Aim The aim of this study is to evaluate the effect of demographic, clinical, and radiographic factors on the duration of surgical extraction of impacted lower third molars. Materials and methods This retrospective study included patients who underwent surgical removal of impacted lower third molars, and the investigated factors were demographic data including age and gender, radiographic data including the impacted tooth angulation and depth of impaction and ramus relation, and clinical data including the state of eruption of the impacted teeth. These factors were evaluated for association with the duration of surgery. Descriptive statistical analysis included percentages and mean ± standard deviation (SD). Student's t-test was used to co

      The detection of diseases affecting plant is very important as it relates to the issue of food security, which is a very serious threat to human life. The system of diagnosis of diseases involves a series of steps starting with the acquisition of images through the pre-processing, segmentation and then features extraction that is our subject finally the process of classification. Features extraction is a very important process in any diagnostic system where we can compare this stage to the spine in this type of system. It is known that the reason behind this great importance of this stage is that the process of extracting features greatly affects the work and accuracy of classification. Proper selection of

Liquid – liquid interface reaction is one of the method to prepare nanoparticles, the preparation of nanoparticles depends on the super saturation of ions which can satisfy by layered two immiscible liquid (toluene and deionized (DI) water). The XRD-diffraction analysis give a mix structure from hexagonal and cubic and the average grain size is 7.73 nm using Sherrer relation and 9.54 nm using Williamson –Hall method. Transmission electron microscopy (TEM) Showed that the size of particles around 3 nm which is comparable with Bohr radius of CdS.
From UV-Visible spectrum analysis which use two model to estimate the radius of particles , the first one is effective mass approximate (EMA) model and the second one is tight binding model

One of the challenging and active research topics in the recent years is Facial Expression. This paper presents the method to extract the features from the facial expressions from still images. Feature extraction is very important for classification and recognition process. This paper involve three stages which contain capture the images, pre-processing and feature extractions. This method is very efficient in feature extraction by applying haar wavelet and Karhunen-Loève Transform (KL-T). The database used in this research is from Cohen-Kanade which used six expressions of anger, sadness fear, happiness, disgust and surprise. Features that have been extracted from the image of facial expressions were used as inputs to the neural networ

     Measuring goat weight on a farm is carried out by two methods. The first method conventionally measures the chest girth (CG) and body length (BL), while the second is performed using a scale. This study aimed to facilitate the CG and BL measurements to estimate goat weight more efficiently through image processing. The endpoints of CG and BL were determined automatically using binary large object (BLOB) segmentation. The images of 120 goats were taken at three different shooting distances of 50 cm, 70 cm, and 90 cm. The statistical testing of the three scenarios in this study explained that the ideal distance to take pictures is the basis for determining whether or not the size of the circumference and BL is appropriate as a fea

       This work demonstrates the synthesis and storage of molecular-imprinted polymers (MIP) at room temperature using bulk polymerisation of Metformin (Met) characterized by high sensitivity, low cost, and high stability. To ensure an acceptable adsorption capacity, the research employed 0.8:4:20 mmol ratios of template, monomer, and cross-linking agents for the polymerization. A functional monomer, 2-acrylamido-2-methyl-1-propane sulphonic acid C₇H₁₃NO₄S, was cross-linked with N,N-methylene bisacrylamide C₇H₁₀N₂O₂ to form Met-MIP, which could be characterized using a UV-VIS spectrophotometer at 236 nm, FT-IR spectroscopy, and scanning electron

Buffering of Local anaesthesia (LA) has been suggested as a mechanism to improve injection comfort and hasten the onset of anaesthesia. Aim This study aimed to evaluate the effectiveness of buffered LA in the extraction of maxillary premolars and molars. Materials and Methods This randomized controlled study included 100 patients who were indicated for extraction of maxillary posterior teeth, they were randomly divided into two groups; a study group that received infiltration of buffered 2% lidocaine hydrochloride with 1:80,000 epinephrine LA, and a control group that received non-buffered 2% lidocaine hydrochloride with 1:80,000 epinephrine LA. The buffering was performed using the Onset® LA buffering system (Onpharma®). The outcome va

    The Fuzzy Logic method was implemented to detect and recognize English numbers in this paper. The extracted features within this method make the detection easy and accurate. These features depend on the crossing point of two vertical lines with one horizontal line to be used from the Fuzzy logic method, as shown by the Matlab code in this study. The font types are Times New Roman, Arial, Calabria, Arabic, and Andalus with different font sizes of 10, 16, 22, 28, 36, 42, 50 and 72. These numbers are isolated automatically with the designed algorithm, for which the code is also presented. The number’s image is tested with the Fuzzy algorithm depending on six-block properties only. Groups of regions (High, Medium, and Lo

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has