American Journal of Computing and Engineering最新文献

{"title":"Kinetic Modeling of Pulp Production from Plantain Trunk","authors":"P. Igbagara, Umukoro Evawere","doi":"10.47672/ajce.735","DOIUrl":"https://doi.org/10.47672/ajce.735","url":null,"abstract":"Plantain pseudostem has high content of lignocellulose used for production of pulp. But ironically, this resource is unexploited, with plantain stem becoming a common domestic waste in many parts of the world. The present work provides a kinetic model based on the kraft process from experimental determination of the rate of delignification reaction of plantain stem aimed at its application for pulp making and eventual paper production. Objectives of the work are twofold: firstly, to create an alternative raw material to wood for pulp production given the dwindling wood resources world – over and secondly, as a means of environmental waste management and control. The Arrhenius kinetic model was used to find the rate constant for the process with precise determination of its activation energy and pre – exponential factor. Results of study showed that Plantain (musa acuminate) is similar in chemical composition and morphology, but has higher amounts of cellulose (which is the major substance in pulping) than banana (musa pradisiaca). Plantain pseudostem is therefore highly recommended as an alternative source of raw material to wood for pulping production.","PeriodicalId":148892,"journal":{"name":"American Journal of Computing and Engineering","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125692851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of Hybrid Optical Amplifiers (Raman-EDFA) with a Standard Fiber (SMF) and a maximum pump power of 200mw in access networks: WDM-PON","authors":"B. Armel, Essiben Dikoundou, K. Same","doi":"10.47672/AJCE.701","DOIUrl":"https://doi.org/10.47672/AJCE.701","url":null,"abstract":"In this paper , we demonstrate the possibility of Raman -EDFA association in access networks. for this purpose, we evaluate the respective performances of these two types through a numerical method for 16 channels. Interesting results can be exploited; it is shown that with EDFAs, a target gain of 20dB can be reached for a wavelength range of 980 to 1440nm but with several perturbations in the received signal due to SNR and OSNR. These problems are solved with the integration of Raman amplification which pushes the gain limit to 27dB, with a better flatness.","PeriodicalId":148892,"journal":{"name":"American Journal of Computing and Engineering","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131683014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Authenticating Passwords by Typing Pattern Biometrics","authors":"Rose Nakasi, Safari Yonasi, J. Ngubiri","doi":"10.47672/AJCE.661","DOIUrl":"https://doi.org/10.47672/AJCE.661","url":null,"abstract":"Passwords are a common measure used in Authentication systems to make sure that the users are who they say they are. The complexity of these Passwords is relied on while ensuring security. However, the role of complexity is limited. Users are forced to write down complex passwords since easy ones are easily guessed. This study aimed at evaluating the uniqueness of typing patterns of password holders so as to strengthen the authentication process beyond matching the string of characters. Using our own dataset, this research experimentally showed that k Nearest Neighbor algorithm using Euclidean distance as the metric, produces sufficient results to distinguish samples and detect whether they are from the same authentic user or from an impostor based on a threshold that was computed. Results obtained indicated that typing patterns are distinct even on simple guessable passwords and that typing pattern biometrics strengthens the authentication process. This research extends work in typing pattern analysis using k Nearest Neighbor machine learning approach to auto detect the password pattern of the authentic and non-authentic users. It also provides an investigation and assessment to the effect of using different k values of the KNN algorithm. Further to this field is the methodology for calculating an optimal threshold value with higher accuracy levels that acted as a basis for rejection or acceptance of a typing sample. Additionally is an introduction of a new feature metric of a combined dataset which is a concatenation of both the dwell and latency timings. A comparison of performance for independent and a combined dataset of the feature metrics was also evaluated.","PeriodicalId":148892,"journal":{"name":"American Journal of Computing and Engineering","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117320369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MATHEMATICALLY MODELING THE SPREAD OF HIV/AIDS INFECTION AFTER THE INTRODUCTION OF ANTIRETROVIRAL THERAPY IN GHANA.","authors":"Richard Ayamah, G. Awuitor, Zutaah Puotier","doi":"10.47672/AJCE.602","DOIUrl":"https://doi.org/10.47672/AJCE.602","url":null,"abstract":"One of the deadliest and highly infectious diseases is Human Immunodeficiency Virus-Acquired Immune Deficiency Syndrome (HIV-AIDS). One person was first diagnosed with HIV-AIDS in the Eastern region part of Ghana in 1986, followed by 41 more in the same year. The spread of the disease was so unbearable in the subsequent years (1987-2003), even after several intervention measures taken by Government and other stakeholders. Hence, in 2003, the antiretroviral therapy (ART) program was introduced by the Ghana AIDS Commission (GAC) through the Ghana Health Service (GHS) to sabotage the virus such that it cannot be transmitted from one person to another, not even from the pregnant mother to the unborn child. It is in this direction that this research was conducted to use differential equations to derive a model for the prediction of the HIV/AIDS infection rate, after the introduction of the ART program in Ghana. The data on the number of HIV infected people per each year (I) for the years 2003-2018 were collated from the reports given by Ghana AIDS Commission (GAC), WHO and UNAIDS published on their associate websites. Differential equations, with the employment of numerical analysis of data, were used to derive a model for the prediction of the yearly number of HIV/AIDS infected people. Graphical analysis on the residuals of the predicted number of HIV/AIDS infected people (residual analysis) were carried out to check whether the derived model was adequate or not. Finally, a model was derived using ordinary differential equations and the yearly numbers of HIV infected people estimated using the model were in descending, order as portrayed in the original data set. The residual analysis on the model adequacy checking proved that the model is adequate for the prediction of the number of HIV infected people in Ghana. In effect, the ART program really played a major role in the reduction of the HIV infection rate. The uniqueness of this research is portrayed in the fact that it is the first time differential equation is being employed in Ghanaian academia to derive a model for the future prediction of the HIV infection rate.   \u0000Keywords: Human Immunodeficiency Virus, Acquired Immune Deficiency Syndrome, antiretroviral therapy, HIV-Infected People, Susceptible People.","PeriodicalId":148892,"journal":{"name":"American Journal of Computing and Engineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116885509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnosis of Diabetic Retinopathy Utilizing Computer-Aided Diagnosis System","authors":"Hattan Omar Mujalled, Y. Kadah","doi":"10.47672/ajce.580","DOIUrl":"https://doi.org/10.47672/ajce.580","url":null,"abstract":"Purpose: Diabetes is considered one of most diseases spread among people; blindness is considered the most resulted effect. Diabetes can damage the retinal blood vessels and cause severe problems to the eyes, which may end with sight loss. Such medical condition is known as \"diabetic retinopathy\" (DR). In such a diagnosis, the retinal microvascular go through several stages of change threat. In the early stages of the DR, detecting the formation that happened to the retinal blood vessels helps prevent the disease's dangerous effects. Therefore, producing a method to diagnose the disease in the early stages is helpful. So, this work aimed to develop a system of detecting and classifying the retina formation, trying to avoid relevant effects.Methodology: The current method depends on vascular edges map extracted from images of retina captured by a fundus camera. Such a map been utilized to extract quantitative texture features. The system tested two independent groups of the region of interest in normal and abnormal images. The two sets were extracted from ground truth images of the 89 fundus images. Fundus images were annotated images from the Standard Diabetic Retinopathy Database (DIARETDB1).Findings: The system provided an accuracy of 71% with a sensitivity of 75%.Recommendation: The current work may open an opportunity for improvement for future work. Other methods may be reached to raise the accuracy and the sensitivity of the system. Besides, the current system may be tested on a larger sample size to study such effects. Finally, the ease of the current method makes it faster in adoption in the appropriate diagnosis especially in the early stages.","PeriodicalId":148892,"journal":{"name":"American Journal of Computing and Engineering","volume":"26 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134560318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"KNOWLEDGE BASED SYSTEM DESIGN FOR DIAGNOSIS OF HEPATITIS B VIRUS (HBV) USING GENERALIZED REGRESSION NEURAL NETWORK (GRNN)","authors":"Ogah U. S., P. B. Zirra, O. Sarjiyus","doi":"10.47672/ajce.270","DOIUrl":"https://doi.org/10.47672/ajce.270","url":null,"abstract":"Purpose: It is obvious that accurate diagnosis of a disease is one of the serious problems in modern medicine. This paper proposes a knowledge base system design for the diagnosis of Hepatitis B virus (HBV) using Generalized Regression Neural Network (GRNN). The aim is to embed an intelligent system for the diagnosis of Hepatitis B virus using GRNN since HBV is one of the most deadly viral infections that has colossal effect on the health of the people suffering from it and has remained a lasting health problem affecting a significant number of the world’s population.Methodology: The data used for this study was obtained from different sources. Primary data was obtained from field through, observations, and scheduled interviews with stakeholders -Medical Doctors Laboratory Technicians, Laboratory Scientists and Patients suffering from the disease. While secondary data was gotten through visits to the libraries, journals, textbooks, articles and conference proceedings.Results: Hepatitis B is one of the most common of all Hepatitis around the world today.  The research found out that using the HBV markers that, if AgHBs = positive, AgHBe = positive and anti-VHD = negative then HBV is Positive, if HBsAg = negative, anti-HBc = positive, IgM anti-HBc = positive and anti-HBs = positive then it is at Acute level, if HBsAg = positive, anti-HBc = positive, IgM anti-HBc = negative and anti-HBs = negative then it is Chronic. Finally, if HBeAg = positive then the Liver is inflammed (HBV profile test). Generalized regression Neural Network (GRNN) is the finest suitable Neural Network for Hepatitis B diagnosis which will help in reducing extra time consumption in treatment. Even if there is any number of missing parameters in blood test, the diagnosis will be done by artificial intelligence using generalized regression neural networks.Unique contribution to theory, practice and policy: This system will help assist the health practitioners and also keep the vulnerable informed, as well the mortality rate and waiting time to see the experts will be reduced by employing the expert system application in this research. The researcher here recommend for further study on HBV drug resistance.","PeriodicalId":148892,"journal":{"name":"American Journal of Computing and Engineering","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126219243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}