Detection and classification of animals is a major challenge that is facing the researchers. There are five classes of vertebrate animals, namely the Mammals, Amphibians, Reptiles, Birds, and Fish, and each type includes many thousands of different animals. In this paper, we propose a new model based on the training of deep convolutional neural networks (CNN) to detect and classify two classes of vertebrate animals (Mammals and Reptiles). Deep CNNs are the state of the art in image recognition and are known for their high learning capacity, accuracy, and robustness to typical object recognition challenges. The dataset of this system contains 6000 images, including 4800 images for training. The proposed algorithm was tested by using 1200

Fading channel modeling is generally defined as the variation of the attenuation of a signal with various variables. Time, geographical position, and radio frequency which is included. Fading is often modeled as a random process. Thus, a fading channel is a communication channel that experiences fading. In this paper, the proposed system presents a new design and simulate a wireless channel using Rayleigh channels. Rayleigh channels using two approaches (flat and frequency-selective fading channels) in order to calculate some path space loss efforts and analysis the performance of different wireless fading channel modeling. The results show that the bite error rate (BER) performance is dramatically improved in the value of signal to

The proposal of this study is demonstrating a simple vapor sensor for chloroform (CHCI₃) utilitizing air gap region of the Mach-Zehnder interferometer (MZI) by using a single mode optical fiber coupler (3 dB) structure. In the last few decades, flammable liquids such as chloroform have been highly used. This chemical liquid has some degrees of carcinogenic effects in humans in addition to acute and chronic exposure results like blurred vision and nausea.  The two arms of MZI contain a free space gap utilized to serve the sensing mechanism by adding chemical liquid volumes (0.2, 0.4, 0.6, 0.8, and 1) ml and to set the phase difference with air-gap distance 0.5 mm. The small variation in the effective refractive index of ch

      In this work, the performance of single-mode optical fibers (SMFs) for ultraviolet (UV) radiation monitoring and dosimetry applications is presented. In particular, this work will focus on the Radiation-Induced Absorption (RIA) phenomena in the Near-Infrared domain (NIR). Such phenomena play a very important role in the sensing mechanism for SMF. Single mode fibers with a diameter of 50 µm were used for this purpose. These fibers were dipped into germanium (Ge) solution with different concentrations (1, 3, and 5 wt%) to produce the sensing part of the sensor. For all optical fiber sensors under investigation, the results indicated the dependence of the RIA on the applied UV radiation energy. Also, a redshi

Photonic crystal fiber interferometers are widely used for sensing applications. In this work, solid core-Photonic crystal fiber based on Mach-Zehnder modal interferometer for sensing refractive index was presented. The general structure of sensor applied by splicing short lengths of PCF in both sides with conventional single mode fiber (SMF-28). To apply modal interferometer theory; collapsing technique based on fusion splicing used to excite higher order modes (LP01 and LP11). Laser diode (1550 nm) has been used as a pump light source. Where a high sensitive optical spectrum analyzer (OSA) was used to monitor and record the transmitted. The experimental work shows that the interference spectrum of Photonic crystal fiber interferometer

Photonic Crystal Fiber (PCF) based on the Surface Plasmon Resonance (SPR) effect has been proposed to detect polluted water samples. The sensing characteristics are illustrated using the finite element method. The right hole of the right side of PCF core has been coated with chemically stable gold material to achieve the practical sensing approach. The performance parameter of the proposed sensor is investigated in terms of wavelength sensitivity, amplitude sensitivity, sensor resolution, and linearity of the resonant wavelength with the variation of refractive index of analyte. In the sensing range of 1.33 to 1.3624, maximum sensitivities of 1360.2 nm ∕ RIU and 184 RIU⁻¹ are achieved with the high sensor resolutions of 7

Landforms on the earth surface are so expensive to map or monitor. Remote Sensing observations from space platforms provide a synoptic view of terrain on images. Satellite multispectral data have an advantage in that the image data in various bands can be subjected to digital enhancement techniques for highlighting contrasts in objects for improving image interpretability. Geomorphological mapping involves the partitioning of the terrain into conceptual spatial entities based upon criteria. This paper illustrates how geomorphometry and mapping approaches can be used to produce geomorphological information related to the land surface, landforms and geomorphic systems. Remote Sensing application at Razzaza–Habbaria area southwest of Razz

Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.