College of Natural and Computational Sciences

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2, 4, 6-Tris (N-Salicylidenehydrazino) S-Triazine and its Copper (II) Complex-Synthesis, Characterization and Antimicrobial Screening
(Addis Ababa Universty, 2008-07) Haile Kiros; Raju V.J.T. (Professor)
A new tripodal ligand 2, 4, 6-Tris (N-Salicylidenehydrazino)-s-Triazine (L) was synthesized by the condensation of salicylaldehyde with 2, 4, 6-tris-(hydrazine)- s-triazine(THSTZ) in acetonitrile. Copper complex of the ligand was synthesized in chloroform-methanol 50% v/v medium. The ligand and the metal complex were characterized by employing spectral (IR,Uv-Vis,AAS, NMR), conductance and magnetic susceptibility studies. The purities of the compounds were established by TLC. The studies support formation of stable metal complex corresponding to the formulae: [Cu(II)LH2O] .4H2O. Conductivity measurement indicates that the complex is a non-electrolyte. Spectral and Magnetic data suggest dibasic ONN donor behavior of the ligand towards Cu(II). Square planar geometry for Cu2+ complex has been proposed. The ligand, metal complex and related compounds were screened for antimicrobial activities against Escherichia coli, Pseudomonas eruginosa, Staphylococcus aureus and Bacillus cereus bacteria by employing tetracycline as test control agent. The result showed that both the ligand and the metal complexes were inactive, while the ligand precursor (THSTZ) and the metal salt (CuCl2.2H2O) were active. As such derivatization and the complexation can help in detoxication purposes. Key words: 2, 4, 6-Tris (N-Salicylidenehydrazino)-s-Triazine (L), tripodal ONN donor, Cu2+ complex, Square planar geometry, antimicrobial.
2d Geometry of Quadrapole Magnetic field Lines from Neutron Star and Associated Radiation Pressure
(Addis Ababa University, 2011-06) Girma, Melkameshet; Wetro, Legesse (PhD)
In this thesis we have derived the vector potential to determine the analytic expressions for the magnetic eld of dipole and quadrupole components of neutron star, we develop the eld line equations and the magnetic eld line geometry of both dipole and quadrupole terms. The magnetic eld varies with time and as well as the induced electric eld. As a result the neutron star can generate electromagnetic radiation. This electromagnetic radiation has pressure. We have derived the radiation pressure at any distance r out side of the surface of the neutron star
A 2D Monte Carlo Investigation of Static and Dynamic Properties of Ring polymer
(Addis Ababa University, 2015-02) Admasu, Ashenafi; Yergou, Tatek (PhD)
Monte Carlo simulation technique has been used to investigate the static properties and translocation characteristics of ring polymers in two dimensions. Each chain consists of exible linkage between monomers forming a closed loop. We consider the unbiased translocation process of the ring where the polymer translocates purely due to thermal uctuations. The average escape time has been analyzed as a function of chain length N. And we found that, the polymer escape time of the ring polymers having a length N < 100, also has a scaling behavior N where is more closer to 1 + 2 in which is the Flory exponent of value 3/4 in 2D and 3/5 in 3D. Such scaling is also the scaling behavior of the unbiased long linear chains. We study the static property of the small cyclical polymer chains by calculating the mean-squared radius of gyration Rg. Bond uctuation method (BFM) is implemented to study both characteristics of the particular ring polymers
2D Spin-Dependent Electron Scattering by Nanomagnets
(Addis Ababa University, 2012-02) Senbeta, Teshome
The 2D scattering problem of an electron by a magnetized nanoparticle is solved in the Born approximation with account of the dipole - dipole interaction of the magnetic moments of electron and nanomagnet. The scattering amplitudes in this problem are the two-component spinors. They are obtained as functions of the electron spin orientation, the electron energy and show anisotropy in scattering angle. The initially polarized beam of electrons scattered by nanomagnet consists of electrons with no spin flipped and spin flipped. The majority of electrons with no spin flipped are scattered by small angles. This can be used as one method of controlling spin currents. 2D spin-dependent scattering of slow unpolarized beams of electrons by charged nanomagnets is analyzed in the Born approximation. The obtained scattering lengths are larger than those from the neutral nanomagnets approximately by one order. It is shown that for particular parameters of the system it is possible to polarize completely the scattered electrons in a narrow range of scattering angles. The most suitable system for realization of these effects is 2D Si electron gas with immersed nanomagnets. The 2D spin-dependent electron scattering by the linear chain of periodic nanomagnets with account of the diffraction effects was studied. This effect takes place in 2D electron gas with immersed nanomagnets. By tuning a distance between nanomagnets, it is possible to obtain diffraction maximum of the scattered electrons at scattering angle, which corresponds to complete spin polarization of electrons. The total diffraction scattering lengths are proportional to N2 (N is a number of nanomagnets). The proposed system can be an efficient separator of spin polarized currents
2D/3D Analysis of Magnetotelluric Data in the Central Main Ethiopian Rift (CMER): Implications for Geothermal Resources
(Addis Ababa University, 2024-01) Aklilu Abossie; Shimeles Fisseha; Bekele Abebe
The Main Ethiopian Rift (MER) is a seismically and volcanically active portion of the East Africa Rift System (EARS). In the Central Main Ethiopian Rift (CMER), there are several active volcanoes and calderas that are known to be constantly changing, with periods of rising and sinking. Geothermal resources are often associated with these active volcanoes. This dissertation deals with the analysis of the 2D/3D crustal geoelectric models obtained through 2D joint (TE - transverse electric and TM - transverse magnetic modes) inversion of magnetotelluric (MT) data across CMER and a 3D inversion model from one of the hydrothermal occurrences in the CMER, Ashute geothermal field, which is found close to the western escarpment. This is aimed at investigating heat sources, heat flow paths, and geothermal resources to delineate and characterize the geothermal structures and comprehend the tectono-magmatic setting of the crust beneath the study area. Furthermore, the static shift correction data were used to obtain better and more accurate estimates of subsurface resistivities structure and thicknesses by using 1D joint inversion of TEM and MT data in the Ashute area. Based on the 3D inversion resistivity model, the subsurface beneath the Ashute geothermal site can be described by three main geoelectric layers. The top layer, which is relatively thin and highly resistant (> 100 Ωm) and extends down to 400 m depth, consists of unaltered volcanic rocks near the surface. Below this is a conductive layer (< 10 Ωm) with a maximum thickness of 1 Km, likely caused by the presence of clay layers (smectite, illite/chlorite zones) resulting from the alteration of volcanic rocks. In the third and deepest layer resistance of the subsurface gradually increases to an intermediate range (10–46 Ωm). This could be linked to the formation of high-temperature alteration minerals such as chlorite and epidote at depth, indicating the presence of a heat source. Similar to a typical geothermal system, the increase in electrical resistance below the conductive clay layer may suggest the existence of a geothermal reservoir Otherwise, no exceptional low resistivity (high conductivity) anomaly is detected at depth. The phase tensor analysis results across the CMER show a small beta value at low periods (nearly below 10 s), which indicates 1D or 2D structures, while at long periods (> 10 s), the data show 3D structures with a large value of |β| > 30. This asserts that the 2D inversion model can suitably describe the resistivity structures of the shallow crust. The dominant geo-electrical strike is estimated to be N150E using a Z-invariant and phase tensor azimuth. The results of 2D joint inversion of TE and TM modes seemingly identified partial melt within an upper crustal fracture zone (fault) with a resistivity of less than 5 Ωm at a depth of 12–22 km. This partial melt extends beneath the SDFZ with a width of approximately 10 kilometers horizontally. It could be related to the source of heat for the Ashute and Aluto geothermal fields.
3D Joint Inversion of Gravity and Magnetics Data to Characterize the Geothermal Field and Reservoir Geometry Beneath the Tulu Moye Volcanic Complex, Central Main Ethiopian Rift
(Addis Ababa University, 2024-06) Aklilu Hailu; Abera Alemu
This study is conducted in the Central Main Ethiopian Rift (CMER) which is located 70km SE of Addis Ababa in Oromia Regional State East Arsi Zone. Geographically the area is bounded by 38.90-39.40 Longitude and 8.10-8.30 latitude. The study is meant to characterize the geothermal field and reservoir geometry beneath the Tulu Moye Volcanic Complex. Specifically, it is meant to define geothermal reservoir components like heat source, permeable zone, clay cap/ cap rock and recharge area of the geothermal system believed to exist in the study area. In the process the geometry and possible extent / volume of the geothermal system is also determined/ estimated. Ground gravity and ground magnetics data, which are collected using Lacoste and Romberg and GSM 19T proton precession magnetometer, respectively are primarily used to reach the main and specific objectives of the study. In addition to the main data, other a priori geoinformations like microseisms and resistivity survey results in the area are used to complement the study methodologies, data processing steps and result analysis. Microsoft products, Oasis montaj, Quantum GIS, and GRAVMAGINV3D applications and algorithms were deployed to organize, analyze, change discrete data to continuous surface, create derivative maps and generate 3D density and magnetic susceptibility models. The main methodology used in the study is 3D joint inversion of ground gravity and magnetics data to obtain 3D models of density and magnetic susceptibility. Both the 3D models obtained along with the a priori geo-information obtained from the area divulge presence of the anticipated main components (heat source, permeable zone/s, recharge area) of a typical geothermal system in the study area. Moreover, the study estimated the possible existent of the geothermal system believed to exist in the study area.
3d Modelling for Urban Cadasteral Regestration,Management and Administration; The Case of Bahir Dar Town Ethiopia
(Addis Ababa Universty, 2016-06) Hamid, Ahmed; Berihan, Getachew (PhD)
High rate of Population growth, coupled urbanization and industrialization results for high demand for land. In order to increase availability of land, the government of Ethiopia has introduced the construction of multipurpose buildings which allows vertical expansion rather than horizontal. Due to this mode of expansion there is a need to establish a land tenure system which considers the use and registration of multipurpose buildings in 3D environment. In Ethiopia, using aerial photography for cadastral mapping is not a new thing for the processes of extraction of 2D cadastral layer but most of the time it is not seen using for 3D cadastral registration system. Method of feature extraction in 3D environment using aerial photograph is cheaper than that of LIDAR. 2D cadastral and property registration system cannot solve the problem related to building height and was difficult to standardize building construction, even if it has been employed for a long period of time. 2D cadastral registration system is not able to clearly indicate the property right of individuals having multi-purpose buildings. Due to this it is difficult to register, manage, and visualize their institute condition for decision making and for a given applications such as infrastructure development. This study is intended to examine the applicability of Aerial photo and CGA script for automated 3D objects modeling, design cadastral information system for commonly owned residential building and commercial centers, examine legal and institutional aspects of 3D property information and representation system for land registration, management, administration, urban planning and decision making process in Bahir Dar town by applying 3D GIS techniques. The existing 2D cadastral registration system was carefully assessed and the gaps are well identified prior to propose a new registration system. The ESRI 3D city engine module was used to reconstruct the multipurpose buildings after carried out photogrammetric processes. CGA rule was written for each textures such as wall, roof, road, façade, window and door to produce an automated 3D urban model. From the study it is found that the existing cadastral registration system in Bahir Dar land management and development office does not consider the registration of multipurpose buildings. Due to this a new registration system was proposed to incorporate multipurpose buildings in the future cadastral registration processes. It was also found that a 3D model cadaster supports better in managing increased demand of land and building constructions. Key words: 3D model; Cadaster; aerial photo; CGA rule; Façade; Registration; Management Administration, Bahir Dar
5W1H-Aware Approach for Retrieving Semantically Rich Multidimensional Events in Social Media Ecosystem
(Addis Ababa University, 2024-08) Siraj Mohammed; Richard Chbeir
Nowadays, multimedia digital ecosystems (e.g., social media sites) become a great source of user-contributed multimedia documents for many types of real-world events. Social media documents about events are multimedia (e.g., image, video, text, and others), contain multiple features (describing different characteristics in it such as 5W1H), and come from multiple sources. Such events can be used to construct Event Knowledge Graph (EKG) which is basic to retrieve semantically rich multidimensional events. However, social media documents cannot be used directly to construct such a knowledge graph. First, social media documents must be represented in order to detect multimedia events as well as their different types of semantic relationships. To achieve these tasks, it is necessary to carry out preliminary event-related tasks, such as detecting, linking, and representing events. By doing these, we can provide an event search API that presents a concise summary of events focused on temporal, spatial, semantic, and participant aspects. For this, we proposed a novel 5W1H-aware framework consisting of six modules. Each of these modules uses 4W elements. More specifically, we first represent social media documents that have been used to detect real-world events with their 4W elements based on event-only descriptive features. The detected events are used to identify the three main event relations categories (such as, spatial, temporal, and sematic) and many relation types under these categories by comparing dimensions over multimedia events. We then used a graph database to store event detection outputs as nodes and relationship identification outputs as edges to construct an Event Knowledge Graph (EKG). Finally, we integrated the EKG with an event retrieval API to retrieve events. Each of these event-related tasks were evaluated using various datasets. For instance, the effectiveness of an incremental event detection algorithm was evaluated using the MediaEval 2013 dataset. The algorithm achieved an NMI score of 0.9914 and an F-score value of 0.9928 when the feature weights were assigned as 0.40 for participant, 0.30 for temporal, 0.35 for spatial, and 0.45 for semantic. Manually crafted spatial and temporal datasets are also used for evaluating the effectiveness of event relationship identification algorithm. Finally, the effectiveness of the developed EKG was evaluated through its downstream tasks, like retrieving similar nodes, whereas the event search API was evaluated via PageRank and search result relevance analysis. Results from the experiments showed that the proposed approach was more effective compared with alternative solutions.
9,9-Disubstituted Fluorene-Based Polymers: Preparation and Characterization
(Addis Ababa Universty, 2009-07) Hussen, Ayalew; Mammo, Wendimagegn (Professor)
A family of conjugated polymers based on 9,9-disubstituted fluorenes and cyanovinylenes were reported. The polymers were synthesized by employing a slightly modified Suzuki coupling polymerization reaction and condensation polymerization utilizing the Knoevenagel reaction. The resulting polymers showed good solubility in chloroform. The energetic positions of the band edges were determined by cyclic voltammetry. The synthesized polymers were characterized by using spectroscopic techniques such as UV-Vis and 1H- NMR. The presented polymers exhibited emission of blue to red colors.
A Case Based Reasoning Knowledge Based System for Type II Diabtes Management: Case of Desire Referral Hospital
(Addis Ababa University, 2011-11-01) Zewditu Sisay; Getachew Jemaneh
Diabetes mellitus (DM) is a common chronic disease around the world in which the boas not produce insulin (type I diabetes) or does not properly use insulin (type II diabetes ) the study investigated the potential of case-based reasoning (CBR)approach for type II DM treatment CBR is an approach to artificial intelligence that is intended to mimic an approach that people typically use to solve problems this is the use of past experiences to reason about new situations In order to acquire the knowledge the researcher conducted unstructured interviews with domain experts selected through expert sampling and other relevant documents then the knowledge is modeled using tree like structure called ladders patient history cards from dessie referral hospital in outpatient department (OPD)were the primary sources of cases. case attribute identification and weight assignment were done with the help of domain experts the case-based contained 42 type II DM cases and stored in plain text file (attribute value pair vector) the prototype is built using Jcolibri a software artifice that promotes software reuse for building CBR systems JCOLIBRI employed nearest neighbor retrieval algorithm for retrieval and propose the most similar cases for reuse manual revision is by the domain expert in order to adapt a stored case’s solution for a new case there is always incremental learning through retaining newly solved cases The prototype performance is evaluated through statistical analysis and user feedbacks recall and precision were the main statistical performance measures using leave-one-out cross validation testing proportion the retrieval performance of the prototype showed average value of 69% recall and 46% precision domain experts were also evaluating the prototype using certain criteria The main objective the research is to design and build CBR knowledge based system that retrieves relevant previously stored cases and proposes appropriate solution the developed prototype scores promising performance and user acceptance
A Case Based Reasoning Knowledge Based System For type II Diabtes Management: Case of Dessie Refreal Hospital
(Addis Ababa University, 2011-11) Zewditu Sisay; Getachew Jemaneh
Diabetes mellitus (OM) is a common chronic disease around the world in which the body does not produce insulin (Type I diabetes) or does not properly use insulin (Type II diabetes). The study investigated the potential of case-based reasoning (CBR) approach for type II DM treatment. CBR is an approach to Artificial Intelligence that is intended to mimic an approach that people typically use to solve problems. This is the use of past experiences to reason about new situations. In order to acquire the knowledge, the researcher conducted unstructured interviews with domain experts selected through expert sampling and other relevant documents. Then the knowledge is modeled using tree like structure called ladders. Patient history cards from Dessie Referral Hospital in outpatient department (OPD) were the primary sources of cases. Case attribute identification and weight assignment were done with the help of domain experts. The case-based contained 42 type II DM cases and stored in plain text file (attribute value pair vector). The prototype is built using jCOLIBRI, a software artifact that promotes software reuse for building CBR systems. jCOLlBRl employed Nearest Neighbor Retrieval algorithm for retrieval and propose the most similar cases for reuse. Manual revision is done by the domain expert in order to adapt a stored case's solution for a new case. There is always incremental learning through retaining newly solved cases. The prototype performance is evaluated through statistical analysis and user feedbacks. Recall and precision were the main statistical performance measures using leave-one-out cross validation testing proportion. The retrieval performance of the prototype showed average value of 69% recall and 46% precision. Domain experts were also evaluating the prototype using certain criteria. The main objective the research is to design and build CBR knowledge based system that retrieves relevant previously stored cases and proposes appropriate solution. The developed prototype scores promising performance and user acceptance.
A Computational Investigation of Hydrated Magnesium Sulfate Clusters and their FAU Composites for Improved Thermochemical Energy Storage
(Addis Ababa University, 2024-06) Belaynew Teshome; Getachew Gizaw; Ahmed Mustefa
The effective use of renewable energy sources and the decrease of greenhouse gas emissions are greatly dependent on thermal energy storage, or TES. We report a computational method for examining the hydrate clusters of hydrated magnesium sulfate (MgSO4) and their compounds with faujasite zeolite (FAU) for enhanced performance in thermoelectric sensing (TES). The optimal hydration states and structural characteristics of the hydrated MgSO4 clusters were revealed through modeling with density functional theory (DFT) calculations. Molecular dynamics techniques were used for optimization of composite structure implemented by Vienna Ab initio Simulation Package (VASP) software. After this, the TES capacity, reversibility, and thermal conductivity of the MgSO4 hydrate-FAU composites were assessed. As a result of their superior heat storage properties over their constituent parts, composite materials are a strong contender for advanced thermal energy storage applications, according to the research. This method of computational research gives a logical way to create high-performance thermoelectric solar materials while also shedding light on the interactions at the molecular level.
A Five-Yeartrend of Hiv/Aids Prevalence on Knowledge, Attitude and Practice, Among Patients, Attending Treatment at Delanta Woreda,Wogeltena Health Center, Southwollo Zone, Amhara Region, North East Ethiopia
(Addis Ababa University, 2024-08) Amisal Aragie; Asnake Desalegn (PhD)
One of the primary pathogenic agents responsible for a multitude of grave illnesses in people, animals, and plants is a virus. HIV/AIDS has a multifaceted and intricate impact. HIV/AIDS continues to be the biggest developmental obstacle for Ethiopia, notwithstanding its stability. The degree of awareness and changes in behavior are the primary factors influencing the incidence of HIV in communities. This study set out to evaluate the HIV/AIDS trends over the previous five years among patients at the Wogeltena health clinic in Delanta Woreda. Between 2011 and 2015, cross-sectional studies comparing HIV/AIDS patients was carried out. A total of 550 retrospective data and84 respondents as a primary data source were selected through systematic sampling. Data analysis was made by SPSS version 16. Respondents in the study area were infected with HIV due to unprotected sex about 62.5%, unsafe blood transfusion about 12.5%, contaminated sharp materials about 6.25% and mother to child about 18.75%. According to this survey, 18.75% of participants said that abstaining from sexual activity effectively lowers the overall incidence of HIV/AIDS. Furthermore, 68.75% of them reported being faithful, and 12.5% of them were aware of the use of condoms. A significant proportion of respondents, both males (75%) and females (62.5%), reported having devoted sexual partners. In 2015 E. C., a sizable patient population was enrolled in HIV care and treatment. Since 2015 E. C., the general trend of connecting patients to care and treatment after HIV positive findings has exhibited a slightly enhanced pattern. The relationship involving care and treatment peaked in 2015 E. C. and peaked in 2011 E. C. Since 2011 E.C., the trend of HIV test positivity, or yield, has been rising. It peaked in 2011 E.C. at 18.7% and increased to 21% in 2015 E.C. The ART coverage trend in the current study demonstrated an improved pattern, rising from 400 (13.74%) in 2011 E.C. to 550 (21%) in 2015 E.C. According to the study, there was a significant gap in knowledge, attitudes, and practices regarding HIV/AIDS preventive practice. Youths were found to have a higher prevalence of HIV/AIDS than other population, and a high proportion of them engaged in risky sexual behaviors like multiple sexual partners, unprotected sex, and inconsistent condom use. In conclusion, even though the general public in the area is well aware about HIV and ART, much more work needs to be done to raise public awareness
A Framework for Detecting Multiple Cyberattacks in IoT Environment
(Addis Ababa University, 2025-02-25) Yonas Mekonnen; Mesfin Kifle (PhD)
The Internet of Things refers to the growing trend of embedding ubiquitous and pervasive computing capabilities through sensor networks and internet connectivity. The growth and expansion of newly evolved cyberattacks, network patterns and heterogeneous nature of cyberattacks trend has become the warfare across the globe and challenges to apply single layer cyberattacks detection techniques to the Internet of Things. This research work identified the lack of cyberattacks detection framework as the major gap for detection of multiple cyberattacks such as denial of services, distributed denial of services, and Mairi attacks while it includes multiple parameters at the same time. The proposed framework contains three modules; data acquisition and preprocessing module that is responsible for capturing and pre-processing the captured data and ready for the construction of the model, then the attack detection module which is the core engine that orchestrates the detection of cyberattacks, the third module notifies and displays the results in a dashboard. This research study used multiple parameters including multiple attack classes, network packet patterns, and three scaler types namely no scaler, MinMax, and Standard, and regardless of the defined parameters used, minmax scaler followed by standard scaler gives better detection performance than models trained with no scaler. The proposed framework is trained and evaluated with different models including CNN, Hybrid, FFNN, and LSTM provides a result of 91.42%, 82.75%, and 78.38% ,74.83% detection accuracy respectively where it is observed that CNN model outperforms the optimal results among followed by hybrid and FFNN.
A Framework for Near Real-Time SIMbox Fraud Detection: the Case of Ethio Telecom
(Addis Ababa University, 2023-12) Kaleab Abebaw; Million Meshesha
Telecom fraud is a major concern for telecom operators as well as for governments especially in Africa and Asia. Bypass fraud is one of the most fertile and costly frauds in today’s mobile industry making mobile operators and telecom regulators face a staggering annual revenue losses due to these fixed/VoIP to GSM/CDMA/Fixed line gateway equipment’s, which are used to terminate international inbound calls to local calls to local Subscribers by deviating traffic away from the legal interconnect gateways. Bypass fraud is more rampant in the countries where the cost of terminating international call exceeds the cost of a national call by a considerable margin or the countries where government carriers monopolize international gateways. Fraudsters through the use of different bypass mechanisms, sell capacity to terminate calls cheaply in these countries, on the open market or through direct connections with interconnect operators. Operators sending outbound international traffic are then attracted by these interconnect operators with lower interconnect rates. This leads to lost revenue for terminating network operators. While several attempts have been made to fight against Bypass Frauds the common approaches have been the use of monitoring calling patterns and profiles through Fraud Management Systems and the use of Test Call Generators. Both approaches have their own set of limitations coping up on frequently changing fraudster’s techniques and have short shelf life. In addition, those approaches took couple of months to detect a single fraudulent service number. The general approach used to perform this research is a design science research methodology. The proposed system works on processing the near real-time data using Spark Streaming. The objective is to build features to process the near real time data with Spark Streaming to reduce the workload on the node(s), achieve low latency to provide a better execution plan for a scalable and fault-tolerant processing of data. The Proposed framework targeted to improve response time and to give real-time solution to real time problem. Domain experts made evaluation In order to assure the proposed system has met the requirement needed. In this work, we intended to create a fraud detection framework, which detects frauds based on big data technology, precisely Apache spark and using its Machine learning libraries in order to minimize the latency and to process transactions in a real-time.
A Hybrid Deep Learning-Based ARP Attack Detection and Classification Method
(Addis Ababa University, 2023-12) Yeshareg Muluneh; Solomon Gizaw
To map the Internet Protocol (IP) addresses to the Media Access Control (MAC) addresses and vice versa in local area network communication, the Address Resolution Protocol (ARP) is the most crucial protocol. ARP, however, is an unauthenticated protocol that lacks security features and is stateless in nature. Therefore, ARP is vulnerable to many attacks, and it can be easily exploited to gain unauthorized access to one's sensitive data and transmit bogus ARP messages to poison the ARP caches of the hosts within the local area network. These attacks may result in a loss of data integrity, confidentiality, and the availability of an organization's information. Many researchers have struggled to detect ARP attacks using different methods. However, some of these papers are not time-effective, require more human effort and involvement, and have high communication overhead. The other works use machine learning and deep learning methods, which have better solutions for detecting ARP attacks. However, those approaches have a significant false alarm rate of 13%, a low attack detection rate, and a classification accuracy of 87%. This thesis work aims to solve those problems using a hybrid deep learning-based ARP attack detection and classification method. In this work, we used a Sparse Autoencoder for important feature extraction and dimensionality reduction for input data and a Convolutional Neural Network for attack detection and classification to achieve the highest attack detection rate and classification accuracy with a minimized false alarm rate. To evaluate the performance of the proposed model, we used an open-source benchmark NSL-KDD dataset for training and testing. The results obtained by the implementation and evaluation are measured in comparison with a single Convolutional Neural Network model with different evaluation metrics. Hence, the proposed approach scores the highest results for attack detection rate of 98.97%, classification accuracy of 99.26%, and minimum false alarm rate of 0.74%.
A Model for Recognition and Detection of the Counterfeit of Ethiopian Banknotes using Transfer Learning
(Addis Ababa University, 2024-06) Hailemikael Tesfaw; Ayalew Belay
Paper currency recognition systems play a pivotal role in various sectors, including banking, retail, and automated teller machines (ATMs). This paper presents a novel approach to the design and development of a paper currency recognition system using customized deep learning techniques. The proposed system utilizes image-processing algorithms to extract features from currency images, followed by customized convolutional neural network models for classification and detection of the counterfeit. The system is trained on a diverse dataset of currency images to ensure robustness and accuracy in recognizing various denominations and currencies. We implemented feature learning techniques architectures. To obtain the best accuracy and efficiency we used RLUs and Softmax as an activation, Adam optimizer, and sparse categorical cross-entropy as a loss function for both as a training strategy. The data was collected from the National Bank of Ethiopia, Commercial Bank of Ethiopia, NIB International Bank, and Bank of Abyssinia. From the experimental results of the alex_customed-design network, 99.82% accuracy is recorded.
A Monte Carlo Study on a 3-Dimensional Comb Polymer Translocation Through a Nanopore Driven by an Electric Field
(Addis Ababa University, 2024-01) Bruh Tesfa; Tatek Yergou
A lattice Monte Carlo study of comb polymers translocation through a nanopore subject to an electric field is presented. Our approach is universal in a sense that we are not limited to single file translocations. Instead, we investigated single file translocations as a particular case in this universal approach. In this way, we have made an extensive study on the translocation dynamics of comb polymers as a function of field strength, pore size, and the comb polymer’s topology. We were able to show the existence of a critical field strength for any particular system. The difference between the most probable translocation time and the mean translocation time is minimum at the critical field strength. Also, the critical field strength helped us to identify two regimes of translocations with different properties. We named them as smooth and chaotic translocations. These results should also be valid for linear polymers because linear polymers are comb polymers without side chains. In addition, we took advantage of the side chains of comb polymers to study the pore-polymer interaction in an unprecedented way by varying the side chain lengths. This enabled us explain the varied values of _ in h_ i _ N_, where h_ i is the mean translocation time and N is the chain length of a linear polymer, in the literature.
A Study of Employees’ Information Security Policy Violation and Rational Choice Theory: The Case of Ethiopia
(Addis Ababa Unversity, 2017-02-01) Tilahun Muluneh; France Belanger
Nowadays, it becomes clear that information systems security (ISS) is one of the most important issues that organizations need to focus on. Despite huge investments made by companies to keep their information systems (IS) safe, there are many ISS breaches that infiltrate companies’ systems and consequently, these cost their reputation, affect customers’ confidence, and bring huge financial losses. Ethiopian companies are not immune to the ISS problem and there are some signs of ISS breaches. The ISS literature suggests that almost all investments in ISS related issues are for technological solutions. However, this type of solutions alone does not work well, and according to some researchers, there is one significant element that has been given very little attention, the human factor. Most of the ISS breaches are caused by employees who are the legitimate users of organizations’ IS. So “how can we counter the illegal action of our own employees?” is the main agenda this research tries to address. Many researchers advocate the use of deterrence mechanisms to decrease the employees’ noncompliance problem. Despite these findings, there is a lot of research output that reported the inability of the deterrent countermeasures alone to protect IS from security breaches. And more importantly, some researchers point out that different cultures require different ISS interventions. Interestingly, in the last decade, some researchers have studied how culture can influence people’s intention towards ISSP (information systems security policy) compliance. However, most of the current ISS (information systems security) studies assume that deterrent countermeasures’ effect is uniform across countries and culture. This situation identifies a gap that needs to be bridged, and this study address the issue by raising the question “To what extent, if any, national culture moderates the influence of formal iv sanctions, perceived benefits, moral beliefs, and shame on employees’ intention to violate ISSP?” We use survey method to collect data and SPSS Amos to conduct SEM (Structural Equation Modeling) based data analysis. Finally, we get results that show the moderating impact of national culture on the influence of formal sanctions, perceived benefits, moral beliefs, and shame on employees’ intention to violate ISSP.
A Study on Ideal with Skew Derivations of Prime Rings
(Addis Ababa University, 2024-09) Gizat Alemu; Tilahun Abebaw
In this work, we apply the theory of generalized polynomial identities with automorphism and skew derivations to investigate the commutativity of a ring R satisfying certain properties on some appropriate subset of R.Let R be a prime ring and set [x,y]1=[x , y]=xy-yx for all x,y ∈ R and inductively[x,y]k=[[x,y]k-1,y] for k> 1 . We apply the theory of generalized polynomial identities with automorphism and skew derivations to obtain the following result: Let R be a prime ring and I a nonzero ideal of R. Suppose that .(𝛿 , 𝜑) is a skew derivation of R such that 𝛿([ x,y] =[x,y]n• for all x , y ∈ I , then R is commutative.

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