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Search Results: 1 - 10 of 20575 matches for " James Ndambuki "
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The level of patients’ satisfaction and perception on quality of nursing services in the Renal unit, Kenyatta National Hospital Nairobi, Kenya  [PDF]
James Ndambuki
Open Journal of Nursing (OJN) , 2013, DOI: 10.4236/ojn.2013.32025

Introduction: Renal failure is on the increase and patients have to identify with renal services and centres where services for renal replacement therapies are rendered. This calls for health care workers to offer services that are perceived as quality and satisfying in order to meet the biophysical and psychological needs of the patients. Study design: This was a descriptive cross-sectional study undertaken at the Renal unit of Kenyatta National Hospital (KNH). Purpose: The study aimed at determining the level of satisfaction and perception of the quality of nursing services in the Renal unit. Methodology: The study population included all patients who were seeking dialysis services during one month period of data collection. The sample size was 151 following data collection. Data collection tools consisted of semi-structured questionnaires which were administered with the aid of research assistants as well as checklists which were self administered. Data analysis and results: Analysis of data was performed using the statistical package of social sciences (SPSS) version 16. Results of data analysis were presented in form of descriptive statistics which included mean, standard deviation and percentages. Regression analysis, t-test and ANOVA were conducted to determine demographic predictors of patient satisfaction with the nursing services. The results of the study revealed that patients in the Renal unit were generally satisfied with the nursing services. The aggregate mean score for all patients on Likert scale was 71.2 out of 105, with a standard deviation of 16.8. Level of satisfaction was 67.8%. The findings also showed that there was no association between demographic characteristics with the levels of satisfaction with the nursing services. Recommendation: The hospital should keep the patients’ level of satisfaction high and maintain it through the provision of more dialysis machines and hiring more nurses.

Accuracy Assessment of Land Use/Land Cover Classification Using Remote Sensing and GIS  [PDF]
Sophia S. Rwanga, J. M. Ndambuki
International Journal of Geosciences (IJG) , 2017, DOI: 10.4236/ijg.2017.84033
Abstract: Remote sensing is one of the tool which is very important for the production of Land use and land cover maps through a process called image classification. For the image classification process to be successfully, several factors should be considered including availability of quality Landsat imagery and secondary data, a precise classification process and user’s experiences and expertise of the procedures. The objective of this research was to classify and map land-use/land-cover of the study area using remote sensing and Geospatial Information System (GIS) techniques. This research includes two sections (1) Landuse/Landcover (LULC) classification and (2) accuracy assessment. In this study supervised classification was performed using Non Parametric Rule. The major LULC classified were agriculture (65.0%), water body (4.0%), and built up areas (18.3%), mixed forest (5.2%), shrubs (7.0%), and Barren/bare land (0.5%). The study had an overall classification accuracy of 81.7% and kappa coefficient (K) of 0.722. The kappa coefficient is rated as substantial and hence the classified image found to be fit for further research. This study present essential source of information whereby planners and decision makers can use to sustainably plan the environment.
Application of SWAT Model to the Olifants Basin: Calibration, Validation and Uncertainty Analysis  [PDF]
Charles Gyamfi, Julius Musyoka Ndambuki, Ramadhan Wanjala Salim
Journal of Water Resource and Protection (JWARP) , 2016, DOI: 10.4236/jwarp.2016.83033
Abstract: The application of the Soil and Water Assessment Tool (SWAT) to the Olifants Basin in South Africa was the focus of our study with emphasis on calibration, validation and uncertainty analysis. The Basin was discretized into 23 sub-basins and 226 Hydrologic Response Units (HRUs) using 3 arc second (90 m × 90 m) pixel resolution SRTM DEM with stream gauge B7H015 as the Basin outlet. Observed stream flow data at B7H015 were used for model calibration (1988-2001) and validation (2002-2013) using the split sample approach. Relative global sensitivity analysis using SUFI-2 algorithm was used to determine sensitive parameters to stream flow for calibration of the model. Performance efficiency of the Olifants SWAT model was assessed using Nash-Sutcliffe (NSE), coefficient of determination (R2), Percent Bias (PBIAS) and Root Mean Square Error-Observation Standard deviation Ratio (RSR). Sensitivity analysis revealed in decreasing order of significance, runoff curve number (CN2), alpha bank factor (ALPHA_BNK), soil evaporation compensation factor (ESCO), soil available water capacity (SOIL_AWC, mm H2O/mm soil), groundwater delay (GW_ DELAY, days) and groundwater “revap” coefficient (GW_REVAP) to be the most sensitive parameters to stream flow. Analysis of the model during the calibration period gave the following statistics; NSE = 0.88; R2 = 0.89; PBIAS = -11.49%; RSR = 0.34. On the other hand, statistics during the validation period were NSE = 0.67; R2 = 0.79; PBIAS = -20.69%; RSR = 0.57. The observed statistics indicate the applicability of the SWAT model in simulating the hydrology of the Olifants Basin and therefore can be used as a Decision Support Tool (DST) by water managers and other relevant decisions making bodies to influence policy directions on the management of watershed processes especially water resources.
An efficient optimisation method in groundwater resource management
JM Ndambuki, FAO Otieno, CBM Stroet, T Terlaky, EJM Veling
Water SA , 2003,
Abstract: Uncertainty in input parameters to groundwater flow problems has been recognised as an impediment to designing efficient groundwater management strategies. The most popular approach to tackling this problem has been through the Monte Carlo approach. However, this approach is generally too expensive in terms of computer time because of the number of scenarios required to ensure reliable statistics. Furthermore, solutions obtained through this approach are not necessarily robust. In this paper, it is shown how groundwater management problems, where input parameters are uncertain can be reformulated as second-order cone optimisation (SOCO) problems, which are efficiently solved by recently developed interior-point methods. Results for a real-world case application of a groundwater aquifer found in Kenya are presented. Water SA Vol.29(4): 359-363
Wildebeest (Connochaetes taurinus) Population Densities and Distribution in Dry and Wet Season in the Kilimanjaro Landscape  [PDF]
Noah Sitati, Kenana Lekishon, Samuel Bakari, Fiesta Warinwa, Stephen Ndambuki Mwiu, Nathan Gichohi, Elphas Bitok, Machoke Mwita, Hamza K. Ija, Joseph Mukeka
Natural Resources (NR) , 2014, DOI: 10.4236/nr.2014.513070
Abstract: The conservation of migratory wildlife species in the savannah habitat can be a challenge because of frequent and prolonged drought and their requirements for a large area. We investigated the performance of the wildebeest (Connochaetes taurinus) population in the 25,624 km2 Kilimanjaro landscape of Kenya and Tanzania, which comprises Amboseli-West Kilimanjaro-Magadi-Natron after 2009 drought. We used total aerial counts to determine the spatial distribution and numbers of wildebeests during wet and dry season in 2010 and 2013. Global Positioning System and digital voice recorders were used to count wildebeests along established transects within blocks. There was an increase in the wildebeest population by 103% during the wet season and 14% during the dry season between 2010 and 2013. The seasonal variation in density occurred between the four counting blocks with Natron and Magadi areas recording the highest densities. Generally, the increase in population could be attributed to the recovery of the population after the 2009 drought. The current cross border collaboration between Kenya and Tanzania in aerial surveys is an important step in the conservation of this migratory species in the landscape. This study demonstrates that detailed knowledge of density and spatial distribution of migratory species is required to plan effective conservation action.
Addressing Social Determinants of Health by Integrating Assessment of Caregiver-Child Attachment into Community Based Primary Health Care in Urban Kenya
John H. Bryant,Nancy H. Bryant,Susanna Williams,Racheal Nduku Ndambuki,Paul Campbell Erwin
International Journal of Environmental Research and Public Health , 2012, DOI: 10.3390/ijerph9103588
Abstract: A principle strategic insight of the Final Report for WHO’s Commission on Social Determinants of Health (SDOH) is that the nurturant qualities of the environments where children grow up, live, and learn matter the most for their development. A key determinant of early childhood development is the establishment of a secure attachment between a caregiver and child. We report initial field-tests of the integration of caregiver-child attachment assessment by community health workers (CHWs) as a routine component of Primary Health Care (PHC), focusing on households with children under 5 years of age in three slum communities near Nairobi, Kenya. Of the 2,560 children assessed from July–December 2010, 2,391 (90.2%) were assessed as having a secure attachment with a parent or other caregiver, while 259 (9.8%) were assessed as being at risk for having an insecure attachment. Parent workshops were provided as a primary intervention, with re-enforcement of teachings by CHWs on subsequent home visits. Reassessment of attachment by CHWs showed positive changes. Assessment of caregiver-child attachment in the setting of routine home visits by CHWs in a community-based PHC context is feasible and may yield valuable insights into household-level risks, a critical step for understanding and addressing the SDOH.
Stochastic Modelling of Great Letaba River Flow Process  [PDF]
Gislar E. Kifanyi, Julius M. Ndambuki, Samuel N. Odai, Charles Gyamfi
Journal of Geoscience and Environment Protection (GEP) , 2019, DOI: 10.4236/gep.2019.76004
A stochastic approach is presented in view that a time series modelling is achieved through an Autoregressive Moving Average (ARMA) model. The applicability of the ARMA model is then further presented using the Great Letaba River as a case study. River flow discharge for 25 years (1989-2014) for the Great Letaba River was obtained from the Department of Water and Sanitation, South Africa and analysed by Autoregressive (AR), Autoregressive Moving Average (ARMA) and Autoregressive Integrated Moving Average (ARIMA) models. Monte Carlo simulation approach was used to generate forecasts of the ARIMA error model for the next 25 years. Initial model identification was done using the Autocorrelation function (ACF) and Partial Autocorrelation function (PACF). The model analysis and evaluations provided proper predictions of the river system. The models revealed some degree of correlation and seasonality behaviour with decreasing river flow. Hence, in conclusion, the Great Letaba River flow has shown a decreasing trend and therefore, should be effectively used for sustainable future development.
Population Status and Trend of Water Dependent Grazers (Buffalo and Waterbuck) in the Kenya-Tanzania Borderland  [PDF]
Moses Makonjio Okello, Lekishon Kenana, Hanori Maliti, John Warui Kiringe, Erastus Kanga, Fiesta Warinwa, Samwel Bakari, Nathan Gichohi, Stephen Ndambuki, Hamza Kija, Noah Sitati, David Kimutai, Machoke Mwita, Daniel Muteti, Philip Muruthi
Natural Resources (NR) , 2015, DOI: 10.4236/nr.2015.62009
Abstract: Even though over many years the IUCN has considered the African buffalo and waterbuck and abundant species in Africa with no conservation concern, the situation is rapidly changing. Using aerial counts in wet and dry season in 2010 and 2013, this study assessed the trend, population status and distribution of the African buffalo and common waterbuck in the Northern Tanzania and Southern Kenya borderland. Both species were rare in the borderland, with the Amboseli region had the highest number of buffalo (241.5 ± 29.9), followed by Magadi/Namanga (58.0 ± 22.0), West Kilimanjaro (38.8 ± 34.9), and lastly Lake Natron (14.5 ± 9.0) areas. In terms of density, Amboseli also led with 0.03 ± 0.00 (buffalo per km2), but rest had similar densities of 0.01 ± 0.00 buffalo per km2. In terms of percent changes in buffalo, Amboseli area had a positive increase (+10.59 ± 27.71), but with a negative growth of -17.12 in the dry season. All other changes in all locations had negative (decline) buffalo numbers over time. For waterbuck numbers, Amboseli area also led with 12.3 ± 3.9 waterbuck), followed by Magadi/Namanga (10.3 ± 3.7.0), Lake Natron (3.8 ± 3.4), and lastly West Kilimanjaro (0.5 ± 0.5) areas. In terms of waterbuck density, they were low and less than 0.00 ± 0.00 per km2. For percent changes in waterbuck numbers, Magadi/Namanga had higher positive change (+458.33 ± 291.67), but all other locations had negative (decline) changes with the worst being West Kilimanjaro and Lake Natron areas. Further, buffalo number was dependent (p = 0.008) on the season, with numbers being higher in the wet season than dry season. For waterbuck, numbers were independent (p = 0.72) of the season, with numbers being similar across seasons. The findings of this study showed that both species were negatively affected by drought. We recommend a constant joint monitoring program between Kenya and Tanzania, and jointly combat poaching, habitat fragmentation and encroachment to build viable populations in the borderland.
Population Status and Trend of the Maasai Giraffe in the Mid Kenya-Tanzania Borderland  [PDF]
Moses Makonjio Okello, Lekishon Kenana, Honori Maliti, John Warui Kiringe, Erastus Kanga, Fiesta Warinwa, Samwel Bakari, Stephen Ndambuki, Hamza Kija, Noah Sitati, David Kimutai, Nathan Gichohi, Daniel Muteti, Philip Muruthi, Machoke Mwita
Natural Resources (NR) , 2015, DOI: 10.4236/nr.2015.63015
Abstract: Among the nine sub-species of giraffes, the Maasai giraffe is the most widespread and common in Northern and Southern Kenya. Although it’s considered by the IUCN to be a species of no conservation concern, they have been reported to have declined in some of their range areas mostly due to bush meat activities, habitat fragmentation and loss. There are also concerns recent climatic changes especially prevalence of droughts is increasingly becoming another threat to their survival. In this regard, this study examined the status and trend of the Maasai giraffe in the Kenya-Tanzania border after the 2007 to 2009 drought. Amboseli had the highest giraffe number (averaging 2, 062.5 ± 534.7 giraffes), followed by a distant Lake Natron area (725.8 ± 129.4 giraffes), Magadi/Namanga (669.5 ± 198.0 giraffes), and lastly West Kilimanjaro area (236.5 ± 47.8 giraffes). Further, the proportion of giraffes were highest in Amboseli (55.09% ± 5.65%) followed by Lake Natron area (20.98% ± 3.42%), Magadi/Namanga area (16.35% ± 3.83%), and lastly West Kilimanjaro (7.58% ± 2.12%). But in terms of population growth after droughts, giraffe had positive growth in all locations in the borderland, with Magadi leading (+339.82 ± 329.99) followed Lake Natron area (+37.62 ± 83.27), Amboseli area (+38.11 ± 7.09), and lastly West Kilimanjaro (+3.21 ± 57.95.27). Their wet season population and density was much higher than that of the dry season. However, though the species was widely spread in the borderland, they seemed to avoid the region between Lake Magadi and Amboseli which is traversed by the Nairobi-Namanga highway both in wet and dry season. There is a need to develop a collaborative management framework for cross-border conservation to enhance their protection, conservation and genetic linkage.
Population Status and Trend of the Maasai Ostrich in the Mid Kenya—Tanzania Borderland  [PDF]
Moses Makonjio Okello, John Warui Kiringe, Lekishon Kenana, Fiesta Warinwa, Hanori Maliti, Noah Wasilwa Sitati, Erastus Kanga, Samwel Bakari, Stephen Ndambuki, Philip Muruthi, Nathan Gichohi, Edeus Massawe, David Kimutai, Machoke Mwita, Daniel Muteti
Natural Resources (NR) , 2016, DOI: 10.4236/nr.2016.710047
Abstract: The Maasai ostrich (Struthio camelus) is a the largest avian species in East Africa and though it’s not considered to be a species of conservation concern, some populations are on the decline and this is attributed to bush meat activities, predation on their eggs illegal consumption by humans, habitat destruction and forage competition with other large wildlife species. Climate change is also emerging to be another major threat due to interference with food availability which in turn interferes with the breeding rhythm. Thus, this study examined the population status, trend and distribution of the Maasai ostrich in the Southern Kenya and Northern Tanzania borderland after the 2007 to 2009 drought. The results showed that the species was found across the entire borderland but the Amboseli region had the highest number and density of Maasai ostrich (726.00 ± 100.9; 0.08 ± 0.01 ostriches per km2), followed by Lake Natron area (330.8 ± 69.8; 0.05 ± 0.01 ostriches per km2) and the least was in West Kilimanjaro (85.5 ± 18.0; 0.03 ± 0.01 ostriches per km2). Drought caused a decline in the population of the Maasai ostrich but the Amboseli area experienced the highest decline in density (?13.44 ± 12.61) compared to other borderland sectors. However, the populations increased in most sectors after the drought, and wet season numbers and densities were higher than the dry season. The highest positive increase in number and density was in Lake Natron area (+85.65 ± 91.06) followed by West Kilimanjaro (+68.39 ± 59.54), and the least was in the Magadi area (+22.26 ± 32.05). There is a need to enhance conservation of avian species like the Maasai ostrich other than just focusing on the charismatic species such as the African elephant and black rhino. We therefore recommend joint collaboration in monitoring all large wildlife populations across the Kenya-Tanzania borderland with a view of understanding their status, trend and best management actions that can enhance their conservation.
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