane gases as pure gases, which are used in domestic applications as a fuel. However, both of them are extracted from natural gas mixed with each other. The paper describes the calibration of both gases in the pure case and also as a mixture between them at different temperatures using three different semiconductor sensors. It also presents a study of the efficiency of Feed forward Back Propagation Neural Network for the detection of gases using the Multi Layer Perceptron (MLP) method to separate between Propane and Butane depending on the data driven from different types of sensors.

Gas identification represents a big challenge for improving detection and pattern recognition of each gas by using inexpensive gas sensor. The detection of gases found in atmosphere such as: Carbon dioxide, Hydrogen and Methane depend on Taguachi gas sensors by varying the load resistance of each sensor, which can increase sensibility and selectivity of gas detection. This paper provides the measurement setup for gas detection by using variation in load resistance and calibration curves of each gas with different concentrations and different sensors. It also presents the combination of a gas sensor array together with surface response modeling algorithms to detect the concentration of gas and to describe the performance of each gas. To investigate, the performance prediction accuracy of each model type, the predicted results for each empirical algorithm are compared with the actual results. The full quadratic empirical model is considered to be the best with, the least error using different sensors.

This paper aims to determine the measurements for the EMF of some appliances for a healthy human subject including a variety of ELF and RF ranges and to detect the Hot Spot distance and time dependent. Two alternative methods are used for measuring the electromagnetic field and are compared with each other. The first method is by using a cell sensor device to obtain the relation between power densities or electromagnetic field strength at various distances from the objects. The second method depends on a hardware design, by using the Hall Effect sensor SS46 and PIC 16F 877A microcontroller for electromagnetic field measuring and monitoring. The measured values are collected from the sensor, and transmitted to the computer through the RS232 serial port. The results of the electromagnetic field measurement are compared against the results of the cell sensor device which are illustrated in the paper. The results of measurements are compared to FCC and ICNIRP guidelines for limiting time exposure. The results of measurements concerning a threshold or Hot Spot using appliances in home and working environment presents the limit of safe exposures as a function of time.

A microcontroller based gas sensing system is presented in this paper. The analysis presented here depends on thin film metal oxide gas sensors, TGS 822, TGS 813, TGS 2600, TGS 3870 and TGS 4160. The differences in the steady state performance among their sensors are used for improving their selectivity and sensitivity, while the combination of gas sensors permits success in gas classification problems. In the approach the gas sensors are embedded into a chamber with a heating system. Different types of gases are used, such as, Methane, Carbon dioxide, Hydrogen, Propane and Butane to pass through this chamber with different concentrations and different operating temperatures. Sets of experimental measurements are done to detect the gas sensitivity for each sensor depending on the output volt of microcontroller, in relation to temperatures, concentration of gases, and variable resistances for each sensor. In this paper, a novel approach for the gas identification is based on the fuzzy technique. The identification rules are directly extracted from the data driven from the microcontroller in the form of (IF-Then rules), where membership functions are employed in the fuzzy classifier. The results of the fuzzy logic are shown to provide gas identification according to variation in different parameters, such as gas concentrations variation in sensor's resistance and output volt of microcontroller at different temperatures and to indicate that the selection of different gases is possible, based on microcontroller, which improves sensitivity and selectivity with high accuracy and reliability.

This paper prescrils an on-linc prediction techniquc oT tlic photovoltaic output power under cloudy skies based
on artificial intelligcncc. Thc technique takes advantagc of thc fX1 tlial fuyq logic can aCCUJatCly siinulalc nonlinear
phenomena using ;i set of IF-THEN rules. These rules are fired partially and in-parallcl. This means that,
at any time. only a very limitcd subsct of the rules is uscd. This cnablcs ;I quick, on-linc estimation of the outpul
power of lhe photovoltaic cclls bascd on the ;iinalysis of thc image of tlic cloudy sky.

Water quality standards usually changes from application to another. For industrial application high water quality is required for boilers and turbines protection. Habitual desalinated planets water is used, but by the time it creates some problems because of salts and silica concentrations. Some important parameters have been studied for desalinated water which are Sodium (Na), Calcium (Ca), Magnesium (Mg), Potassium (k), Sulfate (So), Silica (Sio2), Chloride (Cl), and Fluoride (F-); in addition to PH and conductivity. The linear regression model, based on these parameters, is extracted and its coefficients and error are calculated using Regstat method. The principle component analysis (PCA) is applied for clustering water parameters according to the value of measured parameters; the result indicates that it is important to follow the desalination process by another purification process to improve water quality. The demineralization process can decrease ionic impurities significant...

This paper is a practical implementation of data acquisition system based on navigational devices. The data are extracted from different ship sensors on board. The objective of this paper is to build a navigation system based on sensors to simulate the original system. This system is implemented by collecting data from different sensors which are connected to microcontrollers PIC 16F628A & P16F886 then these data is transmitted wireless using Serial UART wireless module (200M Range-433 Mhz) to a computer station which enable continuous tracking for the all ship's sensor which indicate the situation in receiving site located at another place .The simulated system is built by using Lab View version (13). The ROM cost of the system around (220$).

The fabricated In-doped ZnO gas sensors with different ratios (1, 5 and 10 %) were successfully synthesized via sol gel technique. ZnO is a sensitive material to different kinds of gases especially to Liquefied Petroleum Gas (LPG). The morphological structures of the prepared ZnO were revealed using a scanning electron microscope (SEM). X-ray diffraction (XRD) patterns exhibited a highly crystallized wurtzite structure and were used for identifying phase structure and chemical state of both ZnO and ZnO doped with In. The gas sensitivity and voltage are measured as a function of temperature for the fabricated In-doped and un-doped ZnO gas sensor devices for the LPG gas. The maximum sensitivity is recorded at Zn/In = 95:5 is 111%. This concentration has a good voltage variation. By increasing the load resistances the voltage will decreases.

Commercial string photovoltaic systems exhibit performance degradation due to partial shading and/or irradiance mismatch as a result of missing global maximum power point. Several artificial intelligence based maximum power point tracking (MPPT) techniques tackle this problem and commonly suffer performance versus computational burden trade-off. In this paper, an efficient partial-shadingtolerant MPPT technique is proposed offering simple implementation, dead-beat like performance, minimal oscillation and reduce computational burden.

The demand for LPG (Liquefied Petroleum Gas) detection constitutes a major and critical problem in the field of gas detection. LPG is used for domestic appliances used in the heating of buildings, producing petrochemicals and as a motor fuel. The current paper used the fabricated ZnO, in addition to TGS 813, TGS 2600, TGS 4160, TGS 3870, TGS 822 as semiconductor gas sensors, in varying temperature and load resistance in a prototype setup so as to explore each model’s accuracy for performance prediction for gas detection. The fabricated ZnO gas sensor is used also to detect the LPG. The comparison is done between gas sensors array and the fabricated one from ZnO. The actual results are put in comparison with the empirical algorithms’ predictions. The optimal model is found to be the full quadratic empirical model based on the lowest error with different sensors.

This paper proposes a PLC (Programmable Logic Controller)/HMI (Human Machine Interface) system for tracking oil products refineries. The proposed pipeline includes AOI (Add on Instruction) programming, and PLC to automatically display petroleum products terminal. It provides an AOI in programming to obtain the most utilization of processor capabilities. Besides, it makes use of AOI for programming in cooperation with a ladder logic program. This results in simplifying the ladder program, decreasing scan time, and making troubleshooting easier. The proposed system is constructed in two stages. First is the PLC controller programming stage. In the second stage, the HMI graphic presentations are drawn and connected to the PLC tags. The proposed system outcomes confirmed that the number of logic ladders, maximum program size, and maximum scan time has decreased. The outcomes imply that the AOI can assist in tracing the program more without difficulty in faults situations. Besides, it adds extra program commands in less processor memory, lowering system creation, and upgrade costs.