Addis Ababa Institute of Technology

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2D Hydrodynamic Modeling of Rib River Flooding
(Addis Ababa, 2011-10) Shiferaw, Muluken; Michael, Yonas (PhD)
Flood occurs repeatedly in Ethiopia and cause tremendous losses in terms of property and life, particularly in the lowland areas. The majority of flood disasters’ victims are poor people living in nearby stretch of floodplain. Therefore, the study was carried out to perform floodplain analysis and risk assessment of Fogera and nearby areas. This research involves the integration of 2D Structured Mesh Generator (CCHE-MESH) and hydrodynamic numerical model (CCHE2D model) with Geographic Information Systems (GIS) to develop a regional model for floodplain determination and representation. The study describes the flood extent and depth in the area for flow condition derived from the historical flow data of the Rib River. Triangulated Irregular Network (TIN) was prepared from shape file generated from spot elevations of the floodplain through field survey data and the DEM of the study area in ArcGIS. Triangulated Irregular Network (TIN) is converted to an ASC II format, which is supported by the CCHE-MESH and CCHE2D model. Boundary condition for the inlet is specified as total discharge and discharge hydrograph for steady and unsteady simulation respectively and for the outlet a constant water level of Lake Tana (1788m) is specified as a downstream BC which allows for simulation of the free flow condition at the river outlet. Initial conditions are defined based on information on gauges or through introducing a so called warm-up that precedes the actual simulation period and boundary conditions are generally specified from hydrometric data such as time series data of discharge and stage or simulated discharge hydrograph. Maps of flood Extent, Level, Depth and Velocity are developed using 100 years return period flood. The Flood has the inundation area of 47.13km2 while the simulated flood extent has flood depths less than 5.9m. The depth between 5.9m and 2m is located along the river channel and on the pond which is located south of the rib river. However, the depths below 2m exist largely on the flood plain which extend 4 km and 3 km outside right bank and the left bank of the main river respectively. The simulated water level ranges between 1798.4m ASL at the upstream and 1788m ASL at the downstream end of the main river. The simulation result indicates much of the flooding occur in the middle part of the river where the flow behaviour is mainly dominated by the inflow from the Rib River. Most of the areas around the flood plain are cultivated land with less proportion of Agro-pastoral, Marsh and Pastoral. 85-90% of the flood inundated areas are covered by agricultural land. The remaining 10-15% is covered by Agro-pastoral near inlet to Lake Tana.
3D Gravity Inversion for Mineral Exploration Over Southern Green-stone-Belts of Ethiopia
(Addis Ababa University, 2022-03) Girum, Ashenafi; Tulu, Besha (PhD)
Mainly this study aimed to investigate subsurface geology of the southern green stone mineralization zone for evaluation of gravity inversion is how effectively detecting high-density mineralization. Throughout the project, three main tasks have done: the first task was carrying out necessary correction for observed gravity data. Under this stage three main outputs were obtained: Bouguer gravity anomaly, regional Bouguer anomaly and residual Bouguer anomaly. The target information is represented by residual anomaly therefore it is became the final data for inversion process. The second task was minimizing Tikhonov’s cost function and carrying out inversion with the help of a conjugate gradient algorithm after formulated sensitivity matrix. The interpretation process was the last step of the work. The results obtained from the inversion process are demonstrated in two forms: the first one was a horizontal slice that illustrated the trend of mineralization in a horizontal plane and the second was density contrast model in a vertical plane that illustrated at four different lines of cross-section. In the horizontal density contrast model, the pixels value of high-density contrast under mineralization zone revealed 76.8% of pixels made a good agreement with the mineralization history of the target region. In addition, 90.3% of high-density contrast agreed with the location of metallic minerals in the region. In contrast, very low-density contrast in the region scored 3.77%. Therefore the inverted density contrast model well demonstrated the signature of mineralization in the target region. The vertical slice of the density contrast model indicated the depth condition of the high anomalous density region. Thus cross-section profile 1 up to 4 maximum depth and percentage of high density contrast above 600m depth are 1309.464m, 1089.866m, 847.72m, 661.0338m and 81.5%, 72%, 86.3%, 99.1% respectively. The vertical patterns of high-density contrast are correlated with the information obtained from a borehole at the mineralization zone. From such results and validation, I concluded: gravity anomaly inversion is a good tool to detect the position, depth extent, and the trend of the significant anomalous region.
5D Planning, Scheduling and Control of Construction Projects by Integrating Project Management Software and GIS
(AAU, 2017-12) Sitota, Girma; Abebe, Dinku (Prof.)
Construction industry can be deemed as the most vital driving force of a country. Construction of vast projects such as township, stadiums, and dams is a challenging task both in terms of managing complexities of the project and addressing the demands of all stakeholders. Its success or failure largely depends on cost effectiveness, time-bound delivery, quality and amount of resources available throughout the lifecycle of the project. This clearly turns the focus towards effective construction project management. Today’s demand of construction industry requires highly accurate planning, scheduling and management of the process of a project which can enable the overall optimization of cost, time, and resources. With the advances in information technology, its use is being constantly explored in the area of construction planning and monitoring. The aim of this study is to demonstrate the methodology of integrating Geographic Information System (GIS) with construction project management to provide a better solution for optimization and real time monitoring of the progress of a project. GIS is a computer based tool and being used extensively to solve various engineering problems involving the use of spatial data. The technology provides capabilities to solve problems involving creation and management of data, integration of information, visualization and cost estimation to which most of the construction management software are lacking. In spite of the growing popularity its complete potential to the construction industry has not been realized. Integration of GIS and Project management might assist a planner in a better perception of a project as well as in the integration of other parties’ activities in the planning process. It will provide a common basis of understanding and communication among stakeholders. This helps in reducing construction errors occurring on sites and thereby reduces the amount of administrative time. In this research paper a review of up-to-date work on the applications of GIS technology in construction industry is presented. Methodology to generate 3D view of a building and to represent construction schedule within GIS environment is also discussed. With this, integration of GIS and Project Management is developed using AutoCAD, MS-Excel, ArcGIS, and Visual Studio to assist construction managers in controlling and monitoring a construction progress. With time as the fourth dimension, the progress of construction task can be displayed as 4D (3D + time) view. The 5D (3D + time + cost) model of progress monitoring is beneficial to all stakeholders and can be opted as the future of planning and monitoring in the fast developing construction industry. A case study of one story building is selected for the purpose of presenting the integrated tool for progress monitoring. Ultimately, an easy to use Graphic User Interface (GUI) named as “5D Construction Monitoring Application” is developed to enable project participants have an idea of the current status of a project at run-time. The paper explores the potential of GIS environment in developing a construction project information system for rate analysis; and safety and quality control recommendation. It also suggests that the proposed GIS based methodology may replace manual methods used to extract information from the available database and can be easily updated as most of the information is in digital format. Successful project control is a challenging responsibility, but the job becomes easier when it is complimented with visualization of information. The propositions presented herein could facilitate and accelerate this trend, and as well provide means of measuring the success of implementation of 5D planning in construction projects and be a basis for further research.
(7,3) Maximum - Length Binary Cycle Code Applied to Single Channel Digital Communication System for Error Correction
(Addis Ababa University, 1996-06) snegash, Yohanne; Alemu, Ketema(phD)
This paper presents the design and hardware implementation of the (7,3) maximum-length binary cyclic code applied to a single channel communication system. In hardware implementation of the system a PC with a data acquisition board with time <- sharing for interfacing the analog signals. A 12-bit digital output of the PC is divided into blocks of 3-bits for processing by the channel encoder The implementation of the system is carried out using shift registers and logic gates. A sinusoidal input waveform is applied to the system input and a circuit designed with a combination of D-type flip-flops and logic gates is used to introduce the effects of a single-random-error and a double-adjacent-burst error to observe the performance of the system. The code resulted in good performance in correcting a single-random-error and a double-adjacent-burst-error.
A Comparative Study of Limits on Normalized Axial Loads of Es-En 1998:2015 With Other Current Major Building Codes on Columns
(Addis Ababa University, 2024-04) Abel Negussie; Adil Zekaria (PhD)
Axial loads highly affect the behavior of reinforced concrete members, such as failure mode, yield curvature, ultimate curvature, curvature ductility, beam-column joint, etc. In order to limit the adverse effects of axial loads, Ethiopian Standards based on Euro-Norms limits normalized design axial compressive loads. This research explores the basis for these limits and then compares them with other major codes and standards. The primary aim for these limits is for the axial loads not to exceed loads at balanced failure, . To study the balanced conditions, a series of interaction charts were constructed with the confinement effect of transverse reinforcement on concrete considered. The three main parameters for the charts are the distance of compression reinforcement from the extreme compression fibres normalised with respect to effective depth, ⁄ , mechanical reinforcement ratios, , and mechanical volumetric ratio of confining reinforcement, . Sectional properties, i.e., yield curvature, ultimate curvature and curvature ductility, under the obtained balanced axial loads were compared to their perspective limits. It was concluded that is highly affected by , and to a lesser extent by and . It has an inversely proportional relationship with both , and . Fifteen different column section was also considered as an example, and their results are in alignment with the interaction charts. From the results obtained, it can be concluded that the limits can be more directed for values of . This is especially the case for column sections having lower values of which show a greater load capacity than the set limits.
A gravimetric method to determine horizontal stress field due to flow in the mantle in East Africa Great Rift Valley
(Addis Ababa University, 2023-07) Abenezer Getinet; Andinet Ashagire (Phd)
The gravimetric approach has been widely used to determine the stress field of subsurface geology of the earth crust. Mainly this study aimed to determine lithospheric shear stress in the Earth’s mantle and its temporal changes caused by geodynamical movements. The gravimetric approach is applied, to evaluate the stress at the base of lithosphere and to detect changes in stress using static gravity field model EGM08 and GRACE monthly solutions respectively. In addition to the static gravity field data some physical information about topographic height, crustal thickness, and lithospheric thickness are incorporated in this method. As a result, more geophysical information and data are applied for computation of horizontal lithospheric stress in this approach. To do so, depth of the base of lithosphere determined by subtracting topographic height from lithospheric thickness is needed, thus the lithospheric shear stress component computed at the base of lithosphere. Moreover, the comparison of lithospheric shear stress using different static gravity field models are performed. The estimated horizontal shear stress at the base of the lithosphere throughout the study area revealed 55.68% of the stress is oriented in a northward direction and the remaining 44.32% is oriented in the southward direction; 44.41% of the stress is oriented in an eastward direction and the remaining 55.59% is oriented in the westward direction: and the result of the estimated horizontal shear stress magnitude ranges from ≈ 0.04 MPa to ≈ 15.32 MPa. Furthermore, the estimated horizontal shear stress components show good agreement with the tectonic boundaries and the location of stress regimes in the WSM2016 database, as well as the seismic events in the study area.
A Heuristics and Discrete Event Simulation for Optimized Layout Design in Agricultural Machinery Maintenance - A Case Study of Wereta International Business Plc.
(Addis Ababa University, 2024-07) Fitsumberhan Hailemeskel; Ameha Mulugeta (PhD); Ayele Legesse ((Mr.) Co-Advisor
Agricultural machineries play a vital role in agricultural processes and help in the production of food and non-food items. The efficient layout of agricultural machinery maintenance facilities is crucial for minimizing process times and maximizing throughput. This paper deals with the development and optimization of an agricultural machinery maintenance facility using discrete event simulation considering Wereta International Business Plc.’s agricultural machinery maintenance facility layout as a case. The development of the facility layout is done in a way that introduces flexibility of departments and also that combines the different services given in the facility, maintenance, training (customer & staff) and pre-delivery inspection processes. The research tries to construct a new facility layout that decreases the travel distance, considers the relationship between departments using the CORELAP facility layout construction method. The newly constructed facility layout has been optimized using facility layout improvement technique, CRAFT (excel add-in) to further enhance the optimality of the facility layout by enhancing the material flow between departments to minimize the material handling cost. Finally, an improved facility layout, with 15 departments that include main and supporting facilities and also combines the services and training facilities is developed. The proposed facility layout reduces that has been constructed from scratch and then optimized decreases the distance traveled between departments by 2,015.11 meter (a reduction of 33.66%) and the total monthly material handling cost by 531,093.14 Birr per month (a reduction of 86.85%). The entity output of the existing system is 40 units and for the proposed layout, the entity output is 67, an increase by 67.50%. Also, the system output from the existing simulation model is 125.30 units and the proposed layout simulation modeling system output increased by 58.85% to 199.04 units.
A Hybrid Approach to Strike a Balance of Sampling Time and Diversity in Floorplan Generation
(Addis Ababa University, 2024-05) Azmeraw Bekele; Beakal Gizachew. (PhD)
Generative models have revolutionized various industries by enabling the generation of diverse outputs, and floorplan generation is one such application. Different methods, including GANs, diffusion models, and others, have been employed for floorplan generation. However, each method faces specific challenges, such as mode collapse in GANs and sampling time in diffusion models. Efforts to mitigate these issues have led to the exploration of techniques such as regularization methods, architectural modifications, knowledge distillation, and adaptive noise schedules. However, existing methods often struggle to effectively balance both sampling time and diversity simultaneously. In response, this thesis proposes a novel hybrid approach that amalgamates GANs and diffusion models to address the dual challenges of diversity and sampling time in floorplan generation. To the best of our knowledge, this work is the first to introduce a solution that not only balances sampling time and diversity but also enhances the realism of the generated floorplans. The proposed method is trained on the RPLAN dataset and combines the advantages of GANs and diffusion models while incorporating different techniques such as regularization methods and architectural modifications to optimize our objectives. To evaluate the effect of the denoising step, we experimented with different time steps and found better diversity results at T=20. The diversity of generated floorplans was evaluated using FID across the number of rooms, and the results of our model demonstrate an average 15.5% improvement over the state-of-the-art houseDiffusion model. Additionally, it reduces the time required for generation by 41% compared to the housediffusion model. Despite these advancements, it is acknowledged that the proposed research may encounter limitations in generating non-Manhattan floorplans and when dealing with complex layouts.
A Study on Optical Quality Enhancement of Alpha-Alumina/Titania Pearlescent Pigment Via Insitu Ph Control
(Addis Ababa University, 2023-10) Buziye Guye; Anteneh Marilegn (PhD)
Pigment is a material that changes the color of reflected or transmitted light as the result of wavelength- picky immersion. During high-temperature calcination, there is a problem with the thermal expansion coefficient mismatch between mica and titania and the resulting thermal stress and crack formation. Thermal stress and crack formation is an issue during high-temperature calcination. Formation of cracks in the coating layer results in the scattering of light and the consequent decline of pearl luster. Various researchers have conducted a study on the low temperature rutile phase formation; however, the attempts have resulted in higher rutile phase fraction on the final coating but in most cases with compromised optical quality. In this study, α-Al2O3 platelets of average particle size ⁓ 10μm have been synthesized to be used as a substrate for the pearlescent pigment. Coating of TiO2 on the surface of the synthesized α-Al2O3 was performed via co-precipitation method. Urea was utilized as a hydrolyzing and pH-regulating agent along with TiOSO4 as a precursor to TiO2The sample with lower oxysulfate:urea ratio (i.e. strongly acidic synthesis media) resulted in higher rutile phase fraction (41.5%) while the other two samples, where the oxysulfate:urea ratios are 1:25 (i.e. close to neutral pH) and 1:50 (i.e. strongly basic synthesis media), resulted in extremely lower rutile phase fraction, 2.9% and 1.4% ,respectively. The coated samples' morphology showed that the entire coating was smooth. When compared to samples with lower rutile phase fractions, those with greater rutile phase fractions exhibit higher reflactance in the visible area, according to the optical performance of the samples. The color value measurments have also revealed that, samples with higher rutile fractions exhibit higher lightness values (L*) in comparison to those with lower rutile phase fractions. The study showed that, in general, controlling the rutile phase fraction by adjusting the pH of the synthesis media using in-situ urea decomposition was effective in producing TiO2 coatings with higher rutile phase fractions and better surface smoothness, which in turn results in higher optical quality.
A Study on The Flour Properties and Qualities of Wheat-Based Biscuits Supplemented with Faba-Bean and Cassava Flour
(Addis Ababa University, 2023-09) Gebremedhn Brhane; Shmeles Shumi (PhD)
Faba beans and other legumes are significant due to their high nutritional value. The goal of this study is to investigate on the flour properties and qualities of wheat-based biscuits supplemented with faba-bean and cassava flour. The study examined the proximate composition of both (composite flour and biscuit flour), rheological, and functional properties. Besides mineral content, total energy, gluten content, texture, color attribute, and sensory evaluation have been studied. The formulation for composite flour was developed using a D-optimal mixture design ratio applying Design-Expert®, version 13. Accordingly, 16 composite flour samples were developed (T1, T2……. T16 and control sample) and evaluated using the standard method. The gluten content of wheat flour was significantly different from the whole formulated composite flour and also the samples were significantly different from each other at (p<0.05). The proximate composition shows that the crude protein content of faba-bean flour (23.13±0.00%) is two times more than that of wheat flour (11.75±0.00%) and eight times more than that of cassava flour (2.9±0.02%), respectively. Whereas, composite flours show lower water absorption capacity and higher oil absorption capacity and water solubility than wheat flour. The result showed that the pasting temperature range was 72.55 to 76.70 °C compared with the pasting temperature of the control sample (89.65 °C). Moreover, biscuit developed from 40.5% wheat flour, 40% cassava flour and 19.5% faba-bean flour biscuit looked almost similar to the wheat flour biscuit in all aspect with overall acceptability of 8.05±0.64. In this study the 40.5% wheat flour, 40% cassava flour and 19.5% faba-bean flour biscuit was found to be the most acceptable biscuit and had high crude protein, crude fiber and low gluten content. On the other hand, adding faba-bean flour to wheat-cassava flour positively affects the physical, chemical, color attribute, texture, alkaline water retention capacity, staling rate and sensory characteristics of the biscuits.
A Trilingual Android Application with Automatic Malaria Detection from Microscopic Images of Red Blood Cells
(Addis Ababa University, 2023-12) Berihun Nigussa; Dawit Assefa (PhD)
Malaria, which is a mosquito-borne blood disease caused by Plasmodium parasites, is one of the virulent infectious diseases affecting human beings and other animals since antiquity. Even though there were promising progresses in the reduction of malaria morbidity and mortality in the past two decades before the outbreak of COVID-19, the latest two reports of theWorld Health Organization (WHO) statistics indicate that malaria has been overlooked due to the COVID pandemics. Malaria is still prevalent specifically in low resource setting areas such as the sub-Saharan African countries, including Ethiopia. WHO reported that there were 229 million new cases of malaria and 409,000 deaths globally in 2019, alone. Whereas in the year 2021, the morbidity and mortality was reported to rise up to 247 million and 619,000, respectively. Timely diagnosis and treatment as well as good awareness about the disease play a major role to combat malaria. In the current project work, it was intended to design and develop a multi-lingual Android App that offers useful information about the malaria disease and is capable of automatically detecting malaria infected red blood cells (RBCs) from color microscopic images based on a deep learning approach. The Convolutional Neural Network (CNN) based deep learning model was trained, validated and tested on a publicly available dataset composed of microscopic images of RBCs taken from individuals with confirmed malaria infection as well as normal control groups. Experimental results generated from the deep learning model showed that the detection capability of the model achieved 100% training accuracy, 96% validation accuracy and 96% testing accuracy. The developed App avails useful information about malaria disease in general and tips users with fundamental information regarding its prevention and transmission mechanisms acting as an m-health system.
A Video Coding Scheme Based on Bit Depth Enhancement With CNN
(Addis Ababa University, 2023-06) Daniel Getachew; Bisrat Derebssa (PhD)
Raw or uncompressed videos take a lot of resources in terms of storage and bandwidth. Video compression algorithms are used to reduce the size of a video and many of them have been proposed over the years. People also proposed video coding schemes which works on top of existing video compression algorithms by applying down sampling prior to encoding and restoring them to their original form after decoding for further bitrate reduction. Down sampling can be done in spatial resolution or bit depth. This paper presents a new video coding scheme that is based on bit depth down sampling before encoding and use CNN to restore it at the decoder. However unlike previous approaches the proposed approach exploits the temporal correlation which exists between consecutive frames of a video sequence by dividing the frames into key frames and non-key frames and only apply bit depth down sampling to the non-key frames. These non-key frames will be reconstructed using a CNN that takes the key frames and non-key frames as input at the decoder. Experimental results showed that the proposed bit depth enhancement CNN model improved the quality of the restored non-key frames by an average of 1.6dB PSNR than the previous approach before integrated to the video coding scheme. When integrated in the video coding scheme the proposed approach achieved better coding gain with an average of -18.7454% in Bjøntegaard Delta measurements.
Abay Basin Water Allocation Modelling Using Hec Ressim
(Addis Ababa University, 2009-10) Wondye, Fanuel; Seleshi, Yilma (PhD)
Despite Ethiopia possesses abundant water resources potential, second only to Congo in all of Africa, the country is at critical cross roads with large and increasing population, a depressed national economy, insufficient agricultural production and low no of developed energy sources. 83% of Ethiopians lack access to electricity; only 5 percent of irrigable land and 3% of the hydropower potential in the Blue Nile basin has been developed so far. Nowadays persisting drought and increasing competition for water have left Ethiopia with no more chance other than seeking solutions and assure sustainability of the resource. Even though Ethiopian portion of Blue Nile, Abay possesses a great potential of irrigation and hydropower developments, the financial and political constraints have long hindered the country’s development. This study aims at analyzing the effects of implementing the potential irrigation and hydropower projects that are contemplated in the country. Reservoir system simulation (Hec-ResSim) software has been used to study the out puts of executing different developments in the basin. This has been done by setting up the model and simulating for four scenarios including the base scenario referring to the current situation in the basin. After a curious filtering of all projects mentioned in the basin’s master plan and other project specific reports, 315,431ha (38.7% of total 815,581ha potential) of irrigation and 7,026Mw (89.6% of total 7845Mw potential) of hydropower potential; overall comprising 23 dams having a combined maximum storage capacity of 170.15Bm3 have been preferred to be analyzed and assessed using the model. After categorizing these projects under four scenarios; the simulation has been done based on 33 years (1960-1992) of monthly hydrologic flow series. vi This study under has indicated that If Ethiopia is to develop 315,431ha and 7,029Mw, the resulting decline in the cross border flow will be only 3,382.93Mm3 which is only 7.29% of the currently simulated (under current condition scenario,scenario-1) Abay discharge to Sudan which is 46,396.99 Mm3. Under this condition both Ethiopia and Sudan benefit from regulation of Abay by Ethiopian dams, in that it results in increasing of low flows, giving the whole system uniformity of balance, decreasing water escaping during flood seasons. As concluded from this study regulation works upstream in Ethiopia have resulted in a uniform monthly average flow of 3,584.51Mm3 throughout the year to Sudan. Currently as the base case simulation indicated, Sudan receives monthly average low flow of 1,233.54Mm3 through November to June which then turns to be increasing; August being flood month when 13,456.27Mm3 has been observed. In addition if Ethiopia is to develop 7,029Mw including hydropower projects on the tributaries, then some 38,385.81Gwh/annum of electricity will be produced. Even though Tana-Beles project imposes a big deal of inflow and power out put decline on the main stream hydropower plants, this power decrease was exceeded by the power generated at Tana-Beles power plant. Prior to Tana-Beles project Power output from main stream plants has been 34,284.23 Gwh/annum then increased to 34,736.14 Gwh/annum despite power decrease at Karadobi, Mabil, Mandaya and Border.
Abrasive Wear Behavior of Bamboo Reinforced Polymer Composite with PTFE
(Addis Ababa University, 2020-06) Sentayehu, Worku; Eyasu, Woldesenbet (Prof.)
The aim of the present work is to study the abrasive wear behavior of composites made by reinforcing bamboo fibers with the addition of PTFE and thermoset resin matrix. The fibers are extracted by hand and manual process and the composite samples were prepared to a maximum of 30% volume of fiber. Wear tests were carried out in dry conditions on a pin-ondisc which is modified by me and the machine at a constant sliding distance of 1000 m with sliding velocities of 2m/s and 4m/s and normal loads of 15N and 30N. The effect of PTFE content on abrasive wear properties of composites were investigated and compared with pure BPC composites made under the similar testing conditions. It is observed that the wear loss of composites increase with increase of normal load whereas the specific wear rate decreases. The optimum weight loss and specific wear rate for bamboo fiber reinforced composites were obtained at 30% volume of pure composite.
Accelaration of Preprocessors of the Snort Network Intrusion Detection System Using General Purpose Graphics Processing Unit
(Addis Ababa University, 2015-04) Yihunie, Simegnew; Assamnew, Fitsum
Advances in networking technologies enable interactions and communications at high speeds and large data volumes. But, securing data and the infrastructure has become a big issue. Intrusion Detection Systems such as Snort play an important role to secure the network. Intrusion detection systems are used to monitor networks for unauthorized access. Snort has a packet decoder, pre-processor, detection engine and an alerting system. The detection engine is the most compute intensive part followed by the pre-processor. Previous work has shown how general purpose graphics processing units(GP-GPU) can be used to accellerate the detection engine. This work focused on the pre-processors of Snort, speci cally, the stream5 pre-processor as pro ling revealed it to be the most time consuming of the pre-processors. The analysis shows that the individual implementation of stream5 using Compute Uni ed Device Architecture(CUDA) achieved up to ve times speed up over the baseline. Also, an over all 15.5 percent speed up on the Defense Advanced Research Projects Agency(DARPA) intrusion detection system dataset was observed when integrated in Snort. Key words: Intrusion Detection System, Snort, Graphics Processing Unit, CUDA, Parallelization, Porting, Preprocessor.
Accelerated Shelf-life Prediction and Quality Characterization of Edible Cotton, Peanut and Soybean Seed Oils Produced in Ethiopia
(Addis Ababa University, 2017-10-23) Addisu, Alemayhu; Shimelis, Admassu (Assoc.Prof.)
Edible oils are regarded as an important component of the diet because they are source of energy, essential fatty acids, and also provide characteristic flavors and textures to foods. The purpose of this research study was to determine the qualities of edible cottonseed, peanut and soybean oils processed in Ethiopia and predict their shelf-life using ASTM. The AOAC method of Analysis was employed in the determination of the physical and chemical characteristics of the oils. The result obtained for edible soybean, peanut and cottonseed oils, respectively were; specific gravity at 20/20OC: 0.929, 0.943 and 0.922, refractive index at 20OC: 1.48850, 1.48508, and 1.48565, photometric color index: 5.262, 15.908 and 216.316, insoluble impurities: 0.001, 0.004, and 0.013% (w/w), moisture content: 0.210, 0.219 and 0.220% (w/w), peroxide value: 1.299, 2.398, and 3.396meq O2/kg of oil, iodine value: 136.740, 97.536 and 101.112grams of iodine absorbed/100g oil, Saponification value: 210.345, 210.779 and 208.411mgKOH/g, unsaponifiable matters: 0.169, 0.069 and 0.383% (w/w), and acid value: 0.420, 0.630 and 0.561mgKOH/g. Fatty acid profiles were also determined by GC-MS as methyl esters. The results showed that the predominant fatty acid in edible soybean and cottonseed oils was linoleic acid 42.807 and 41.587%, respectively while oleic acid (46.252%) was major fatty acid in edible peanut oil. The shelf-life of edible oils was tested applying ASTM. The oils were subjected to three different elevated temperatures: 35, 45 and 55OC in acceleration chamber and hydrogen peroxides formation were monitored for six successive weeks. The evaluation was performed graphically (fitting of experimental data to a linear equation) after completion of the experiments. Accordingly, the model that best fitted the experimental data corresponds to a zero order kinetic model for all edible oil investigated. Arrhenius relation was applied to model that effect of temperature on the rate constant of peroxide formation. Combining the kinetic model identified and the rate constant model equation, a general shelf-life model equation that could help to predict the shelf-life of oils studied at any temperature was developed. Employing predictive model developed, the shelf-life of the domestic edible oils was determined at room temperature (25OC) and amounts 36.9 weeks for soybean oil, 42.1 weeks for peanut oil and 37.8 weeks for cottonseed oil. The result obtained for most physicochemical quality parameters of the edible oils considered were within the standard range indicated by Ethiopia Standard Agency. From fatty acid profile analysis it can be concluded that edible soybean, peanut and cottonseed oils are an excellent source of essential fatty acid omega-6 (linoleic acid) and omega-9 (oleic acid). Comparatively edible peanut oil had longer shelf-life than edible soybean and cottonseed oils. The shelf-life of properly refined edible oils is typically 12 – 18 months at ambient temperature. From shelf-life assessment, all edible oils investigated scored lower shelf-life. So, to minimize the oxidation of edible oils and maximize the shelf-life, it is recommended to use: antioxidants, sequestering agents and selection of appropriate packaging material (colored glass bottle). Besides, FFAs are more susceptible to oxidation than the glycerol esters of these fatty acids. Therefore, any increase in the acidity of the oil must be absolutely avoided during refining of the oil.
Acceleration and Energy Reduction of Object Detection on Mobile Graphics Processing Unit
(Addis Ababa University, 2019-06) Fitsum, Assamnew; Jonathan, Rose (Prof.); Dereje, Hailemariam (PhD)
The evolution of high performance computing in today’s smartphones is enabling their use in compute-intensive applications. As the compute requirement increases, the energy required to do the computation cannot increase in proportion because the cost of providing that energy available and cooling would become prohibitive. An alternative, potentially power-reducing approach is to use graphics processing units or special accelerator cores. Today’s smartphones are equipped with systemon-chip (SoC) devices that house many cores such as graphics processing units, digital signal processors, and special multimedia encoder/decoder hardware along side multi-core central processing units. Their inclusion enables applications that require greater computational power such as real-time computer vision. In this work, we study the capability of the recently introduced general-purpose graphics processing unit (GPU) in a smartphone SoC to enable energy-efﬁcient object detection. This will include understanding the architecture of the recent GPUs that will be used (the Adreno 320 and Adreno 420 from Qualcomm), the implementation and optimization of the object detection algorithm used in the Open Computer Vision library (OpenCV) using these GPUs and measuring the energy consumption of this implementation. We implemented the Viola-Jones based object detection on the GPU in an Android tablet. The implementation is 35% faster on average than the same algorithm running on the CPU on the same device. The implementation also reduces the average energy consumption by 68% compared to the CPU on the same device. An application that utilized the object detector on the mobile GPU to detect Ringworm skin disease was developed. A classiﬁer was trained for this application and it has an accuracy of 75%.
Acceleration of Convolutional Neural Network Training using Field Programmable Gate Arrays
(Addis Ababa University, 2022-01) Guta, Tesema; Fitsum, Assamnew (PhD)
Convolutional neural networks (CNN) training often necessitates a considerable amount of computational resources. In recent years, several studies have proposed CNN inference and training accelerators, which the FPGAs have previously demonstrated good performance and energy efficiency. To speed processing, the CNN requires additional computational resources such as memory bandwidth, a FPGA plantform resource usage, time, and power consumption. As well as training the CNN needs large datasets and computational power, and they are constrained by the requirement for improved hardware acceleration to support scalability beyond existing data and model sizes. In this study, we propose a procedure for energy efficient CNN training in collaboration with an FPGA-based accelerator. We employed optimizations such as quantization, which is a common model compression technique, to speed up the CNN training process. Additionally, a gradient accumulation buffer is used to ensure maximum operating efficiency while maintaining gradient descent of the learning algorithm. Subsequently, to validate our design, we implemented the AlexNet and VGG16 models on an FPGA board and a laptop CPU and GPU. Consequently, our designs achieve 203.75 GOPS on Terasic DE1-SoC with the AlexNet model and 196.50 GOPS with the VGG16 model on Terasic DE-SoC. This, as far as we know, outperforms existing FPGA-based accelerators. Compared to the CPU and GPU, our design is 22.613X and 3.709X more energy efficient respectively.
Accessibility and Suitability Analysis of Light Rail Station Location by using (AHP) and GIS: Case study on Existing and Future Expansion of Addis Ababa LRT Respectively
(Addis Ababa University, 2016-12) Gomeju, Taye; Alemayehu, Ambo (PhD)
Addis Ababa city metropolitan constructed phase one light rail transit line aiming to solve current transport problem. This Light Rail Transit is assumed to transport 80,000 passengers per hour per direction. For the system to hit the targeted objective on the proposed line, stations have to be positioned at a place where it can attract maximum users which enable the system to solve the problem and to be independent of subsidies. This is all about integrating Light rail system with other transport modes in Addis Ababa. This paper examines the existing station sites accessibility to other transportation modes or access mode, and adopts Geographic Information Systems and Multi-Criteria Evaluation technique to carry out suitability mapping of station locations for phase two light rail transit route in Addis Ababa. For the station suitability analysis, eleven different criteria were identified and each criterion was weighted using Analytical Hierarchy Process AHP. The output of Analytical hierarchy process was used as an input for geographic information system GIS special analysis. Finally, based on these criteria requirements using overlaying, Euclidean distance calculation, Rasterisation, buffering reclassification and weighted overlay analysis, the station site suitability map was generated. The map revealed five classifications as: “less suitable”, “suitable”, “moderately suitable”, highly suitable and “extremely suitable”.
Accuracy assessment and bias correction for open sources Digital elevation model (DEM): a case study in and around Diredawa city, Ethiopia
(Addis Ababa University, 2022-02) Mesfin, Delelegn; Tulu, Besha (PhD)
Digital elevation model (DEM) is a digital and mathematical representation of the real-world topographic surface by using elevation data. The global open-access DEM data contain errors and are not suitable for engineering and other high accuracy requiring applications. The main aims of this study are vertical accuracy assessment and bias correction for open-source global DEM data. Conventional global DEM data; SRTM DEM 1-arc second and ASTER-GDEM 1-arc second, and new global DEM data ALOS-PALSAR both 12.5 m and 30 m spatial resolution DEM data were applied for this study. Ground control point GCP, RTK-GPS data, and photogrammetric DEM reference data were used to evaluate the accuracy of the selected open-source global DEM data. Accuracy assessment was applied in different approaches, one is a point-based approach using statistical measurement. The computed Root mean square (RMSE) for SRTM is 3.68 m, 4.24m, and 3.41m in GCP, RTK-GPS, and Photogrammetric DEM reference data, for ASTER-GDEM the RMSE value is 8.87 m, 7.08 m, and 7.05 m, for ALOS-PALSAR12.5 m it is 4.58 m, 4.46 m and 4.58 m and for ALOS- PALSAR30 m the value is 5.79 m, 5.10 m and 5.34 m, respectively. The accuracy of SRTM showed better in three reference data and ALOS-PALSAR12.5 m is followed the SRTM in the accuracy. Whereas the accuracy of ASTER-GDEM showed less accuracy among the selected global DEM data. The second approach is based on land use land cover data using RTK-GPS reference data; bare land, road line, drainage pattern, rock area, and tree areas point data are collected using TRIMBLE R8 GNSS/R6/5800 instrument, the accuracy of rock area showed less accuracy in all DEM data except SRTM DEM and the accuracy of the bare land area showed better in all DEM averagely. And the third approach of vertical accuracy assessment is terrain classification; the terrain of this study area is segmented into three classes (flat area, moderate slope, and steep slope), the accuracy of the flat area showed high and the accuracy of the steep slope is less for all DEM data. Finally, bias correction was applied using linear transformation parameters to reduce the residual of the global DEM data, the accuracy of ASTER-GDEM was improved by 22.9 % after the bias correction, while the accuracy of SRTM is improved by 6.7 % and the accuracy of PALSAR12.5m and PALSAR30 m was improved by 5.1 % and 2.2 % after the bias correction.

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