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Comparative Study of Anemia Classification Algorithms for International and Newly CBC Datasets
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Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative study of several classification algorithms by testing 12 different classifiers using two international datasets to provide an accurate indicator of their efficiency and the future possibility of combining efficient algorithms to achieve better results. Finally, building several CBC datasets for the first time in Iraq helps to detect blood diseases from different hospitals. The outcome of the analysis step is used to help researchers to select the best system structure according to the characteristics of each dataset for more organized and thorough results. Also, according to the test results, four algorithms achieved the best accuracy (Logitboost, Random Forest, XGBoost, Multilayer Perceptron). Then use the Logitboost algorithm that achieved the best accuracy to classify these new datasets. In addition, as future directions, this paper helps to investigate the possibility of combining the algorithms to utilize benefits and overcome their disadvantages.

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Publication Date
Tue Jun 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Comparison of the RLS and LMS Algorithms to Remove Power Line Interference Noise from ECG Signal
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    Biomedical signal such as ECG is extremely important in the diagnosis of patients and is commonly recorded with a noise. Many different kinds of noise exist in biomedical environment such as Power Line Interference Noise (PLIN). Adaptive filtering is selected to contend with these defects, the adaptive filters can adjust the filter coefficient with the given filter order. The objectives of this paper are: first an application of the Least Mean Square (LMS) algorithm, Second is an application of the Recursive Least Square (RLS) algorithm to remove the PLIN. The LMS and RLS algorithms of the adaptive filter were proposed to adapt the filter order and the filter coefficients simultaneously, the performance of existing LMS

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Publication Date
Sun Jun 30 2024
Journal Name
Journal Of Sustainable Studies
The Scope of Resorting to Amicus Curiae at the Regional and International Levels
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The amicus curiae is one of the judicial procedures adopted in many judicial and legal systems around the world, under which a person who is not a party to the case, and without having a personal and direct interest in it, intervenes to draw the court’s attention to many factual and legal aspects

Publication Date
Mon May 27 2024
Journal Name
Pakistan Journal Of Criminology
The Liability of Maritime Carrier under the Iraqi Transport Law and International Conventions
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Everywhere carriers incur a measure of liability for the safety of the goods. Carriers are liable for any damage or for the loss of the goods that are in their possession as carriers unless they prove that the damage or loss is attributable to certain excepted causes. Damaged and lost items can unfortunately be a common problem when shipping freight. Legal responsibilities arise due to loss or damage during transit while cargo is in their care. This study intends to investigate the nature of the liability of the maritime carrier when this liability is realized, and the extent to which it can be paid or disposed of given the risks realized from the transportation process, which may result in damage or loss of the goods, and the damag

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Publication Date
Mon May 18 2026
Journal Name
Journal Of Baghdad College Of Dentistry
A Comparative Study of Clinicopathological and Immunohistochemical Expression of CD1a, RANK and RANKL in Langerhans Cell Histiocytosis of Jaw and Skull Lesions
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Background: Langerhans' cell histiocytosis (LCH) is a group of conditions affecting the reticuloendothelial system. It includes Letterer-Siwe disease, Hand-Schuller-Christian disease and eosinophilic granuloma and most often presents in childhood. Materials and methods: Twenty-five cases of LCH were diagnosed histologically and confirmed by CD1a antibody and assessed immunohistochemically using anti-RANKL and anti-RANK antibodies to evaluate osteoclastogenic mechanism. Results: Regarding jaw cases, there was a significant correlation between CD1a and RANK (P=0.016). While in the skull, highly significant correlation existed between RANK and RANKL (p=0.001). Among the sites, there was no statistically significant difference found for each

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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Tue Feb 27 2024
Journal Name
Tem Journal
Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
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Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

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Publication Date
Sun Feb 18 2024
Journal Name
Fitness, Performance And Health Journal
A Comparative Study of Some Types of Muscular Strength Among Middle-Distance Runner Athletes
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The research aims to conduct a comparative study between the events (800) m and (1500) m track in the types of muscular strength and to identify the differences between them among Iraqi sports club players. The sample represented the players participating in the Iraqi Athletics Championship for the period between (02/11/2023) and (04 /11/2023), and their number was (16) players (8) for each event, as the selection was made intentionally.  The researchers used the descriptive approach to achieve the goal of the research and used the statistical package (SPSS) to process the data statistically. According to the results collected, it was found that there was superiority among the intermediate track players (800) m in explosive power and the s

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Publication Date
Tue Jul 01 2025
Journal Name
Minerva Dental And Oral Science
Evaluation of the microleakage of new bioactive restorative materials: a comparative in-vitro study
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Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Comparative Study between RIPASA Scoring System and ALVARADO Scoring System in Diagnosing Acute Appendicitis in Adults
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Background: Acute appendicitis is regarded as one of the most common inflammation that needs surgical intervention. Different scoring systems have been used for diagnosing of acute appendicitis. ALVARADO score is one of the most widely used score in diagnosing of acute appendicitis, but the accuracy of the latter is insufficiently low in Middle-East patients. Thus a new scoring system called RIPASA score has been designed for diagnosing of acute appendicitis in those patients. The aim of this study is to use RIPASA score and compare its result with ALVARADO score in diagnosing of acute appendicitis.

Subjects and Methods: The study includes 200 patients with symptoms and signs of

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