Evaluating the Effectiveness and Challenges of the Solid Waste Management System in Lilongwe City Council, Malawi
Posture and Stress Detection System using Open CV and Media Pipe
City Council Help Desk Support System
DDoS Attacks Detection using Different Decision Tree Algorithms
Comprehensive Study on Blockchain Dynamic Learning Methods
Efficient Agent Based Priority Scheduling and LoadBalancing Using Fuzzy Logic in Grid Computing
A Survey of Various Task Scheduling Algorithms In Cloud Computing
Integrated Atlas Based Localisation Features in Lungs Images
A Computational Intelligence Technique for Effective Medical Diagnosis Using Decision Tree Algorithm
A Viable Solution to Prevent SQL Injection Attack Using SQL Injection
The current state of Solid Waste Management in Lilongwe City underscores the need to integrate contemporary and technological approaches for more efficient waste handling, with the support of digital solutions. Despite the severity of the solid waste issue impacting various sectors, including households, businesses, industries, and agriculture, there has been minimal effort to educate communities and townships on the importance of waste separation prior to collection. Recognizing that certain types of waste can be recycled for specific purposes, such as in agriculture, is essential. There is also a need for increased individual involvement to address solid waste management challenges, aiming to shift public perception and promote sustainable waste management practices. The rapid pace of waste production, driven by industrialization and population growth, is concerning. Unauthorized dumping has led to an unpleasant environment, noxious odors, and significant health risks through contamination of land, air, and water resources. Addressing these challenges requires focusing on technology and innovative solutions to manage solid waste effectively. This approach should enhance coordination and improve waste management from the point of creation and categorization to disposal at the dumping site. Implementing such methods could help reduce public health issues related to waste mishandling in urban areas. A proposed digital waste management solution, such as a cloud-based application, could represent a significant step towards achieving effective waste management practices in the city.
Posture and stress are two critical factors affecting a person's physical and mental well-being. Proper posture and stress management can help avoid a range of health issues. Poor posture may result in chronic discomfort, decreased mobility, and an increased risk of musculoskeletal problems. Similarly, stress can negatively impact physical and mental health, contributing to conditions such as depression, anxiety, and cardiovascular disease. Traditional methods for assessing posture and stress, including physical examinations or self-reporting, can be subjective and time-consuming. Recent advances in machine learning and computer vision techniques have enabled the development of models that automatically detect posture and stress levels from video data. In this study, a Django framework was built that incorporates models to assess posture by calculating angles between tracked distance vectors. Stress levels are evaluated based on facial features and expressions. The use of skeleton data for human posture recognition is a key research area in human-computer interaction. By employing the MSR 3D Action Dataset, 33 key skeletal points on the body are detected, aiding in posture determination. Additionally, analyzing facial features and emotions is essential for estimating stress levels. The approach relies on convolutional neural networks.
The City Council Help Desk Support System is a comprehensive web-based software designed to assist city residents with complaints, queries, and services. This system enhances the efficiency of the City Council and improves the quality of life for citizens by addressing various issues, including fire alerts from specific locations, waste management, community grievances, interference with protected vegetation, and traffic light damage reports. Each query submitted through the portal is stored in a database for future reference. The system's AI-based chatbot provides support by offering relevant information even in the absence of staff. By leveraging digital and internet technologies, this system significantly reduces response times and automates processes across administrative, user, and staff modules. The project utilizes Agile methodology, emphasizing incremental delivery, team collaboration, continual planning, and learning to ensure value delivery at each stage. This paper explores the system's detailed functionalities, its application of Agile principles, and the results of its real-world implementation.
In today's world, the banking sector, government organizations, and various users in the finance and insurance sectors have grown exponentially. In such situations, they become primary targets for attackers. The main focus of these attackers is to disrupt services for legitimate users. Recently, attackers have targeted banks in Ukraine during the Russia- Ukraine war, causing a shortage of money in banks and making it difficult for people to withdraw funds. These types of attacks fall under the category of Distributed Denial of Service (DDoS) attacks. The primary objectives of these DDoS attacks are to gain financial control and damage the reputation of the affected organization or country. The purpose of this paper is to detect DDoS attacks using various Decision Tree Classifiers in Machine Learning algorithms. We utilized the 'caret' package in R, which is well-known for its Classification and Regression Techniques. We split the KDD'99 dataset based on the outcome variable. We employed the 'rpart' method to classify the dataset using CART and C4.5 algorithms. Experimental results indicate that our classification methods achieve a better accuracy rate compared to other decision tree methods.
Blockchain technology has been growing at a substantial growth rate over the last decade. Blockchain, originally developed to support the cryptocurrency ecosystem, has recently been used in various other fields to achieve extraordinary levels of security. Blockchain technology has applications beyond cryptocurrencies, including risk management, healthcare facilities, financial and social services, and more. Blockchain has been used in the healthcare industry for several purposes including secure data logging, transactions, and maintenance using smartcontracts. The healthcare sector integrating blockchain into various aspects of this digital age. Its features such as micro-transactions, decentralized exchanges, consensus mechanisms, and smart contracts allow for securing the privacy of the health data of patients who are key stakeholders in the healthcare domain. The User Interface (UI) of the HealthChain system highlights the development of blockchain peers with background data on blockchain network construction. By digitally linking patients, payers, and providers over an open network, Health Chain is building a data- driven healthcare community. The modular Hyperledger fabric architecture, which promotes secrecy, scalability and security in health informatics, is a major asset of HealthChain which is powered by Blockchain. The smartcontracts guarantees that the right people are authorised and given the rights on its network of permissions. This review's primary goal is to offer an extensive look and assessment of blockchain technology. The intention is to provide readers with a comprehensive understanding of blockchain technology, its present status, and its possible effects on a range of industries, including supply chain management, healthcare, banking, and more.
