Epidemiological investigation on the prevalence of brown dog tick (Rhipicephalus sanguineus) and Babesia canis infection among household dogs was conducted in Ugep between March and August 2018. A total of 200 dogs randomly sampled from the four wards of Ugep were examined for tick infestation and B. canis infection. Of the 200 local and exotic dogs screened, 160 (80.0%) were positive for R. sanguineus. Out of 300 Rhipicephalus sanguineus collected, the most preferred sites for tick attachment were the ear 152 (50.7%), back 92 ( 30.7%), inter-digital space 28 (9.3%), neck 17 (5.7%) and abdomen 11 (3.7%). There was significant difference (x2 = 88.8. p< 0.001) in the prevalence of R. sanguineus according to the months of the year. Parasitological examination of 200 blood samples from randomly selected dogs in the four wards of Ugep, revealed that 23 (11.5%) were infected with B. canis. Blood samples screened from local and exotic breeds showed higher infestation of babesiosis in local dogs than exotic, although statistically insignificant (x2 = 3.9 p > 0.05) Male dogs were more infected 14 (12.4%) than females 9 (8.0%), with significant difference of (x2 = 9.3 p < 0.01). In respect to age, dogs within age group 1 – 6 showed the highest 11 (17.2%) infestation with significant difference of (x2 = 14.3 p < 0.01) between age groups. The high prevalence of R. sanguineus is of public health importance.
- Page(s): 01-06
- Date of Publication: 19 June 2019
- Cletus Inah Iboh Department of Animal Health and Environmental Biology, Faculty of Biological Sciences, Cross River University of Technology, PMB 1123 Cross River State, Nigeria.
References
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Cletus Inah Iboh "Prevalence of Rhipicephalus sanguineus and Babesia canis infection among dogs in Ugep, Yakurr Local Government Area of Cross River State, Nigeria" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.01-06 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/01-06.pdf
Essential oils are valuable natural products used as raw materials in many fields and can be define as a volatile and liquid aroma compounds from natural sources usually plants. They may be found in different parts of plant, some could be leaves, seed, flower, peel, and Stem bark. This study aims at screening the antimicrobial property from the essential oil extracted from Ricinodendron huedelotii fresh seed and stem bark using soxhlet method with two distinct solvents(N-hexane and ethyl acetate). Antibacterial activity was carried out using well agar diffusion technique against multiple resistance clinical isolates. The N-hexane oil extracts from Ricinodendron heudelotii seed revealed Bacillus subtilis and Pseudomonas aeruginosa having the widest zone of inhibition (15.0mm) at 100mg/ml while the least zone of inhibition (1.0mm) was recorded for Escherichia coliat 12.5mg/ml with essential oil ethyl acetate extracts from Ricinodendron huedelotiistem bark. Phytochemical analysis of the plant showed the present of active components such as cardiac glycoside, steroid, flavonoid, phenol, alkaloid, reducing sugar,tannin, saponin, pyrrolizidine, terpenoid and volatile oil. The present of these components enhances the effectiveness of plant essential oilin treating various diseases and helped to act as an antibacterial agent. Essential oil extracted from Ricinodendrn huedelotii seed using two solvents was further analysed by gas chromatography – mass spectrophotometer. The main constituents were Oxycycloheptadec 8-en-one (20.48%), Pentadecanoic acid (11.95%), n-propyl 9,12-Octadecadienoic acid (6.40%), Octadesetrienoic acid ethyl ester (10.30%), Ascorbic acid(11.27%), Gamolenic acid (17.74%), Linolenic acid, methyl ester (6.74%) and Eicososatrienoic acid (8.94%).Those components aid the antibacterial activities of essential oil from the seed and stem bark of Ricinodendron heudelotii. The results obtained suggest that the Ricinodendron heudelotii essential oil can serve as an effective antibacterial agent.
- Page(s): 07-25
- Date of Publication: 19 June 2019
- Oludare Temitope OsuntokunDepartment of Microbiology, Faculty of Science, Adekunle Ajasin University, Akungba-Akoko, Ondo State Nigeria.
- Thomas O. IdowuDepartment of Pharmaceutical Chemistry, Obafemi Awolowo University,Ile-Ife, Osun, state Nigeria.
- Jatto F.OyinyozaDepartment of Microbiology, Faculty of Science, Adekunle Ajasin University, Akungba-Akoko, Ondo State Nigeria.
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Oludare Temitope Osuntokun, Thomas O. Idowu, Jatto F.Oyinyoza, "In Vitro Analysis, Secondary Metabolite Screening and GC-MS Profile of Ricinodendron Heudelotii(Muh.Arg) Essential Oil Extracts Against Selected Multiple Drug Resistance Clinical Isolates" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.07-25 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/07-25.pdf
Culex quinquefasciatus Say is the principal vector of filariasis and a major biting nuisance. Palakkad district in Kerala has had a long history of Lymphatic filariasis and there has been a sudden increase in the number of filarial cases reported in the district from 2014. The present study aims at assessing the resistance status of Cx. quinquefasciatus in the district towards Organophosphates, and Pyrethroids and to investigate the occurrence of kdr mutation in the field populations of Cx. quinquefasciatus collected from 4 different sites. Susceptibility to organophosphates and pyrethroids were tested by WHO susceptibility kit using insecticide impregnated papers (Malathion - 5%, Cyfluthrin - 0.15%, and Deltamethrin - 0.05%). Biochemical analyses were done to identify the levels of detoxifying enzymes. All the 4 populations showed resistance to the three insecticides tested and higher resistance shown towards pyrethroids. Biochemical assays showed the presence of elevated enzyme levels and molecular assays using AS-PCR confirmed the presence of kdr mutations in the 4 populations of mosquitoes tested.
- Page(s): 26-29
- Date of Publication: 19 June 2019
- Anju Viswan,K Biopesticides & Toxicology Laboratory, Department of Zoology, University of Calicut, Malappuram Dist, Kerala, 673635, India
- Evangeline Surya Hermon Biopesticides & Toxicology Laboratory, Department of Zoology, University of Calicut, Malappuram Dist, Kerala, 673635, India
- Pushpalatha, E. Biopesticides & Toxicology Laboratory, Department of Zoology, University of Calicut, Malappuram Dist, Kerala, 673635, India
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Anju Viswan,K, Evangeline Surya Hermon, Pushpalatha, E. "Insecticide Susceptibility/ Resistance status and distribution pattern of kdr genotype in Culex quinquefasciatus of Palakkad District, Kerala" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.26-29 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/26-29.pdf
This paper presents a detailed speed control analysis of PV powered BLDC (Brushless DC Motor) motor equipped electric vehicles using sliding mode control. The performance of the BLDC motor is compared with PI and sliding mode control. The parameters like torque, speed, direct current and quadrature currents are considered for analysis. The test results of SMC method gives better performance than the existing control method. The results of the proposed system have been validated using MATLAB/SIMULINK.
- Page(s): 30-35
- Date of Publication: 19 June 2019
- Dr. R. IlangoProfessor, Department of EEE, K. Ramakrishnan College of Engineering, Tiruchirappalli, Tamilnadu, India.
- Prof. V.AshokkumarAsst. Professor, Department of EEE, K. Ramakrishnan College of Engineering, Tiruchirappalli, Tamilnadu, India.
- Prof. G. Gabriel Santhosh KumarAsst. Professor, Department of EEE, K. Ramakrishnan College of Engineering, Tiruchirappalli, Tamilnadu, India.
References
[1]. R.Forester,M.Ghassemi and A. Cota , Solar Energy Renewable Energy and the Environment, CC ,New York, 2012. [2]. R.Z.Wang and T.S.Ge, Advances in solar heating and cooling Woodhead Publishing 2016. [3]. R.Antonello,M.Carraro,A.Costababer “Energy-Efficient Autonomous Solar Water –pumping system for Permanent Magnet Synchronous Motors‖,” IEEE Trans. Industrial Electronics,vol.64,no.1pp.43- 51,Jan.2017. [4]. K.Dhayalini, “Active power filter for vehicle to grid application using bidirectional conversion techniques in manufacturing industries,”International Journal of Pure Applied Mathematics,vol.118,no,18,pp.1971-1980,2018. [5]. M. Jayalakshmi, G. Asha and K. Keerthana, “Control of Single Phase Z-Source Inverter Fed Induction Motor Using Simple Boost Controller,” International Journal of Emerging Trends in Electrical and Electronics,vol.10, no.3.pp.44-48,Apr.2014. [6]. M.Rezkallah, S.K. Sharma, B.Singh and D.R.Rousee, “Lyapunav function and sliding mode control approach for solar pv grid interface system‖,” IEEE Trans. Industrial Electronics, vol.64,no. 1, pp.785- 795, Jan 2017. [7]. O.Khan and W.Xiao, “An efficient modelling technique to simulate and control sub module intergrated PV system for single phase grid connection‖,” IEEE Trans. sustainable energy, vol.7, no.1, pp 96- 107, Sept2016. [8]. S.Titus , R.Pandiyan. “Intelligent control systems to improve the performance of PMDC Motor Drives” published in the Association for the advancement of modelling and simulation techniques in enterprises (AMSE) journal, vol.69, no.01, pp.69-84, July 2014, [9]. S.A. Priyadarshini, A. Durgadevi, R. Anbumozhi, G.Gabriel Santhosh Kumar. “Single phase nine level PWM Inverter with DC source for Photovoltaic Systems,” Imperial Journal of Interdisciplinary Research, vol.3, issue 9, 2017. [10]. S.Angayarkanni, A. Senthilnathan, R. Ilango. “SVPWM Controlled Permanent Magnet Synchronous Motor,” International Journal of Innovative Technology and Research . vol.1,issue1, pp. 042-045, 2013. [11]. M.Mohammadi,E.Adib, “Family of PWM Soft-Switching DC-DC Converters with coupled inductors,” IEEE Transactions Industrial Electronics,vol.62,no .6,pp 2018-2114,June 2015. [12]. R.Ilango, M.R.K.Venkatesa Vimal Chand. “Selective Harmonics Elimination - PWM Technique In Single Phase Hybrid Cascaded Multi Level Inverter Using Bee Algorithm‖,” International Journal Of Innovative Research In Engineering Science And Technology, ISSN no. 2320-981X, vol. 3 no. 4, pp.13-18, 2015. [13]. M.S. Agamy, M.H.Todorovic, “A High efficiency DC-DC converter topology suitable for distributed for large commercial and utility scale,” Proc. IEEE Conf, Sep2012
Dr. R. Ilango, Prof. V.Ashokkumar, Prof. G. Gabriel Santhosh Kumar "Analysis of PV Powered BLDC Drive using SMC Control Technique " International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.30-35 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/30-35.pdf
Water treatment has been a regulated approach in the purification of polluted water system getting rid of toxic and pathogenic agents before usage. Chlorination of water by Sodium-dichloro-iso-cyanurate is a common and cheap disinfection process with a limitation of depositing extra chlorine radical in the system after treatment which indirectly induces carcinogenic compounds as by-products in the living tissues. This research exploited the neutralization and elimination of residual chlorine in chlorinated and treated water sample(TW) actively by commercial water disinfectant known as water guard in form of Sodium-dichloro-iso-cyanurate with Ascorbic acid(AA) and its derivative; Sodium ascorbate (SA). Selected physicochemical parameters such as pH, in situ temperature, dissolved oxygen, turbidity, total dissolved oxygen, and fecal coliform were estimated on raw water sample (WS), mixture of raw water sample with water guard(WS+WG), mixture of raw water sample, water guard with the neutralizing agents(WS+WG+AA)/(WS+WG+SA) and the treated distilled water sample (TW). SA presented a better pH adjustment of 7.2 to AA of 6 after distillation. Dissolved oxygen was better with AA at 9.2mg/l to 86.8mg/l; while SA was from 9.2mg/l to 87.3mg/l after treatment, neutralization and distillation. Total chlorine in both cases was completely neutralized after distillation. Turbidity, TDS were significantly controlled below WHO standards. Fecal coliforms in both cases were completely cleared after treatment, neutralization, and distillation of the water sample. Both Ascorbic acid (AA) and Sodium ascorbate (SA) to an extent proved to be cheap and safe dechlorinating agents in the treatment of water.
- Page(s): 36-43
- Date of Publication: 20 June 2019
- Musa Omale.PDepartment of Internal Medicine, Ahmadu Bello University Teaching Hospital Shika, Zaria Kaduna State, Nigeria.
- Ochigbo-Ejembi Maria.OScientific and Industrial research Department National Research for Chemical Technology, Zaria Kaduna State, Nigeria.
- Ochigbo VictorScientific and Industrial research Department National Research for Chemical Technology, Zaria Kaduna State, Nigeria.
- Musa latayoScientific and Industrial research Department National Research for Chemical Technology, Zaria Kaduna State, Nigeria.
- Aishat lasisiPetrochemical Department National Research for Chemical Technology, Zaria Kaduna State, Nigeria.
- Yakubu Obadiah .SDepartment of Chemistry, University of Jos Plateau State, Nigeria.
- Mustapha MohammedIndustrial and Environmental Pollution Department, National Research for Chemical Technology, Zaria Kaduna State, Nigeria.
- Simon IstifanusIndustrial and Environmental Pollution Department, National Research for Chemical Technology, Zaria Kaduna State, Nigeria.
- Mohammed Yakubu .GAgricultural Technology Department, College of Agriculture Zuru, Kebbi State, Nigeria.
- Olabimtan Olabode. HIndustrial and Environmental Pollution Department, National Research for Chemical Technology, Zaria Kaduna State, Nigeria.
References
[1]. West, Larry (March 26, 2006). "World Water Day: A Billion People Worldwide Lack Safe Drinking Water". About.com. [2]. Pink, Daniel H. (April 19, 2006). "Investing in Tomorrow's Liquid Gold". Yahoo. Archived from the original on April 23, 2006. [3]. Cheremissinoff----etal.1981 (2019). [Online]Available…at: https://www.researchgate.net/publication/16484548_Pasturisation_of_naturally_contaminated_water_with_solar_energy [Accessed 20 May 2019]. [4]. Ciochetti—and—Metcalf.1984.(2019).[online]Available…at: https://sswm.info/sites/default/files/reference_attachments/CIOCHETTI%20and%20METCALF%201984%20Pasteurization%20of%20Naturally%20Contaminated%20Water%20with%20Solar%20Energy.pdf [Accessed 20 May 2019]. [5]. Acra et al. 1980 Almashriq.hiof.no. (2019). Water Disinfection Methods. [Online] Available at: http://almashriq.hiof.no/lebanon/600/610/614/solar-water/idrc/20-25.html [Accessed 20 May 2019]. [6]. Acra, A.et al .The halosol process for water disinfection and dehalogenation. Journal Volume: 45:5; Conference: 1. annual meeting of the International Society for Environmental Epidemiology, Upton, NY (USA), 13-15 Sep 1989; Journal ID: ISSN 0003-9896 [7]. (WHO 1993) World Health Organization. [8]. Scully et al., 1985. [Online] Available at: https://www.researchgate.net/publication/5930313_Reactions_of_Chlorine_with_Inorganic_and_Organic_Compounds_During_Water_Treatment--Kinetics_and_Mechanisms_A_Critical_Review [Accessed 20 May 2019]. [9]. Anon, (2019). [Online] Available at: https://www.academia.edu/33365007/A_historical_review_of_the_benefits_and_hypothetical_risks_of_disinfecting_drinking_water_by_chlorination [Accessed 20 May 2019]. [10]. Madungwe, E. and Sakuringwa, S. (2019). Greywater reuse: A strategy for water demand management in Harare. [11]. En.wikipedia.org. (2019). Water chlorination. [Online] Available at: https://en.wikipedia.org/wiki/Dechlorinator [Accessed 20 May 2019]. [12]. En.wikipedia.org. (2019). Sodium hypochlorite. [Online] Available at: https://en.wikipedia.org/wiki/Free_chlorine [Accessed 20 May 2019]. [13]. Scirp.org. (2019). Mmbando, E. (2004). Effectiveness of Water Guard as a Disinfectant in Water Treatment. MSc. Thesis, University of Dar es salaam, Dar es salaam. - References - Scientific Research Publishing. [Online] Available at: https://www.scirp.org/reference/ReferencesPapers.aspx?ReferenceID=1371012 [Accessed 20 May 2019]. [14]. Butterfield1943andWhitlock.Disinfection…of..water.1953https://www.sciencedirect.com/science/article/pii/B97803 40720189500114.https://doi.org/10.1016/B978-034072018-9/50011-4 [15]. NaturalHealth365. (2019). Chlorine neutralized by using vitamin C | NaturalHealth365. [Online] Available at: https://www.naturalhealth365.com/chlorine-vitamin-C-2520.html [Accessed 20 May 2019]. [16]. https://www.worldatlas.com , October 2, 2015. [17]. Method 8074 Membrane Filtration. Standard Methods for the Examination of Water and Wastewater, 9222 B and 9221 B. [18]. WHO (2008) Sodium dichloroisocyanurate in drinking-water. Background document for preparation of WHO Guidelines for drinking-water quality. Geneva, World Health Organization (WHO/HSE/AMR/08.03/3). [19]. Linus Pauling Institute, Oregon Stare University: "Bioavailability of Different Forms of Vitamin C". Retrieved 2013-09-27 [20]. UK Food Standards Agency: "Current EU approved additives and their E Numbers". Retrieved 2011-10-27. [21]. US Food and Drug Administration: "Listing of Food Additives Status Part II". Retrieved 2011-10-27. [22]. Australia New Zealand Food Standards Code “Standard. Retrieved 2011-10-27. [23]. http://msdssearch.dow.com/webapps/include/GetDoc.aspx?filepath=liquidseps/pdfs/noreg/609-00308.pdf&pdf=true
Musa Omale.P, Ochigbo-Ejembi Maria.O, Ochigbo Victor, Musa latayo, Aishat lasisi, Yakubu Obadiah .S, Mustapha Mohammed, Simon Istifanus, Mohammed Yakubu .G, Olabimtan Olabode. H "Neutralization of Residual Chlorine Deposit by Sodium-dichloro-iso-cyanurate on Disinfected Water Sample using Ascorbic Acid and Sodium Ascorbate Derivative" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.36-43 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/36-43.pdf
To improve decision making accuracy in any given airport requires selecting important variables that can be used in building a predictive model. The choice of appropriate independent variables will improve the model precision. However, the choice of the independent variables depends on the data that is recorded by the airlines and airports on the flights. The airport managers would want to understand the key factors behind flight delays. It is thus important to make a comparison on the mostly used factors in many modelling studies of flight delays and the factors that influence flight delays at Jomo Kenyatta International Airport (JKIA). The factors mostly used are the weather and the flight features. The factors available at JKIA include; the day of the flight (that is, Monday to Sunday), the month (that is, January to December), the airline, the flight class (that is, domestic or international), season (that is, summer (March to October) or winter (October to March), capacity of the aircraft, flight ID (tail number) and whether the flight had flown at night or during the day. The data used was obtained from Kenya Airports Authority for the JKIA flights for the period from March 2017 to March 2018. The analysis was done using R-Gui statistical software. Descriptive statistics were generated to give a general overview of how the above factors influenced flight delays at JKIA. Logistic model was then fitted to demonstrate how the factors could be applied in predicting flight delays. This model was also used to extract the significant factors in predicting flight delays. The selected factors were also compared on the performance they yielded in modelling as compared to features which had been used in other studies. The results revealed that the significant factors were days of the week, months, flight class and capacity. Modelling using these factors yielded models with average F1 score of 76.95%. This was better performance when compared to results from another study that used predictive features such as: the previous aircraft arriving late, weather, and departure timeand achieved an average F1 score of 58.7%. Another study predicted airline delays using flight departure times, and weather conditions. Their prediction algorithms achieved F1 score of 56.6%. This shows that the factors that influence flight delays at JKIA improves the performance of predictive models of flight delays.
- Page(s): 44-49
- Date of Publication: 21 June 2019
- Gachoki PKDepartment of Physical Sciences, Chuka University, P.O Box 109-60400, Chuka, Kenya
- Munyiri LMDepartment of Pure and Applied Sciences, Kirinyaga University, P.O Box 143-10300, Kerugoya, Kenya
- Moses MburuKenya Medical Research Institute, PO Box 230-80108,Kilifi, Kenya
References
[1]. Arjoun, M., Aaron, N. & Kenny, N. (2013). Predicting Flight on-Time Performance.Retrieved from https://pdfs.semanticscholar.org/ad5f/f1f4170218ac8b816e940e75a5e5f941fd42.pdf. [2]. Ball, M., Barnhart, C., Dresner, M., Hansen, M., Neels, K., Odoni, A. &Britto, R. (2010). Total delay Impact Study. In Nextor Research Symposium, Washington DC.Retrieved from http://www. nextor.org. [3]. Bandyopadhyay, R. J. & Guerrero, R. (2012). Predicting Airline Delays.Retieved fromhttp://cs229.stanford.edu/proj2012/bandyopadhyayguerrero-predictingflightdelays. pdf. [4]. Bureau of Transportation Statistics (2015). Transportation Statistics Annual Report. Retrieved from https://www.chegg.com/.../bureau-transportation-statistics-reports-time-performance. [5]. Bureau of Transportation Statistics, (2018). On-time Performance-Flight Delays at a Glance. Retrieved from http://libguides.utoledo.edu/Statistics [6]. Burgauer, D.& Peters, P. (2000). Airline Flight Delays and Flight Schedule Padding.Science Investigative Report, University of Pennsylvania, Philadephia. [7]. Cole, S. &Donoghue, T. (2014). Predicting Departure Delays of US Domestic Flights.Retrieved from https://cseweb.ucsd.edu/classes/wi17/cse258-a/reports/a062.pdf [8]. European Union Air Transport (2016). Air Transport Industry Analysis Report.Retrieved from http://www.academia.edu/download/3446218/Samenvatting_proefschrift_Burghouwt.doc [9]. Federal Aviation Administration (FAA) (2010). The Economic Impact of Civil Aviation on the U.S Economy.Retrieved from https://www.ncbi.nlm.nih. gov/pmc/articles/PMC1117774. [10]. Gachoki, P. K., &Muraya, M. M. (2019). Comparison of Models Used to Predict Flight Delays at Jomo Kenyatta International Airport. Asian Journal of Probability and Statistics, 1-8. [11]. Hsiao, C. Y.& Hansen, M. (2006). Econometric Analysis of US Airline Flight Delays with time-of-day Effects. Transportation Research Record: Journal of the Transportation Research Board, 104-112. [12]. International Civil Aviation Organization (ICAO) (2016). Annex 14 Volume 1, Aerondromes Design and Operations.Retrieved from www.ssd.dhmi.gov.tr/ getBinaryFile.aspx?Type=3&dosyaID=920 [13]. Ison, D. C., Weiland, L., McAndrew, I. & Moran, K. (2015). Identification of Air Traffic Management Principles Influential in the Development of an Airport Arrival Delay Prediction Model. Journal of Aviation/Aerospace Education and Research, 24(2), 39. [14]. Kalliguddi, A.M.&Leboulluec AK (2017). Predictive Modeling of Aircraft Flight Delay. UniversalJournal of Management 5(10): 485-491. [15]. Lawson, D., & Castillo, W. (2012). Predicting flight delays. Technical report, Computer Science Department, CS 229, Stanford University, Stanford, CA. [16]. Liu, W. &Cai, X. (2004). Statistical Analysis of Airport Network of China. Physical ReviewE69, 046106 [17]. Mueller, E.R.&Chatterji.G.B.(2002). Analysisof Aircraft Arrival andDepartureDelayEquilibrium.University of California, Berkeley. [18]. Rebollo, J. J., &Balakrishnan, H. (2014). Characterization and Prediction of Air Traffic Delays. Transportation Research Part C: Emerging Technologies, 44, 231-241. [19]. Sridhar, B., Wang, Y., Klein, A., &Jehlen, R. (2009, June). Modeling flight delays and cancellations at the national, regional and airport levels in the United States. In 8th USA/Europe ATM R&D Seminar, Napa, California (USA). [20]. Sternberg, A., Soares, J., Carvalho, D. & Ogasawara, E. (2017). A Review on Flight Delay Prediction.arXiv preprint arXiv:1703.06118. [21]. Steven, A.& Clifford, W. (2007). The Effect of FAA Expenditures on Air Travel Delays. Journal of Urban Economics 63 669–678 [22]. Zou, B. & Hansen, M. (2012). Impact of Operational Performance on Air Carrier Cost Structure:Evidence from US airlines. Transportation Research Part E: Logistics and Transportation Review, 48(5), 1032-1048
Gachoki PK, Munyiri LM and Moses Mburu "Application of Predictive Modelling to Determine Factors Influencing Flight Delays at Jomo Kenyatta International Airport, Kenya" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.44-49 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/44-49.pdf
A preliminary experiment was carried out to analyze the growth performance of Pleurotus florida mushroom culture using Potatoes Dextrose Agar (PDA), based on the stipe size of the mushroom. This study is mainly aimed to investigate how fast the mycelia of a mushroom can grow in a culture media plate in relation to the length of stipe. Studies revealed that the joint portion of cap and stripe produced vigorous mycelium growth in minimum time; the average maximum growth was obtained from the shortest mushroom stipe. This shows that, the mycelium is more viable or active in a growing mushroom with short stipe than a fully grown mushroom with a longer stipe. Different length of mushroom was used for the experiment. Three treatments were observed: Treatment (A1, A2, A3), (B1, B2, B3) and (C1, C2, C3). Where treatment (C1, C2, C3) was the least in the stipe size, but had the highest or rapid growth rate of mycelia in the petri dish. This was followed by treatment (B1, B2, B3), and lastly treatment (A1, A2, A3). The study concluded that there are more active mycelia with shorter stipe of Pleurotus florida mushroom. This will help to speed up in the spawn preparation for the production of mushroom.
- Page(s): 50-52
- Date of Publication: 22 June 2019
- Haastrup, N. O.Ecologist, Forest Conservation and Protection Department, Forestry Research Institute of Nigeria, Jericho, Ibadan, Nigeria.
- Oladipo, A.DPlant scientist, Forest Conservation and Protection Department. Forestry Research Institute of Nigeria, Jericho, Ibadan, Nigeria
References
[1]. Alam, S.M., Raza, M.S. (2001). Importance of mushrooms. Industry and Economy. [2]. Chang, S.T. and W.A. Hayes(1978). The biology andcultivationof edible mushrooms. Academic Press,INC. London [3]. Masarirambi, M.T., Mamba, M.B. and Earnshaw, D.M. (2011). Effect of various substrates on growth and yield of oyster mushrooms. Asian J. Agric. Sci. 3(4): 375-380 [4]. Santosh, K. Amarendra, .K. Gireesh, C., Nadeem, A., and Tribhuwan, K.. (2018). Optimization of Mycelia Growth Parameters for Pleurotus floridaand Pleurotus sajor-caju. International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706Special Issue-7pp. 4818-4823
Haastrup, N. O., Oladipo, A.D "Effect of Stipe Size on the Mycelia Performance of Pleurotusflorida" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.50-52 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/50-52.pdf
This paper highlights cultivation procedures of Pleurotussajor-cajuas a source of food, income in home gardens and making good use of materials that are termed waste which could be hazardous to the environment when not recycled. Cultivation of Oyster mushroom (P.sajor-caju) with commercial viability has been prepared in a way of model, keeping in view the agro-climatic conditions and other related aspects for successful cultivation of the mushroom. Evaluation on the growth, yield and biological efficiency of P.sajor-cajucultivated on Pennisetumpurpureum (Elephant grass) was investigated. The sawdust of Triplochitonscleroxylon was used as a control measure for mushroom cultivation. Each treatment was replicated three times. Each of the sample consisted of 400g weight of substrate per bag. The produce of the mushroom, mycelia growth, diameter of the pileus, length of stipe, mushroom height were analyzed. The results indicated that the mean yield (g) produced from elephant grass substrates, though not higher than the saw dust, but it is enough weight for a better yield 48.65±7.87 and sawdust with their yield values of, 53.95±4.62 respectively. The biological efficiency (%) obtained is an indication that the P.sajor-caju utilizes the given substrates effectively. The highest B.E was found in elephant grass followed by sawdust which is the control with mean value of 95.29, and 40.05% respectively. The length of stipe, diameter of pileus and mushroom height showed that the mushroom produced from the two substrates used were of good sizeable stage.
- Page(s): 53-55
- Date of Publication: 22 June 2019
- Haastrup, N. O.Ecologist, Department of Forest Conservation and Protection, Forestry Research Institute of Nigeria, Jericho, Ibadan, Nigeria
- Aina Oduntan A.O.Ecologist, Department of Forest Conservation and Protection, Forestry Research Institute of Nigeria, Jericho, Ibadan, Nigeria
References
[1]. Chang, et al. (1981).The cultivation and nutritional value of Pleurotussajor-caju.Article in Applied Microbiology and Biotechnology 12(1):58-62 • [2]. Ekpo, E.N; Olasupo, O.O and Eriavbe, M.A (2008). Effect of different supplement on the growth and yield of Pleurotusflorida. Obeche Science journal .Vol 27(1): 23-25 [3]. Nurudeen T.A; Ekpo E.N; Olasupo O.O and HaastrupN.O. (2013).Yield and Proximate Composition of Oyster Mushroom (PleurotusSajor - Caju) Cultivatedon Different Agricultural Wastes.Science Journal of Biotechnology ISSN:2276-6375http://www.sjpub.org/sjbt.html © Author(s) 2013. CC Attribution 3.0 License. [4]. Ogunsanwo, O. Y.(2001). Effective Management of Wood Waste for sustainable Wood Utilization in Nigeria, Popoola, L., J. E. Abu, and P. I. Oni (Eds.) Proceedings of the 27thAnnual Conference of the Forerstry Association of Nigeria, Abuja, Nigeria. Pp. 226 -234.
Haastrup, N. O., Aina Oduntan A.O. "Comparative Study on the Growth and Yield of Pleurotus Sajor-Caju Mushroom Cultivated on Pennisetum Purpureum (Elephant Grass) and Saw Dust of Triplochiton Scleroxylon as an Environmental Control Measure" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.53-55 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/53-55.pdf
Increasing performance and decreasing cost of microprocessors are making it feasible to move more processing power to the data source. This allows us to investigate new methods of storage delivery and management of data that were not plausible in the past. Our architecture, inspired by agent-based techniques and active disk technology, promotes an open source agent storage management platform called SPADE that is adopted to implement an agent based simulation model called SABSA. Mobile agent technology and Map-Reduce functionality has been promoted as an emerging technology that makes it much easier to design, implement, and maintain distributed system. In order to Realize the storage technology’s full potential requires careful consideration across a wide range of metadata file handling systems and networking issues. This research contrasts four network storage architectures: Store and forward processes(SAF), Object Storage Devices(OSD), Mobile agent Domain Controller (DMC) enhanced with map-reduce function and Mobile agent based Domain Controller with child DMC enhanced with Map-reduce (ABMR): both handling sorted and unsorted metadata. To estimate the potential performance benefits of these architectures, we developed an analytic simulation model and then performed experiments based on the identified storage architectures. Our results suggest that all the agent based storage architectures minimize latencies up to 40 % and OSD architectures and consequently increasing performance in the same margin.
- Page(s): 56-73
- Date of Publication: 22 June 2019
- Benard Ong’era OseroDepartment of Computer Science, Chuka University, Kenya
- Dr. Elisha AbadeSchool of Computing and Informatics, University of Nairobi, Kenya
- Dr. Stephen MburuUniversity of Nairobi, Kenya
References
[1]. Al-shishtawy, A. (2012) Self-Management for Large-Scale Distributed Systems. [2]. Alberola, J. M. et al. (2010) ‘A performance evaluation of three Multiagent Platforms’, Artificial Intelligence Review, 34(2), pp. 145–176. doi: 10.1007/s10462-010-9167-9. [3]. Amazon (2019) 10-Minute Tutorials. Available at: https://aws.amazon.com/getting-started/tutorials/. [4]. Andrei, P. S. et al. (2014) ‘Evolution towards Distributed Storage in a Nutshell’, pp. 1267–1274. [5]. Anon (2016) Concordia White paper. Available at: https://www.cis.upenn.edu/bcpierce/629/papers/Concordia-Whitepaper/ (Accessed: 17 March 2016). [6]. Arias (2018) Introduction to Redis:Installation,CLI commands and Data-Types. [7]. Avilés-González, A., Piernas, J. and González-Férez, P. (2014) ‘Scalable metadata management through OSD+ devices’, International Journal of Parallel Programming, 42(1), pp. 4–29. doi: 10.1007/s10766-012-0207-8. [8]. Caidi, M. et al. (2008) ‘The Google File System Sanjay’, Journal de Chirurgie, 145(3), pp. 298–299. doi: 10.1016/S0021-7697(08)73776-1. [9]. Ceph (2016) Welcome to Ceph. Available at: http://docs.ceph.com/docs/master/# (Accessed: 30 April 2019). [10]. Chaturvedi, V. (no date) Deep Dive into Docker. Available at: https://www.edureka.co/blog/what-is-docker-container (Accessed: 26 March 2019). [11]. CORP (2016) Content addressed storage systems, EMC. Available at: http:www.emc.com/products/systems/centera.jsp?openfolder=platform (Accessed: 26 June 2016). [12]. Docker (2019) Docker Docs. Available at: https://docs.docker.com/v17.09/compose/install/ (Accessed: 27 March 2019). [13]. EMC2 (2008) Where information lives:current benefit and future potential technology concepts and business considerations. [14]. Escriv, M., C, J. P. and Bada, G. A. (2014) ‘A Jabber-based Multi-Agent System Platform ∗’, (January 2006). doi: 10.1145/1160633.1160866. [15]. Escriva, R. and Wong, B. 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Benard Ong’era Osero, Dr. Elisha Abade, Dr. Stephen Mburu "Performance Analysis of an Agent Based Architecture using Map-reduce: Using the SABSA Simulator " International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.56-73 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/56-73.pdf
Low back pain a musculoskeletal problem that affects about 50 to 80 percent of adults in the world at some time caused by a problem in the muscle, ligaments, discs, joints or nerves of the spine. Despite the prevailing cases in Nigeria, there is no currently published data on assessment of MRI findings of patients with lower back pain in this region. A retrospective cross-sectional study using secondary data was carried out to sort out the causal effect of various MRI findings/investigations upon non-traumatic low back pain at the radiology department, of one of Nigerian Teaching Hospitals in Jos. 200MRI images comprising 108 males and 92 female of the lumbar spine for three years (2012-2014) of adults aged 18 – 80 years were used in the study and were evaluated according to age, sex, occupation and region on lumbar spine. Data was analysed for descriptive statistics such as percentage and mean using SPSS version 19.0. Results show that, patients with non-traumatic low back pain are mostly prone to have Lumbar Spondylosis and Disc Prolapse which is the most common pattern of MRI findings mostly affecting farmers and civil servants within 31 – 50 years of age at the L4/L5 region of the spine. While, Lumbar Spondylosis was more prevalence among civil servants affecting mostly male than female, Disc Prolapse was more in farmers affecting mostly females than male. The MRI findings will assist the radiologist, radiographers and other medical personnel to understand the common MRI findings pattern of patients with low back pain so as to help in communication between surgeons and radiologists for medical decisions and optimal management of the patient’s clinical issues.
- Page(s): 74-81
- Date of Publication: 23 June 2019
- Samson D. YusufLecturers Department of Physics, Nasarawa State University, Keffi, Nigeria
- Lucas W. LumbiLecturers Department of Physics, Nasarawa State University, Keffi, Nigeria
- Ibrahim UmarLecturers Department of Physics, Nasarawa State University, Keffi, Nigeria
- Tejumade, F. TokumboStudent Department of Physics, Nasarawa State University, Keffi, Nigeria
References
[1]. Wise C. Back pain and common musculoskeletal problem. 2nd ed. ACP Medicine; 2003, Sec, 17. [2]. Chou R, Thompson T, Dahlo GH. Diagnosis and treatment of low back pain. Journal of Annual Internal Medicine 2010; 20(9):1-12. [3]. Secer M, Muradov J, Dalgic, A. Evaluation of congenital lumbosacral malformations and neurological findings. Journal of Turkish Neurosurgery 2009; 8(8):1-8. [4]. Igbinedion B, Akhigbe A. Correlation of MRI findings in patients with low back pain. Nigeria Medical Journal 2011; 52(40):28-34. [5]. Harvey M. Black’s medical dictionary. 7th ed. London: Soho Square; 2006, 48(30):50-60. [6]. Polansky R. Diagnosing acute low back pain. Journal of Medicine and Surgery 2011; 20(5):1-6. [7]. Davidson S. Davidson’s principles and practice of Medicine. 20th ed. London: Churchill Livingstone; 2006, 29, 31, 40, 45. [8]. Deyo RA. Three-year incidence of low back pain in an initially asymptomatic cohort. Journal of Imaging Science 2007; 29(41):1-10. [9]. Wheeler AH. Low back pain and sciatica. 1st ed. London: WebMD professionals; 2011, 11, 17. [10]. Atul A, Abana I. Long-term outcomes of surgical and nonsurgical management of lumbar spinal stenosis from the Maine lumbar spine study. Journal of Physiological Sciences 2010; 40(4):1-9. [11]. Harris B, Helfard J, Woolf CB. Diagnostic evaluation of low back pain with emphasis on imaging. Journal of Radiology 2009; 40(20):1-10. [12]. Jarvik JG. Imaging of adults with low back pain in the primary care setting. Journal of Neuroimaging 2003; 20(12):1-9. [13]. Slovin Q. Imaging of adults with low back pain in the primary care setting and sample size formula. Journal of Neuroimaging 2005; 21(19):9-20. [14]. Cassazza AG. Diagnostic evaluation of low back pain with emphasis on imaging. Journal of Radiology and Imaging 2006; 30(16):1-11. [15]. Bach ST, Holten CJ. Accessement of low back pain. Journal of Clinical Medicine 2009; 10(18):1-10. [16]. Pease H, Henry A, Ernest M. Causes of low back pain. Journal of Clinical Medicine 2007; 10(20):1-8. [17]. Federal republic of Nigeria 2006 population census (PDF). Web.archive.org. Archived from the original (PDF) on March 5, 2012; [accessed 24 November 2018]. [18]. Wikipedia. Jos, https://en.m.wikipedia.org/wiki/jos; [accessed 28 November 2018]. [19]. Muraki G, Lois T, Hollingworth W. Surgery for degenerative lumbar spondylosis Journal of Imaging Sciences 2008; 30(14):1-11. [20]. Fishly F, Middleton I, Gillan M. Low back pain, influence of early MR imaging or CT on treatment and outcome of multi-center randomized trial. Journal of Radiology 2004; 69(27):1-13.
Samson D. Yusuf, Lucas W. Lumbi, Ibrahim Umar, Tejumade, F. Tokumbo "Evaluation of Magnetic Resonance Imaging Findings in Adult Patients with Non-Traumatic Low Back Pain " International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.74-81 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/74-81.pdf
This study investigated the prevalence and health implications of geohelminth ova in selected households’ backyards in Okitipupa Local Government Area of Ondo State. A total of 500soil samples were obtained from tendifferent streets, and examined for geohelminth ova using zinc sulphate flotation technique. The results showed that 67.2% of the soil sampled were positive for different species of the parasites. Four different species of soil-transmitted helminths were encountered from the sampled soil, namely, Ascarislumbricoides (30%), Acylostomaduodenale(17.2%), Trichuiristrichiura (12.4%) and Strongyloidesstercoralis (7.6%). Soil sampled from Okeloro street was the most contaminated (80%), while the lowest (60%) were found among Government Reserved Area (G.R.A.), New-garage and Old-garage streets. The distributions of geohelminths ova among the streets revealed that three streets were significantly different from others. The study indicated high rate of helminths contamination of the environments in the study area. There is therefore a need to enlighten the general public on the contamination of environment with faecal matters in order to prevent Soil-transmitted helminth infections.
- Page(s): 82-85
- Date of Publication: 23 June 2019
- Bagbe, A.S.Department of Biological Sciences, Ondo State University of Science and Technology, Okitipupa, Nigeria
- Bagbe, A.Department of Mathematical Sciences, Ondo State University of Science and Technology, Okitipupa, Nigeria
References
[1]. Arora DR, Arora B (2006). Medicine Parasitology. Second edition. CBS publishers and distributors. New Delhi, pp 212-213. [2]. Baker M C, Krotkik K, Sankara D P (2013). Measuring treatment coverage for neglected tropical disease control program: analysis of a survey dedsign. Am. J. Epidemiology 178: 268-75. [3]. Bethony J, Brooker S, Albonico M, Geiger SM, Loukas A, Diemert D, Hotez PJ (2006). Soil-transmitted helminth infections:ascariasis, trichuriasis, and hookworm. The Lancet.367(9521): 1521–1532. [4]. Dada E O, Egbunu A A (2016). Dispersion of human intestinal Geohelminth ova in selected refuse dumpsites in Igbara-Oke, Ifedore, Local Government Area, Ondo State, Nigeria. International Journal of Current Microbiology and Applied Sciences 5 (4): 924-928. [5]. Murray CJ, Vos T, Lozano R, Naghavi M, Flaxman AD (2013). Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 380: 2197–2223. [6]. Ogbolu DO, Terry Alli AO, Amoo AOJ, Olaosun II, Ilozavbie GW, Olusoga-ogbolu FF (2011). High-level parasitic contamination of soil sample in Ibadan metropolis. African Journal of Medicine and Medical Sciences.40: 8587. [7]. Stephenson LS (1987). Impact of helminthes infection on human nutrition. Taylor and Francis, New York; 252-260. [8]. Stojčević D, Sušic V, LućingerS (2010).Contamination of soil and sand with parasite elements a risk factor for human health in public parks and playgrounds in Pula, Croatia. Veterinarski Achiv. 80(6): 733-742. [9]. Ukpai OM, Ugwu CD (2003). The Prevalence of Gastro-Intestinal Tract Parasites in Primary School Children in Ikwuano Local Government Area of Abia State, Nigeria. The Nigerian Journal of Parasitology, 24, 129-136. [10]. World Health Organization, (2013).“Soil-transmitted helminth infections”factsheet, No.366.Retrieved 2014-01-09.
Bagbe, A.S. and Bagbe, A. "Statistical Analysis and Health Implications of Geohelminth Ova in Selected Households’ Backyards in Okitipupa Local Government Area of Ondo State, Nigeria" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.82-85 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/82-85.pdf
The paper studies the effects of crude oil price, its volatility and subsidy removal on Nigeria’s economic growth. The time series data on gross domestic product (GDP) and crude oil price (COP) used covered the period of 1973 to 2017. GARCH(1,1) was adopted to measure volatility of crude oil price. And the results of least squares(LS) estimation method applied to the multiple regression model specified showed that; COP and its volatility have positive effect on economic growth, significant at 1% and 5% levels respectively. This implies that the effects of positive shocks of global oil price are greater than negative shocks, hence, GDP growth rate is higher when crude oil price rises than GDP decline rate when crude oil price drops. The result also showed negative effect of subsidy removal on economic growth and it is significant under 1% level. This implies that GDP decreases as government withdraws subsidy. Hence, it becomes imperative for government and policy makers to reassess its economic policies frameworks to make Nigeria more investment friendly, so that other areas of the sector can contribute more to GDP growth.
- Page(s): 86-93
- Date of Publication: 23 June 2019
- Amaefula C.GDepartment of Mathematics and Statistics, Federal University Otuoke Bayelsa, Nigeria
References
[1]. Adebayo B.,(2018). Nigeria overtakes India in extreme poverty ranking; June 26, 2018 CNN. Retrived March 23rd, 2019 from: https://edition.cnn.com/2018/06/26/africa/nigeria-overtakes-india-extreme-poverty-intl/index.html [2]. Akinlo, T., Apanisile, O.T. (2015), The impact of volatility of oil price on the economic growth in sub-saharan Africa. British Journal of Economics, Management and Trade, 5(3), 338-349. [3]. Akinwale, Y., Jesuleye, O. and Siyanbola, W., (2013). Empirical Analysis of the Causal Relationship Between Electricity Consumption and Economic Growth in Nigeria. British Journal of Economics, Management & Trade, 3(3), pp. 277-295. [4]. Akinyemi, O., Alege, O., Oluseyi, O.Amaghionyeodiwe, L., &Ogundipe, A. (2015): „Fuel Subsidy Reform and Environmental Quality in Nigeria‟ International Journal of Energy Economics and Policy, 5(2): 540-549. [5]. Amir M. T, Mohammad A. S,(2017). The Impact of Oil Price Volatility on the Economic Growth in Iran: An Application of a Threshold Regression Model. International Journal of Energy Economics and Policy, 2017, 7(4), 165-171. [6]. Ani, W., Ugwunta, D., Inyiama, O. and Eneje, B. (2014) Oil Price Volatility and Economic Development: Stylized Evidence in Nigeria, Journal of Economics and International Finance, 6(6), 125 – 133. [7]. Benramdane, A. (2017), Oil price volatility and economic growth in Algeria. Energy Sources, Part B. Economics, Planning, and Policy, 12(4), 338-343. [8]. Delavari, M., Bakhsh, S.S., Bozorgi, Z.D. (2008), The examination of the oil price effect on the economic growth by using asymmetric cointegration. Quarterly Energy Economics Review, 5(18), 65-80. [9]. Gyoh, S. (2012) Nigeria The case against fuel subsidy and the argument for deregulated petroleum sub sector Retrieved March 19, 2012. https://www.awarenessforex.com/ [10]. International Monetary Fund (2018). Nigeria: Out of Recession and Looking Beyond Oil. Retrieved March 15, 2018 from https://www.imf.org/en/News/Articles/2018/03/15/na031518-nigeria-out-of-recession-and-looking-beyond-oil [11]. Jelilov, G., & Alimi, R. (2017).Discussion on Subsidy Removal from Nigerian Economy; Effect on Growth. The Journal of Middle East and North Africa Sciences, 3(8), 20-32. [12]. Lardic, S., Mignon, V. (2008), Oil prices and economic activity: An asymmetric cointegration approach. Energy Economics, 30(3), 847-855. [13]. Mgbame, C.O., Donwa, P.A., Onyeokweni, O.V. (2015), Impact of oil price volatility on economic growth: Conceptual perspective. International Journal of Multidisciplinary Research and Development, 2(9), 80-85. [14]. Musa, A., Hounsou, R., & Adeyele, I. T. (2014). The Impact Of Fuel Subsidy Removal On Socio-Economic Development In Nigeria An Econometric Investigation. International Journal of Economics, Commerce, and Management. 2(12), 1-14. [15]. Nwanna, I.O., Eyedayi, A.M. (2016), Impact of crude oil price volatility on economic growth in Nigeria (1980-2014). IOSR Journal of Business and Management (IOSR-JBM), 18(6), 10-19. [16]. Ogundipe, S., Ndujihe, C., Ahiuma-Young, V., Idonor, D., & Adeoye, Y. (2011). We didnt okay subsidy removal - OPS. Retrieved March 13, 2019, from http://www.vanguardngr.com/2011/10/we-didnt-okay-subsidy-removal-ops/ [17]. Olomola, P.A., Adejumo, A.V. (2006), Oil price shock and macroeconomic activities in Nigeria. International Research Journal of Finance and Economics, 3, 28-34. [18]. Oriakhi, D.E., Iyoha, D.O. (2013), Oil price volatility and its consequences on the growth of the Nigerian economy: An examination (1970- 2010). Asian Economic and Financial Review, 3(5), 683-702. [19]. Oyeyemi, A. M. (2013) The Growth Implications of Oil Price Shock in Nigeria, Journal of Emerging Trends in Economics and Management Sciences, 4(3), 343-349. [20]. Sarzaiem, A. (2007), Impacts of oil price shocks on economic variables in a VAR model. Quarterly Energy Economics Review, 4(12), 27-51 [21]. The Guardian Newspaper (2011), Fuel subsidy, who is subsidising Retrived March 23rd, 2019 from: https://guardian.ng/opinion/columnists/fuel-subsidy-who-is-subsidising-who-1/ [22]. Umar, H., & Umar, M. (2013): An assessment of the Direct Welfare Impact of Fuel Subsidy Reform in Nigeria. American Journal of Economics, 3(1): 23-26.
Amaefula C.G "The Effects of Crude Oil Price, its Volatility and Subsidy Removal on Economic Growth: Experience from Nigeria " International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.86-93 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/86-93.pdf
Wheatgrass is a food prepared from the cotyledons of the common wheat plant, Triticum aestivum (subspecies of the family Poaceae). It is sold either as a juice or powder concentrate . It contains a plethora of vitamins, minerals, amino acids and vital enzymes like superoxide dismutase and cytochrome oxidase. The vitamin content makes it an important adjuvant in anti-allergic and anti-asthmatic treatment; it has maximum health benefits like an advance therapy for cancer as well as thalassemia disease. Some of the essential elements in Wheatgrass are Manganese, Calcium, Selenium, Magnesium, Zinc and Iron. The study of essential nutritional elements (Calcium, Magnesium, Iron, Zinc and Chromium) in wheatgrass powder using Flame Atomic Absorption Spectroscopy revealed that indeed it contains a substantial amount of these elements; calibration curves of Calcium, Magnesium, Iron, Zinc and Chromium were drawn and had good positive linear regression coefficients of R2 =0.9968, 0.9992, 0.9974, 0.9996 and 0.9990 respectively. The correlation graphs of Magnesium vs. Calcium and Iron vs. Zinc were drawn. Iron vs. Zinc pair had lower linear correlation coefficient (R²=0.75220) as compared to Magnesium vs. Calcium (R2=0.9295). This suggests that species in the same group of the Periodic Table exhibited much higher correlation than the ones in the same row of the periodic table.
- Page(s): 94-102
- Date of Publication: 29 June 2019
- S.M. OndwasiDepartment of Chemistry, Jomo Kenyatta University of Agriculture and Technology, P.O. Box, 62000 – 00200, Nairobi, Kenya
- P. G. MuigaiDepartment of Chemistry, Jomo Kenyatta University of Agriculture and Technology, P.O. Box, 62000 – 00200, Nairobi, Kenya
References
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S.M. Ondwasi and P. G. Muigai "Determination of Calcium, Magnesium, Iron, Zinc and Chromium Contents in Wheatgrass Powder Sold in Nakuru Town, Thika Town and Nairobi City Regions, Kenya" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.94-102 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/94-102.pdf
This research work was conducted on the design and implementation of a diabetes prediction system, a case study of Fudawa Health Centre. This research will help in automating prediction of diabetes even before clinicians arrived. The current process of carrying this activity is manually which tends not to analyzing data flexible for the doctors, and transmission of information is not transparent. The system was design using Java Programming Language, Weka Tool, and MySQL (Microsoft Structured Query Language) as the back end and a strategic approach to analyse the existing system was taking in order to meets the demands of this system and solve the problems of the existing system by implementing the naïve beyes classifier. The implementation of this new system will help to reduce the stressful process, doctors’ face during prediction of diabetes, the result of the experiment shows that the proposed system has a better prediction in terms of accuracy.
- Page(s): 103-111
- Date of Publication: 29 June 2019
- Desmond Bala BisanduDepartment of Computer Science University of Jos, Nigeria
- Dorcas Dachollom DatiriDepartment of Computer Science University of Jos, Nigeria
- Eva Onokpasa3Department of Computer Science University of Jos, Nigeria
- Godwin ThomasDepartment of Computer Science University of Jos, Nigeria
- Musa Maaji HarunaDepartment of Computer Science University of Jos, Nigeria
- Aminu AliyuFederal University Kebbi, Nigeria
- Jerry Zachariah YakubuDepartment of Science and Technology University of Jos, Nigeria
References
[1]. Acharya, Rajendra, U and Yu, Wenwei, (2010).Data Mining Techniques in Medical Informatics. The Open Medical Informatics Journal, PMCID: PMC2916206. [2]. Aflori C., and Craus, M., (May 2007) Grid Implementation of the Apriori algorithm Advances in Engineering Software, 38(5), pp. 295-300. A. J.T. Lee, Y.H. Liu, H.Mu Tsai, H. [3]. Anbarasi M., (2010). ‘Enhanced Prediction of Heart Disease with Feature Subset Selection using Genetic Algorithm,’ International Journal of Engineering Science and Technology, 2(10), 5370-5376. [4]. Bronzino, D. Joseph, Medical Devices and Systems, 2006 [5]. Chauraisa V., and Pal, S.,(2013). ‘Data Mining Approach to Detect Heart Diseases’, International Journal of Advanced Computer Science and Information Technology (IJACSIT), 2, (4), pp 56-66. [6]. Clifton, Christopher (2010), Encyclopedia Britannica: Definition of Data Mining Retrieved 2016. [7]. Data Mining Curriculum, ACM SIGKDD, 2006-04-30, retrieved 2016 [8]. Fayyed, Usama., (15 June1999), First Editorial By Editor-In-Chief, SIGKDD Explorations 1:1, doi: 10.1145/2207243.2207269 [9]. Fayyed, Usama., Piatetsky- Shapiro, Gregory., Smyth, Padhraic., (1996) From Data Mining to Knowledge Discovery in Databases. [10]. Han J.,and Kamber, M. (2010). Data Mining: Concepts and Techniques, 2nd ed., the Morgan Kaufmann Series. [11]. Han Jiawei., & Kamber, Micheline. (2001), Data Mining: Concepts and Techniques, pp. 5 [12]. Hastie, Trevor, Tibshirani Robert, Friedman, Jerome. (2009), ‘The Elements of Statistical Learning’, [13]. HninWintKhaing,(2011). “Data Mining based Fragmentation and Prediction of Medical Data”, IEEE. [14]. Hui Lin,H-W. Wu, (2009) ‘Mining frequent patterns in image databases with 9DSPA Representation’, Journal of Systems and Software, 82(4), pp.603-618. [15]. Lazakidou A. Athina and Siassiakos M. Konstantinos, (2009), ‘Handbook of Research on Distributed Medical Informatics and E-health’, [16]. Madzov, G., Gjorgevikj, D. and Chorbev, I. (2009) ’A multi-class SVM classifier utilizing binary decision tree’, informatica, vol.33, NO.2, pp233-241 [17]. Maimon,Oded., Rokach, Lior.,( 2010), Introduction to knowledge discovery in databases, University of Tel Aviv, Springer Science and Business Media. [18]. Mena, Jesus. (2011), Machine Learning Forensics for Law Enforcement, Security and Intelligence, Boca Raton, FL: CRC Press, ISBN 978-1-4398-6069-4 [19]. Obenshain, Mary, K., (2004) Application of Data Mining Techniques to Healthcare Data, Statistics for Hospital Epidemiology [20]. Paitetsky-Shapiro, Gregory. Parker,Gary. (2011), Lesson: Data Mining, Knowledge Discovery: An Introduction. [21]. Quinlan, J. Induction of Decision Trees. Mach Learn 1986; 1:81-106. [22]. Reutemann, Peter. Witten, Ian, H. (2010), WEKA Experiences with a Java Open- source Project, Journal of Machine Learning Research, 11: pp 2533-2541 [23]. Robert. E., Hoyt, A and Yoshihashi, Ann, (2014), ‘Health Informatics, Practical Guide for Health Care’, 6th ed., See e.g. OKAIRP (2005) Fall Conference, Arizona State University: Data mining. [24]. Shanta, Kumar, .Patil, P and Kumaraswamy, Y.S., (2011). “Predictive data mining for medical diagnosis of heart disease prediction” IJCSE, 17. [25]. Srinivas, K., (2010). “Analysis of Coronary Heart Disease and Prediction of Heart Attack in coal mining regions using data mining techniques”, IEEE Transaction on Computer Science and Education (ICCSE), p(1344 - 1349). [26]. Witten, Ian, H., Frank, Eibe. and Mark A., (2011). Data Mining: Practical Machine Learning Tools and Techniques (3rd Ed.) Elsevier, ISBN 978-0-12-374856-0 [27]. World Health Day (2016) WHO calls for global action to halt rise in and improve care for people with diabetes http://www.who.int/diabetes/global-report/WHD16-press-release-EN_3.pdf?ua=1 [28]. Yoo, Illhoi., Alafaireet, Patricia., Marinov, Miroslav., Pena-Hernandez, Keila, Gopidi, Rejitha., Chang, Jia-Fu and Hua, Lei, (2011). Data Mining in Healthcare and Biomedicine: A Survey of the Literature, Med Syst DOI, Springer.
Desmond Bala Bisandu, Dorcas Dachollom Datiri, Eva Onokpasa, Godwin Thomas, Musa Maaji Haruna, Aminu Aliyu, Jerry Zachariah Yakubu "Diabetes Prediction Using Data Mining Techniques " International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.103-111 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/103-111.pdf
In this paper, the flexibility of the Generalized Euclidean Least Square (GELS) Approximation scheme is explored to obtain a more accurate approximation to the nonlinear part of Bratu-Gelfand equation. The resulting equation is solved using differential transform method and perturbation method. The problem is also solved using the conventional differential transform method and the perturbation method with the Maclaurin’s approximation of the nonlinear part. The results obtained are better when GELS approximation is employed before applying any of the two methods.
- Page(s): 112-116
- Date of Publication: 05 July 2019
- Abayomi Samuel OKEAdekunle Ajasin University, Akungba Akoko, Nigeria
References
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Abayomi Samuel OKE "Application of GELS Approximation to Bratu-Gelfand Equation" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.112-116 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/112-116.pdf
Background: Critical success factor (CSF) appeared in the literature in the 1980s when there was interest in why some organizations seemed to be more successful than others. Blendedlearning approach refers to a combination of online and face to face methods in response to learner need and for the achievement of instructional objectives. A macro perspective suggested some critical success factors that can assist faculty and universities in e-learning environment development. Some e-learning CSFs included intellectual property, the suitability of the course for e-learning environment, building the e-learning course, e-learning course content, e-learning course maintenance, e-learning platform, and measuring the success of an e-learning course. In order to match this expectation, there’s a need to investigate and address the CSFs that influence the implementation of blended approach teaching and learning of undergraduate nursing. Blending represents a fundamental change in the way teachers and students approach the teaching-learning experience. adoption. Purpose: The study aimed at the success-critical factors of blended approach mode in teaching and learning in Kenyan universities during the pre-intervention phase of the study. Methodology: This study applied a mixed design method in order to obtained detailed information from the study participants of interest to the researcher. The study involved conducting teaching and managing one fourth-year course “NRSG 400: Education Concept and Teaching Strategies in Nursing” in the selected study sites for one trimester, by use of blended mode and conventional teaching and learning strategies. Four out of nineteen (4/19) universities in Kenya that offered Bachelor of Science in Nursing were sampled by use of convenience non-probability sampling. The sample population included two public and two private universities. One public and one private university were used as experimental group and control group respectively. The study participants comprised of only general nursing lecturers and fourth-year nursing students. Consent forms were filled from the study sites and study participants, anonymity and confidentiality during the study period was maintained. Data were collected by the use of, self-reported questionnaire. Descriptive and inferential data was processed and analyzed in order to generate simplified information. Results:A total population of (n= 486) comprised of 175 (36.0%) male and 311 (64%) female participants who consented for the study. The students had a mean age of 22 years. Of the total respondents, 30% of them Disagreed that they had knowledge on how eLearning via Moodle works while 46.3% were ready to integrate e-learning into their study. On whether they had acquired competence in access and use of e-Learning materials that had been prepared and posted on the university website by their respective lecturers 50 % of the population remained neutral.The fourth question which was whether students preferred e-learning to face to face learning as a method of learning 75% of the population was on neural. Recommendations: infrastructural support is important for the application and success of the blended mode of teaching and learning. This is among the highest scored critical factors which respondents acknowledged that should be in place for the success of the system. It’s imperative to note that institutions should invest in their infrastructure to provide a conducive environment for the application of blended mode of teaching and learning. Conclusion: There are a number of critical factors of blended teaching and learning mode among universities offering Bachelor of Science in Nursing in Kenya but not fully addressed by the university management as shown in the above and similar studies in the world.
- Page(s): 117-122
- Date of Publication: 09 July 2019
- David KaniaruMasinde Muliro University of Science and Technology, School of Nursing Midwifery and Paramedics, Kenya
- Anne Karani Nursing and Nursing Education, School of Nursing Science University of Nairobi, Kenya
- Waithira Mirie Nursing and Nursing Education, School of Nursing Science University of Nairobi, Kenya
- Elijah Nyangena Kabianga University Nursing School, Kenya
References
[1]. Rose Marie. N (2007): Foundations of Nursing Research; 6th Ed Pearson Education New Jersey. [2]. Yamane, Taro. (1967). Statistics: An Introductory Analysis, 2nd Edition, New York: Harper and Row. [3]. Kashorda, M., &Waema, T. (2014). E-Readiness survey of Kenyan Universities (2013) report. Nairobi: Kenya Education Network. [4]. Taurus, J.K, Gichoya, D. and Muumbo, A. (2015), Challenges of Implementing E-Learning in Kenya: A Case of Kenyan Public Universities, International Review of Research in Open and Distributed Learning, Vol 16 No 1. [5]. Isabirye, A.K., and Dlodlo, N. (2014). Perceived Inhibitors of Innovative E-Learning Teaching Practice at a South African University of Technology. Mediterranean Journal of Social, Vol 5 No 4 March 2014. [6]. Oroma. J. and Mduma, N. (2013a). Evaluating the Challenges of Technology Enhanced Learning in Universities in Tanzania, ISTAfrica 2013 Proceedings, IEEE Xplore. . [7]. Ingram, H., Biermann, K., Cannon, J., Neil, J., & Waddle, C. (2007). Internalising action learning: a company perspective. Establishing critical success factors for action learning courses. International Journal of Contemporary Hospitality Management, 12(2), 107–113 [8]. Freund, Y. P. (2005). Critical success factors. Planning Review, 67 (12), 1049-1053 [9]. Papp, R. (2000). Critical success factors for distance learning. Paper presented at the Americas Conference on Information. [10]. Benigno, V., &Trentin, G. (2007). The Evaluation of Online Courses. Journal of Computer Assisted Learning Vol. 3, 121-129. [11]. Volery, T., & Lord, D. (2011). Critical success factors in online education. The International Journal of Educational Management, 7(5) 537-547. [12]. Atkinson, R.J., Mc Beath, C., Soong, S. K. A. & Cheers, C. (2007). ICT: Providing choices for learners and learning. Proceedings of ASCILITE 2007 Conference .Centre for Educational Development, Nanyang Technological University, Singapore. [Online]http://www.ascilite.org.au/conferences/singapore07/procs/kennedy.pdf [13]. Dillon, C. L., &Guawardena, C. N. (2010). A framework for the evaluation of telecommunications-based distance education. International Journal of Science and Technology 43 (4) 214-222. [14]. Leidner, D. E., &Jarvenpaa, S. L. (2012). The information age confronts education: case studies in the electronic classroom. Advanced journal of Education, 7 (14): 245-249. [15]. Helmi, A. (2008). An analysis on the impetus of online education Curtin University of Technology, Western Australia. The journal of Information Systems Research, 4(1), 24–54. [16]. Govindasamy, T. (2002). Successful implementation of e-learning; pedagogical considerations. The Internet and Higher Education, 4(3–4), 287–299. [17]. Baylor, A. L., & Ritchie, D. (2009). What Factors Facilitate Teacher skill, Teacher morale, and perceived Student learning in Technology-using classrooms? Journal of Computers & Education. Vol. 72, 667-678. [18]. Bourne, J.R., McMaster, E., Rieger, J., and Campbell, J.O. (2010). Paradigms for Online Learning: A case study in the design and implementation of an asynchronous learning network (ALN) course. Journal of Asynchronous Learning Networks. 6:2, pp 21-27. August. [19]. Willis, B. (2009). Enhancing faculty effectiveness in distance education. (7th Ed). Educational Technology Publications, Inc. [20]. Collis, B. (2010). Anticipating the Impact of Multimedia in Education: lessons from the literature. Computers in Adult Education and Training, 13(2), 52–123. [21]. Creswell J.W. (2003). Research Design: Qualitative & Quantitative Approaches SAGE International Educational and Professional Publisher. London. [22]. Webster, J., & Hackley, P. (1997). Teaching effectiveness in technology-mediated distance learning. Academy of Management Journal, 40(6), 1282–1309.
David Kaniaru, Anne Karani, Waithira Mirie, Elijah Nyangena "Identifying Critical Success Factors for Blended Approach Mode in Teaching and Learning for Undergraduate Nurses in Kenya " International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.117-122 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/117-122.pdf
The epileptic electricity supply from the Abuja Electricity company of Nigeria (AEDC) has resulted in extensive demand for alternative sources of electricity generation. Solar renewable energy is one area of focus among the renewable energy resources that can be harnessed to address power crisis in most institutions in Nigeria. As we all know renewable energy is the other of the day as it can complement the non-renewable sources of energy by enhancing smooth research activities in an academic environment. In this research work, an inverter thatwas solar powered was designed for some offices in Electrical and Electronics Engineering Department of Federal University of Technology (FUT) Minna. The load profile, the sizing of the photovoltaic (PV) cell, charge controller, inverter and the number of batteries expected to be used were designed. The result shows that the total load profile, total energy demand per day, the nominal rated PV module output, the total ampere-hour capacity of the batteries, the maximum short circuit current of the array and the power of the inverters were calculated respectively as 3716 watt-hours, 742watts, 1200 amp-hours, 50A and 5kVA. The performance of the system gives a stable output voltage and current that was sufficient enough to charge the batteries and power the equipment.
- Page(s): 123-127
- Date of Publication: 12 July 2019
- Chizea D. FrancisNational Space Research and Development Agency (NASRDA)
- Akachukwu M. ChichebeNational Space Research and Development Agency (NASRDA)
References
[1]. Galvin, Robert, and Kurt Yeager. (2010). “Perfecting Power: In Search of a Secure, Sustainable Future.” IEEE Power and Energy Magazine 8(1). [2]. Sambo, A. S., B. Garba, I. H. Zarma, and M. M. Gaji. (2012). “Electricity Generation and the Present Challenges in the Nigerian Power Sector.”of Energy and Power … (July 2016):1–17. [3]. Sule, A. H. (2010). “Major Factors Affecting Electricity Generation, Transmission, and Distribution in Nigeria.” International Journal of Engineering and Mathematical Intelligence 1(1): 159–164. [4]. Emodi, Nnaemeka Vincent. (2016). Energy Policies for Sustainable Development Strategies.http://link.springer.com/10.1007/978- 981-10-0974-7. [5]. Aniefiok, Essien, I E Igweonu, C V Eguzo, and B J Robert. (2013). “Integrating Smart Grid Model in Nigeria Power Network.” International Journal of Advances in Engineering & Technology 6(4):1760- 1768. [6]. Vincent, Emodi Nnaemeka, and Samson D Yusuf. (2014). “Integrating Renewable Energy and Smart Grid Technology into the Nigerian Electricity Grid System.” Smart Grid and Renewable Energy 5(9): 220–238. http://www.scirp.org/journal/doi.aspx?DOI=10.4236/sgre.2014.59021. [7]. Mshelia, I H. (2012). “Energy Access for All: The Role of Clean Energy in Alleviating Energy Poverty.” Green Deal Nigeria39. [8]. Al-Salaymeh A., Z. Al-Hamamre, F. Sharaf, M.R. Abdelkader .(2010). “Technical and Economical Assessment of the Utilization of Photovoltaic Systems in Residential Buildings: The Case of Jordan.” Energy conversion and management 51(8): 1719–1726. [9]. Oko, COC, Diemuodeke EO, Omunakwe NF, Nnamdi E. (2012). “Design and Economic Analysis of a Photovoltaic System: A Case Study.” Int.Journal of Renewable Energy Development 1(3): 65–73. [10]. Guda, H. A., & Aliyu U. O. (2015). “Design of a Stand-Alone Photovoltaic System for a Residence in Bauchi.” International Journal of Engineering and Technology 5(1): 278-284. [11]. Li, D.H.W., Cheung K.L., Lam T.N.T., & Chan W. (2012). “ A Study of Grid Connected Photovoltaic (PV) System in Hong Kong. ” Applied Energy 90 (doi:10.1016/ j.apenergy. 2011.01.054).122–127. [12]. Bayar T. (2013). “Germany Must Manage Growth and Costs of Renewable Energy .” Renewable Power World.com: Retrieved from http://www.renewableenergyworld.com. [13]. Tyagi V.V., Rahim A. A. N, Rahim N.A., and Selvaraj J. A/L. (2013). “Progress in Solar PV Technology: Research and Achievement.” Renewable and Sustainable Energy Reviews 20: 443–461. [14]. Ekechukwu, L. C. & Akuru, U. B. (2013). “Challenges in Power Generation in Nigeria- The Way Forward.” In Electrical Engineering National Conference on Energy Sources for Power Generation.,897-907. [15]. Jim Dunlop Solar.(2012) "System Sizing Principles, interactive vs standalone systems, calculations and software tools ppt” 1-33.SEIAPI Sustainable Enerrgy Practice Best. (2012). “OFF GRID PV POWER SYSTEMS”. Sustainable Energy Industry Association of the Pacific Islands in Collaboration with the Pacific Power Association 1-20. Lead, Convening, and Lead Authors LA. “Energy and Economy.” [16]. Tutorial work sheet on Stand Alone PV System Sizing Worksheet. (2015)
Chizea D. Francis and Akachukwu M. Chichebe "Promoting High Photovoltaic Penetration in Academic Environment: A Case Study of FUT Minna" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.123-127 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/123-127.pdf
This research proposes a novel method for modifying, improving and deploying sensing techniques in cognitive radio on instruments in the oil and gas sector so as to improve the reliability of frequency spectrum sensing using genetic algorithm. Matlab/Simulink would be employed for the simulation.
- Page(s): 128-131
- Date of Publication: 12 July 2019
- Chizea D. FrancisNational Space Research and Development Agency (NASRDA)
- Akachukwu M. ChichebeNational Space Research and Development Agency (NASRDA)
- Ovie Ese OgheneNational Space Research and Development Agency (NASRDA)
References
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Chizea D. Francis, Akachukwu M. Chichebe, Ovie Ese Oghene "A Proposal on Improving Frequency Spectrum Sensing Reliability in Cognitive Radio Using Genetic Algorithm" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.128-131 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/128-131.pdf
The attempt to develop brown sugar processing technology in Nigeria was initiated by the Federal Government in 1986 through the Federal Ministry of Industries. Meanwhile, brown sugar hardens during storage as a result of moisture loss into the atmosphere. In the light of this development, some local commercial crude brown sugars in a solid form known as “Masarkwoilla” within the Zaria Kaduna State of Nigeria were evaluated for moisture composition which is as well a function of their shelf lives.The samples A (Kwangilla) 18%, B (Sabo gari) 38%, C (Samaru) 55%, D (Tundun Wada) 65% and E (Zaria city) 86% were subjected to routine oven drying at 120oC with an initial dose of 10g and 5min each to the final drying period of 60min (10min interval) with constant weight achievement. The ANOVA results disclose the disparities between the means of these sugar samples. Therefore, two independent samples T-test was conducted between two sugar samples at random in order to define the areas of significance as predicted by ANOVA. The mean significant differences were observed with samples A & E, B & E, and C & E, while A & B, B & C, C & D, A & C, A& D, and B & D are not significantly different with each other. These imply that moisture contents of brown sugar needs to be standardized and maintained for longer shelf life and quality. Brown sugar processing generally should be regulated and standardized such that moisture which plays a strong role in preserving the molasses and other components in inhibiting the attack of microorganisms and shelf life can be conditioned.
- Page(s): 132-136
- Date of Publication: 12 July 2019
- Olabimtan Olabode HIndustrial and Environmnetal Pollution Department, National Research Institute for Chemical Technology Zaria Kaduna State, Nigeria.
- Mohammed Yakubu.G Agricultural Technology Department,College of Agriculture Zuru Kebbi State, Nigeria.
- Abdulkadir JibrinIndustrial and Environmnetal Pollution Department, National Research Institute for Chemical Technology Zaria Kaduna State, Nigeria.
- Obidah Timothy.YIndustrial and Environmnetal Pollution Department, National Research Institute for Chemical Technology Zaria Kaduna State, Nigeria.
- Mustapha MohammedIndustrial and Environmnetal Pollution Department, National Research Institute for Chemical Technology Zaria Kaduna State, Nigeria.
- Aribanusi Funke RIndustrial and Environmnetal Pollution Department, National Research Institute for Chemical Technology Zaria Kaduna State, Nigeria.
- Oshodin Joy.OIndustrial and Environmnetal Pollution Department, National Research Institute for Chemical Technology Zaria Kaduna State, Nigeria.
- Yohanna Sarah.TIndustrial and Environmnetal Pollution Department, National Research Institute for Chemical Technology Zaria Kaduna State, Nigeria.
- Musa Omale.PDepartment of Internal Medicine, Ahmadu Bello University Teaching Hospital Shika, Zaria Kaduna State, Nigeria.
References
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Olabimtan Olabode H, Mohammed Yakubu.G, Abdulkadir Jibrin, Obidah Timothy.Y, Mustapha Mohammed, Aribanusi Funke R, Oshodin Joy.O, Yohanna Sarah.T, Musa Omale.P "Moisture Composition and Evaluation of Solid State Crude Brown Sugars (Masarkwoilla) in Zaria Metropolis, Northern Nigeria" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.132-136 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/132-136.pdf
KMS are information technology (IT) systems that manage the knowledge of organizations, these systems aid organizations generate new knowledge, record, utilize and allocate knowledge. This study examines the adoption of knowledge management systems at the University of Jos. Centred on the UTAUT2 theory, this study puts forth a framework and then investigates its constructs to explain individual’s behavioural intentions to adopt knowledge management system. This work also examines the moderating effects of individualism/Collectivism at individual level on knowledge management system adoption. Data was gathered from staff and faculty of the University of Jos using an online questionnaire. The collected data was analyzed using SPSS to perform an exploratory factor analysis. AMOS was then used to test the model fit and the proposed hypothesis of the research by conducting a confirmatory factor analysis test. The findings of this study showed that performance expectancy, hedonic motivation are important factors that explained individual’s behavioural intention to adopt knowledge management system. The results from this study also showed the impact of habit and facilitating condition on use behaviour. The result also showed that the moderating effect of individualism/collectivism at individual level on knowledge management system adoption was significant. Implications and future research works are presented and explained.
- Page(s): 137-154
- Date of Publication: 13 July 2019
- Desmond Bala Bisandu Department of Computer Science, Faculty of Natural Sciences, University of Jos, Nigeria,
- Dorcas Dachollom Datiri Department of Computer Science, Faculty of Natural Sciences, University of Jos, Nigeria,
- Eva Onokpasa Department of Computer Science, Faculty of Natural Sciences, University of Jos, Nigeria,
- Alams Titus Mammuam Department of Computer Science, Faculty of Natural Sciences, University of Jos, Nigeria,
- Godwin A. Thomas Department of Computer Science, Faculty of Natural Sciences, University of Jos, Nigeria,
- Nentawe Yusuf Gurumdimma Department of Computer Science, Faculty of Natural Sciences, University of Jos, Nigeria,
- David Enekai Oguche Department of Computer Science, Faculty of Natural Sciences, University of Jos, Nigeria,
- Emmanuel Simon Ikoojo Department of Computer Science, Faculty of Natural Sciences, University of Jos, Nigeria,
- Jimme Mangai Madugu Department of Computer Science, Faculty of Natural Sciences, University of Jos, Nigeria,
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Desmond Bala Bisandu, Dorcas Dachollom Datiri, Eva Onokpasa, Alams Titus Mammuam, Godwin A. Thomas, Nentawe Yusuf Gurumdimma, David Enekai Oguche, Emmanuel Simon Ikoojo, Jimme Mangai Madugu "A Framework for the Adoption of Knowledge Management System (KMS) in University of Jos, Nigeria" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.137-154 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/137-154.pdf
Military standards such as MIL-STD-188-125-1 are usually applied when testing HEMP (High-Altitude Electromagnetic Pulse) resilience of industrial civil electronic equipment on military test benches. This article discusses the feasibility of adhering to requirements of section “Pulsed Current Injection (PCI) Test Procedures” of this standard and concludes that it is not practical to use it for industrial electronic equipment testing.
- Page(s): 155-158
- Date of Publication: 13 July 2019
- Vladimir Gurevich Central Electric Laboratory, Israel Electric Corp., Israel, Haifa
References
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Vladimir Gurevich "Using the Requirements of the MIL-STD-188-125-1 Concerning Injection of Current Pulse at Testing Resilience of Electronic Equipment to HEMP" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.155-158 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/155-158.pdf
The study investigated geotechnical properties of soils along with other soil’s properties and classified soils derived from Imo Clay Shale. Free soil survey technique was used in siting profile pits. The Ultimate Bearing Capacity was estimated from the Shear Strength values, using the ten soil samples from the two profile pits investigated. The objectives of this study was to utilize these geotechnical properties to classify soils of this region and to measure the degree of variation among soil properties. Results revealed the presence of gravel (19%-53%,). The Liquid Limit (56.6-65%) was higher than the Plastic Limit (21.0%-22.5%). Plasticity Index was between 35.6%-43.3%, Optimum Moisture Content 20%-34%, Maximum Dry Density 1.32%-1.50%, COLE 0.32-0.16, Volumetric Shrinkage 56.1-130.0, Shear Strength 72.32KN/m2-80KN/m2, Angle of Internal Friction 16.10-20.30, Cohesion 21.0KN/m2-14KN/m2 and Ultimate Bearing Capacity 303KN/m2-326KN/m2 was observed in soils analyzed. The soils were classified as VerticHapludult and TypicHapludult.
- Page(s): 159-163
- Date of Publication: 17 July 2019
- Adaobi.U.OnyechereDepartment of Soil Science and Technology, Federal University of Technology Owerri, Nigeria.
- Emmanuel U. OnweremaduDepartment of Soil Science and Technology, Federal University of Technology Owerri, Nigeria.
- Ignatius C. OnyechereDepartment of Civil Engineering, Federal University of Technology Owerri, Nigeria.
References
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Adaobi.U.Onyechere, Emmanuel U. Onweremadu, Ignatius C. Onyechere, "Geotechnical Properties and Classification of Some Soils Formed on Shale in Imo State, Nigeria" International Journal of Research and Innovation in Applied Science -IJRIAS vol.4 issue 6 June 2019, pp.159-163 URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.4&Issue6/159-163.pdf