Bacterial meningitis is a leading cause of illness and death worldwide. It is crucial for clinical and public health care, as well as disease control, to identify the meningitis-causing agent promptly. Between June 2021-February 2022, a total of 100 cerebrospinal fluid (CSF) and blood samples were collected from suspected cases of meningitis admitted to Raparin Paediatric Teaching Hospital, Erbil city-Iraq. Cytochemical, cultural, and biochemical tests were conducted, and confirmed by molecular techniques. Bacterial culture findings were positive in 7% of CSF samples and just one positive among blood samples. The most common pathogens found by cultural characteristics and VITEK 2 Compact System were Staphylococcus sciuri in two

Dates are considered one of the most important foods consumed in Arab countries. Dates are commonly infested with the sawtoothed grain beetle, Oryzaephilus surinamensis. Consequently, the date yield, quantity, and quality (economic value and seed viability) are negatively affected. This study was designed to investigate the effectiveness of air evacuation as eco-friendly and safe control method against adult O. surinamensis. Insects were obtained from the infested date purchased from a private store in sakaka city, Aljouf region, Saudi Arabia. Air evacuation (using a vacuum pump) and food deprivation were applied to O. surinamensis, and insect mortality was observed daily in comparison with the control group (a

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

PMMA/TiO2 homogeneous thin films were deposited by using plasma jet system under normal atmospheric pressure and room temperature. PMMA/TiO2 nanocomposite thin film synthesized by plasma polymerization. Titanium oxide was mixed with Methyl Methacrylate Monomer (MMA) with specific weight ratios (1, 3 and 5 grams of TiO2 per 100 ml of MMA). Optical properties of PMMA/TiO2 nanocomposite thin films were characterized by UV-Visible absorption spectra using a double beam UV-Vis-NIR Spectrophotometer. The thin films surface morphological analysis is carried out by employing SEM. The structure analysis are achieved by X-ray diffraction. UV-Visible absorption spectra shows that the increasing the concentration of titanium oxide added to the polym

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Data <span>transmission in orthogonal frequency division multiplexing (OFDM) system needs source and channel coding, the transmitted data suffers from the bad effect of large peak to average power ratio (PAPR). Source code and channel codes can be joined using different joined codes. Variable length error correcting code (VLEC) is one of these joined codes. VLEC is used in mat lab simulation for image transmission in OFDM system, different VLEC code length is used and compared to find that the PAPR decreased with increasing the code length. Several techniques are used and compared for PAPR reduction. The PAPR of OFDM signal is measured for image coding with VLEC and compared with image coded by Huffman source coding and Bose-

The heat exchanger is a device used to transfer heat energy between two fluids, hot and cold. In this work, an output feedback adaptive sliding mode controller is designed to control the temperature of the outlet cold water for plate heat exchanger. The measurement of the outlet cold temperature is the only information required. Hence, a sliding mode differentiator was designed to estimate the time derivative of outlet hot water temperature, which it is needed for constructing a sliding variable. The discontinuous gain value of the sliding mode controller is adapted according to a certain adaptation law. Two constraints which imposed on the volumetric flow rate of outlet cold (control input) were considered within the rules of the proposed