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Using Trophy Hunting to Save Wildlife Foraging Resources: A Case Study from Moyowosi-Kigosi Game Reserves, Tanzania
Get PDFThis research article published by MDPI, 2022Globally, the role of trophy hunting in wildlife conservation has been a topic of much debate. While various studies have focused on the financial contribution of trophy hunting towards wildlife conservation, little is known about whether hunting activities can protect wildlife forage resources. We examined the effect of illegal livestock grazing on wildlife habitat in operational and non-operational wildlife hunting blocks in Moyowosi-Kigosi Game Reserves (MKGR), Tanzania. We assessed whether the physical presence of hunting activities lowered illegal grazing and, thus, led to higher vegetation quality. We compared 324 samples of above-ground biomass (AGB) and grass cover between control (0.0007 cattle ha−1), moderately (0.02 cattle ha−1), and intensively (0.05 to 0.1 cattle ha−1) grazed hunting blocks. Likewise, we assessed soil infiltration, soil penetration, soil organic carbon (SOC), and soil Nitrogen, Phosphorus, and Potassium (N-P-K) across grazing intensity. Illegal grazing decreased AGB by 55%, grass cover by 36%, soil penetration by 46%, and infiltration rate by 63% compared to the control blocks. Illegal grazing further lowered SOC by 28% (F2,33 = 8, p < 0.002) but increased soil N by 50% (F2,33 = 32.2, p < 0.001) and soil K by 56% (H (2) = 23.9, p < 0.001), while soil P remained stable. We further examined if Hunting Company (HC) complements anti-poaching efforts in the Game Reserves (GR). We found that HC contributes an average of 347 worker-days−1 for patrol efforts, which is 49% more than the patrol efforts conducted by the GR. However, patrol success is higher for GR than HC (F1,21 = 116, p < 0.001), due to constant surveillance by HC, illegal herders avoided invading their hunting blocks. We conclude that illegal grazing severely reduced vegetation and soil quality in MKGR. We further claim that trophy hunting contributes directly to wildlife habitat preservation by deploying constant surveillance and preventing illegal grazing. We propose maintaining trophy hunting as an essential ecological tool in wildlife conservation
Mathematical Approach to Investigate Stress due to Control Measures to Curb COVID-19
Get PDFThis research article published by Hindawi, 2022COVID-19 is a world pandemic that has affected and continues to affect the social lives of people. Due to its social and economic impact, different countries imposed preventive measures that are aimed at reducing the transmission of the disease. Such control measures include physical distancing, quarantine, hand-washing, travel and boarder restrictions, lockdown, and the use of hand sanitizers. Quarantine, out of the aforementioned control measures, is considered to be more stressful for people to manage. When people are stressed, their body immunity becomes weak, which leads to multiplying of coronavirus within the body. Therefore, a mathematical model consisting of six compartments, Susceptible-Exposed-Quarantine-Infectious-Hospitalized-Recovered (SEQIHR) was developed, aimed at showing the impact of stress on the transmission of COVID-19 disease. From the model formulated, the positivity, bounded region, existence, uniqueness of the solution, the model existence of free and endemic equilibrium points, and local and global stability were theoretically proved. The basic reproduction number () was derived by using the next-generation matrix method, which shows that, when , the disease-free equilibrium is globally asymptotically stable whereas when the endemic equilibrium is globally asymptotically stable. Moreover, the Partial Rank Correlation Coefficient (PRCC) method was used to study the correlation between model parameters and . Numerically, the SEQIHR model was solved by using the Rung-Kutta fourth-order method, while the least square method was used for parameter identifiability. Furthermore, graphical presentation revealed that when the mental health of an individual is good, the body immunity becomes strong and hence minimizes the infection. Conclusively, the control parameters have a significant impact in reducing the transmission of COVID-19
Combining Clinical Symptoms and Patient Features for Malaria Diagnosis: Machine Learning Approach
Get PDFThis research article published by Taylor & Francis Online, 2022Presumptive treatment and self-medication for malaria have been used in limited-resource countries. However, these approaches have been considered unreliable due to the unnecessary use of malaria medication. This study aims to demonstrate supervised machine learning models in diagnosing malaria using patient symptoms and demographic features. Malaria diagnosis dataset extracted in two regions of Tanzania: Morogoro and Kilimanjaro. Important features were selected to improve model performance and reduce processing time. Machine learning classifiers with the k-fold cross-validation method were used to train and validate the model. The dataset developed a machine learning model for malaria diagnosis using patient symptoms and demographic features. A malaria diagnosis dataset of 2556 patients’ records with 36 features was used. It was observed that the ranking of features differs among regions and when combined dataset. Significant features were selected, residence area, fever, age, general body malaise, visit date, and headache. Random Forest was the best classifier with an accuracy of 95% in Kilimanjaro, 87% in Morogoro and 82% in the combined dataset. Based on clinical symptoms and demographic features, a regional-specific malaria predictive model was developed to demonstrate relevant machine learning classifiers. Important features are useful in making the disease prediction
Real time battery voltage level monitoring system for telecommunication towers a case study: Habari Node public limited company Arusha, Tanzania
Get PDFA Project Report Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Science in Embedded and Mobile System of the Nelson Mandela African Institution of Science and TechnologyVoltage fluctuations in batteries during consumption are amongst the challenges facing
telecommunication towers. Due to these fluctuations, many injuries that cause deaths and
environmental poisoning have been reported. These fluctuations and injuries mainly occur due to
poor management and lack of battery voltage-level monitoring systems after installation. This
paper proposes a battery voltage-level monitoring system to be used in telecommunication towers.
The proposed solution is incorporated with a centralized mobile application dashboard that allows
access to the live data of the installed battery due to integration with components for sensing the
battery’s voltage, current, and temperature levels, as well as fire, and gas contents. An Arduino
Uno microcontroller board was used in the processing and analysis of the data collected from the
sensors. The global service message module (GSM) internet connectivity was used to store and
monitor data in the cloud. The user was then alerted about low voltage, detected fire, and increased
levels of harmful gases in the tower through a short message service (SMS). The experiment was
conducted at Ngorongoro and Manyara telecommunication towers and it revealed that the
developed battery voltage-level monitoring system could access battery information remotely
while allowing users to continually monitor the battery usage in telecommunication towers in real time. The unique value of this study is the proposed battery voltage-level monitoring system that
contributes to the elimination of battery hazards in telecommunication towers. The proposed
battery voltage-level monitoring system can be adopted by telecommunication towers engineers
to reduce voltage fluctuation risks like injuries, environmental degradation, and deaths
Design of an automatic escaped animal detection and monitoring system: a case study of Volcanoes National Park (VNP)
Get PDFA Project Report Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Science in Embedded and Mobile Systems of the Nelson Mandela African Institution of Science and TechnologyThe results have been shown that the people especially farmers living at the edge of Volcanoes
National Park (VNP) practiced agricultural business due to the fertile soil found in the region.
The rising number of agronomies in the zone, number of tourists, and illegal forest users such
as poaching, and deforestation cause wild animals to get out of their habitats. Therefore, their
crops are raided by forest animals which present a likely risk to damage crops whenever they
get out of the forest. The current systems such as “Buffer Wall also known as wall of stones”
was manually operated; electric fence systems resulted in death and pain to wild animals. Due
to the development of automatic systems for detecting and monitoring all moving wild animals
and intruders, it was stated that using automation at Buffer wall could be helpful for both wild
animals and farmers keep safe. Security is an importance in the VNP whereby detection and
monitoring wildlife would determine the needs by park officials. The objectives of developing
an Automatic Escaped Animal Detection and Monitoring System were to reduce the probability
of crop raids, death and injuries between wild animals and farmers, warning the wild animals
through the use of buzzer, speaker with a recorder voice of lion and block of LEDs to remain
in their habitats and the notifications sent to the park officials related to the forest animals
getting out of the forest. Since wild animals and intruders found in buffer zone targeting to pass
by the buffer wall for crop raiding and poaching activities; this system should primarily use
sensing devices to detect and monitor their presence. On the other hand, for buffer wall security,
warning equipment’s such as block of LEDs, Buzzer, SIREN Alarm and speaker should all
together be activated. Whenever wild animals and trespassers would search to pass by another
part would be activated the same way as the previous. The specialty of this technological
system developed was to automate manual and improve the current systems by using Arduino
NANO Microcontroller to execute system’s operations, GPS NEO 6M for locating moving
wild animal, Ultrasonic sensor for detecting wildlife and calculating its speed, PIR sensor to
detect intruders, GSM SIM900 to notify park rangers, reduction of crop raiding, and finally
reducing death and pain of wild animals caused by current systems
Complementary feeding practices and the risk of exposure to aflatoxins among infants and young children in Kongwa, Tanzania
Get PDFA Thesis Submitted in Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Life Sciences of the Nelson Mandela African Institution of Science and TechnologyAflatoxins (AFs) are secondary fungal metabolites that commonly contaminate foods like nuts and
cereals and pose major public health concerns like impaired child growth, immune system
suppression, liver cancer and death. In sub-Saharan Africa, infants and young children (IYC) feed
on complementary foods (CFs) containing ingredients susceptible to contamination with AFs.
Although the presence of AFs in foodstuffs has been reported for over 60 years, very few studies
have focused on CFs, yet children are more vulnerable due to relatively small bodyweights and
underdeveloped immune systems. This study was conducted in Kongwa District, Tanzania in 2017
and 2018, to estimate the contribution of the main CF ingredients to aflatoxin exposure among
IYC. The study documented the common ingredients of CFs and the intake of CFs by 35 (6-12-
month-old) IYC using multiple-pass 24-h dietary recalls. The levels of AFs contamination in the
collected samples were determined using High-Performance Liquid Chromatography while the
exposure of IYC to AFs was estimated by a deterministic approach. The study further tested
acceptability of Aflatoxin-safe maize-groundnut pre-blended flour (AFSaBF) and groundnut
powder (AFSaGP). The key ingredients of CFs were milled maize, sorghum, pearl-millet, rice,
and groundnuts (pre- or post-blended with cereals) prepared as thin/stiff porridge. The average
per-capita daily intake of CFs flour was 89.45 g. About 82.14% of the samples had AFB1 levels
ranging from 0.27–317 μg/kg, and the exposure levels ranged from 0.33-1168 ng/kg body weight
(bw)/day. The Margins of Exposure were < 10 000 for all IYC, signifying a public health concern.
The mothers and IYC generally accepted the improved porridge flour and groundnut powder. This
is important information for future studies aiming at reducing exposure to AFs in this community.
Groundnut and maize flours are the main contributors to the exposure of IYC to AFB1 in Kongwa
district. Community education on mycotoxins-mitigation practices like appropriate pre and post harvest handling and complementary feeding practices may minimize aflatoxin exposure among
IYC in Kongwa and other communities with similar settings. Appropriate feeding practices may
entail diet diversification and substitution of groundnut or maize with other food ingredients that
are less-prone to AFs contamination
Mobile and web based applications for supporting locating of hospital services: a case of micro-health initiative organization
Get PDFA Project Report Submitted in Partial Fulfillment of the Requirements of the Award the Degree of Master of Science in Embedded and Mobile Systems of the Nelson Mandela African Institution of Science and TechnologyTanzania has various health policies and strategic plans including the digital health strategy
2019 - 2024". However, these policies mainly address systematic issues to ensure better
availability and delivery of health services. The adoption of technology on the health sectors
in Tanzania is growing rapidly. Other factors such as income and health insurance status also
affect utilization of health services, and are not as widely captured. This study aimed at
improving health services seeking behavior through the development of mobile applications
and web applications that help patients identify health facilities near their locations, the services
available at these facilities and the cost of services. The study employed quantitative research
method where data were collected from community and health workers using questionnaires
and observations. The data were analyzed using Jupiter python. The results indicated that both
mobile and web applications improved accessibility of patients get to know nearby hospitals,
services the hospital provides, prices of the services on different hospital. Therefore, it is easy
for patient to decide depending on the money he or she have. The other key finding is that
patients to be able to book the appointment depending on the hospital services chosen. Hence,
provides easiness to the community for patients or anyone who need hospital services
Evaluation of recharge areas of Arusha aquifer, northern Tanzania: application of water isotope tracers
Get PDFDissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Master’s in Hydrology and Water Resources Engineering of the Nelson Mandela African Institution of Science and TechnologyIn Arusha urban, northern Tanzania, groundwater contributes about 80% of the water supply.
However, elevated fluoride levels and evidence of anthropogenic pollution have been reported
in the groundwater around Mount Meru which is a water source for Arusha urban. This study
aims at understanding the recharge areas and flow pathways of groundwater in what has been
a poorly monitored area. The study uses the isotopic ratio of oxygen and hydrogen to estimate
the groundwater recharge area and flow pathway. The results show the recharge elevation of
groundwater is between 1800 and 3500 m above mean sea level on the slopes of Mount Meru.
Fluoride showed an increasing trend with elevation while NO3
-
decreased with sampling
altitude. The high content of NO3
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and Cl in water samples from sources in the lower part of
the study area is evidence of anthropogenic contamination. The average fluoride contents in
the study area are 5.3 ± 0.4 mg/L greater than the limits of 1.5 mg/L and 4 mg/L set by the
World Health Organization (WHO) and Tanzania respectively. The nitrate concentration of
83.9 mg/L at the lower elevation areas (<1400 m above mean sea level) exceeds the 50 mg/L
WHO limit. The relationship of F- with δ18O and NO3
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suggests the leaching of fluoride in high
altitudes and dilution in lower altitudes. Two flow pathways were identified, that start from the
recharge area in the south and south-western slopes of Mount Meru towards the southern part
of Arusha urban
Improved handover decision scheme for 5g mm-wave communication: optimum base station selection using machine learning approach.
Get PDFA Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Information and Communication Science and Engineering of the Nelson Mandela African Institution of Science and TechnologyThe rapid growth in mobile and wireless devices has led to an exponential demand for data traf fic and exacerbated the burden on conventional wireless networks. Fifth generation (5G) and
beyond networks are expected to not only accommodate this growth in data demand but also
provide additional services beyond the capability of existing wireless networks, while main taining a high quality-of-experience (QoE) for users. The need for several orders of magnitude
increase in system capacity has necessitated the use of millimetre wave (mm-wave) frequencies
as well as the proliferation of low-power small cells overlaying the existing macro-cell layer.
These approaches offer a potential increase in throughput in magnitudes of several gigabits per
second and a reduction in transmission latency, but they also present new challenges. For exam ple, mm-wave frequencies have higher propagation losses and a limited coverage area, thereby
escalating mobility challenges such as more frequent handovers (HOs). In addition, the ad vent of low-power small cells with smaller footprints also causes signal fluctuations across the
network, resulting in repeated HOs (ping-pong) from one small cell (SC) to another.
Therefore, efficient HO management is very critical in future cellular networks since frequent
HOs pose multiple threats to the quality-of-service (QoS), such as a reduction in the system
throughput as well as service interruptions, which results in a poor QoE for the user. How ever, HO management is a significant challenge in 5G networks due to the use of mm-wave
frequencies which have much smaller footprints. To address these challenges, this work in vestigates the HO performance of 5G mm-wave networks and proposes a novel method for
achieving seamless user mobility in dense networks. The proposed model is based on a double
deep reinforcement learning (DDRL) algorithm. To test the performance of the model, a com parative study was made between the proposed approach and benchmark solutions, including a
benchmark developed as part of this thesis. The evaluation metrics considered include system
throughput, execution time, ping-pong, and the scalability of the solutions. The results reveal
that the developed DDRL-based solution vastly outperforms not only conventional methods but
also other machine-learning-based benchmark techniques.
The main contribution of this thesis is to provide an intelligent framework for mobility man agement in the connected state (i.e HO management) in 5G. Though primarily developed for
mm-wave links between UEs and BSs in ultra-dense heterogeneous networks (UDHNs), the
proposed framework can also be applied to sub-6 GHz frequencies
Evaluation of the composition and quality of watermelon and mango juices fermented by Levilactobacillus brevis, Lacticaseibacillus casei and Pediococcus pentosaceus and subsequent simulated digestion and storage
Get PDFThis research article was published by John Wiley & Sons, Inc., 2022This study evaluated the composition of watermelon and mango juices fermented by Levilactobacillus (L.) brevis, Lacticaseibacillus (La.) casei and Pediococcus (P.) pentosaceus and subsequently simulated in vitro digestion and storage (4°C for 35 days). After fermentation (24 h), the microorganisms grew (~9 log CFU mL−1) and fermented watermelon (FWJ) and mango juice (FMJ) became more red and yellow, respectively. DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid)) free radical scavenging capacities significantly increased in L. brevis and La. casei FMJ. After in vitro digestion, all the strains except La. casei in FMJ significantly decreased (P < 0.05), and P. pentosaceus survival was 2.4 and 4.5 times higher in FWJ and FMJ, respectively, than as pure culture. After storage, cell counts remained above 7 log CFU mL−1, and no changes in quality attributes, total phenolic content and antioxidant capacity were recorded in P. pentosaceus FMJ. Thus, watermelon and mango are suitable matrices for lactic acid bacteria