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Results in Journal Asian Journal of Research in Computer Science: 246

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H. P. Suresha, Mutturaj Uppaladinni, Krishna Kumar Tiwari
Asian Journal of Research in Computer Science pp 147-159; https://doi.org/10.9734/ajrcos/2021/v12i430300

Abstract:
In this study several characteristics are taken into account so that the crop price forecast is accurate. Forecasting the price of agriculture commodities based on Volume, diesel price helps the agriculturist and also the agriculture mandi’s in India. We look at onion, tomato, and potato trading in India and present the evaluation of a price forecasting model, and anomaly detection and compared differently Supervised, Unsupervised and Forecasting prediction models. We prefer to use wholesale prices, retail prices, arrival volumes of the agricultural commodities and Diesel prices in India. We also provide an in-depth forecasting analysis of the effect on these retail prices. Our results are encouraging and point towards the likelihood of building pricing models for agricultural commodities and to detect anomalies. These data can then be stored and analyzed. The empirical comparison of the chosen methods on the various data showed that some methods are more suitable than others for this type of problem. In this research, we did a comparative study of Auto ARIMA (Autoregressive Integrated Moving Average), RNN (Recurrent Neural Network), LSTM, VAR (vector autoregressive model), and Random Forest Regression, XGBoost in their ability to predict Retail prices of potatoes, onions and tomatoes.
Richard Essah,
Asian Journal of Research in Computer Science pp 132-146; https://doi.org/10.9734/ajrcos/2021/v12i430299

Abstract:
Cocoa industry of Ghana employs above a million people across Ghana areas of cocoa-growing, and it is the principal source of revenue for above 6 million people. The government of Ghana spends an important amount of money yearly on cocoa procurements in addition to farm inputs. However, the business of cocoa stays to meet many obstacles in testing and procurement, leading to lower annual yields. The study seeks to examine the issues of Ghana's cocoa purchasing process and develop IoT based automatic cocoa quality testing system. The method of the study will be descriptive design with quantitative method to pinpoint the procurement process and quality assurance process of cocoa in Ghana. The quantitative results will be used to develop IoT based automatic cocoa quality testing system to address cocoa testing issue. The study will analyze the impact of the proposed system for procurement process on the cocoa quality testing and procurement process in Ghana.
Yaw Adjei Asante,
Asian Journal of Research in Computer Science pp 111-131; https://doi.org/10.9734/ajrcos/2021/v12i430298

Abstract:
In network designs, the decision made when implementing dynamic routing protocols is very paramount to the speed of the network. To make the best choice of protocol to deploy, several decisions has to be considered. Usually, these decisions are made based on the performance of the routing protocol with respect to some quantitative parameters. The protocol that performs better than other protocols involved in a research is selected for routing purposes. In this research paper, performance comparison of two mixed protocols namely OSPFv3/IS-IS and RIPng/IS-IS in IPv6 network has been made. Their performances have been measured and comparison made by simulation using Riverbed Modeller Academic Edition. The objective of this paper is mainly to determine which of the mixed protocols will be more suitable to route traffic in IPv6 network. The main motivation for this paper is to find out if the difference in the routing algorithms of RIPng and IS-IS will offset and produce a better performance than a combination of two routing protocols of the same routing algorithm (thus OSPFv3 and IS-IS). To achieve this paper’s objective, the simulation was divided into two scenarios. The first scenario was an OSPFv3/IS-IS configured IPv6 network topology. The second scenario is a copy of the first scenario but configured with RIPng/IS-IS. The two scenarios were simulated and the effect of using each of the scenarios to separately route the selected applications was measured and recorded. The performance comparison of the mixed protocols was based on the following quantitative parameters: database query response time, database query traffics received, email upload/download response time, ftp upload/download response time, ftp traffic received, http page response time, remote login response timeandIPv6 traffics dropped. The results obtained from the simulation indicated that RIPng/IS-IS scenario performed better in email download/upload response time, remote login response time, IPv6 traffics dropped and remote login response time while the mixture of OSPFv3/IS-IS performed better in database query response time, database query traffics received, ftp download/upload response time, ftp traffic received and http page response time. Hence OSPFv3/IS-IS is the better option when the choice is between RIPng/IS-IS and OSPFv3/IS-IS for most of the quantitative parameters involved in this paper. This is because the combination of RIPng and IS-IS took a longer time to converge, affecting the speed on the network scenario. The time the RIPng/IS-IS combination took to access most of the application servers is slower than that of OSPFv3/IS-IS network scenario. On the basis of database query and ftp traffics received, the simulation results showed that network configured with OSPFv3/IS-IS performs better than RIPng/IS-IS. This is because the OSPFv3/IS-IS received the highest database and ftp traffics. The mixture of OSPFv3/IS-IS sent and received more application packets because it had very high throughput values which had an effect on the total quantity of application traffics received. Although the OSPFv3/IS-IS network scenario recorded the highest database and ftp traffics, this could not affect its speed to become lower than the RIPng/IS-IS scenario.
, Maxwell Dorgbefu Jnr., William Brown-Acquaye
Asian Journal of Research in Computer Science pp 97-110; https://doi.org/10.9734/ajrcos/2021/v12i430297

Abstract:
The benefits that individuals and organizations derive from the digital era comes with its own challenges. Globally, data has become one of the greatest assets for decision making and operational improvements among businesses, government agencies and even individuals. Data on its own and at its source does not make so much contribution to business processes. Data is transmitted from one location to another towards attainment of its goal as a critical resource in decision making. However, data including sensitive or confidential ones are transmitted via public channels such as the Internet. The data so transmitted via the Internet is vulnerable to interception and unauthorized manipulation. This demands that data in transit is protected from the prying eyes of the malicious internet users. One of such strategies for transmitting data via public channels such as the Internet without attracting attention from intruders is steganography. In this paper, the least significant bit algorithm was used with an audio file for hiding data in transit. The algorithm used in this research proves to be one of the simplest ways of securing data using audio steganography. The method employed the LSB technique by using audio files as the stego object for the final implementation in the Java programming language. The experimental results proved to be one of the best methods of implementing steganography. The accuracy of the stego objects shows high quality, and similarity scores with an improved processing time.
Daniel Etiemble
Asian Journal of Research in Computer Science pp 67-83; https://doi.org/10.9734/ajrcos/2021/v12i430295

Abstract:
For more than 60 years, many ternary or quaternary circuits have been proposed based on similar assumptions. We successively examine four of these assumptions and demonstrate that they are wrong. The fundamental reason for which m-valued combinational circuits are more complicated than the corresponding binary ones is explained. M-valued flash memories are used in USB devices because access times in not critical and a trade-off is possible between access time and chip area. If m-valued circuits are reduced to a very small niche in the binary world with semi-conductor technologies, there is a significant exception: quantum devices and computers are a true breakthrough as qbits are intrinsically multivalued. Successful m-valued circuits need m-valued devices as qbits.
Oyekanmi Ezekiel Olufunminiyi, Oladoja Ilobekemen Perpetual, Omotehinwa Temidayo Oluwatosin
Asian Journal of Research in Computer Science pp 52-66; https://doi.org/10.9734/ajrcos/2021/v12i430294

Abstract:
Cloud is specifically known to have difficulty in managing resource usage during task scheduling, this is an innate from distributed computing and virtualization. The common issue in cloud is load balancing management. This issue is more prominent in virtualization technology and it affects cloud providers in term of resource utilization and cost and to the users in term of Quality of Service (QoS). Efficient procedures are therefore necessary to achieve maximum resource utilization at a minimized cost. This study implemented a load balancing scheme called Improved Resource Aware Scheduling Algorithm (I-RASA) for resource provisioning to cloud users on a pay-as-you-go basis using CloudSim 3.0.3 package tool. I-RASA was compared with recent load balancing algorithms and the result shown in performance evaluation section of this paper is better than Max-min and RASA load balancing techniques. However, it sometimes outperforms or on equal balance with Improved Max-Min load balancing technique when using makespan, flow time, throughput, and resource utilization as the performance metrics.
Solomon Ofori Jnr Gyane, , Isaac Ampofo Atta Senior, Abraham Tetteh
Asian Journal of Research in Computer Science pp 84-96; https://doi.org/10.9734/ajrcos/2021/v12i430296

Abstract:
The automated selection system used by colleges of education affiliated to the University of Cape Coast is a multiuser computerized system which students can access and apply to universities at any place with internet access, and can be admitted, rejected, or included in a waiting list for further assessment. The study sought to investigate the extent to which the computerized selection system at educational colleges affiliated with the Cape Coast University has impacted the efficiency and credibility of the process, by evaluating the step by step stages in admission processes that are handled electronically. The study contribute to literature since there is no studies on the reliability and efficiency of Ghanaian colleges of education affiliated to the universities. The type of research design for the study was descriptive design with a quantitative research method. The total population comprises of all admission officers, quality assurance staff, and Heads of departments at the colleges of education affiliated with the University of Cape Coast. The researchers' sample size for the study was one hundred and ninety-two (192). The questionnaire survey was carried out to collect data for the study. Quantitative analysis was done with the use of Statistical Package for Social Sciences. The results show that electronic sorting and selection of applications is efficient in checking the application forms, testing duplicate files, verifying college requirements, and verifying seat availability. The study revealed that there was a positive and high relationship between the efficiency of electronic sorting and selection of admission applications and the reliability of the computerized system.
, Darpan Anand
Asian Journal of Research in Computer Science pp 31-51; https://doi.org/10.9734/ajrcos/2021/v12i430293

Abstract:
A collection of interconnected devices that deal with communication protocols that are common to share resources provided by nodes of a network over digital interconnections is a computer network. The process of determining the most efficient route from a source to a given target is called routing. Cisco's Enriched Internal Routing Gateway Protocol for IPv6 and the IETF's OSPFv3 (First Version 3 of Open Shortest Path) are two of the most frequently studied IPv6 routing protocols among researchers (EIGRPv6). As a result of the popularity of EIGRPv6 and OSPFv3, it is necessary to undertake a thorough contrast of the two protocols once working inside a minor enterprise network on IPv6. Thus, the study analysed the performance comparison of OSPFV3 and EIGRP with IPv6 networks with regards to convergence time, end-to-end delay, and packet loss. Packet Tracer 6.2.2 was used to compare the performance of routing protocols of different kinds. In the simulation, Cisco routers, switches, and generic computers were employed in the test. In these topologies, standard IPv6 addresses have been used. The findings of the study revealed that EIGRPv6 outperforms OSPFv3. As a result, we advocate using EIGRPv6 as an internal routing protocol in a network of IPv6.
, Endang Lestariningsih, Rara Sriartati Redjeki, Eka Ardhianto
Asian Journal of Research in Computer Science pp 25-30; https://doi.org/10.9734/ajrcos/2021/v12i430292

Abstract:
The rapid technological revolution had an impact on a variety of information security techniques. This will be important because information can be confidential to some entities that communicate with each other. Internet in intelligent technology will be a loophole for cryptanalysts to look for information vulnerabilities. Cryptography is a method of securing data and information which is currently still supported by the development of the method. However, the data and information that are secured will still have vulnerabilities in their delivery. The combination of fuzzy logic techniques with cryptographic techniques has been applied to support the improvement of information security. This study applies a systematic literature review method, to find articles that combine the two fields. The purpose of this study is to see the development of information security techniques with a fuzzy logic approach. As a result, it is found that the development of cryptographic and steganographic techniques that utilize fuzzy logic to help improve information security. In addition, the use of fuzzy logic is also not limited to increasing security. Fuzzy logic also plays a role in selecting the best key and password and issuing random numbers from a Pseudo-Random Number Generator (PRNG).
Fei Liang, Taowen Zhang
Asian Journal of Research in Computer Science pp 12-24; https://doi.org/10.9734/ajrcos/2021/v12i430291

Abstract:
Artificial Neural Network (ANN) is established by imitating the human brain's nerve thinking mode. Because of its strong nonlinear mapping ability, fault tolerance and self-learning ability, it is widely used in many fields such as intelligent driving, signal processing, process control and so on. This article introduces the basic principles, development history and three common neural network types of artificial neural networks, BP neural network, RBF neural network and convolutional neural network, focusing on the research progress of the practical application of neural networks in chemical process optimization.
S. M. Abdullah Al Shuaeb, Shamsul Alam, Mizanur Rahman, Abdul Matin
Asian Journal of Research in Computer Science pp 1-11; https://doi.org/10.9734/ajrcos/2021/v12i430289

Abstract:
Students’ academic achievement plays a significant role in the polytechnic institute. It is an important task for the technical student to achieve good results. It becomes more challenging by virtue of the huge amount of data in the polytechnic student databases. Recently, the lack of monitoring of academic activities and their performance has not been harnessed. This is not a good way to evaluate the academic performance of polytechnic students in Bangladesh at present. The study on existing academic prediction systems is still not enough for the polytechnic institutions. Consequently, we have proposed a novel technique to improve student academic performance. In this study, we have used the deep neural network for predicting students' academic final marks. The main objective of this paper is to improve students' results. This paper also explains how the prediction deep neural network model can be used to recognize the most vital attributes in a student's academic data namely midterm_marks, class_ test, attendance, assignment, and target_ marks. By using the proposed model, we can more effectively improve polytechnic student achievement and success.
, Ravi Shukla, Krishna Tiwari
Asian Journal of Research in Computer Science pp 44-52; https://doi.org/10.9734/ajrcos/2021/v12i330288

Abstract:
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; https://doi.org/10.9734/ajrcos/2021/v12i330287

Abstract:
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; https://doi.org/10.9734/ajrcos/2021/v12i330286

Abstract:
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; https://doi.org/10.9734/ajrcos/2021/v12i330285

Abstract:
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; https://doi.org/10.9734/ajrcos/2021/v12i330282

Abstract:
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; https://doi.org/10.9734/ajrcos/2021/v12i230281

Abstract:
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; https://doi.org/10.9734/ajrcos/2021/v12i230280

Abstract:
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; https://doi.org/10.9734/ajrcos/2021/v12i230279

Abstract:
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; https://doi.org/10.9734/ajrcos/2021/v12i230278

Abstract:
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; https://doi.org/10.9734/ajrcos/2021/v12i230277

Abstract:
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.
Asian Journal of Research in Computer Science pp 37-48; https://doi.org/10.9734/ajrcos/2021/v12i130275

Abstract:
In this 21st Century technology extent of time and worldwide integration, various narrow and medium enterprises exist adopting cloud calculate for their trade operations. Cloud calculate exist an increasing information in visible form Centre technology in accordance with the becoming more intense traffic connected to the internet fashionable the period of the Internet of Things (IoT). These electronics outwit the defect of conventional servers for speed, scalability and effectiveness. However, skilled exist still narrow enterprises that exist undecided of the appropriate of cloud computing time in military operation fashionable trade movement. Thus, this paper is inscribed to survey the views of person who is very involved in education and learning about the benefits of cloud computing rite of a fashionable trade movement that motivate bureaucracy to legally care for business enterprise. The aims of the study include to ascertain the benefits of cloud to small-scale enterprises in India, to determine the challenges facing cloud users and to unravel the strategies that can improve the strategic growth of cloud users in India enterprises. The researcher used a case study design and a qualitative research approach. The place of the study is Chandigarh University of India and Busy Network company in India.
Asian Journal of Research in Computer Science pp 49-63; https://doi.org/10.9734/ajrcos/2021/v12i130276

Abstract:
Most multi-national organizations in Kenya are adopting an entire suite of enterprise resource planning Software and customize them to fit the business processes. Despite the continued review of the enterprise resource planning suite, the realization of a successful enterprise resource planning implementation for multi-national organizations is becoming difficult, owing to user involvement issues. This research, therefore, addressed this by assessing the effect of user involvement on enterprise resource planning implementation for multi-national organizations in Kenya. The study used a descriptive research design, where it obtained a sample size of 70 respondents and selected the respondents from 85 subjects using stratified proportionate sampling. The data for the study was gathered from primary sources using a questionnaire. Data was evaluated using quantitative analysis to provide descriptive statistics accompanied by inferential analysis to estimate the model. Guided by the study findings, it was concluded that; there is a positive and significant relationship between users’ functional requirements activities and enterprise resource planning implementation; users’ presentation requirement activities positively significantly influence enterprise resource planning implementation, users’ quality assurance activities has a significant moderate influence on its enterprise resource planning implementation, and users’ project management activities have a significant moderate influence on enterprise resource planning implementation. The study recommends that these organizations should; develop users’ functional requirements activities policy, review policies on business processes to accommodate different system implementation practices; review current quality assurance activities by consumers to satisfy the planned enterprise resource planning system demand of the provider, and acquire as well as retain the appropriate users’ project management.
Ming-Jong Lin
Asian Journal of Research in Computer Science pp 26-36; https://doi.org/10.9734/ajrcos/2021/v12i130274

Abstract:
The purpose of this article is to explore and improve the effect of Bipolar Junction Transistor amplifier base-emitter on temperature changes. The prelude starts with Shockley's theory and its formula calculation. Research motivation, literature data and book principles cooperate with MATLAB application software skills to develop programs; it is used to calculate the relationship between various component parameters and temperature changes. The artificial calculation steps are too cumbersome and prone to clerical errors. Therefore, the program approach has been developed with report-style calculation results with both text and pictures. The feature of computer program calculation is the ability to compare and analyze the results produced at different temperatures, rapidly and repeatedly. The lack of known Bipolar Junction Transistors is replaced by Field Effect Transistors that are not affected by temperature. If the Bipolar Junction Transistor is used as the basis for the design, temperature changes must be considered to ensure the design quality. The purpose of this article is to introduce that the process of calculation has made the shift from an artificial-based way to a computer-based one.
Christian Adu-Boahene, Solomon Nii Nikoi, Alberta Nsiah-Konadu
Asian Journal of Research in Computer Science pp 7-25; https://doi.org/10.9734/ajrcos/2021/v12i130273

Abstract:
Network intruders are becoming more sophisticated in their approach, resulting in many difficulties in preventing them. They exploit both well-configured systems and vulnerable systems. Aims: To examines the performance of a campus network against attacks on the network systems. Place and Duration of Study: University of Education, Winneba- Kumasi campus. Methodology: Penetration testing was adopted to investigate the vulnerabilities that may occur in a university network. This helps to test for vulnerabilities on the network system that may expose the system to exploits. Results: The test revealed that system-based attacks might be propelled by malignant pariahs on the Internet and noxious insiders straightforwardly associated with inward systems. The perpetrators can exploit vulnerabilities in network foundations and frameworks, for example, servers (web servers, software servers, file and mail servers, etc.), routers, and firewalls. Conclusion: This work presents a way to deal with evaluating the security stance of a college utilizing penetration testing that meddles negligibly with the flow of traffic and activities on the network infrastructure. attack Insurance against network-based attacks is mind-boggling and, in the offer, to relieving one framework normally gives a stage that can be utilized to dispatch more attacks.
Chenxi Zhao, Haoxuan Yu
Asian Journal of Research in Computer Science pp 1-6; https://doi.org/10.9734/ajrcos/2021/v12i130272

Abstract:
According to our previous work, we have found that the ZigBee WSN technology and sensors are actually suitable for the underground monitoring, but there are still many problems. So in this viewpoint paper, we showed our viewpoint that the underground driver-less electric transport vehicles could also play an important role in the underground monitoring, that is, underground electric transport vehicles running in the mine roadway could carry mobile sensors to monitor the environmental conditions in the transport roadway. If it could be realized, it will save the number of sensors installed around the mine so as to reduce costs. If it could be realized, the monitoring of underground mines will become more convenient.
, Dorgbefu Jnr. Maxwell, Kulbo Nora Bakabbey, , Ohemeng Asare Andy, , Boansi Kufuor Oliver,
Asian Journal of Research in Computer Science pp 52-71; https://doi.org/10.9734/ajrcos/2021/v11i430270

Abstract:
The survival of the global economy is rooted in the production of goods, rendering of valuable services, and formulation and implementation of favorable trade policies. These goods and services supported by related policies however, must reach prospective customers unblemished in good time, through planned advertisement strategies. Advertisement over the years has evolved from the traditional one-on-one to technology induced ones such as digital marketing and sales. Technological advancement has diversified advertisement into a multi-faceted and dynamic channel with enormous growth and prospects. In this paper, we made a significant effort to identify actual online data to justify why short video (SV) adoption is essential in e-commerce and digital marketing. A total of 23589 datasets were drawn from three global B2C and C2C websites using the scrappy web crawlers to investigate a resilience model in the relationship between SV advertising adoption, quality signals, customer satisfaction, price fairness, and sales in digital marketing. Whereas shop location is vital in traditional shopping, logistics service quality overrides its influence in online shopping settings.
, Krishna Kumar Tiwari
Asian Journal of Research in Computer Science pp 72-83; https://doi.org/10.9734/ajrcos/2021/v11i430271

Abstract:
Market Basket Analysis (MBA) is a method for determining the association between entities, and it has often been used to study the association between products in a shopping basket. Trained Computer vision models are able to recognize objects in photos so accurately that it can even outperform humans in some instances. This study shows that combining objective detection techniques with market basket analysis can assist Stores/Kirana in organizing the products effectively. With the use of MBA and Object detection, we formulated recommendations for store arrangements along with putting a recommendation engine on top to help shoppers. After deploying this to local Kirana stores, the Kirana store was able to see an increase of 7% in the sale. The recommendation engine performed better than just the domain knowledge of the kirana store.
, Azar Abid Salih, Adel Al-Zebari, Naaman Omar, Karwan Jameel Merceedi, Abdulraheem Jamil Ahmed, Nareen O. M. Salim, Sheren Sadiq Hasan, Shakir Fattah Kak, Ibrahim Mahmood Ibrahim, et al.
Asian Journal of Research in Computer Science pp 35-51; https://doi.org/10.9734/ajrcos/2021/v11i430269

Abstract:
The term "Real-Time Operating System (RTOS)" refers to systems wherein the time component is critical. For example, one or more of a computer's peripheral devices send a signal, and the computer must respond appropriately within a specified period of time. Examples include: the monitoring system in a hospital care unit, the autopilot in the aircraft, and the safety control system in the nuclear reactor. Scheduling is a method that ensures that jobs are performed at certain times. In the real-time systems, accuracy does not only rely on the outcomes of calculation, and also on the time it takes to provide the results. It must be completed within the specified time frame. The scheduling strategy is crucial in any real-time system, which is required to prevent overlapping execution in the system. The paper review classifies several previews works on many characteristics. Also, strategies utilized for scheduling in real time are examined and their features compared.
, Adel Al-Zebari, Naaman Omar, Karwan Jameel Merceedi, Abdulraheem Jamil Ahmed, Nareen O. M. Salim, Sheren Sadiq Hasan, Shakir Fattah Kak, Ibrahim Mahmood Ibrahim, Hajar Maseeh Yasin, et al.
Asian Journal of Research in Computer Science pp 19-34; https://doi.org/10.9734/ajrcos/2021/v11i430268

Abstract:
The use of technology has grown dramatically, and computer systems are now interconnected via various communication mediums. The use of distributed systems (DS) in our daily activities has only gotten better with data distributions. This is due to the fact that distributed systems allow nodes to arrange and share their resources across linked systems or devices, allowing humans to be integrated with geographically spread computer capacity. Due to multiple system failures at multiple failure points, distributed systems may result in a lack of service availability. to avoid multiple system failures at multiple failure points by using fault tolerance (FT) techniques in distributed systems to ensure replication, high redundancy, and high availability of distributed services. In this paper shows ease fault tolerance systems, its requirements, and explain about distributed system. Also, discuss distributed system architecture; furthermore, explain used techniques of fault tolerance, in additional that review some recent literature on fault tolerance in distributed systems and finally, discuss and compare the fault tolerance literature.
, Hajar Maseeh Yasin, Azar Abid Salih, Adel Al-Zebari, Naaman Omar, Karwan Jameel Merceedi, Abdulraheem Jamil Ahmed, Nareen O. M. Salim, Sheren Sadiq Hasan, Shakir Fattah Kak, et al.
Asian Journal of Research in Computer Science pp 1-18; https://doi.org/10.9734/ajrcos/2021/v11i430267

Abstract:
Distributed systems, which may be utilized to do computations, are being developed as a result of the fast growth of sharing resources. Data mining, which has a huge range of real applications, provides significant techniques for extracting meaningful and usable information from massive amounts of data. Traditional data mining methods, on the other hand, suppose that the data is gathered centrally, stored in memory, and is static. Managing massive amounts of data and processing them with limited resources is difficult. Large volumes of data, for instance, are swiftly generated and stored in many locations. This becomes increasingly costly to centralize them at a single location. Furthermore, traditional data mining methods typically have several issues and limitations, such as memory restrictions, limited processing ability, and insufficient hard drive space, among others. To overcome the following issues, distributed data mining's have emerged as a beneficial option in several applications According to several authors, this research provides a study of state-of-the-art distributed data mining methods, such as distributed common item-set mining, distributed frequent sequence mining, technical difficulties with distributed systems, distributed clustering, as well as privacy-protection distributed data mining. Furthermore, each work is evaluated and compared to the others.
Humberto Cuteso Matumueni
Asian Journal of Research in Computer Science pp 35-43; https://doi.org/10.9734/ajrcos/2021/v11i330265

Abstract:
Nowadays, common diseases like malaria, typhoid and cholera become more dangerous problems for people living in this world. The objective is how it can avoid the queue of patients in hospital. In this article, the author has proposed a model of expert systems using the knowledge of physician and other health professionals. The rule based expert system XPerMal useful for patients infected with common diseases and this system will give an answer as similar to a doctor or medical expert and also this system is very useful in rural areas where we have young medical experts or have no medical expert. The reasoning strategy is a key element in many medical tasks. It is well known that developing countries face a shortage of medical expertise in the medical sciences. Patients also find a huge queue in hospitals. Because of this, they are unable to provide good medical services to their inhabitants. The knowledge is acquired from literature review and human experts in the specific field and is used as a basis for analysis, diagnosis and decision-making. Knowledge is represented by an integrated formalism that combines rules and facts.
, Naaman Omar, Adel Al-Zebari, Karwan Jameel Merceedi, Abdulraheem Jamil Ahmed, Nareen O. M. Salim, Sheren Sadiq Hasan, Shakir Fattah Kak, Ibrahim Mahmood Ibrahim, Hajar Maseeh Yasin, et al.
Asian Journal of Research in Computer Science pp 44-60; https://doi.org/10.9734/ajrcos/2021/v11i330266

Abstract:
Mobile malware is malicious software that targets mobile phones or wireless-enabled Personal digital assistants (PDA), by causing the collapse of the system and loss or leakage of confidential information. As wireless phones and PDA networks have become more and more common and have grown in complexity, it has become increasingly difficult to ensure their safety and security against electronic attacks in the form of viruses or other malware. Android is now the world's most popular OS. More and more malware assaults are taking place in Android applications. Many security detection techniques based on Android Apps are now available. Android applications are developing rapidly across the mobile ecosystem, but Android malware is also emerging in an endless stream. Many researchers have studied the problem of Android malware detection and have put forward theories and methods from different perspectives. Existing research suggests that machine learning is an effective and promising way to detect Android malware. Notwithstanding, there exist reviews that have surveyed different issues related to Android malware detection based on machine learning. The open environmental feature of the Android environment has given Android an extensive appeal in recent years. The growing number of mobile devices, they are incorporated in many aspects of our everyday lives. In today’s digital world most of the anti-malware tools are signature based which is ineffective to detect advanced unknown malware viz. Android OS, which is the most prevalent operating system (OS), has enjoyed immense popularity for smart phones over the past few years. Seizing this opportunity, cybercrime will occur in the form of piracy and malware. Traditional detection does not suffice to combat newly created advanced malware. So, there is a need for smart malware detection systems to reduce malicious activities risk. The present paper includes a thorough comparison that summarizes and analyses the various detection techniques.
Elizabeth A. Amusan, Akinbami O. Popoola, Sanni A. O. Ogirima
Asian Journal of Research in Computer Science pp 23-34; https://doi.org/10.9734/ajrcos/2021/v11i330264

Abstract:
This work is aimed at adding an extra layer of security to the login process of an electronic examination system as security has been identified as one of the critical success factors in the management of such exams. It proposes to secure the login process of an e-exam system through authentication and encryption to control access and avoid impersonation. A model of the e-exam system with Quick Response (QR) code generation capability was designed where a student’s matriculation number is accepted as input which is then converted into a two-dimensional bar code using a QR generator. Outputs from the QR code generator are then secured by encryption using MD5 and SHA-224 encryption algorithms. MD5 algorithm produces a 32-bit hash value which is further encrypted using SHA-224 that produces a resulting 56-bit hash value that is then saved in the password column of the user table in the database. This research resulted in a secure and web-based electronic examination authentication system implemented and tested on a client-server architecture. Performance evaluation of the developed system revealed that it is fast and effective, capable of authenticating students in an average of 0.624 seconds when the smartphone flashlight is off, and 0.318 seconds with flashlight turned on and consequently, resistant to brute force attacks. This paper fulfils an identified need to develop an electronic exam system that not only secures the question bank but equally ensures the security of the login process as well as the login details using a combination of two security techniques.
Upasana Mukherjee, Vandana Thakkar, Shawni Dutta, Utsab Mukherjee,
Asian Journal of Research in Computer Science pp 9-22; https://doi.org/10.9734/ajrcos/2021/v11i330263

Abstract:
The growth of regularly generated data from many financial activities has significant implications for every corner of financial modelling. This study has investigated the utilization of these continuous growing data by a means of an automated process. The automated process can be developed by using Machine learning based techniques that analyze the data and gain experience from the underlying data. Different important domains of financial fields such as Credit card fraud detection, bankruptcy detection, loan default prediction, investment prediction, marketing and many more can be modelled by implementing machine learning methods. Among several machine learning based techniques, the use of parametric and non-parametric based methods are approached by this research. Two parametric models namely Logistic Regression, Gaussian Naive Bayes models and two non-parametric methods such as Random Forest, Decision Tree are implemented in this paper. All the mentioned models are developed and implemented in the field of Credit card fraud detection, bankruptcy detection, loan default prediction. In each of the aforementioned cases, the comparative study among the classification techniques is drawn and the best model is identified. The performance of each classifier on each considered domain is evaluated by various performance metrics such as accuracy, F1-score and mean squared error. In the credit card fraud detection model the decision tree classifier performs the best with an accuracy of 99.1% and, in the loan default prediction and bankruptcy detection model, the random forest classifier gives the best accuracy of 97% and 96.84% respectively.
Fatama Sharf Al-Deen, Fadl Mutaher Ba-Alwi
Asian Journal of Research in Computer Science pp 1-8; https://doi.org/10.9734/ajrcos/2021/v11i330262

Abstract:
Due to the rapid development in information technology, Big Data has become one of its prominent feature that had a great impact on other technologies dealing with data such as machine learning technologies. K-mean is one of the most important machine learning algorithms. The algorithm was first developed as a clustering technology dealing with relational databases. However, the advent of Big Data has highly effected its performance. Therefore, many researchers have proposed several approaches to improve K-mean accuracy in Big Data environment. In this paper, we introduce a literature review about different technologies proposed for k-mean algorithm development in Big Data. We demonstrate a comparison between them according to several criteria, including the proposed algorithm, the database used, Big Data tools, and k-mean applications. This paper helps researchers to see the most important challenges and trends of the k-mean algorithm in the Big Data environment.
, Nareen Abdulla Sabry
Asian Journal of Research in Computer Science pp 46-57; https://doi.org/10.9734/ajrcos/2021/v11i230260

Abstract:
In the last few days, data and the internet have become increasingly growing, occurring in big data. For these problems, there are many software frameworks used to increase the performance of the distributed system. This software is used for available ample data storage. One of the most beneficial software frameworks used to utilize data in distributed systems is Hadoop. This software creates machine clustering and formatting the work between them. Hadoop consists of two major components: Hadoop Distributed File System (HDFS) and Map Reduce (MR). By Hadoop, we can process, count, and distribute each word in a large file and know the number of affecting for each of them. The HDFS is designed to effectively store and transmit colossal data sets to high-bandwidth user applications. The differences between this and other file systems provided are relevant. HDFS is intended for low-cost hardware and is exceptionally tolerant to defects. Thousands of computers in a vast cluster both have directly associated storage functions and user programmers. The resource scales with demand while being cost-effective in all sizes by distributing storage and calculation through numerous servers. Depending on the above characteristics of the HDFS, many researchers worked in this field trying to enhance the performance and efficiency of the addressed file system to be one of the most active cloud systems. This paper offers an adequate study to review the essential investigations as a trend beneficial for researchers wishing to operate in such a system. The basic ideas and features of the investigated experiments were taken into account to have a robust comparison, which simplifies the selection for future researchers in this subject. According to many authors, this paper will explain what Hadoop is and its architectures, how it works, and its performance analysis in a distributed systems. In addition, assessing each Writing and compare with each other.
Diyar Qader Zeebaree, Adnan Mohsin Abdulazeez, Lozan M. Abdullrhman, , Omar Sedqi Kareem
Asian Journal of Research in Computer Science pp 29-45; https://doi.org/10.9734/ajrcos/2021/v11i230259

Abstract:
Prediction is vital in our daily lives, as it is used in various ways, such as learning, adapting, predicting, and classifying. The prediction of parameters capacity of RNNs is very high; it provides more accurate results than the conventional statistical methods for prediction. The impact of a hierarchy of recurrent neural networks on Predicting process is studied in this paper. A recurrent network takes the hidden state of the previous layer as input and generates as output the hidden state of the current layer. Some of deep Learning algorithms can be utilized in as prediction tools in video analysis, musical information retrieval and time series applications. Recurrent networks may process examples simultaneously, maintaining a state or memory that recreates an arbitrarily long background window. Long Short-Term Memory (LSTM) and Bidirectional RNN (BRNN) are examples of recurrent networks. This paper aims to give a comprehensive assessment of predictions based on RNN. Additionally, each paper presents all relevant facts, such as dataset, method, architecture, and the accuracy of the predictions they deliver.
Mehedi Rahman Rana, Farjana Rahman, , Anisur Rahman
Asian Journal of Research in Computer Science pp 16-28; https://doi.org/10.9734/ajrcos/2021/v11i230258

Abstract:
Coronavirus has become a significant concern for the whole world. It has had a substantial influence on our social and economic life. The infection rate is rapidly increasing at every moment throughout the world. At present, predicting coronavirus has become one of the challenging issues for us. As the pace of COVID-19 detection increases, so does the death rate. This research predicts the number of coronavirus detection and deaths using Fbprophet, a tool designed to assist in performing time series forecasting at a large scale. Two major affected countries, India and Japan, have been taken into consideration in our approach. Using the prophet model, a prediction is performed on the number of total cases, new cases, total deaths and new deaths. This model works considerably well, and it has given a satisfactory result that may help the authority in taking early and appropriate decisions depending on the predicted COVID situation.
Ruslan Pozinkevych
Asian Journal of Research in Computer Science pp 11-15; https://doi.org/10.9734/ajrcos/2021/v11i230257

Abstract:
Aims/ Objectives: The research presented in the following application aims to prove use of Ternary Maths for calculating machines and to simplify the process of calculating In it we will try to justify the use of triplets and describe how it works. An earlier research presented in “Logical Principles in Ternary Mathematics” [1,2,3] shows that we can transit from one expression of a number such as a "component form" to another, e.g a decimal, or still another, that is it’s vector form [4]. The aim of our further research is to explain why we associate Triplets of numbers in such choice {-1,0,1} and not the numbers 1,2,3 for example, or a set {1,2,3} The explanation seems obvious as a set of decimal numbers consists of 10 entries not 3 At the same time we have to prove that the mentioned set of triplets is a unique and the only one to be used as a Ternary Set or a base, as we might call it, for our calculating machines.
, Habibullah Slimanzai
Asian Journal of Research in Computer Science pp 41-48; https://doi.org/10.9734/ajrcos/2021/v11i130255

Abstract:
In the present period of computerized handling, high level of online information is looked with digital threats. There are unlimited dangers and difficulties to information existence online. Cyber-attacks which are considered the emerging and serious threats that are going on each second and investigation of those dangers and threats are exceptionally hard to confine and vanquish them. Cybercrimes have a terrible effect on governmental and non-governmental organizations, educational institutions, financial banks and economic infrastructures. Numerous worldwide societies, policy makers and intelligent agencies are trying to react and control cybercrimes. One of the most serious issue in the online processing is that how to secure and deal with our day by day information against digital misrepresentation and cybercrimes. To comprehend cybercrime and save our digital assets, this paper will analyze about various cybercrimes and addresses the effective prevention and detection ways and methods used for the avoidance, controlling, detection and combatting of those crimes.
J. O. Jooda, A. O. Oke, E. O. Omidiora, O. T. Adedeji
Asian Journal of Research in Computer Science pp 1-10; https://doi.org/10.9734/ajrcos/2021/v11i230256

Abstract:
Unimodal biometrics system (UBS) drawbacks include noisy data, intra-class variance, inter-class similarities, non-universality, which all affect the system's classification performance. Intramodal fingerprint fusion can overcome the limitations imposed by UBS when features are fused at the feature level as it is a good approach to boost the performance of the biometric system. However, feature level fusion leads to high dimensionality of feature space which can be overcame by Feature Selection (FS). FS improves the performance of classification by selecting only relevant and useful information from extracted feature sets being an optimization problem. Artificial Bee Colony (ABC) is an optimizing algorithm that has been frequently used in solving FS problems because of its simple concept, use of few control parameters, easy implementation and good exploration characteristics. ABC was proposed for optimized feature selection prior to the classification of Fingerprint Intramodal Biometric System (FIBS). Performance evaluation of ABC-based FIBS showed the system had a Sensitivity of 97.69% and RA of 96.76%. The developed ABC optimized feature selection reduced the high dimensionality of features space prior to classification tasks thereby increasing sensitivity and recognition accuracy of FIBS.
, Adegbola Oluwole Abiodun, Adedeji Oluyinka Titilayo, Makinde Bukola Oyeladun, Taiwo Olayinka David, Damilare Gbohunmi Aduragbemi
Asian Journal of Research in Computer Science pp 28-40; https://doi.org/10.9734/ajrcos/2021/v11i130254

Abstract:
Home security is extremely important, and several methods of security have been improved, such as the usage of alarms, monitoring systems, and the interplay of electronic hardware, software, and other factors. Keys can be misplaced and found by others, putting the guarded structure at risk; keys can also be fabricated or stolen. This project entails creating a voice message-based door access system that can both open the door and identify intruders, trespassers, criminals, or any other type of illegal behaviour. The speech-controlled door was meant to generate a voice message based on the input data and was developed around a microcontroller (ATmega328p). A speech recognition module is used to allow the owner or user entry to the door. To gain access to the door, the owner must first utter the specific speech or key word required to open it. A voice notification is then outputted through the associated speaker if the pronounced word does not match the speech recognized by the microcontroller. To signify that access is refused, a red-light emitting diode will flash. The microprocessor would activate a relay and current will flow through the latch, allowing the door to be unlocked, if the uttered speech matches. A speech recognition module is used to allow the owner or user entry to the door. To gain access to the door, the owner must first utter the specific speech or key word required to open it. A voice notification is then outputted through the associated speaker if the pronounced word does not match the speech recognized by the microcontroller. To signify that access is refused, a red light emitting diode will flash. The microprocessor will activate a relay and current will flow through the latch, allowing the door to be unlocked, if the uttered speech matches.
Abdulraheem Abdul, Rafiu M. Isiaka, Ronke S. Babatunde, Jumoke F. Ajao
Asian Journal of Research in Computer Science pp 17-27; https://doi.org/10.9734/ajrcos/2021/v11i130253

Abstract:
Aims: This work aim is to develop an enhanced predictive system for Coronary Heart Disease (CHD). Study Design: Synthetic Minority Oversampling Technique and Random Forest. Methodology: The Framingham heart disease dataset was used, which was collected from a study in Framingham, Massachusetts, the data was cleaned, normalized, rebalanced. Classifiers such as random forest, artificial neural network, naïve bayes, logistic regression, k-nearest neighbor and support vector machine were used for classification. Results: Random Forest outperformed other classifiers with an accuracy of 98%, a sensitivity of 99% and a precision of 95.8%. Feature selection was employed for better classification, but no significant improvement was recorded on the performance of the classifier with feature selection. Train test split also performed better that cross validation. Conclusion: Random Forest is recommended for research in Coronary Heart Disease prediction domain.
Chunli Li, Chunyu Wang
Asian Journal of Research in Computer Science pp 8-16; https://doi.org/10.9734/ajrcos/2021/v11i130252

Abstract:
Distillation is a unit operation with multiple input parameters and multiple output parameters. It is characterized by multiple variables, coupling between input parameters, and non-linear relationship with output parameters. Therefore, it is very difficult to use traditional methods to control and optimize the distillation column. Artificial Neural Network (ANN) uses the interconnection between a large number of neurons to establish the functional relationship between input and output, thereby achieving the approximation of any non-linear mapping. ANN is used for the control and optimization of distillation tower, with short response time, good dynamic performance, strong robustness, and strong ability to adapt to changes in the control environment. This article will mainly introduce the research progress of ANN and its application in the modeling, control and optimization of distillation towers.
, Zulfikar Ali Ansari, Riya Singh, Mohit Singh Rawat, Fiza Zafar Khan, Shubham Kumar Yadav
Asian Journal of Research in Computer Science pp 1-7; https://doi.org/10.9734/ajrcos/2021/v11i130251

Abstract:
Artificial Intelligence (AI) technologies are new technologies with new complicated features emerging quickly. Technology adoption has been beneficial for many general models. The models help in train the voice user-interface assistance (Alexa, Cortona, Siri). Voice assistants are easy to use, and thus millions of devices incorporate them in households nowadays. The primary purpose of the sign language translator prototype is to reduce interaction barriers between deaf and mute. To overcome this problem, we have proposed a prototype. It is named sign language translator with Sign Recognition Intelligence which takes the user input in sign language and processes it, and returns the output in voice out load to the end-user.
, Evans F. Osaisai, S. Dienagha Nicholas, Abalaba Ineyekineye
Asian Journal of Research in Computer Science pp 58-68; https://doi.org/10.9734/ajrcos/2021/v10i430250

Abstract:
With the internet fast-penetrating the Nigerian populace, e-commerce businesses have become commonplace, this has given rise to an increase in the number of Nigerians shopping online. However, there is a growing concern that most Nigerian e-shoppers prefer foreign to local online shops, resulting in an online fund-leak from the local economy. This work presents a comparative analysis of the usability of e-commerce websites in Nigeria, highlights the key findings viz: security and lack of trust. The findings were then related to why Nigerians prefer shopping from foreign rather than local e-commerce websites. We argued that for e-commerce to thrive; usability should be given prime consideration, security should be guaranteed and trust-building ethos is practiced. We conclude that despite the ‘pay on delivery’ mode applied by e-commerce websites to woo customers and gain trust, the insecurity posed by the prevalence of online fraud in Nigeria has created apprehension and distrust among Nigerians towards local e-commerce websites and is contributing to why Nigerians prefer to buy from foreign rather than local e-commerce websites.
Asian Journal of Research in Computer Science pp 47-57; https://doi.org/10.9734/ajrcos/2021/v10i430249

Abstract:
Image compression research has increased dramatically as a result of the growing demands for image transmission in computer and mobile environments. It is needed especially for reduced storage and efficient image transmission and used to reduce the bits necessary to represent a picture digitally while preserving its original quality. Fractal encoding is an advanced technique of image compression. It is based on the image's forms as well as the generation of repetitive blocks via mathematical conversions. Because of resources needed to compress large data volumes, enormous programming time is needed, therefore Fractal Image Compression's main disadvantage is a very high encoding time where decoding times are extremely fast. An artificial intelligence technique similar to a neural network is used to reduce the search space and encoding time for images by employing a neural network algorithm known as the “back propagation” neural network algorithm. Initially, the image is divided into fixed-size and domains. For each range block its most matched domain is selected, its range index is produced and best matched domains index is the expert system's input, which reduces matching domain blocks in sets of results. This leads in the training of the neural network. This trained network is now used to compress other images which give encoding a lot less time. During the decoding phase, any random original image, converging after some changes to the Fractal image, reciprocates the transformation parameters. The quality of this FIC is indeed demonstrated by the simulation findings. This paper explores a unique neural network FIC that is capable of increasing neural network speed and image quality simultaneously.
, Ibrahim Mahmood Ibrahim, Naaman Omar, Omar M. Ahmed, Zryan Najat Rashid, Awder Mohammed Ahmed, Rowaida Khalil Ibrahim, Shakir Fattah Kak, Hajar Maseeh Yasin, Azar Abid Salih
Asian Journal of Research in Computer Science pp 30-46; https://doi.org/10.9734/ajrcos/2021/v10i430248

Abstract:
Android is now the world's (or one of the world’s) most popular operating system. More and more malware assaults are taking place in Android applications. Many security detection techniques based on Android Apps are now available. The open environmental feature of the Android environment has given Android an extensive appeal in recent years. The growing number of mobile devices are incorporated in many aspects of our everyday lives. This paper gives a detailed comparison that summarizes and analyses various detection techniques. This work examines the current status of Android malware detection methods, with an emphasis on Machine Learning-based classifiers for detecting malicious software on Android devices. Android has a huge number of apps that may be downloaded and used for free. Consequently, Android phones are more susceptible to malware. As a result, additional research has been done in order to develop effective malware detection methods. To begin, several of the currently available Android malware detection approaches are carefully examined and classified based on their detection methodologies. This study examines a wide range of machine-learning-based methods to detecting Android malware covering both types dynamic and static.
Ming-Jong Lin
Asian Journal of Research in Computer Science pp 19-29; https://doi.org/10.9734/ajrcos/2021/v10i430247

Abstract:
The aim of this article describes the program of computerized how to calculate the feeder fault current in a distribution substation. This article adopts Thevenin theory as the basis of calculation, and narrates them in two ways: the artificial and the computerized algorithm. It leaves aside the artificial and delves the computerized algorithm. The latter is divided for two computerized algorithm - separate and all of equipment. In the computerized algorithm, all data inputting, procedure steps, and report form were carefully been designed by MATLAB application software. As for data Inputting refers to the specification parameters of equipment component. The characteristics of this article are described with both text and Fig. to achieve operation simple and understanding easy. References include a representative textbook and several journal articles. Verify with real cases and reveal the pros and cons of artificial and program algorithms. The purpose of this article is to discard waste - an artificial calculation that is time - consuming, cumbersome and prone to clerical errors. The computer programs algorithm can compensates for defects and improves accuracy and timeliness. This method has been proven to be an economical design aid tool that is of great help to maintenance or designers in the field of electrical engineering.
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