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Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis
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Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutilized crossbar regions and supports rapid on-chip training within two clock cycles. This research also leverages plasticity mechanisms such as neurogenesis and homeostatic intrinsic plasticity to strengthen the robustness and performance of the SP. The proposed design is benchmarked for image recognition tasks using Modified National Institute of Standards and Technology (MNIST) and Yale faces datasets, and is evaluated using different metrics including entropy, sparseness, and noise robustness. Detailed power analysis at different stages of the SP operations is performed to demonstrate the suitability for mobile platforms.

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Human Sport And Exercise - 2019 - Spring Conferences Of Sports Science
The use of the electrical stimulation device for the muscles in the limit determines the elbow joint during the lifting of the disabled weightlifting players
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Publication Date
Fri Sep 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Reliability of the multipeg™ transducer in measuring dental implant stability by using a resonance frequency analysis device (Osstell®): An observational clinical study
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Background: Measuring implant stability is an important issue in predicting treatment success. Dental implant stability is usually measured through resonance frequency analysis (RFA). Osstell® RFA devices can be used with transducers (Smartpeg™) that correspond to the implants used as well as with transducers designed for application with Penguin® RFA devices (Multipeg™). Aims: This study aims to assess the reliability of a MultiPeg™ transducer with an Osstell® device in measuring dental implant stability. Materials and Methods: Sixteen healthy participants who required dental implant treatment were enrolled in this study. Implant stability was measured by using an Osstell® device with two transducers, namely, Smartpeg™ and M

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
Cognitive Beliefs and Their Relationship to Self-Organized Learning Strategies at the Preparatory Stage
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The study aims to identify the level of cognitive beliefs, as well as to identify the level of self-organized learning strategies among intermediate school students. The study also aims to identify the differences in the level of self-organized learning strategies among intermediate school students in term of gender, branch (scientific, literary). In order to achieve the research objectives, the researcher designed a scale to measure the cognitive beliefs. As for the scale of self-organized learning strategies, the researcher adopted a scale of (Pintrich et al. 1991), which was translated by (Izzat Abdelhamid, 1999) , For self-organized learning strategies, the sample consisted of (400) students from the research population, whic

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Training Program Based on Connectivism Theory in Developing E-Learning Competencies among Teachers of Islamic Education in Dhofar Governorate
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Abstract

The study aims to build a training program based on the Connectivism Theory to develop e-learning competencies for Islamic education teachers in the Governorate of Dhofar, as well as to identify its effectiveness. The study sample consisted of (30) Islamic education teachers to implement the training program, they were randomly selected. The study used the descriptive approach to determine the electronic competencies and build the training program, and the quasi-experimental approach to determine the effectiveness of the program. The study tools were the cognitive achievement test and the observation card, which were applied before and after. The study found that the effectiveness of the training program

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Publication Date
Sun Sep 14 2025
Journal Name
Journal Mustansiriyah Of Sports Science
The Impact of an Educational Curriculum according to the Five-year Learning Cycle on Some Offensive Skills in Basketball for Female Students
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Modern trends have appeared recently in educational thought that call for the achievement of the outcomes of the educational process. Some of these trends are the development of individual thinking skills, considering the individual differences, and learning basic skills. The five-year learning cycle is one of these models. It is called as five-year learning cycle because it passes through five stages. These five stages are: (operate - discover - clarify - expand – Evaluate), which make the learner as the main axis for activating thinking processes. This can be done by organizing study materials through research, investigation, and identifying concepts by himself, as in learning sports skills that depend on motor performance and teamwork,

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Evaluation of Interleukin-31 Serum Levels in Patients with Chronic Kidney Disease on Hemodialysis with and without Uremic Pruritus
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الخلاصة: الحكة اليوريمية لدى مرضى غسيل الكلى يؤثر على أكثر من 40٪ من المرضى. وربما ترتبط الحكة المستمرة بمستويات عالية من الإنترلوكين 31. الاهداف: النظر إلى مستويات مصل إنترلوكين 31 لدى مرضى غسيل الكلى المصابين بمرض الكلى في المرحلة النهائية، سواء مع أو بدون حكة يوريمية. النتائج: لم يكن مستوى المصل [الوسيط (] لـ IL-31 في المرضى الذين يعانون من الحكة اليوريميةأو بدون حكة في عينة مصل ما قبل غسيل الكلى مختلفًا بشكل م

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
Cervical Pain Related to Position of the Neck during E-Learning
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Background: During the pandemic, Corona virus forced many people, especially students, to spend more time than before on the computer and smartphone to study and communicate. The poor posture of the body may have worse effect on its body parts , most of which is the cervical spine (forward head posture). Objective: To assess the incidence of neck pain and the associated factors among undergraduate medical students related to position during E learning Subjects and Methods: Cross-sectional study was conducted among medical students in three Iraqi universities during 2021. The sample size was 152. Online questionnaire by Google forms sampling method were used to collect the data which was analysed using SPSS 25. Results: The perce

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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
Cervical Pain Related to Position of the Neck during E-Learning
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Background: During the pandemic, Corona virus forced many people, especially students, to spend more time than before on the computer and smartphone to study and communicate. The poor posture of the body may have worse effect on its body parts , most of which is the cervical spine (forward head posture).

Objective: To assess the incidence of neck pain and the associated factors among undergraduate medical students related to position during E learning

Subjects and Methods: Cross-sectional study was conducted among medical students in three Iraqi universities during 2021. The sample size w

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