Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or living in it to assist people in recognizing between a secured and an unsecured environment. Geo-location, combined with new approaches and techniques, can be extremely useful in crime investigation. The aim is focused on comparative study between three supervised learning algorithms. Where learning used data sets to train and test it to get desired results on them. Various machine learning algorithms on the dataset of Boston city crime are Decision Tree, Naïve Bayes and Logistic Regression classifiers have been used here to predict the type of crime that happens in the area. The outputs of these methods are compared to each other to find the one model best fits this type of data with the best performance. From the results obtained, the Decision Tree demonstrated the highest result compared to Naïve Bayes and Logistic Regression.
A field experiment was conducted at the experimental field of botanical garden, faculty of science, university of Baghdad, in order to study the effect of plant density on growth and yield of two local cultivars of sunflower (Sin Althieb and Shumose). The densities used were 4.4 and 8.8 plant/m2. The results showed difference between cultivars in their agronomic traits and their yields. There was a significant increase in plant height and leaf area index by increasing the plant density, while head diameter, number of seeds and leaf area decreased. But the most significant effect was the increasing in yield and biological yield by increasing the plant density. There was an increase by 72% and 58% in the yield and 79% an
... Show MoreSemantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s
... Show MoreBiological drugs have an active substance that is made by a living organism or derived from a living organism. They are one of the important therapy options used in a wide range of diseases especially life-threatening diseases. Biological therapy opens new opportunities for treating different diseases for which drug therapy is minimal, but they have considerable differences in the safety consequences in comparison with non-biological drugs. The aim of the current study was to assess the post-marketing safety profile of biological drugs used in Iraqi hospitals by the analysis of the reported adverse drug reactions regarding their severity, seriousness, preventability, expectedness, and outcome. It is a retrospective study of the individu
... Show MoreSTAG proteins, which are part of the cohesin complex and encoded by the STAG genes, are known as Irr1/Scc3 in yeast and as SA/STAG/stromalin in mammals. There are more variants as there are alternate splice sites, maybe three open reading frames (ORFs) code for three main proteins, including: SA1 (STAG1), SA2 (STAG2) and SA3 (STAG3). The cohesin protein complex has various essential roles in eukaryotic cell biology. This study compared the expression of the STAG1 gene in four different breast cancer cell lines, including: MCF-7, T-47D, MDA-MB-468, and MDA-MB-231 and normal breast tissue. RNA was extracted from these cell lines and mRNA was converted to cDNA, and then expression of the STAG1 gene was quantified by three sets of specific prim
... Show MoreSome species, such as the Eurasian Collared-Dove (S. decaocto) are fast expanding around the planet, while others, such as the European Turtle-Dove (S. turtur), are experiencing precipitous population declines. Climate change, habitat loss, greater cultivated areas, and hunting pressure are the major threats to the diversity of Streptopelia. A few species require urgent conservation action. Priority for subsequent research should be to redress outstanding taxonomic uncertainties, ascertain the effect of climate change on distributions, and put in place conservation measures for declining taxa. We provide here a detailed review on how it is possible to understand the diversity of Streptopelia and how such an understanding can con
... Show MoreIn Computer-based applications, there is a need for simple, low-cost devices for user authentication. Biometric authentication methods namely keystroke dynamics are being increasingly used to strengthen the commonly knowledge based method (example a password) effectively and cheaply for many types of applications. Due to the semi-independent nature of the typing behavior it is difficult to masquerade, making it useful as a biometric. In this paper, C4.5 approach is used to classify user as authenticated user or impostor by combining unigraph features (namely Dwell time (DT) and flight time (FT)) and digraph features (namely Up-Up Time (UUT) and Down-Down Time (DDT)). The results show that DT enhances the performance of digraph features by i
... Show MorePKE Sharquie MD, PDPAA Noaimi MD, DDV, FDSM Al-Ogaily MD, IOSR Journal of Dental and Medical Sciences (IOSR-JDMS), 2015
The aerodynamic characteristics of general three-dimensional rectangular wings are considered using non-linear interaction between two-dimensional viscous-inviscid panel method and vortex ring method. The potential flow of a two-dimensional airfoil by the pioneering Hess & Smith method was used with viscous laminar, transition and turbulent boundary layer to solve flow about complex configuration of airfoils including stalling effect. Viterna method was used to extend the aerodynamic characteristics of the specified airfoil to high angles of attacks. A modified vortex ring method was used to find the circulation values along span wise direction of the wing and then interacted with sectional circulation obtained by Kutta-Joukowsky theorem of
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