Asian Journal of Research in Computer Science

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.

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).

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.

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.

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.

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.

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.

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.

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.

Design Method: The feeder construction type adopts π－type (nominal π) transmission mode. The total feeder impedance value makes up of feeder impedance and load impedance, and then the feeder impedance value is derived from the hyperbolic function of mathematical formula, and the wire diameter parameter and length by a computer program to calculate. The load impedance composition is divided into two types: resistance parallel reactance or resistance series reactance, and the difference analysis of the feeder current obtained after being connected in series with the line impedance. The impact of voltage changes on the load end, load impedance and adjustment capacitors are deeply analyzed and discussed, and their differences are shown graphically. At the same time, the relationship between the load power factor and the resistance and inductance ratio of the adjusting capacitor and the load impedance are analyzed.

Design Purpose: Based on the frequent changes in the test data of related equipment parameters during design, the above calculation steps are been complied for a computer programming by MATLAB application software.

Design Effectiveness: The program has been tested for excellent performance. So that it is a powerful tool for designers to improve the accuracy of repetitive computer programming calculations.

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.

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.  

Most chemical processes, such as distillation, absorption, extraction, and catalytic reactions, are extremely complex processes affected by multiple factors. As a result, the relationships between their input and output variables are non-linear, and it is not easy to optimize or control them using traditional methods. Artificial neural network is a systematic structure composed of multiple neuron models. By simulating many basic functions of the nervous system of living organisms, nonlinear control can be realized without relying on mathematical models, and it is especially suitable for more complex control objects. This article will introduce artificial neural networks' basic principles and development history, and review its application research progress in chemical process control, fault diagnosis, and process optimization.