Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

Roughness length is one of the key variables in micrometeorological studies and environmental studies in regards to describing development of cities and urban environments. By utilizing the three dimensions ultrasonic anemometer installed at Mustansiriyah university, we determined the rate of the height of the rough elements (trees, buildings and bridges) to the surrounding area of the university for a radius of 1 km. After this, we calculated the zero-plane displacement length of eight sections and calculated the length of surface roughness. The results proved that the ranges of the variables above are Z_H (9.2-13.8) m, Z_d (4.3-8.1) m and Z_o (0.24-0.48) m.

        In this work, an anti-reflection coating was prepared in the region (400-1000) nm of wavelength, with a double layer of silicon dioxide (SiO₂) as an inner layer and the second layer of the mixture (SiO₂) and titanium dioxide (TiO₂) with certain ratios, as an outer layer using the chemical spraying method with a number of 6 sprays of layer SiO₂ and 12 sprays of layer SiO₂ - TiO₂. Using the method of chemical spraying deposited on the glass as a substrate with a different number of sprays of SiO₂, and a fixed number of TiO₂-SiO₂. The optical and structural properties were determined using UV-Vis spectroscopy and atomic force mi

The study aims to build a water quality index that fits the Iraqi aquatic systems and reflects the environmental reality of Iraqi water. The developed Iraqi Water Quality Index (IQWQI) includes physical and chemical components. To build the IQWQI, Delphi method was used to communicate with local and global experts in water quality indices for their opinion regarding the best and most important parameter we can use in building the index and the established weight of each parameter. From the data obtained in this study, 70% were used for building the model and 30% for evaluating the model. Multiple scenarios were applied to the model inputs to study the effects of increasing parameters. The model was built 4 by 4 until it reached 17 parame

The semiempirical (PM3) and DFT quantum mechanical methods were used to investigate the theoretical degradation of Indigo dye. The chemical reactivity of the Indigo dye was evaluated by comparing the potential energy stability of the mean bonds. Seven transition states were suggested and studied to estimate the actually starting step of the degradation reaction. The bond length and bond angle calculations indicate that the best active site in the Indigo dye molecule is at C10=C11.  The most possible transition states are examined for all suggested paths of Indigo dye degradation predicated on zero-point energy and imaginary frequency. The first starting step of the reaction mechanism is proposed. The change in enthalpy, Gibbs free energ

This study investigates the changes occurring in the province of Basra using geospatial methods and analyzes the variations in land surface temperature among the various types of land cover. For the months of July and December in the years 2013 and 2021, Landsat images were used in Landsat 8 OLI/TIRS, and satellite images were processed using ArcGIS 10.8 software. The study's categories for land use and land cover were generated through the application of supervised classification techniques, and the land surface temperature was calculated using data from a satellite sensor's brightness temperature. According to the study's findings, there has been an increase in urban areas (including barren land). From 2013 to 2021, a greater correlati

The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.