Asian Journal of Research in Computer Science

In today’s world using data mining and classification is considered to be one of the most important techniques, as today’s world is full of data that is generated by various sources. However, extracting useful knowledge out of this data is the real challenge, and this paper conquers this challenge by using machine learning algorithms to use data for classifiers to draw meaningful results. The aim of this research paper is to design a model to detect diabetes in patients with high accuracy. Therefore, this research paper using five different algorithms for different machine learning classification includes, Decision Tree, Support Vector Machine (SVM), Random Forest, Naive Bayes, and K- Nearest Neighbor (K-NN), the purpose of this approach is to predict diabetes at an early stage. Finally, we have compared the performance of these algorithms, concluding that K-NN algorithm is a better accuracy (81.16%), followed by the Naive Bayes algorithm (76.06%).

The internet protocols are increasingly imposed in recent times, there is a need to propose a study on the performance analysis on OSPFV3 and EIGRP in IPV6 application. IP is currently involved in sensitive areas of internet protocols, remote sensing, telepresence, computer networks and so on. The IP exists in two versions (IPv4 and IPv6), the difference between these two protocols is distinguished in terms of features, operation, and performance. In this study, measuring and evaluation on the performance of the two IPv4 and IPv6 protocols in the networks of communicating companies are proposed for further studies based on the literature gaps identified. The study should be performed by varying the routing protocols RIP, RIPnG, OSPF, OSPFv3, IS-IS and ISIS v6. Further studies should conduct simulation on performance analysis of OSPFV3 and EIGRP in IPV6 applications. The gaps identified after reviewing a number of literature on OSPFV3 and EIGRP with IPV6 network needs to be done since it sought to bridge gaps in literature.

Firewalls are a fundamental element of network security systems with the ability to block network data traffic flows according to predefined rules. They work on the main purpose to prevent the spread of any deleterious event both on the host as well as network side from any intrusion. Conventional firewalls rely on functions specified by a sequence of rules, which often conflict. Also, various forms of tunnels, wireless and dial-up access methods allow individuals to bypass all the security mechanisms provided by the traditional firewall. Thus, in this paper we discuss the uses and classification of both host and network-based firewalls, other firewall approaches to overcome the cons of traditional firewalls, various firewall policies, including some anomalies.

Wireless Sensor Network (WSN) is a rising technology that offers a great assurance towards a variety of revolutionary applications such as military and public. As wireless sensor networks continue to develop, there is a high importance in security mechanisms. As sensor networks works with responsive data and operate in antagonistic environments, it is crucial to address the security issues. The sensing technology united with wireless communication and processing power makes it rewarding. Due to these computing and inherent constraints in resource, sensor network security has special challenges. The low cost and collaborative nature of the wireless networks (WNs) offers significant advantages upon the conventional communication techniques. The wireless communication technology has several kinds of security threats. The spotlight of this paper is towards addressing the security issues and challenges of WSNs. Here the idea is to identify the threats and security mechanism of wireless sensor networks among WSNs companies in Accra. This paper will contribute to the literature of Wireless sensor networks security issues and challenges in society especially in Ghana. It is concluded that wireless sensor networks have security impact and challenges on information security in IT companies in Accra.

There are numerous baby-monitoring devices available in the market that parents use to keep an eye on babies while they are away. The majority of them are reliant on the installation of expensive hardware, which many parents cannot afford. Another issue with these devices is that they detect high-pitched sounds and frequently give false alarms, causing both children and parents to be disturbed. The majority of smartphone applications in the market work on sound wave and only sound an alarm when the infant start crying. In this project, we proposed the design of a mobile application to detect the status of a baby inside a crib/ on a bed. The application will alert parents when their child requires assistance, will be able to determine whether the child is sleeping in a safe or hazardous position, and will keep track of the child's sleeping patterns. It is less reliant on hardware, making it less expensive. Here the only requirement is two paired mobile phones with the application installed instead of expensive hardware (IoT-based devices). The application is utilizing the transfer-learning technique on tensor flow lite Mobilenet classification and SSD_mobilenet_V1_coco object detection models. The accuracy of the model is 97% for the Mobilenet classification model and 98% for the object detection model.