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109 articles for “neighbor”
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A Nation in Disarray: Communal Conflicts and Socio-political Stability in Nigeria
Abstract: This paper investigated communal conflicts and socio-political stability in Nigeria. The Nigerian state has witnessed a lot of cataclysms arising from misunderstanding or disarticulation of interest between or among communities and this has affected the political stability of the State. Methodologically, the study adopted secondary data which was analyzed through content analysis. The Frustration and Aggression theory was adopted as the framework for analysis. The study observed that land disputes, …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 14, Issue 1, 2024 · pp. 28–35 Read article
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Integrated risk assessment framework for mixed use real estate development: Retail–office configuration
Abstract: Mixed-use real estate development is a multifaceted challenge that offers significant potential benefits, yet developers and urban planners face skepticism and uncertainty. Despite the promise of enhancing property values, promoting secure neighborhoods, stimulating economic vitality, and creating synergies, the associated risks demand a critical examination. This research seeks to address this gap by constructing a comprehensive risk assessment framework for mixed-use real estate projects. The literature review underscores the substantial …
Published in International Journal of Rural and Regional Development · Vol. 2, Issue 1, 2024 · pp. 22–36 Read article
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Optimizing Heart Disease Prediction: Comparative Analysis of Machine Learning Algorithm for Early Detection
Abstract: The expanding realm of data analysis holds considerable importance in healthcare, particularly in the medical sector where forecasting heart disease is considered a complex endeavor. Early prediction of serious health conditions can be the determining factor between survival and fatality, with heart disease being one such critical health issue. Over the past decade, the main reason for death has been heart disease. Heart disorders come in many different forms, and …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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A Supervised Learning Approach for Toxic Comment Detection on Social Media Platforms
Abstract: Nowadays everyone uses social media platforms like X (formerly Twitter), Instagram, Facebook, etc. for various purposes. With the help of this, we share our opinions, ideas, and feelings. Generally, the datasets obtained from the internet are constructive; however, there is a significant proportion of toxic ones. The datasets are filtered to remove noise, and noise is removed in post-processing. The study initiates with the upload and preprocessing of a toxic …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 7–14 Read article
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Context of Different Graph Operations: Fibonacci Product Cordial Labeling of Herschel Graph
Abstract: The function φ: V (G) → {F1, F2,..., Fn}, where Fj is the jth Fibonacci number (j = 1,..., n), is said to be Fibonacci product cordial labeling if the induced function φ*: E (G) → {0, 1} defined by 𝜑∗ (𝑢𝑣) = (𝜑(𝑢)𝜑 (𝑣))(𝑚𝑜𝑑 2) meets the criterion |𝑒𝜑∗(0) – � �𝜑∗(1)| ≤ 1. A graph known as the Fibonacci product cordial graph is one that permits Fibonacci product …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 1, 2024 Read article
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Data Handling Algorithms for the Healthcare System for the Prediction of Diabetes in Health Data Science (HDS): A Review Report
Abstract: In recent years, diabetes has become the biggest disease in different countries around the world. This disease is caused by adulteration in food ingredients, unhealthy food habits, a lack of physical exercise, and changing the lifestyle every time without a routine chart. The main objective of this review paper is to provide a proper understanding of the machine learning algorithm used in the healthcare system to handle diabetic patients' data. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Prediction of Mobile Phone Price Using Machine Learning Classifiers
Abstract: One cannot imagine one's life without mobile phones; in today's digital era, mobile phones have become a necessity for everyone to fulfil their various demands like messaging, communication, entertainment, productivity, research, shopping and many more. In a thriving market of mobile phones where new smartphones are launched every year with new advanced features and various designs, determining the expense of a mobile can be a trouble-some tasks for consumers. In …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 101–108 Read article
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Regulatory Requirements for Pharmaceutical Product Registration in Zambia
Abstract: There is a significant burden of diseases in Zambia and its neighboring countries, such as malaria, HIV/AIDS, and other ailments. These health challenges necessitate a high consumption of pharmaceutical products. Currently, the majority of essential health drugs in Zambia are imported from outside of Africa. This reliance on external sources presents an opportunity for new investments in the local manufacturing of pharmaceutical products. Although Zambia may not be the largest …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 2, 2024 · pp. 33–41 Read article
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A Study of Environmental Pollution in Some Areas of the City of Najaf for Some Heavy Metals
Abstract: Pollution is one of the most important problems that people face at the present time, and the problem of soil pollution is the most serious, due to its relationship to human health and other organisms. Soil sample collection areas in the city of Najaf were chosen based on several factors, including traffic, industrial and urban activities, and population density. Soil samples were taken at a depth level ranging between 0-15 …
Published in Research & Reviews : Journal of Ecology · Vol. 13, Issue 2, 2024 · pp. 14–23 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Advancements in Intrusion Detection: Tackling Imbalanced Network Traffic with Machine Learning and Deep Learning Techniques
Abstract: Malicious cyberattacks can frequently hide enormous amounts of typical data in unbalanced network traffic. It is very stealthy and obfuscating in cyberspace, which makes it challenging for Network Intrusion Detection Systems (NIDS) to guarantee the precision and promptness of detection. This essay investigates. Machine learning and deep learning are utilized for intrusion detection in imbalanced network traffic. It offers a novel method for addressing the problem of class imbalance termed …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 18–24 Read article
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Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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Autism Spectrum Disorder Prediction Using Classification Techniques: A Comparative Analysis
Abstract: Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder marked by difficulties in social interaction, communication, and repetitive behaviors. Identifying and addressing ASD early is essential for enhancing the quality of life for those affected. Data mining techniques have emerged as powerful tools in analyzing large datasets to predict and diagnose ASD, aiding in early identification and intervention. This article presents a comprehensive comparative analysis of classification techniques employed in …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 66–71 Read article
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Flares and Fields: Sun's Impact on Earth
Abstract: This paper delves into the multifaceted motivations driving the study of the Sun, exploring its pivotal role in shaping Earth's climate, influencing space weather dynamics, and serving as a key astronomical entity in our cosmic neighborhood. Investigating the Sun as a physical laboratory, the discussion unfolds the intricate processes of nuclear fusion and magnetic fields, unveiling technological and research pursuits with potential applications in clean energy and space exploration. Examining …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 3, 2024 · pp. 1–12 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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Don’t We Have Anything to Learn From the Past? Perspective of Epidemics
Abstract: History gives us the chance to learn from the past. In this article, a few of history’s biggest outbreaks, epidemics, and pandemics have been chronicled. The difference between these three are: an outbreak is when an illness occurs in an unexpectedly high number of individuals. It may stay in one area or extend more widely. An outbreak lasts up to several days to years. Sometimes, a single case of a …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 21–27 Read article
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Performance Analysis of Machine Learning Algorithms For Disease Prediction
Abstract: In this 21st century, where Digitization makes humans measure, record, analyze and to manipulate the huge amount of data as per the requirement, prediction of the decease based on Machine Learning models will be representing one of the good applications of the efficient data handling. An Automatic Decease Prediction system based on the symptoms would be the great boon for the medical practitioners. The Supervised Machine Learning models, such as …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 9–18 Read article
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Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article