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The Effects of Conductance on Metastable Switches in Memristive Devices Based on Anti-Hebbian and Hebbian (AHaH) Learning Rules
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     In the last few years, the literature conferred a great interest in studying the feasibility of using memristive devices for computing. Memristive devices are important in structure, dynamics, as well as functionalities of artificial neural networks (ANNs) because of their resemblance to biological learning in synapses and neurons regarding switching characteristics of their resistance. Memristive architecture consists of a number of metastable switches (MSSs). Although the literature covered a variety of memristive applications for general purpose computations, the effect of low or high conductance of each MSS was unclear. This paper focuses on finding a potential criterion to calculate the conductance of each MMS rather than the whole conductance as reported in the literature. Anti-Hebbian and Hebbian (AHaH) learning rules are used to mimic the changes in memristance of the memristors. This research will concentrate on the effect of conductance on an individual MSS to simulate the nanotechnology devices of the memristors. A single synapse is presented by a couple of memristors to mimic its resistance switching. The learning circuit of artificial synapses could be used in many applications, such as image processing and neural networks, for pattern classification of synapses, represented by a map of the memeristors. These synapses are essential elements for data processing and information storage in both real and artificial neural systems.

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
A Survey on Arabic Text Classification Using Deep and Machine Learning Algorithms
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    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
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<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
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Publication Date
Thu Sep 19 2024
Journal Name
Baghdad Science Journal
Effects of Ultrasonic Treatment and Hydrogen Donor Addition on the Viscosity of Iraqi Heavy Crude Oil
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The current investigation examines the combined impacts of ultrasonic radiation and hydrogen donors on the viscosity of heavy crude oil. The impact of exposure time, power, duty cycle, and temperature on the viscosity of Iraqi heavy crude oil with 20.32 API was studied. Also, the viscosity of the oil samples, which were mixed with a hydrogen donor (decalin) and subjected to ultrasonic treatment under optimal conditions, was examined to evaluate the combined impact of ultrasonic radiation and hydrogen donor on the viscosity of crude oil. The viscosity experienced a decrease of 52.34% at 2 min of irradiation, 360 W ultrasonic power, 0.8 duty cycle, 35 ⁰C, and 8vol% decalin. To validate the outcomes of the experiments, asphaltene content, s

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Publication Date
Sun Oct 01 2023
Journal Name
Journal Of Taibah University Medical Sciences
Histological evaluation of the effects of bone morphogenetic protein 9 and angiopoietin 1 on bone healing
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Publication Date
Sun Jun 23 2024
Journal Name
Asee Annual Conference And Exposition
Undergraduate Research Impact on Students' Retention and Academic Development Based on Their Study Field and the Mentoring Approach
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The impact of undergraduate research experiences on students' academic development and retention in STEM fields is significant. Students' success in STEM fields is based on developing strong research and critical thinking skills that make it essential for students to engage in research activities throughout their academic programs. This work evaluates the effectiveness of undergraduate research experiences with respect to its influence on student retention and academic development. The cases presented are based on years of experience implementing undergraduate research programs in various STEM fields at Colorado State University Pueblo (CSU Pueblo) funded by HSI STEM Grants. The study seeks to establish a correlation between students' reten

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Publication Date
Mon Dec 28 2020
Journal Name
The Iraqi Journal Of Veterinary Medicine
Stereological and Histopathological Effects of Trigonella foenum-graecum Seeds on Rabbits Ovary
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This study aimed to investigate the impacts of the Trigonella foenum-graecum (T. foenum-graecum) seeds on the female gonad. A total of twenty local rabbits were used in this study; were divided into four groups (5 each): first group (G1) was considered as the control group. The second group (G2), third group (G3) and fourth group (G4) were fed daily1.5%, 3%, and 4.5% of T. foenum-graecum seeds respectively for 60 days (twice daily). At the end of the experiment, the animals were euthanized by diethyl ether (C2H52O). Then the abdomen was incised, and the samples of ovaries were collected and fixed by 10% neutral buffered formalin. The histological assessment was done with a paraffin embedding technique and the histological sections w

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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Interactive Effects of Status Judgments and Individualism -Collectivism Orientation on Organizational Identification
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يهدف البحث الحالي الى استكشاف علاقات التفاعل والتاثير بين الاحتكام للمكانة والتوجه للفردية– الجماعية والدمج التنظيمي مستنداً على مزج اختلاف القيم الشخصية مع افكار نظرية الهوية الاجتماعية لبلورة نموذج البحث. وفي ضوء هذا تم صياغة عدد من الفرضيات التي توضح علاقات التفاعل ما بين ابعاد الاحتكام للمكانة والتوجه للفردية– الجماعية للتنبؤ بوجود الدمج التنظيمي. جمعت البيانات باستخدام استمارة الاستبيان ووزع

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