Asian Journal of Research in Computer Science

Journal Information
EISSN : 2581-8260
Published by: Sciencedomain International (10.9734)
Total articles ≅ 233

Latest articles in this journal

, Ravi Shukla, Krishna Tiwari
Asian Journal of Research in Computer Science pp 44-52;

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.
Ahmed T. Shawky, Ismail M. Hagag
Asian Journal of Research in Computer Science pp 33-43;

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%).
Yashraj Singh Tomar,
Asian Journal of Research in Computer Science pp 25-32;

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.
, Darpan Anand
Asian Journal of Research in Computer Science pp 14-24;

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.
, , Afroj Jahan Badhon, Yaw Adjei Asante, Amoa-Boateng Patrick
Asian Journal of Research in Computer Science pp 1-13;

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.
Ashikur Rahman Khan, Masudur Rahman, Jayed Us Salehin, Saiful Islam, Fazle Rabbi
Asian Journal of Research in Computer Science pp 57-68;

Data mining techniques are used to extract interesting patterns and discover meaningful knowledge from huge amount of data. There has been increasing in usage of data mining techniques on medical data for determining useful trends and patterns that are used in analysis and decision making. About eighty percent of human deaths occurred in low and middle-income countries due to heart diseases. The healthcare industry generates large amount of heart disease data which are not organized. These data make the prediction process more complicated and voluminous. Data mining provides the techniques for fast and accurate transformation of data into useful information for heart diseases prediction. The main objectives of this research is to predict heart diseases more accurately using Naïve Bayes, J48 Decision Tree, Neural Network, Random Forest classification algorithms and compare the performance of classifiers. The research uses raw dataset for performance analysis and the analysis is based on Weka Tool. This research also shows best technique from them which is Random Forest on the basis of accuracy and execution time.
, Isaac Ampofo Atta Senior, Darpan Anand
Asian Journal of Research in Computer Science pp 40-56;

The Analysis of common conceptual frameworks associated with Performance analysis of OSPFV3 and EIGRP in applications in IPV6 for analysis of articles published in Scopus between 2016 and 2021 by applying the Corresponding method analysis. The number of times an article is downloaded is also being considered as a measurement instrument or method of analysis. The Corresponding analysis method has analysis 117 articles from 2016 to 2021. All the articles are based on performance analysis of OSPFV3 AND IPV6.IPv6 has gained legitimacy and inevitability as a result of the internet's expansion, which has resulted in IPv4 address space exhaustion. An internet next-generation protocol that will replace eventually IPv4 is IPv6. Using Riverbed Modeler Academic Edition, 2state link protocols’ performance for IPv6, IS–IS and OSPFv3 was compared and tested for the greatest commonly utilized applications enterprise for example remote login, database query, file transfer, web surfing, and email. The major characteristics used to assess performance include IPv6 packets dropped, network convergence time, link utilization, throughput, remote login response time, file upload/download response times, http page response times, email, and database query response time,. The primary goal of this dissertation is to compare, simulate, and assess both routing protocols’ performance in order to decide which one is best for routing IPv6 network traffic. Based on the parameters utilized, the protocol that performed better than the others would be suggested for routing network traffic in IPv6. The study was separated into two scenarios to achieve this goal: the IS–IS and OSPFv3 scenario. After the simulation for the IS–IS scenario was completed, the data from both scenarios were compared and examined using the provided parameters to see which protocol worked better. Based on the majority of the simulation parameters employed, the simulation results showed that OSPFv3 was performed as compared toIS–IS.
, Prince O. Asagba
Asian Journal of Research in Computer Science pp 30-39;

Jaundice is the abnormal accumulation of Bilirubin in the blood, constant checking of their content level in the blood of new born children is vital as going for Anti-natal because its effect is dangerous and irreversible. At the moment, the standard method to determining the concentration of bilirubin in neonates is Laboratory Blood Test (TSB) test and this method can be traumatic for babies due to the constant blood extraction. Our goal in this research is to use hybridized machine learning techniques to develop a jaundice detection system using all the possible physiological characteristics or symptoms. The developed jaundice detection system is capable of detecting the presence of jaundice in neonate non-invasively, it also has a 0.07% standard error coefficient and a Percentage Value of 0.001 when the outcome was compared to TSB of all Test and Validation samples.
H. P. Suresha, Krishna Kumar Tiwari
Asian Journal of Research in Computer Science pp 13-29;

Twitter is a well-known social media tool for people to communicate their thoughts and feelings about products or services. In this project, I collect electric vehicles related user tweets from Twitter using Twitter API and analyze public perceptions and feelings regarding electric vehicles. After collecting the data, To begin with, as the first step, I built a pre-processed data model based on natural language processing (NLP) methods to select tweets. In the second step, I use topic modeling, word cloud, and EDA to examine several aspects of electric vehicles. By using Latent Dirichlet allocation, do Topic modeling to infer the various topics of electric vehicles. The topic modeling in this study was compared with LSA and LDA, and I found that LDA provides a better insight into topics, as well as better accuracy than LSA.In the third step, the “Valence Aware Dictionary (VADER)” and “sEntiment Reasoner (SONAR)” are used to analyze sentiment of electric vehicles, and its related tweets are either positive, negative, or neutral. In this project, I collected 45000 tweets from Twitter API, related hashtags, user location, and different topics of electric vehicles. Tesla is the top hashtag Twitter users tweeted while sharing tweets related to electric vehicles. Ekero Sweden is the most common location of users related to electric vehicles tweets. Tesla is the most common word in the tweets related to electric vehicles. Elon-musk is the common bi-gram found in the tweets related to electric vehicles. 47.1% of tweets are positive, 42.4% are neutral, and 10.5% are negative as per VADER Finally, I deploy this project work as a fully functional web app.
J. Sabo, Y. Skwame, T. Y. Kyagya, J. A. Kwanamu
Asian Journal of Research in Computer Science pp 1-12;

In this article, the direct simulation of third order linear problems on single step block method has been proposed. In order to overcoming the setbacks in reduction method, direct method has been proposed using power series to reduce computational burden that occur in the reduction method. Numerical properties for the block method are established and the method developed is consistent, convergent and zero-stable. To validate the accuracy of the block method, certain numerical test problems were considered, the results shown that the accuracy of our method are more accurate over the existing method in literature.
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