Search results for: Mesele Negash

Authors: Gadisa Demie, Mesele Negash, Zerihun Asrat, Lojka Bohdan

Abstract:

Deforestation and forest degradation in the tropics have led to significant carbon (C) emissions. Agroforestry (AF) is a suitable land-use option for tackling such declines in ecosystem services, including climate change mitigation. However, it is unclear how biomass models, AF practices, and socio-ecological factors determine these roles, which hinders the implementation of climate change mitigation initiatives. This study aimed to estimate the ecosystem C stocks of the studied AF practices in relation to socio-ecological variables in central Ethiopia. Out of 243 AF farms inventoried, 108 were chosen at random from three AF practices to estimate their biomass and soil organic carbon. A total of 432 soil samples were collected from 0–30 and 30–60 cm soil depths; 216 samples were taken for each soil organic carbon fraction (%C) and bulk density computation. The study found that the currently developed allometric equations were the most accurate to estimate biomass C for trees growing in the landscape when compared to previous models. The study found higher overall biomass C in woodlots (165.62 Mg ha-¹) than in homegardens (134.07 Mg ha-¹) and parklands (19.98 Mg ha-¹). Conversely, overall, SOC was higher for homegardens (143.88 Mg ha-¹), but lower for parklands (53.42 Mg ha-¹). The ecosystem C stock was comparable between homegardens (277.95 Mg ha-¹) and woodlots (275.44 Mg ha-¹). The study found that elevation, wealthy levels, AF farm age, and size have a positive and significant (P < 0.05) effect on overall biomass and ecosystem C stocks but non-significant with slope (P > 0.05). Similarly, SOC increased with increasing elevation, AF farm age, and wealthy status but decreased with slope and non-significant with AF farm size. The study also showed that species diversity had a positive (P <0.05) effect on overall biomass C stocks in homegardens. The overall study highlights that AF practices have a great potential to lock up more carbon in biomass and soils; however, these potentials were determined by socioecological variables. Thus, these factors should be considered in management strategies that preserve trees in agricultural landscapes in order to mitigate climate change and support the livelihoods of farmers.

Keywords: agricultural landscape, biomass, climate change, soil organic carbon

Procedia PDF Downloads 50

Authors: Miftah Hassen Jemal, Solomon Negash

Abstract:

This study focuses on undertaking a qualitative meta-analysis of qualitative studies conducted on ICT4D implementations. The interpretive approach of synthesis of the interpretation of qualitative studies is adopted to guide the whole process of the study. The traditional criteria of trustworthiness of qualitative studies in terms of transferability, consistency, and credibility are used as quality metrics of the output of the interpretive synthesis process. The findings of the study are anticipated to be of value for policymakers in providing guidance to decisions related to ICT4D implementations. The study is also anticipated to have contributions to research by extracting valuable insights from extant literature and identifying potential areas that warrant further investigation.

Keywords: ICT4D implementations, interpretive synthesis, qualitative meta-analysis, qualitative studies

Procedia PDF Downloads 155

Authors: Dereje Ferede, Solomon Negash

Abstract:

Artificial Intelligence (AI) is a key enabler and driver to transform and revolutionize the healthcare industries. However, utilizing AI and achieving these benefits is challenging for different sectors in wide-ranging, more difficult for developing economy healthcare. Due to this, real-world clinical execution and implementation of AI have not yet aged. We believe that examining the determinants is key to addressing these challenges. Furthermore, the literature does not yet particularize determinants of AI capabilities and ways of empowering the healthcare ecosystem to develop AI capabilities in a developing economy. Thus, this study aims to position AI as a digital transformation weapon for the healthcare ecosystem by examining AI capability determinants and providing insights on better empowering the healthcare industry to develop AI capabilities. To do so, we base on the technology-organization-environment (TOE) model and will apply a mixed research approach. We will conclude with recommendations based on findings for future practitioners and researchers.

Keywords: artificial intelligence, capability, digital transformation, developing economies, healthcare

Procedia PDF Downloads 242

Authors: Young Min Kim, Dong Gil Shin, Assmelash Assefa Negash

Abstract:

This study describes the application of a single loop organic Rankine cycle (ORC) for recovering waste heat from an excavator. In the case of waste heat recovery of the excavator, the heat of hydraulic oil can be used in the ORC system together with the other waste heat sources including the exhaust gas and engine coolant. The performances of four different cases of single loop ORC systems were studied at the main operating condition, and critical design factors are studied to get the maximum power output from the given waste heat sources. The energy and exergy analysis of the cycles are performed concerning the available heat source to determine the best fluid and system configuration. The analysis demonstrates that the ORC in the excavator increases 14% of the net power output at the main operating condition with a simpler system configuration at a lower expander inlet temperature than in a conventional vehicle engine without the heat of the hydraulic oil.

Keywords: engine, excavator, hydraulic oil, organic Rankine cycle (ORC), waste heat recovery

Procedia PDF Downloads 306

Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

Abstract:

The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

Procedia PDF Downloads 114

Authors: Abebe Mulugojam Negash, Yongbin Yu, Ekong Favour, Bekalu Nigus Dawit, Molla Woretaw Teshome, Aynalem Birtukan Yirga

Abstract:

Breast cancer remains a significant health concern, necessitating advancements in diagnostic methodologies. Addressing this, our paper confronts the notable challenges in breast cancer classification, particularly the imbalance in datasets and the constraints in the accuracy and interpretability of prevailing deep learning approaches. We proposed an attention-based residual neural network (ResNet), which effectively combines the robust features of ResNet with an advanced attention mechanism. Enhanced through strategic data augmentation and positive weight adjustments, this approach specifically targets the issue of data imbalance. The proposed model is tested on the BreakHis dataset and achieved accuracies of 99.00%, 99.04%, 98.67%, and 98.08% in different magnifications (40X, 100X, 200X, and 400X), respectively. We evaluated the performance by using different evaluation metrics such as precision, recall, and F1-Score and made comparisons with other state-of-the-art methods. Our experiments demonstrate that the proposed model outperforms existing approaches, achieving higher accuracy in breast cancer classification.

Keywords: residual neural network, attention mechanism, positive weight, data augmentation

Procedia PDF Downloads 101

Authors: Abduselam Faris, Rijalu Negash, Zera Kedir

Abstract:

This study was initiated to identify constraints and opportunities of the wood production value chain in Southwest Ethiopia. About 385 wood trees growing farmers were randomly interviewed. Similarly, about 30 small-scale wood processors, 30 retailers, 15 local collectors and 5 wholesalers were purposively included in the study. The results of the study indicated that 98.96 % of the smallholder farmers that engaged in the production of wood trees which is used for wood were male-headed, with an average age of 46.88 years. The main activity that the household engaged was agriculture (crop and livestock) which accounts for about 61.56% of the sample respondents. Through value chain mapping of actors, the major value chain participant and supporting actors were identified. On average, the tree-growing farmers generated gross income of 9385.926 Ethiopian birr during the survey year. Among the critical constraints identified along the wood production value chain was limited supply of credit, poor market information dissemination, high interference of brokers, and shortage of machines, inadequate working area and electricity. The availability of forest resources is the leading opportunity in the wood production value chain. Reinforcing the linkage among wood production value chain actors, providing skill training for small-scale processors, and developing suitable policy for wood tree wise use is key recommendations forward.

Keywords: value chain analysis, wood production, southwest Ethiopia, constraints and opportunities

Procedia PDF Downloads 94

Authors: Almaz Negash, Dessie Tibebe, Marye Mulugeta, Yezbie Kassa

Abstract:

Large-scale textile industries use large amounts of toxic chemicals, which are very hazardous to human health and environmental sustainability. In this study, the removal of various dyes from effluents of textile industries using the electrocoagulation process was investigated. The studied dyes were Reactive Red 120 (RR-120), Basic Blue 3 (BB-3), and Basic Red 46 (BR-46), which were found in samples collected from effluents of three major textile factories in the Amhara region, Ethiopia. For maximum removal, the dye BB-3 required an acidic pH 3, RR120 basic pH 11, while BR-46 neutral pH 7 conditions. BB-3 required a longer treatment time of 80 min than BR46 and RR-120, which required 30 and 40 min, respectively. The best removal efficiency of 99.5%, 93.5%, and 96.3% was achieved for BR-46, BB-3, and RR-120, respectively, from synthetic wastewater containing 10 mg L1of each dye at an applied potential of 10 V. The method was applied to real textile wastewaters and 73.0 to 99.5% removal of the dyes was achieved, Indicating Electrocoagulation can be used as a simple, and reliable method for the treatment of real wastewater from textile industries. It is used as a potentially viable and inexpensive tool for the treatment of textile dyes. Analysis of the electrochemically generated sludge by X-ray Diffraction, Scanning Electron Microscope, and Fourier Transform Infrared Spectroscopy revealed the expected crystalline aluminum oxides (bayerite (Al(OH)3 diaspore (AlO(OH)) found in the sludge. The amorphous phase was also found in the floc. Textile industry owners should be aware of the impact of the discharge of effluents on the Ecosystem and should use the investigated electrocoagulation method for effluent treatment before discharging into the environment.

Keywords: electrocoagulation, aluminum electrodes, Basic Blue 3, Basic Red 46, Reactive Red 120, textile industry, wastewater

Procedia PDF Downloads 53

Authors: Kidane Workelul, Yohans Tekle, Guesh Negash, Haftay Abraha, Nigus Abebe Shumuye, Yisehak Tsegaye Redda

Abstract:

Bovine papillomatosis (wart) is one of the economically important bovine skin diseases worldwide, caused by a group of viruses named papillomaviruses (PVs). However, it has often been misdiagnosed as other skin diseases and remained untreated. In order to determine the status of the diseases, twenty-two farms were visited, and fourteen infected cattle with cutaneous papillomatosis were identified from a total of 235. Papilloma biopsies were taken for molecular and histopathological characterization, the therapeutic trial of an autogenous vaccine was evaluated on infected animals. The overall status of bovine papillomatosis in this study was calculated as 5.96% (14/235). The disease was found to be statistically significant in the age groups less than two years (X² = 26.69, P = 0.0001). The more prominent histologically characterized lesions in the sampled tissue were identified as squamous papilloma and fibro-papilloma. The Polymerase Chain Reaction (PCR) based identification revealed that all the clinically and histo-pathologically characterized papillomatosis cases were found to be infected with Bovine Papilloma Virus1(BPV1), indicating that BPV1 was the most common and sole causative agent of the diseases in the study area. In immunizing active bovine papillomatosis, an autogenous vaccine therapeutic trial demonstrated excellent results, with practically full recovery and no recurrence of the infection. Hence, it is concluded that bovine papillomatosis is an economically important disease of young age group cattle as well as a treatable disease. So, the production of marketable autogenous vaccines against bovine papillomatosis should be started and given at an early stage.

Keywords: autogenous vaccine, bovine papillomatosis, bovine papilloma virus1 clinical-pathology, polymerase chine reaction, wart

Procedia PDF Downloads 80

Authors: Getachew Belay, Getachew Kahsu, Brhane Berhe, Kebede Tesfay, Fitsum Mardu, Nigus Shishay, Hadush Negash, Aster Tsegaye

Abstract:

Background: Malaria kills million people around the world, and it is still a serious public health problem in Ethiopia. Over the past years, the disease has been consistently reported as leading cause of outpatient visits, hospitalization and death in health facilities across the country. This study assessed malaria trend in Humera Town Kahsay Abera Hospital Tigrai region, Northern Ethiopia. Method: A Health facility retrospective cross sectional study was conducted in Kahsay Abera General Hospital from January 2011 to December 2019. Data of Malaria cases were reviewed from Health Management Information System with the help of experts in the office. The nine year data were extracted and analyzed using Excel by excluding those which lack demographic data. Result: A total of 36,604 smear positive malaria cases were confirmed in last nine years in the study area. Plasmodim falcifarum was the most prevalent reported species. Higher number of malaria cases were reported during October season.Males were more infected by the disese (63.1%) than females and males aged 15 years and above were the most iffected ones. The percentage proportion of P.falcifarum and P.vivax were 61.6% to 38.4%, respectively. There was a decreasing trend over the nine years following the peak in 2013. Conclusion: Malaria smear positivity, with highest cases being recorded in October, was declined over the nine years after peaking in 2013. Males aged 15 years and above were more affected, and P falciparum was the predominat species. Strengtheing the prevention and control activities is warranted in the study area.

Keywords: trend, malaria, kahsay abera general hospital, tigray, ethiopia

Procedia PDF Downloads 91

Authors: Sisay Negash, Zebene Asfaw, Kibreselassie Daniel, Michael Zech

Abstract:

A significant portion of the Ethiopian landscape features scattered trees that are deliberately managed in crop fields to enhance soil fertility and crop yield in which the compatibility of crops with these trees varies depending on location, tree species, and annual crop type. This study aimed to examine the effects of scattered Vachellia tortilis and Vachellia nilotica trees on selected physico-chemical properties of the soil, as well as the yield and yield components of sorghum in Ethiopia. Vachellia tortilis and Vachellia nilotica were selected on abundance occurrence and managed in crop fields. A randomized complete block design was used, with a distance from the tree canopy (middle, edge, and outside) as a treatment, and five trees of each species served as replications. Sorghum was planted up to 15 meters in the east, west, south, and north directions from the tree trunk to assess growth and yield. Soil samples were collected from the two tree species, three distance factors, three soil depths(0-20cm, 20-40cm, and 40-60cm), and five replications, totaling 45 samples for each tree species. These samples were analyzed for physical and chemical properties. The results indicated that both V. tortilis and V. nilotica significantly affected soil physico-chemical properties and sorghum yield. Specifically, soil moisture content, EC, total nitrogen, organic carbon, available phosphorus and potassium, CEC, sorghum plant height, panicle length, biomass, and yield decreased with increasing distance from the canopy. Conversely, bulk density and pH increased. Under the canopy, sorghum yield increased by 66.4% and 53.5% for V. tortilis and V. nilotica, respectively, due to higher soil moisture and nutrient availability. The study recommends promoting trees in crop fields, management options for new saplings, and further research on root decomposition and nutrient supply.

Keywords: canopy, crop yield, soil nutrient, soil organic matter, yield components

Procedia PDF Downloads 25