Research Articles

Permanent URI for this collectionhttps://atuspace.atu.edu.gh/handle/123456789/31

Browse

Now showing 1 - 20 of 29

Adoption of Smart Grid in Ghana Using Pattern Recognition Neural Networks
(Institute of Electrical and Electronics Engineers Inc., 2019) Abubakar, R.; Effah, E. K.; Frimpong, S. A.; Acakpovi, A.; Acheampong, P.; Kadambi, G. R.; Kumar, K. M. S.
Deployment of Smart Grid is neither a goal nor a destination, but rather an enabler to the provision of reliable, secured and clean electricity for the end-user or consumer. Overall Smart Grid vision is very well explained with the future of electricity systems, which largely depends on digitization and automation of the overall electricity value-chain, by enhancing electric power information to bi-directional flow and the provision of services that can support the operations of the generation, distribution and end-user usage of power can lead to improvement of electric power system efficiency. This work aims at analyzing factors and forecast effects on the adoption of Smart Grid in Ghana using Pattern Recognition Neural Net. The Primary data was collected using structured questionnaire and the questions were designed to test the perception of consumers on the deployment of Smart Grid. Also, the target group of respondents covered 80% of the regions in Ghana. Based on the collected data, the pattern recognition neural networks was employed in the analysis of data. Results indicated that education, government policy, cost and safety were the main drivers to the deployment of Smart Grid in Ghana. Other drivers like culture and societal perception recorded as insignificant variables to the deployment of distributed generation in Ghana. It is recommended that further research work should examine the extent of infrastructural preparedness of Ghana for the deployment of Smart Grid.
Application of machine learning in predicting construction project profit in Ghana using Support Vector Regression Algorithm (SVRA)
(Emerald Group Holdings Ltd., 2021) Adinyira, E.; Adjei, E. A. G.; Agyekum, K.; Fugar, F. D. K.
Purpose: Knowledge of the effect of various cash-flow factors on expected project profit is important to effectively manage productivity on construction pwas conducted to develop and test the sensitivity of a Machine Learning Support Vector Regression Algorithm (SVRA) to predict construction project profit in Ghana. Design/methodology/approach: The study relied on data from 150 institutional projects executed within the past five years (2014–2018) in developing the model. Eighty percent (80%) of the data from the 150 projects was used at hyperparameter selection and final training phases of the model development and the remaining 20% for model testing. Using MATLAB for Support Vector Regression, the parameters available for tuning were the epsilon values, the kernel scale, the box constraint and standardisations. The sensitivity index was computed to determine the degree to which the independent variables impact the dependent variable. Findings: The developed model's predictions perfectly fitted the data and explained all the variability of the response data around its mean. Average predictive accuracy of 73.66% was achieved with all the variables on the different projects in validation. The developed SVR model was sensitive to labour and loan. Originality/value: The developed SVRA combines variation, defective works and labour with other financial constraints, which have been the variables used in previous studies. It will aid contractors in predicting profit on completion at commencement and also provide information on the effect of changes to cash-flow factors on profit.
Assessment of High Network Latency on Broadband Powerline Communication
(Institute of Electrical and Electronics Engineers Inc., 2019) Antwi, O. A.; Mohammed, H.; Acakpovi, A.; Donkor, L. M.
This paper focuses on the evaluation of broadband power line communication taking in terms of data transmission and the delayed measured and compared to theoretical values. The utilization of communication systems has expanded rapidly. However, there is a need to deploy new telecommunication systems and transmission technologies that can carry more data and allows faster transmission at a minimal cost. Due to this, the effect of high latency, noise and interference in communication networks is one major challenge that pose great danger to faster and successful data transmission. We use data obtained from the software tool (ICMP) which recorded the ping statistics and (SPSS) in data coding and analysis. Broadband power line communication may be seen as complementary or alternative solutions to traditional fixed line networks and wireless networks according to existing network architectures with PLC bandwidths set to increase
Automatic fault detection and location in power transmission lines using GSM technology.
(International Journal of Advance Research in Science and Engineering, 2016) Agbesi, K.; Okai, F. A.
Many electricity transmission companies across the world and Ghana in particular are continuously looking for ways to utilise modern technologies, in order to improve reliability of power supply to consumers. These transmission companies manly relies on circuit indicators (FCIs) to assist in locating specific spots within their transmission lines where power fault had occured. In this paper, a smart GSM based fault detection and location system was used to adequatly and accurately indicate and locate the exact spot where fault had occured. This will ensure a shorter response time for technical crew to rectify these faults and thus help save transformers from damage and disasters. The system uses a current transformer, a voltage transformer, PIC 16F877 Microcontroller, RS-232 connector, and a GSM modem. The system automatically detects faults, analyses and classifies these faults and then, calculates the fault distance from the control room using an impedance-based algorithm method. Finally the fault information is transmitted to the control room. In conclusion, the time required to locate a fault is drastically reduced, as the system automatically and accurately provides accurate fault location information.
Classification of Public Health Centres in Accra through a Web-Based Portal Integrated with Geographical Information System (GIS)
(Hindawi Limited, 2021) Asabere, N. Y.; Lawson, G.; Badu-Marfo, G.; Kwofie, L.; Mensah, D. O.; Lartey, R.
A health system is described as a logically organized collection of resources, agents, and institutions that offer healthcare to a specific population based on the finance, regulation, and delivery of health services. Many health centres have been established in Accra, the capital city of Ghana, due to the importance of good health. People in other developed nations can seek adequate healthcare, since information about relevant health centres is readily available. However, there is a paucity of information about the services provided by existing health institutions in Ghana, particularly in Accra. The majority of patients commute to either Korle-Bu Teaching Hospital or Greater Accra Regional Hospital, putting a considerable medical strain on these facilities. In this study, we use a Geographic Information System (GIS) to establish a database for all of Accra's health centres and categorize them according to the services they provide. This research tackled the previously mentioned problem by proposing and developing a web-based map called Geohealth for the classification of public health centres in Accra using GIS to assist users in accessing information and locating health centres. We utilized a mixed-method approach consisting of quantitative as well as Build Computer Science Research Methods. Results of our study show that the majority of the participants and stakeholders in our research are eager to embrace Geohealth. Furthermore, in comparison with existing techniques such as Google Maps, our proposed approach, Geohealth, takes less time to obtain information and locate public health centres in Accra, Ghana.
Collaborative and social-personality aware recommendation of programmes.
(Mobile Information Systems, 2022) Asabere, N. Y.
Globally, the selection of tertiary programmes for higher education in a university by prospective applicants is a daunting task. Different universities offer a wide range of programmes using different education delivery modes for teaching and learning. This creates information overload in the context of tertiary programmes. To tackle the information overload problem of tertiary programmes in the context of higher education institutions (HEIs), this paper, therefore, proposes a novel recommendation model called Collaborative and Social-Personality Aware Recommendation of Programmes (CoSPARP) for tertiary programme selection. CoSPARP utilizes a hybrid filtering system that incorporates the computation of similarities relating to the CF, personality traits, and the tie strength of users (prospective applicants) to generate effective programme recommendations for a tertiary programme applicant (TPA). The proposed CoSPARP recommendation method employs the above recommendation entities to create profiles of the TPAs as a basis of profile similarity for tertiary programme recommendations. Results of benchmarking experiments showed that CoSPARP overcomes cold-start due to the proposed (innovative) hybridization process. Additionally, using a relevant real-world dataset and suitable evaluation metrics such as precision, recall, and F-measure, CoSPARP produces more favourable outcomes in comparison to other state-of-the-art methods.
A configuration-based approach to mitigating man-in-the-middle attacks in enterprise cloud IaaS Networks running BGP.
(International Journal of Computer Applications, 2016) Oti, S. B.; Bansah, I.; Adegboyega, T. M.
Cloud IaaS service providers offer virtualized computing resources to enterprises over the internet. As with most internet based services, cloud service providers may need to establish BGP peering relationships with upstream/neighbor ISPs for the purposes of exchanging routing information between their respective Autonomous systems thereby making it possible for a rogue AS to carry out a Man-In-The-Middle (MITM) attack. Available literature supports the fact that BGP as an infrastructure protocol is vulnerable to MITM attacks yet a good number of proposals aimed at counteracting these attacks have not been fully implemented. Secure BGP, Secure Origin BGP and Pretty Secure BGP are all proposals which have not been fully implemented due to high overhead and invariable router load. We believe however that an existing cloud IaaS service provider could mitigate the risk of a MITM attack by optimizing their configurations and ensuring that upstream providers do a proper job filtering prefixes using a prefix-list. This paper presents a GNS-3 simulation of a MITM attack by mimicking a section of the internet and goes on to show how the application of a prefix-list can help mitigate the attack.
Design of power distribution network fault data collector for fault detection, location and classification using machine learning
(IEEE Computer Society, 2018) Sowah, R.; Dzabeng, N. A.; Ofoli, A. R.; Acakpovi, A.; Koumadi, K. M.; Ocrah, J.; Martin, D.
The protection and maintenance of a power transmission system during fault condition is indispensable to ensure efficient and reliable power supply to consumers. Most methods of fault detection and location rely on measurements of electrical quantities provided by current and voltage transformers. In this paper, a prototype data collecting device was built for collecting data during different faulted conditions in a single-phase distribution network. Machine learning algorithms were developed for fault detection, location and classification on single-phase distribution lines. The transmission line was modelled using resistor network in the device; the current and voltage sensors were used in the prototype model with the data collection device for current and voltage readings under open-circuit and short-circuit faulted conditions. Training data was collected by varying the load on the line during the simulation of the fault type, sensor location on the node and analyzed. The test data was assessed using three (3) machine learning algorithms namely: K-Nearest Neighbor (KNN), Decision Trees and Support Vector Machines (SVM) for prediction of fault, location and classification within the single-phase distribution network. Test results showed that a higher accuracy rate of 99.42 % was obtained by using the Decision Trees algorithm compared to the others investigated.
Evaluation of Inter-Cell Interference and BER on a Downlink PDSCH of the LTE Network
(Institute of Electrical and Electronics Engineers Inc., 2019) Antwi, O. A.; Acakpovi, A.
In this paper, a comprehensive evaluation of intercell interference and BER on the physical downlink channel of an LTE cellular network is undertaken. Because spectrum bandwidth is a scarce resource, operators are compelled to reassign frequency in a process called frequency reuse. However, the downlink channel of the currently deployed LTE network in Ghana, has low average throughput and data rate. This results from the fact that an interfering cell from adjacent eNodeB interrupts with the serving eNodeB. For cell-edge users (CEUs), the effect of inter-cell interference is especially severe. MATLAB was used to build models and to carry out simulations on the evaluation of this form of interference in LTE network. Simulation results were obtained for BER considering different adaptive modulation and also for simulation of the PDSCH transceiver which depicts the effect of inter-cell interference on the downlink throughput.
Exploiting cyber-attack prediction through socially-aware recommendation.
(International Journal of Decision Support System Technology, 2022) Asabere, N. Y.; Fiamavle, E.; Agyiri, J.; Torgby, W. K.; Dzata, J. E.; Doe, N. P.
In the domain of cyber security, the defence mechanisms of networks has traditionally been placed in a reactionary role. Cyber security professionals are therefore disadvantaged in a cyber-attack situation due to the fact that it is vital that they maneuver such attacks before the network is totally compromised. In this paper, we utilize the Betweenness Centrality network measure (social property) to discover possible cyber-attack paths and then employ computation of similar personality of nodes/users to generate predictions about possible attacks within the network. Our method proposes a social recommender algorithm called socially-aware recommendation of cyber-attack paths (SARCP), as an attack predictor in the cyber security defence domain. In a social network, SARCP exploits and delivers all possible paths which can result in cyber-attacks. Using a real-world dataset and relevant evaluation metrics, experimental results in the paper show that our proposed method is favorable and effective.
Exploiting the adoption and implementation of electronic learning in a technical university in Ghana
(IGI Global, 2019) Asabere, N. Y.; Acakpovi, A.; Torgby, W.; Sackey, J. Y. A.; Kwaikyi, S.
Although in Accra Technical University (ATU), Ghana, there exists a traditional Face-to-Face (F2F) mode of education already in place, the implementation of electronic learning (e-learning) through ICT in education will increase the number of students admitted yearly. Lack of academic facilities makes e-learning an attractive alternative. Consequently, this article employed a questionnaire as a research instrument with reference to the Technology Acceptance Model (TAM-2) as a theoretical framework. In all, questionnaires were administered to 190 students and 14 lecturers in the Faculty of Applied Sciences in Accra Technical University (ATU). Based on the responses received, various types of e-learning systems were exploited and a SWOT (Strength Weaknesses Opportunities and Threats) analysis was conducted to validate the sustainability of proposing and developing a suitable e-learning system for ATU. It is envisaged that successful implementation of the e-learning system proposed in this article will practically increase the use of ICT in education by both lecturers and students in ATU.
How do digital technologies influence the dynamic capabilities of micro and small businesses in a pandemic and low-income country context?
(John Wiley and Sons Inc, 2022) Owoseni, A.; Hatsu, S.; Tolani, A.
It is not clear how extreme disruptions like COVID-19 pandemic affects the dynamic capabilities (DCs) of micro and small businesses (MSBs) in the context of low-income countries. Therefore, this study makes sense of how MSBs leverage DCs through digital technologies (DTs). Using mixed-method and interpretive research approaches, the first phase of the study applied a deductive coding technique to analyze interviews from 30 MSB managers in Ghana. Coding activities revealed 21 DC constructs of MSBs in Ghana. Next, we contextualized and simplified the DC framework by proposing an interpretive blueprint of DC framework applicable to Ghana and other low-income countries. The second phase, through a questionnaire, progressed the research by assessing how DTs influence the 21 DC constructs. Findings suggest that collective DCs of MSBs as a business sector did not change in a pandemic situation; nonetheless, the extent to which MSBs demonstrate DCs increased by up to 82%; and the use of DTs such as mobile payment and social media tools increased significantly. Interpretive reflections on the research outcomes argued that whilst the collective DCs of MSBs remain the same, each MSB uniquely explored opportunities by manifesting different combinations of DC constructs and DTs, at varying extents, and the knowledge of how MSB combines DCs could promote MSB management and digital innovation as low-income countries seek to recover from the COVID-19 economic downturn. Consequently, this research extends literature and progresses the UN sustainable development goals 8.3 as it helps to enhance policies that promote digital innovation, entrepreneurship, and growth of MSBs.
An ICT model for integrating teaching, learning and research in Technical University Education in Ghana.
(International Journal of Education and Development using ICT, 2017) Asabere, N. Y.; Togo, G.; Acakpovi, A.; Torgby, W.; Ampadu, K
Information and Communication Technologies (ICT) has changed the way we communicate and carry out certain daily activities. Globally, ICT has become an essential means for disseminating information. Using Accra Technical University in Ghana as a case study, this paper proposes an ICT model called Awareness Incentives Demand and Support (AIDS). Our proposed AIDS model depicts how different ICTs can be integrated in tertiary education for effective teaching, learning and research. Currently, Accra Technical University does not have a resilient means of providing ICT in education. In this study, relevant data was obtained through a quantitative research method involving questionnaires. The questionnaire was developed using the main components of the proposed AIDS model. In all, ninety (90) students and twelve (12) lecturers were considered from a maximum of three (3) schools in Accra Technical University. Samples of lecturers and students from all the three (3) schools were surveyed. Based on the responses received from the participants, the AIDS model was proposed. Successful implementation of the AIDS model practically increased the use of ICT for education by both teachers and students in Accra Technical University.
Improving education delivery in a technical university in Ghana through mobile learning technology.
(International Journal of ICT Research in Africa and the Middle East (IJICTRAME), 2020) Asabere, N. Y.; Agyiri, J.; Acakpovi, A.; Nachanja, A.; Awuku, P.
Although in Accra Technical University (ATU), Ghana there exists a traditional face-to-face (F2F) mode of education already in place, the implementation of mobile learning (m-learning) through ICT in education will solve problems such as small classroom size, inappropriate time schedule for lectures, and provision technological resources needed to run successful classroom education. In order to validate successful implementation of m-learning in ATU, this paper employed a questionnaire research instrument with reference to the technology acceptance model (TAM-2) as a theoretical framework. Closed-ended questionnaires were administered to a sample size of 160 students and 15 lecturers in the Faculty of Applied Sciences (FAS) in ATU. Based on the responses received, the authors established positive technological acceptance of respondents, which paved the way to propose and develop a suitable m-learning system for ATU. It is envisaged that successful implementation of the m-learning system proposed in this paper will practically increase the use of ICT in education by both lecturers and students in ATU.
Improving Socially-Aware Recommendation Accuracy Through Personality
(Institute of Electrical and Electronics Engineers Inc., 2018) Asabere, N. Y.; Acakpovi, A.; Michael, M. B.
In order to innovatively solve cold-start problems, research involving trust and socially aware recommender systems is currently proliferating. The relative importance of academic conferences has led to the necessity of recommender systems that seek to generate recommendations for conference attendees. In this paper, we aim to improve the recommendation accuracy of socially-aware recommender systems by proposing a linear hybrid recommender algorithm called Personality and Socially-Aware Recommender (PerSAR). PerSAR hybridizes the social and personality behaviours of smart conference attendees. Our recommendation methodology mainly aims to employ an algorithmic framework that computes the personality similarities and tie strengths of conference attendees so that effective and reliable recommendations can be generated for them using a relevant dataset. The experimental results substantiate that our proposed recommendation method is favorable and outperforms other related and contemporary recommendation methods and techniques.
An integrated framework for benchmarking e-government projects
(Institute of Electrical and Electronics Engineers Inc., 2017) Hatsu, S.; Ngassam, E. K.
Governments worldwide are using e-Governance to improve efficiency and effectiveness of public administration systems and service delivery. The digitally dynamic nature of the world today represents an opportunity for developing countries to fully embrace e-Governance and thereby contributing to meeting the needs of the citizenry. Successful implementation of e-governance projects ought to be guided by sound mechanisms to minimize failure and ensure a positive impact. Frameworks such as e-Readiness, strategy-based and maturity as well as stage-based e-governance frameworks seldom focus on monitoring and evaluation of projects and lack emphasis on the project life-cycle. We hereby rely on the foregoing shortcomings to propose an integrated framework for benchmarking the implementation of e-governance projects. Our suggested framework represents an important tool to be relied upon by stakeholders to increase accountability on e-governance projects and maximize their chance for success.
Intrusion detection on campus network, the open-source approach: Accra Technical University case study
(International Journal of Computer Applications, 2017) Gbedawo, V.; Agbesi, K.; Adukpo, T.
The computer network security landscape in recent times has become a crucial area in computer networking for both network administrators and network users such that, a compromise of this network security makes the services it provides and more importantly the data it holds, highly susceptible to exploits by malicious people for different purposes and reasons. This is particularly so for campus networks in view of the fact that, they do not only provide services to promote academic work directly but in many ways are integrated into the administrative setup of the institutions they serve. This research therefore seeks to investigate the security threats and vulnerabilities of campus networks and systems to a great extent, so as to propose interventions to resolving these threats, vulnerabilities and exploits, so as to improve the security of these networks by conducting a penetration test that simulates Intrusion Detection employing free and open source software (FOSS) tools. The research adopted “Cloppert‟s kill chain” Approach to Penetration Testing. The elements of the simulation included the following FOSS tools VMware Fusion (Operating System simulator), Zentyal Server (unified network server), Snort (Intrusion Detection System), Suricata (Intrusion Prevention System), Nmap (Network scanning), OpenVAS (Vulnerability Assessment Software) and Metasploit Framework (Exploitation tool). Results of the simulation revealed injection flaws to be the prevalent security vulnerability that was exploited and hence, discussed to improve computer network and application security in a rather cost effective fashion
Mapping and auditing internet addiction in technical education
(IGI Global, 2021) Asabere, N. Y.; Torgby, W.; Acakpovi, A.; Enguah, S. E.; Asare, I. O.
The current proliferation of social networking sites (e.g., Facebook), electronic devices (e.g., smartphones and tablets), and the internet has paved the way for a charge in promoting the phenomenon of internet addiction (IA). This paper analyzed and examined the validity and appropriateness of a well-established instrument for measuring IA among technical education students in Ghana, specifically students of Accra Technical University (ATU). Using a quantitative research method involving questionnaires, data collected from 260 (n=260) students in ATU was used to validate the research objectives and also measure the levels of IA among the students. The principal component tool in statistical package for social sciences (SPSS) was employed to analyze the received data. Analytical results of the study showed that a sizeable majority of students in ATU, especially male students, suffer frequent addiction problems due to the use of the internet. Additionally, results of the study showed that IA psychometric constructs in the Western world differ from those in the African context.
Measuring the constructs that influence student and lecturer acceptance of an E-library in accra technical university, Ghana
(IGI Global, 2021) Asabere, N. Y.; Acakpovi, A.; Agyiri, J.; Awuku, M. C.; Sakyi, M. A.; Teyewayo, D. A.
Even though many universities across the world have incorporated internet-based educational and academic systems, the success of their implementation requires an extensive understanding of the end user acceptance process. Access to academic resources for teaching and learning using technology (electronic library) has become a popular approach within higher education institutions due to the continuous growth of internet innovations and technologies. This case study research, conducted at Accra Technical University uses the technology acceptance model (TAM) as a theoretical framework. The study investigates the effects of the system characteristics such as appropriate user interface (UI), software design, and relevance towards the perceived ease of use and perceived usefulness on intention to use the proposed e-library system. Two hundred (200) students and sixteen (16) lecturers participated in this quantitative study. Results show that improvement of the existing e-library system in ATU will enable students to utilize digital learning resources for effective teaching and learning, especially during the current global COVID-19 pandemic.
Modelling an Efficient Gap Filler for DTT Network Using ADS Software
(Proceedings - 2019 International Conference on Computing, Computational Modelling and Applications, ICCMA 2019, 2019) Mensah, F.; Acakpovi, A.; Osumanu, F.; Sowah, R.; Fifatin, F. -X. N.; Nounangnonhou, T. C.
This paper proposes the modelling and simulation of a special gap filler intended to cover grey areas in the DTT network of Accra. This has become necessary due to the numerous areas of low signal coverage in the Accra DTT and the incapability of previous methods to efficiently address the problem. The ADS simulation consists of arrangements of components from the DBV-T library which consists of filters, amplifiers and a power source. This setup mimics a gap filler system with a better noise reduction implementation, several frequency values are being used for the simulation process. A significant increase in the output signal as in comparison to the input means the shaded areas will be properly covered. The results derived from the simulation of the ADS setup highly improved upon the output signal values, when compared to the ITU standard. Three (3) out of five (5) simulation results show values beyond the minimum signal level requirement. Also using MATLAB, the RF propagation toolbox which has the map tool feature was able to implement the gap fillers into the Accra area and gave a visual representation of the signal strength. Modelling a gap filler system which has better noise cancellation and which propagates better with a dipole antenna was achieved in this paper. The outcome of the paper shows that the gap filler modelling increase signals in grey areas.

Browse

Browsing Research Articles by Title