VISUALIZING E-VOTING RESULTS

Recently, the urge for e-voting has been described to be the inevitable future of electioneering in most countries of the world. Despite all its good features, like the other voting systems it has been seen to also be susceptible to rigging and fraud. Some of its undesirable features include not allowing recounting of votes after election in case of a protest like the others. Another issue is that of erroneous software which can greatly affect the result of the election. All these is further compounded by the fact that voting systems deals with very large amount of data that is collected from a distributed population source hence the raw data are extremely difficult to comprehend and therefore monitor. This paper attempts to solve this problem using a TreeMap based visualization technique to monitor in real-time the distributed balloting and voting processes. The paper proved that TreeMap algorithms can be configured and deployed on the central server to monitor effectively the voting transactions in real-time and hence enable transparency

A Rough Set Approach to Dimensionality Reduction for Performance Enhancement in Machine Learning

Machine learning uses complex mathematical algorithms to turn data set into a model for a problem domain. Analysing high dimensional data in their raw form usually causes computational overhead because the higher the size of the data, the higher the time it takes to process it. Therefore, there is a need for a more robust dimensionality reduction approach, among other existing methods, for feature projection (extraction) and selection from data set, which can be passed to a machine learning algorithm for optimal performance. This paper presents a generic mathematical approach for transforming data from a high dimensional space to low dimensional space in such a manner that the intrinsic dimension of the original data is preserved using the concept of indiscernibility, reducts, and the core of the rough set theory. The flue detection dataset available on the Kaggle website was used in this research for demonstration purposes. The original and reduced datasets were tested using a logistic regression machine learning algorithm yielding the same accuracy of 97% with a training time of 25 min and 11 min respectively

INTELLIGENT ADVISORY SYSTEM FOR SUPPORTING COMPUTER-BASED AUTHENTICATION USERS

Authentication is one of the cornerstones of computer security systems today, and most users of computers interact withthese mechanisms on a daily basis. However, human factor has often been described as one of the weakest part of computersecurity as users of authentication are often identified to be the weakest link in the security chain. In related development ithas been demanding to merge usability with security in the choice of authentication method by computer users. To addressthe serious problem, this paper presents an intelligent advisory system based on artificial neural network that can assist usersof authentication systems on making decision on the authentication method that best suits them.Keywords: Intelligent, Advisory system, Authentication, Human Factor

Prevalence of HIV and Malaria parasites co-infection in pregnant mothers and their babies post delivery

Worsened perinatal outcomes and increased rates of maternal morbidity are consequences of co-infection of HIV and Plasmodium falciparum in pregnant women. This study was designed to ascertain the proportion of co-infection of both diseases in pregnant mothers and babies born to HIV-infected mothers. A total of 149 pregnant mothers and 30 babies of HIV-infected mothers were engaged in a longitudinal study for 18 months in the endemic area of Saki and Ibadan. Only babies born to HIV infected mothers were enrolled and systematically followed-up for six months post delivery. Determine(R) and Unigold rapid diagnostic tests kits were used for HIV test in mothers whereas HIV screening was conducted on the babies using polymerase chain reaction at six months post delivery. Giemsa stained thick blood smear was used to determine the presence of asexual stages of Plasmodium falciparum. Descriptive statistics was used to determine the percentage of infections status. Chi-square and student t-test was used to compare maternal data and babies six months after birth. The results showed that 85/149(57.0%) mothers and 11/30(36.7%) babies had microscopically detectable malaria parasites whereas the seroprevalence were 64(33.0%) and 19(10.7%) for mothers and infants respectively. In mothers, 19(12.8%) had HIV alone, 51/149(34.2%) malaria only, 34/149 (22.8%) were co-Infected and 45/149(30.2%) had neither HIV nor malaria. In infants, 9/30 (30.0%), 10/30(33.3) had HIV only, 2/30(6.7%) had malaria only whereas 9/30(30.0%) had neither malaria nor HIV. Parasitemia ranged between 251.5 of cells/µL in mothers and 205.7 of cells/µL in babies born to HIV infected mothers. Keywords: Perinatal, Plasmodium falciparum, Seroprevalence, co-infected, Parasitemia

Effect of optimizing process variables on the quality characteristics of cassava-wheat composite bread

The optimisation of bread-making process can have a positive impact in ramping up the quality characteristics of cassava-wheat bread to  that of whole wheat bread. In this study, a threevariable Box-Behnken design response surface methodology was employed to investigate and optimise independent variables namely cassava flour composition, water content and proofing time in relation to response variables namely dough yield, loaf specific volume and loaf protein of cassava-wheat-composite bread. The data from the experimental design were fitted into second-order regression models and their validity and reliability were confirmed by analysis of variance. Optimal cassava flour composition, water content and proofing time were derived as; 100 g/kg, 589 g/kg and 90 min, respectively. It was revealed that cassava flour composition had the most effect on the quality characteristics of cassava-wheat-composite bread. At constant cassava flour  composition, increase in water content and proofing time had a positive effect on all the studied quality characteristics of cassava-wheat composite bread. Increase cassava flour composition regardless of proofing time and water content had a negative effect on loaf specific volume and protein. This study has provided bread-making conditions which can be utilised in enhancing the consumer acceptability of cassava-wheat composite bread. &nbsp

Preparation, Release Pattern and Antibacterial Activities of Chitosan-Silver Nanocomposite Films

The present study examined the preparation of chitosan-silver   nanocomposite films as carriers for silver release pattern. Chitosan a biopolymer   having immense structural possibilities for chemical and mechanical modifications   to generate novel properties, functions and applications. Chitosan–silver   nanocomposite films has been synthesised by reduction method, which is a simple   and inexpensive method. The chitosan-silver nanocomposite films was   characterized in terms of its surface plasmon resonance and crystalline structure by   using UV-Visible spectroscopy, X-ray diffraction, Fourier transform infrared and   Scanning electron microscope. Swelling and release studies were carried out on   crosslinked and un-crosslinked nanocomposite films. Antibacterial activities of   chitosan-silver nanocomposite films were investigated on some pathogens:   Staphylococcus aureus, Shigella dysenteriae, Escherichia coli, Salmonella typhii   and Klebsiella pneumonia using agar well diffusion method. crosslinked chitosan-silver nanocomposite demonstrated a slower release pattern relative to un-crosslinked chitosan-silver nanocomposite. The crosslinked and un-crosslinked   nanocomposite became dislodged and completely released at 120 minutes and 90   minutes respectively. The results of the antibacterial activities revealed that the   cross-linked chitosan-silver nanocomposite films has higher antibacterial   properties than un-crosslinked chitosan-silver nanocomposite films. This study   provides nanocomposite films potentially useful for delivery system.</p

Age-specific prevalence of human papilloma virus infection among Nigerian women

Background: Inconsistent trends in HPV prevalence by age have been described in Africa. We examined the age prevalence pattern and distribution of 37 HPV-DNA types among urban Nigerian women. Methods: The study population was a sample of 278 women who presented to cervical cancer screening programs in Abuja, Nigeria, between April and August 2012. Using a nurse administered questionnaire, information on demographic characteristics and risk factors of cervical cancer was collected and samples of cervical exfoliated cells were obtained from all participants. Roche Linear Array HPV Genotyping Test® was used to characterize prevalent HPV and log-binomial regression models were used to examine the association between potential correlates and the prevalence of HPV infection. Results: The mean age (SD) of the women enrolled was 38 (8) years. The overall prevalence of HPV was 37%. HPV 35 was the most prevalent HPV type in the study population. Among women age ≤ 30 years, 52% had HPV infection compared to 23% of those women who were older than 45 years (p = 0.006). We observed a significant linear association between age and the prevalence of HPV infections. The prevalence ratio (PR) and 95% confidence interval (CI) was 2.26 (1.17, 4.34) for any HPV infection, 3.83 (1.23, 11.94) for Group 1 HPV (definite carcinogens), and 2.19 (0.99, 4.84) for Group 2a or 2b HPV (probable or possible carcinogens) types, among women aged 18–30 years, compared to women who were older than 45 years. Conclusion: The prevalence of HPV infection was highest among younger women and decreased steadily with age among this population of urban Nigerian women

Quality Assessment of Selected Public Recreational Waters in Sango-Ota Metropolis, Nigeria

The evaluation of selected public swimming pools within Sango-Ota metropolis was done to determine whether the pools adapt to the recommended WHO standard for swimming pool water. Six pools were selected based on the average population per use and user ratings. A total of 12 water samples were analysed physicochemical and microbial qualities using standard methods. The&nbsp; physicochemical characterization results are as follows; pH, 5.00 - 5.73 with mean value of 5.3; Total Dissolved Solids (TDS), 44.00 - 48.50 mg/L with mean 46.0 mg/L; Alkalinity, 24.00 - 28.50 mg/L with mean 26.0 mg/L; total hardness, 0.80 - 1.23 mg/L with mean 1.0 mg/L; iron, 0.05 – 0.69 mg/L with mean 0.3 mg/L; residual chlorine, 1.06 – 3.25 mg/L with mean 1.9 mg/L. The microbial characterization results are as follows; Zero count for Salmonella-shigella; Total Aerobic Plate Count (TAPC),1360 - 7270 cfu/mL; Escherichia coli count, 0 - 7 cfu/mL; coliform count, 2 – 25 cfu/mL.&nbsp; The isolated microorganisms from the pools were Escherichia coli, Proteus Vulgaris, Yersinia Enterocolitica, Proteus Mirabilis, Citrobacter Freundi and Vibro Chlorea occurred in 8.33%, respectively while Klebsiella Pneumonia, Entrobacter Aerogenes, Pseudonomas sp. occurred 16.67%. The pH of the analysed pools didn’t comply with the WHO standards while other physicochemical parameters conform to the standard except for pools C and F which had a higher concentration of iron. However, the existence of pathogenic microorganisms in the pools classified them as unsafe for swimming activities. This study recommends routine testing and comprehensive treatments with respect to regulatory standards.&nbsp; Pool managers should strictly adhere to the bathing load limit and ensure the pool users take shower before using the swimming pools to forestall the outbreak of waterborne disease

HIV associated high-risk HPV infection among Nigerian women

Background: In developed countries, the incidence of cervical cancer has remained stable in HIV+ women but the prevalence and multiplicity of high-risk HPV (hrHPV) infection, a necessary cause of cervical cancer, appears different comparing HIV+ to HIV- women. Little is known about HIV and HPV co-infection in Africa. Methods: We enrolled women presenting at our cervical cancer screening program in Abuja, Nigeria between April and August 2012, and collected information on demographic characteristics, risk factors of HPV infection and samples of exfoliated cervical cells. We used Roche Linear Array HPV Genotyping Test® to characterize prevalent HPV and logistic regression models to estimate the association between HIV and the risk of hrHPV infection. Results: There were 278 participants, 54% (151) were HIV+, 40% (111) were HIV-, and 6% (16) had unknown HIV status. Of these, data from 149 HIV+ and 108 HIV- women were available for analysis. The mean ages (±SD) were 37.6 (±7.7) years for HIV+ and 36.6 (±7.9) years for HIV- women (p-value = 0.34). Among the HIV+ women, HPV35 (8.7%) and HPV56 (7.4%) were the most prevalent hrHPV, while HPV52 and HPV68 (2.8%, each) were the most prevalent hrHPV types among HIV- women. The multivariate prevalence ratio for any hrHPV and multiple hrHPV infections were 4.18 (95% CI 2.05 – 8.49, p-value <0.0001) and 6.6 (95% CI 1.49 – 29.64, p-value 0.01) respectively, comparing HIV + to HIV- women, adjusted for age, and educational level. Conclusions: HIV infection was associated with increased risk of any HPV, hrHPV and multiple HPV infections. Oncogenic HPV types 35, 52, 56 and 68 may be more important risk factors for cervical pre-cancer and cancer among women in Africa. Polyvalent hrHPV vaccines meant for African populations should protect against other hrHPV types, in addition to 16 and 18

APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS AND GENETIC ALGORITHMS IN DRYING OF FRUITS AND VEGETABLES : A REVIEW

oai:ojs2.laujet.com:article/1Fruits and vegetables play an important role in the diet of human beings and economic development of a country. They are cheapest and most available sources of important proteins, vitamins, minerals and essential amino acids. Considering the perishable nature of fruits and vegetables it is necessary to preserve them and drying is one such method to do it. The drying of fruits and vegetables is a complex operation that demands much energy and time. Due to this complexity, the use of drying mathematical models in estimating the drying kinetics, the behaviour and the energy needed in the drying of fruits and vegetables becomes indispensable. Numerous mathematical models, empirical and semi-empirical, have been proposed to estimate the drying characteristics of fruits and vegetables. But these models are generally solutions of simultaneous heat and mass transfer differential equations and the final result may be very complicated and difficult to use in actual drying systems. This article present a comprehensive review on the applications of artificial neural networks and genetic algorithms in drying of fruits and vegetables. The paper starts with the drying of fruits and vegetables, the introduction of basic theoretical knowledge of ANN and GA. Then summarize their application on modeling, predicting, and optimization of heat and mass transfer, thermodynamic performance parameters, and quality indicators as well as physicochemical properties of dried fruits and vegetables. Conclusively, opportunities and limitations of ANN and GA technique in are outlined to provide more ideas for research and development in this field