North American Academic Research

NAAR is an international, open access journal, published weekly online by TWASP.
Online ISSN: 1945-9098
Impact Factor : 3.75 (2023) 
5-Year Impact Factor: 4.6 (2023)
Acceptance rate: 42% 
Submission to first decision: 2 days

 

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May 2024 Total article: 13


  Volume: 7 Issue: 5
Article: Enhancing Fused Magnesia Smelting Process Demand Forecasting Through the Integration of System Identification and Advanced Deep Learning Techniques
Abdullah Al Mahamud, Shenwei, Shekh Minhaz Uddin, Tunazzina Tafannum
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) , 112-126. May 2024. doi: https://doi.org/10.5281/zenodo.11525206
Abstract: Accurate demand forecasting is essential for industrial production optimization, particularly in the fused magnesia smelting process. Current forecasting models can be complex, requiring rigorous system identification and lack the flexibility to adapt to various scenarios. This paper proposes a novel approach to demand forecasting using Bidirectional Long Short-Term Memory (BiLSTM) networks, a type of deep learning model, which simplifies the modeling process while retaining robust predictive capabilities. We constructed and trained a BiLSTM model using time series data from the fused magnesia smelting process. We implemented an efficient data preprocessing approach to convert time series data into a supervised learning format. The model was trained on multiple features over 20 epochs, with a configuration that balanced training speed and gradient estimate noise. Our results demonstrate the effectiveness of our approach. With an R-Squared value of 0.930745, our model could explain approximately 93% of the variance in our dependent variable, reflecting high predictive accuracy. Compared to existing research, which employs a combination of system identification and deep learning, our model simplifies the forecasting process and maintains comparable performance levels. However, the model assumes a stable market environment and might not capture non-linear relationships within different datasets effectively. Future research could explore the integration of our BiLSTM model with other forecasting methodologies or deep learning architectures, and investigate ways to enhance the model's robustness to abrupt market fluctuations. This research opens up new possibilities for flexible, accurate, and efficient demand forecasting in the fused magnesia smelting process.

Cite this article as: Abdullah Al Mahamud, Shenwei, Shekh Minhaz Uddin, Tunazzina Tafannum;  Enhancing Fused Magnesia Smelting Process Demand Forecasting Through the Integration of System Identification and Advanced Deep Learning Techniques;  North American Academic Research, 7(5) , 112-126. May 2024. doi: https://doi.org/10.5281/zenodo.11525206

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  Volume: 7 Issue: 5
Article: Investigating Privacy Security Risks for Elderly Individuals in Telemedicine: A Survey-Based Analysis
Ji Jiangming, Akwanwi Lourine Azanwi
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5), 214-224. doi:https://doi.org/10.5281/zenodo.12734979
Abstract: Since the onset of the COVID-19 pandemic, healthcare systems have undergone significant transformations to enhance accessibility, improve health outcomes, and reduce costs. Among these changes, telemedicine has emerged as a popular avenue for delivering medical services, allowing patients to receive care remotely. How- ever, the adoption of telemedicine among older individuals, who often require specialized medical attention due to age-related health issues, has been slow. This reluctance to embrace telemedicine exacerbates healthcare disparities, particularly among the elderly population. This project aims to investigate privacy and security threats faced by elderly individuals in the context of telemedicine. Specifically, the study seeks to analyze data collected from a survey of 500 individuals aged 60 and above to identify prevalent privacy concerns among the elderly in Cameroon. A survey-based approach will be employed to gather insights into the privacy and security concerns of older individuals regarding telemedicine. The survey will be designed to capture demographic information, assess perceptions of privacy risks associated with telemedicine. Logistic regression analysis will be conducted to explore associations between demographic factors and privacy concerns. The study findings will provide an understanding of the privacy and security challenges faced by elderly individuals in telemedicine. Logistic regression analysis will reveal demographic factors influencing privacy concerns among older adults. This research contributes to improving privacy and security measures in telemedicine for elderly individuals by identifying existing privacy and security concerns and bringing to light where to better improve it. By addressing these challenges, healthcare providers and policymakers can promote the equitable access and utilization of telemedical services among the elderly, thereby enhancing overall healthcare delivery and outcomes.

Cite this article as: Ji Jiangming, Akwanwi Lourine Azanwi;  Investigating Privacy Security Risks for Elderly Individuals in Telemedicine: A Survey-Based Analysis;  North American Academic Research, 7(5), 214-224. doi:https://doi.org/10.5281/zenodo.12734979

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  Volume: 7 Issue: 5
Article: Formulation and Synthesis of Thiazole Pyrimidine-Derived Compounds as Turn-On Fluorescent Probes for Selective Metal Ion Detection
Anum Alia
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 127-143 May 2024, https://doi.org/10.5281/zenodo.11536085
Abstract: The development of sensitive and specific chemosensors for detecting heavy metal ions, particularly mercury (Hg2+), is crucial due to the harmful effects of these ions on human health and the environment. In this study, we synthesized ethyl 8-(benzyloxy)-4-(2-hydroxy-3-methylphenyl)-2-methyl-4H-benzo[4,5]thiazolo[3,2-a]pyrimidine-3-carboxylate, a fused heterocyclic compound, through a multi-step synthetic route starting from readily available starting materials. Each intermediate compound was characterized using various analytical techniques including thin layer chromatography (TLC), Fourier-transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance (1H NMR), and carbon-13 nuclear magnetic resonance (13C NMR). The final product was evaluated for its potential application as a chemosensor for heavy metal ions, particularly mercury (Hg+2). UV-Vis absorption and photoluminescence spectroscopy were employed to investigate the sensing capabilities of the synthesized compound. The results demonstrate the successful synthesis of the target compound and its promising potential as a fluorescent probe for detecting mercury ions. The synthesis of ethyl 8-(benzyloxy)-4-(2-hydroxy-3-methylphenyl)-2-methyl-4H-benzo[4,5] thiazolo[3,2-a]pyrimidine-3-carboxylate represents a significant advancement in the field of chemosensors for heavy metal ion detection. By utilizing a multi-step synthetic approach, we were able to access a novel heterocyclic compound with potential applications in environmental monitoring and biomedical diagnostics. The characterization of intermediate compounds using TLC, FT-IR, 1H NMR, and 13C NMR provided valuable insights into the reaction pathways and structural features of the synthesized molecules. Furthermore, the evaluation of the final product as a chemosensor for mercury ions highlights its potential utility in real-world applications. The observed changes in UV-Vis absorption and photoluminescence spectra upon interaction with mercury ions underscore the compound's sensitivity and selectivity towards the target analyte. These findings lay the groundwork for further optimization and development of the synthesized compound as a fluorescent probe for mercury detection. Overall, this study contributes to the ongoing efforts in designing and synthesizing innovative chemosensors for heavy metal ion detection. The successful synthesis and characterization of ethyl 8-(benzyloxy)-4-(2-hydroxy-3-methylphenyl)-2-methyl-4H-benzo[4,5]thiazolo[3,2-a]pyrimidine-3-carboxylate pave the way for future research aimed at addressing environmental and health concerns associated with heavy metal contamination.

Cite this article as: Anum Alia;  Formulation and Synthesis of Thiazole Pyrimidine-Derived Compounds as Turn-On Fluorescent Probes for Selective Metal Ion Detection;  North American Academic Research, 7(5) 127-143 May 2024, https://doi.org/10.5281/zenodo.11536085

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  Volume: 7 Issue: 5
Article: Light-Weighted Humanoid Robotic Arm Design and Simulation
RAFAH KHAN, SYED HASEEB Ul HASSAN
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 144-151 May 2024, https://doi.org/10.5281/zenodo.11552084
Abstract: In this paper, an 8-DoF (with end effector) manipulator is designed and simulated. The 3D model of the humanoid robotic arm is designed in Solidworks (each part is designed separately), and simulation of the manipula-tor is performed in V-REP software; every part is exported as an STL (stereolithography)file and then imported to simulation software. In the simulation of the robotic manipulator, an inverse kinematic model is developed by using Damped Least Squares (DLS) for calculation. The D-H parameter is used to determine the position and orientation of joints. The experiments have been carried out to show the flexibility, humanoid and smooth movement of robotic manipulator. The robotic manipulator is tested by placing a cuboid on a cuboid in which the stability of the robot is revealed; the pick and place experiment demonstrates flexible movement; the catch the box experiment illustrates the quick response of the robot, which shows the flexible, smooth and humanoid movement of a robotic arm.

Cite this article as: RAFAH KHAN, SYED HASEEB Ul HASSAN;  Light-Weighted Humanoid Robotic Arm Design and Simulation;  North American Academic Research, 7(5) 144-151 May 2024, https://doi.org/10.5281/zenodo.11552084

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  Volume: 7 Issue: 5
Article: Functions of Moringa Leaves for Health Reviewed From Social and Community Aspects
Junardi Harahap, Rita Destiwati
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 104-111 May 2024, https://doi.org/10.5281/zenodo.11486961
Abstract: Moringa leaves have so many benefits and are a medicinal plant that has benefits from various aspects and also various uses that are used by the community. The question in this article is: How do moringa leaves function in terms of health and social aspects? The method used is a qualitative method using a literature study. The results of the study found that moringa leaves have such great health benefits that it is proven that many diseases can be cured by consuming moringa leaves, and it also turns out that moringa leaves can also provide prevention from disease. Apart from that, moringa leaves have benefits in terms of public health aspects, namely social aspects, and also ex-isting community aspects because moringa leaves are part of society and have been integrated into society. Health aspects, social aspects, and community aspects are important for moringa leaves and are an important part of the function and benefits of moringa leaves. What is inside moringa leaves has ethnic and regional philosophy and mean-ing, which is called social and cultural meaning. Moringa leaves are also related to the development of good products for the development of moringa leaves as a food source, which is related to the good nutritional aspects of moringa leaves. And one thing that is also important is the aspect of preserving moringa leaves by developing the use of moringa leaves.

Cite this article as: Junardi Harahap, Rita Destiwati;  Functions of Moringa Leaves for Health Reviewed From Social and Community Aspects;  North American Academic Research, 7(5) 104-111 May 2024, https://doi.org/10.5281/zenodo.11486961

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  Volume: 7 Issue: 5
Article: MSCS-Unet A Melanoma Segmentation Network Based on Multi-Scale Feature Fusion
Zhengang Ji
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 89-97 May 2024, https://doi.org/10.5281/zenodo.11379853
Abstract: The most deadly skin disease is melanoma. The disease worsens quickly and is incurable in its advanced stages, so it should be detected and treated early. The main clinical diagnostic basis for the development of this dis-ease is changes in the melanoma focus area. However, my country's current per capita medical resources are tight, resulting in dermatologists' work pressure being very high, and patients' health also facing some challenges. The use of deep learning-based technology for auxiliary diagnosis and treatment can alleviate this contradiction to a certain extent. In the problem of melanoma segmentation, U-Net network and its many variants based on U-shaped structure are now the mainstream solutions. The U-shaped structure can be divided into three major modules: encoder, decoder, and connection part. For the problem of melanoma segmentation, some special requirements are put forward for these three modules: (1) Since the size of the melanoma lesion area is different, First, there are many cases of lesion occlusion in the data set, so the segmentation model is required to adapt to the variability of lesions in the encoder stage, capture the local features of different areas, and distinguish the lesions from the background to improve the accuracy of segmentation (2) Due to clinical Due to the particularity of the application, it is more necessary to reduce the information loss caused by upsampling in the decoder stage (3) In order to better integrate the lower levels con-taining more local and detailed information and the higher levels in the decoder containing more For global and semantic information, the connection part should not be limited to the encoder and decoder of the same layer. Based on the above reasons, this paper designs the melanoma segmentation model MSCS-Unet based on the principle of increasing information fusion and reducing information loss, using a variety of feature fusion technologies, multi-scale feature extraction technologies, and attention mechanisms. On the ISIC2016 and ISIC2017 data sets, the accuracy of MSCS-Unet is 2.01% and 1.55% ahead of U-Net. The model has achieved an excellent balance between lightweight and efficient and accurate segmentation, and can assist experienced medical personnel. Reduce the burden of identi-fying disease areas. And using U-Net as Baseline, ablation experiments were conducted on the ISIC2016 and ISIC2017 data sets for the three proposed modules. Using the modules proposed in this article alone, the segmentation results are better than Baseline, proving the effectiveness of the proposed method.

Cite this article as: Zhengang Ji;  MSCS-Unet A Melanoma Segmentation Network Based on Multi-Scale Feature Fusion;  North American Academic Research, 7(5) 89-97 May 2024, https://doi.org/10.5281/zenodo.11379853

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  Volume: 7 Issue: 5
Article: Mechanical Vibration and Control Dynamic System Analysis
Md Rakibul Islam, Fahad Al Arman
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 61-66 May 2024, https://doi.org/10.5281/zenodo.11286963
Abstract: Mechanical Vibrations and Control: Dynamic System Analysis presents a comprehensive exploration of mechanical vibrations and their control within dynamic systems. The study delves into the principles, analysis techniques, and control strategies that govern mechanical vibrations in engineering systems. Through a combination of theoretical foundations and practical applications, this research aims to enhance our understanding of vibration phenomena and equip engineers with tools to effectively manage and control vibrations in various mechanical systems. The study addresses both free and forced vibrations, resonance phenomena, damping mechanisms, and control methods, providing a holistic perspective on dynamic system behavior and control strategies. Keywords: Mechanical vibrations, dynamic system analysis, control strategies, free vibrations, forced vibrations, resonance, damping mechanisms, control methods, engineering systems.

Cite this article as: Md Rakibul Islam, Fahad Al Arman;  Mechanical Vibration and Control Dynamic System Analysis;  North American Academic Research, 7(5) 61-66 May 2024, https://doi.org/10.5281/zenodo.11286963

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  Volume: 7 Issue: 5
Article: Comparison of Postoperative Analgesic Efficacy and Side Effects of Morphine with Fentanyl Added to Intrathecal Bupivacaine in Cesarean Section
Ajay Kumar Pajiyar, Amit kumarKarna, Sandeep Sharma, Naveen Sah, Brijmohan Kumar Rajak, RajKishor Pandit
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 67-72 May 2024, https://doi.org/10.5281/zenodo.11287275
Abstract: Objective: Spinal anesthesia is a commonly used practice during cesarean sections due to its simplicity and ease of administration. Supplementing opioid drugs as adjuncts to spinal anesthesia can enhance the quality of sensory blockade and lead to improved postoperative analgesia. Morphine and fentanyl are commonly used opioids for this purpose. The objective of this study is to compare the postoperative analgesic efficacy and adverse effects of morphine and fentanyl when administered as supplements to intrathecal bupivacaine in cesarean section. Methods:This is a prospective, randomized, single-blinded study. Sixty parturients were selected and randomly di-vided into two groups: GroupM and GroupF, with 30 parturients in each group. GroupM received 1.8ml of 0.5% hy-perbaric bupivacaine with 0.1mg of preservative-free morphine (diluted in 0.4ml of normal saline), while GroupF re-ceived 1.8ml of 0.5% hyperbaric bupivacaine with 20μg of fentanyl. Both groups received a total of 2.2ml of local an-esthetic solution for each patient. In each group, the patients received 1gm of intravenous paracetamol infusion every 6 hours. The time from the induction of spinal anesthesia to the first dose of rescue analgesia, as well as the total con-sumption of rescue analgesia (i.e., morphine) within 24 hours, were recorded. Opioid-related side effects were also recorded postoperatively. Result:A total of 60 patients were selected for the study, with 30 patients in each group. The demographic data indi-cates no significant differences between the two groups. The duration from induction to the administration of the first rescue analgesia dose was significantly longer in group M (252.23±23.46 minutes) compared to group F (176.16±4.74 minutes) (p<0.0001). Moreover, the total consumption of rescue analgesia (morphine) over a 24-hour period was sig-nificantly lower in group M (7.6±0.77 mg) compared to group F (9.44±1.15 mg) (p<0.001). Additionally, the incidence of nausea/vomiting that required treatment was significantly higher in group M compared to group F (p<0.008). Conclusion:The inclusion of intrathecal morphine in combination with hyperbaric bupivacaine results in an extended duration of analgesia post-cesarean section, when compared to fentanyl. Additionally, the morphine group requires less rescue analgesia (specifically, morphine) in comparison to the fentanyl group

Cite this article as: Ajay Kumar Pajiyar, Amit kumarKarna, Sandeep Sharma, Naveen Sah, Brijmohan Kumar Rajak, RajKishor Pandit;  Comparison of Postoperative Analgesic Efficacy and Side Effects of Morphine with Fentanyl Added to Intrathecal Bupivacaine in Cesarean Section;  North American Academic Research, 7(5) 67-72 May 2024, https://doi.org/10.5281/zenodo.11287275

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  Volume: 7 Issue: 5
Article: Principles of Emotional Management in Theravada Jataka Stories
Rev Kadihingala Hemasiri Thero
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 73-86 May 2024, https://doi.org/10.5281/zenodo.11311739
Abstract: The purpose of the study is that developing Buddhist view on psychological conceptual background, help understanding the application of Buddhist literature and introducing an enhancement of emotional in-telligence. Selected 50 tales of Theravada Buddhist Jataka collection from “The book of five hundred and fifty Jataka Stories”, and they were analysed through emotional management principles in the book ‘Practicable guide to manage Emo-tions’ written by Kumarasena A.K. This study analyzed each of stories according to the book’s principles. And finally the conclusion of research hypothesis is done based on the relationship between variables. The result provides the significant correlation between Jataka stories and emotional managing techniques in Kumarasena’s book. The study suggests that fol-lowing Jathaka stories as educational tool is effective method to enhance emotional abilities in people. Further researches are essential on this field to investigate psychological support of Jataka literature and Bodhisattva concept for the well-being in current communities. This research is limited to discuss only emotional function in 50 stories and further researches are needed to identify other psychological functions in all Jataka stories of Theravada Buddhist literature related to Bodhisattva concept.

Cite this article as: Rev Kadihingala Hemasiri Thero;  Principles of Emotional Management in Theravada Jataka Stories;  North American Academic Research, 7(5) 73-86 May 2024, https://doi.org/10.5281/zenodo.11311739

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  Volume: 7 Issue: 5
Article: A Study on The Cross Cultural Adaptability of International Students in China
Mohammadi Hafizullah, Hou Tao, Liu Rong
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 39-45 May 2024, https://doi.org/10.5281/zenodo.11284986
Abstract: In recent years, with the improvement of China's comprehensive national strength and the promotion of the "the Belt and Road" initiative, the number of overseas students in China has been increasing. The cultural differ-ences between different countries and regions lead to cultural conflicts for international students who come to China. This article analyzes the cultural adaptation barriers faced by international students from Chinese Universities in China in terms of communication, academic performance, thinking concepts, and social culture in a cross-cultural context, and proposes countermeasures from three levels: government, school, and individual. It emphasizes the importance of strengthening the international dissemination of Chinese Universities culture, establishing a reasona-ble education management system for international students, external support, and the knowledge reserves of inter-national students themselves. Through joint efforts from multiple aspects, international students in China can quickly become familiar with, accept, and internalize Chinese culture, enhance their cultural identity, and achieve cross-cultural adaptation.

Cite this article as: Mohammadi Hafizullah, Hou Tao, Liu Rong;  A Study on The Cross Cultural Adaptability of International Students in China;  North American Academic Research, 7(5) 39-45 May 2024, https://doi.org/10.5281/zenodo.11284986

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  Volume: 7 Issue: 5
Article: Bangladesh's Journey Towards Climate Resilience: A Focus on Sustainable Development Goal 13
Muhammad Abeed
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 7-16 May 2024, https://doi.org/10.5281/zenodo.11221061
Abstract: Climate change is one of the most severe challenges in the 21st century. Bangladesh is one of the countries most adversely impacted by climate change. Every sector of its society is directly or indirectly influenced, including agriculture, public health, education, and the economy. It has brought serious consequences for its people due to the hostile impacts of climate change, such as the excessive rise of temperature, prolonged floods and cyclones, which extremely hinder the country's development process. Thus, climate change has become an essential issue in Bangladesh, and it plays a significant role in determining its politics, security, and foreign relations. In international forums, the government of Bangladesh always raises its voice on climate change issues because it seeks common platforms and agreements to combat the most formidable challenge in human history. Therefore, the Sustainable Development Goal (SDG) 13, dedicated to climate action for combating global impacts of climate change, can be an excellent pathway for Bangladesh in gaining resilience towards climate change impacts. This article mainly analyzes the progress and challenges that the Bangladesh government has faced during the half-time frame of the implementation of SDG 13 in Bangladesh.

Cite this article as: Muhammad Abeed;  Bangladesh's Journey Towards Climate Resilience: A Focus on Sustainable Development Goal 13;  North American Academic Research, 7(5) 7-16 May 2024, https://doi.org/10.5281/zenodo.11221061

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  Volume: 7 Issue: 5
Article: Research on the Impact of Digital Inclusive Finance on Green Technology Innovation
Othman Anas Mohammed Abdo
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 31-38 May 2024, https://doi.org/10.5281/zenodo.11284044
Abstract: Green innovation is essential for supporting economic transitions, restructuring the economy, and fostering sustainable, consistent growth. The adoption of growth methods driven by green innovation is primarily reliant on the technical developments produced by organisations. Green inclusive finance, a combination of conventional fi-nance and digital technology, is crucial for the progress of technological innovation. This article examines the field of green inclusive finance and the invention of green technology in enterprises. At first, a thorough analysis was conducted on three types of literature: green inclusive finance, green technology innovation, and the relationship between them. This article gives precise definitions for important topics such as green inclusive finance, green tech-nological innovation, and financing restrictions by referring to relevant literature. Moreover, unlike other studies, this study considers the notion of financing restrictions when analysing the impact of green inclusive finance on business innovation. Additionally, it examines the role of finance limitations as an intermediary factor in this associ-ation.

Cite this article as: Othman Anas Mohammed Abdo;  Research on the Impact of Digital Inclusive Finance on Green Technology Innovation;  North American Academic Research, 7(5) 31-38 May 2024, https://doi.org/10.5281/zenodo.11284044

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  Volume: 7 Issue: 5
Article: Machine Learning Based on Neural Network Model for User Behavior Prediction in Online Advertising
Blajam Abdullah Omar Abdulrahman, Zhong Long
Vol 7, Issue 5; May 2024
North American Academic Research, 7(5) 25-30 May 2024, https://doi.org/10.5281/zenodo.11280842
Abstract: This paper compares and analyzes the DA-FM and Fi-HGNN models using the publicly available datasets Criteo and Avazu. The experimental results demonstrate that the DA-FM model and Fi-HGNN model suggested in this thesis outperform similar models in the datasets, as evidenced by better AUC values. Consequently, the CTR prediction results are more precise. Simultaneously, the impact of each module is validated by ablation experiments, demonstrating that the significance of directing attention towards characteristics in two distinct manners is advanta-geous for enhancing the predictive capability of the model. Furthermore, empirical studies have demonstrated that employing heterogeneous graph neural networks enhances the model's capacity to represent and interact with fea-tures, thereby leading to improved prediction accuracy.

Cite this article as: Blajam Abdullah Omar Abdulrahman, Zhong Long;  Machine Learning Based on Neural Network Model for User Behavior Prediction in Online Advertising;  North American Academic Research, 7(5) 25-30 May 2024, https://doi.org/10.5281/zenodo.11280842

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