The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets, and feature selection is based on a fitness function that is proportional to the accuracy achieved using a Naive Bayesian Classifier (NBC). When measuring the performance of the BBH with the SpamBase dataset, the performance of the classifier and the dimension of the selected feature vector used as a classifier input are considered. The experiments revealed that the BBH can produce good FS results even with a small set of selected features. This shows that when utilizing the NBC-based BBH, good spam email categorization accuracy is possible.
Background: Sirenomelia is a rare congenital malformation characterized by fusion of the lower limbs giving a characteristic mermaid-like appearance to the affected fetus. It is commonly associated with gastrointestinal, genitourinary, cardiovascular and musculoskeletal system defects.
Objective : To report the clinical manifestations of an extremely rare and complex malformation along with the associated anomalies.
Case report: A case of sirenomelia was reported in a one of a set of twin delivered at term by caesarean section to a 39 year old Iraqi mother. According to the search that has been done, it seems that this is the first reported case in this country. The following associated anomalies ( imperforate anus, absence of exte
E-mail is an efficient and reliable data exchange service. Spams are undesired e-mail messages which are randomly sent in bulk usually for commercial aims. Obfuscated image spamming is one of the new tricks to bypass text-based and Optical Character Recognition (OCR)-based spam filters. Image spam detection based on image visual features has the advantage of efficiency in terms of reducing the computational cost and improving the performance. In this paper, an image spam detection schema is presented. Suitable image processing techniques were used to capture the image features that can differentiate spam images from non-spam ones. Weighted k-nearest neighbor, which is a simple, yet powerful, machine learning algorithm, was used as a clas
... Show MoreIn this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant
... Show Moreيهدف البحث الى تقديم استراتيجية مقترحة لشركة نفط الشمال ، وأخذت الاستراتيجية المقترحة بنظر الاعتبار الظروف البيئية المحيطة واعتمدت في صياغتها على اسس وخطوات علمية تتسم بالشمولية والواقعية ، اذ انها غطت الانشطة الرئيسية في الشركة (نشاط الانتاج والاستكشاف , نشاط التكرير والتصفية , التصدير ونقل النفط , نشاط البحث والتطوير , النشاط المالي , تقنية المعلومات , الموارد البشرية ) وقد اعتمد نموذج (David) في التحليل البيئي
... Show MoreThe research aims to present a proposed strategy for the North Oil Company, and the proposed strategy took into account the surrounding environmental conditions and adopted in its formulation on the basis and scientific steps that are comprehensive and realistic, as it covered the main activities of the company (production and exploration activities, refining and refining activities, export and transport of oil, research and development activity, financial activity, information technology, human resources) and the (David) model has been adopted in the environmental analysis of the factors that have been diagnosed according to a
... Show MoreRandom laser gain media is synthesized with different types of dye at the same concentration (1×10-3 M) as an active material and silicon dioxide NPs (silica SiO2) as scatter centers through the Sol-Gel technique. The prepared samples are tested with UV–Vis spectroscopy, Fluorescence Spectroscopy, Field Emission Scanning Electron Microscopy (FESEM), and Energy Dispersive X-ray Diffraction (EDX). The end result demonstrates that doped dyes with silica nanoparticles at a concentration of 0.0016 mol/ml have lower absorbance and higher fluorescence spectra than pure dyes. FESEM scans revealed that the morphology of nanocrystalline silica is clusters of nano-sized spherical particles in the range (25-67) nm. It is con
... Show MoreBN RASHİD, 2023
The main objective of this study is to experimentally investigate the effect of the CMC polymeric drag reducer on the pressure drop occurred along the annulus of the wellbore in drilling operation and investigate the optimum polymer concentration that give the minimum pressure drop. A flow loop was designed for this purpose consist from 14 m long with transparent test section and differential pressure transmitter that allows to sense and measure the pressure losses along the test section. The results from the experimental work show that increasing in polymer concentration help to reduce the pressure drop in annulus and the optimum polymer concentration with the maximum drag reducing is 0.8 kg/m3. Also increasing in flow rate a
... Show MoreText Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t
... Show MoreThe purpose of the research is to present a proposed accounting system model for converting and aggregating accounting information within the framework of the differentiated accounting systems, and the research methodology consists of: The research problem is the existence of differentiated and dispersed accounting systems that operate within governmental economic units and at the same time seek to achieve a unified vision and goals for the organization, and the central research hypothesis is the possibility of conducting the process of conversion accounting information from the government accounting system to the unified accounting system, and then aggregate those systems. The research was conducted at the College of Administrat
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