97 10 3074 https://www.repository.gctu.edu.gh/files/original/7c9bfdf096cf4d5663fcee0f6adeeafd.pdf ddf48eb733313a1b8c490917b2f2ca4f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty of IT Business Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The Rwanda National Football League: Implications for Economic Governance Creator An entity primarily responsible for making the resource Robert Ebo Hinson Description An account of the resource The purpose of this exploratory study is to highlight the potential of sports and especially football as a nation building tool. Taking the particular case of a little known name in international football circles, the study highlights a potential avenue for domestic league development vis-à-vis the national league. The study is primarily documentary analysis driven, drawing upon a mixture of official statistics, contingent literature and personal observation-especially the on-pitch performance of the Rwanda National Professional League Football. Insights are also drawn from the National Team, i.e., “The Wasps” or “Amavubi” in Kinyarwanda – the local language. A similar approach has been undertaken for the case of the Sharjah Football Club in the United Arab Emirates, The Nigerian Football Federation and the “the War Elephants,” i.e., (Thai national football team). The study weaves in stadium development such as those featured at the recently concluded AfCON, i.e., Japoma Stadium (Douala), Ahmadou Ahidjo Stadium, and Olembé Stadium (Yaoundé), and Kouekong Stadium (Bafoussam), Roumdé-Adjia Stadium (Garoua) and the Limbe Omnisport Stadium (Limbe-Buea). Similarly, Rwanda-based stadia are showcased, e.g., Stade Amahoro and Stade Régional de Nyamirambo (Kigali); Stade Huye; Bugesera Stadium; and Stade Umuganda. Overall, the study advances a potential avenue for football governance, infrastructure development, investments, and a perception change of a range of stakeholders including fans and other regional and international observers (including potential investors) of football in a country at the forefront of African development. Source A related resource from which the described resource is derived https://www.researchgate.net/profile/Nnamdi-Madichie-2/publication/359717621_The_Rwanda_National_Football_League_Implications_for_Economic_Governance/links/624af8275e2f8c7a035a4143/The-Rwanda-National-Football-League-Implications-for-Economic-Governance.pdf Language A language of the resource English https://www.repository.gctu.edu.gh/files/original/37cbb1afd106351eec97890cdd7c2d14.pdf 5656d8ca90c6ee82aee66d432687758b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty of IT Business Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Prediction of Electricity Consumption in Ghana: Long or Short Memory Creator An entity primarily responsible for making the resource S Twumasi Ankrah, Isaac Ankrah Description An account of the resource In this study, we explore both univariate and multivariate aspects of time series analysis. In the univariate aspect, we evaluated the predictive performance of three widely used univariate time series methods in forecasting the electricity consumption in Ghana during the 1980–2011 periods. The three univariate time series approaches are autoregressive integrated moving average (ARIMA), autoregressive fractional integrated moving average (ARFIMA) and exponential smoothing. In each approach, we examined competing models and the “best” model according to the minimum information criterion and diagnostic checking was selected. The forecast accuracy measure (ie; mean absolute forecast error, MAFE) was computed for each “best” model in the three different approaches. The empirical results revealed that the MAFE for ARIMA, ARFIMA and exponential smoothing were 31.3%, 9.4% and 41.6% respectively. Thus, the comparative analysis of the forecast performance of these methods clearly concluded that the ARFIMA method gives better forecast in predicting electricity consumption in Ghana. And, in the multivariate aspect, we examined whether GDP, export, import and population influences electricity consumption. The results revealed a feedback causality between electricity consumption and economic growth. Again, we established that there exists an uni-directional influence of import, export, population towards electricity consumption. The “best” model of the univariate approach is ARFIMA (2, 0.31, 1) with MAFE of 9.4% while the “best” model for the multivariate approach is vector error correction model VECM (3) with MAFE of 1.5 … Publisher An entity responsible for making the resource available Advances in Economics and Business Date A point or period of time associated with an event in the lifecycle of the resource 2015 Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=qSyX_i8AAAAJ&citation_for_view=qSyX_i8AAAAJ:UeHWp8X0CEIC Language A language of the resource English https://www.repository.gctu.edu.gh/files/original/849a7f21fca14617c2d03c014e314441.pdf 84f015de136159c6d4107ebf089b62a3 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty of Computing and Information Systems Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Batani, John 7, 12, 89 Bayaga, Anass 20 Blose, Max 187 Buhat-Mendoza, Dorothy 215 Creator An entity primarily responsible for making the resource Laurie Butgereit, Chumani Charlie, Bester Chimbo, Willie Chinyamurindi, Liezel Cilliers, Paul Danquah, Saurav Deoraj, Saheed Faremi, Yinusa Faremi, Stephen Fashoto, Emmanuel Freeman, Vusumzi Funda, Fatima Gamieldien, Dennis Gookyi, Marilou Gravides, Raymond Gyaang, Andre Henney, Sanele Hlabisa, Abdulati Jahbel Description An account of the resource Author Index Page 1 Author Index Abrahams, Shamir 175 Abugosseisa, Muna 26 Agbehadji, Israel Edem 114, 121 Agbehadzi, Richard Koblah 121 Agyemang, Justice 181 Ahmad, Tohari 52, 64 Akinnuwesi, Boluwaji 89 Akinyemi, Dr Lateef Adesola 187 Allie, Mogammad 193 Ampaguey, Jocelyn 215 Aroba, Oluwasegun Julius 38 Arthur, Ewura 1, 181 Asiedu, Derek 181 Avulekpor, Ebenezer 108 Batani, John 7, 12, 89 Bayaga, Anass 20 Blose, Max 187 Buhat-Mendoza, Dorothy 215 Butgereit, Laurie 26 Charlie, Chumani 32 Chimbo, Bester 102 Chinyamurindi, Willie 96 Cilliers, Liezel 32, 96 Danquah, Paul 1 Deoraj, Saurav 38 Faremi, Saheed 89 Faremi, Yinusa 89 Fashoto, Stephen 89 Freeman, Emmanuel 108, 114, 121 Funda, Vusumzi 44 Gamieldien, Fatima 193 Gookyi, Dennis 1, 181 Gravides, Marilou 215 Gyaang, Raymond 1 Henney, Andre 140, 193 Hlabisa, Sanele 199 Jahbel, Abdulati 52 237 2024 … Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=rQvaaoMAAAAJ&cstart=20&pagesize=80&citation_for_view=rQvaaoMAAAAJ:qxL8FJ1GzNcC Language A language of the resource English Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty of IT Business Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Re-engaging with Europe and the Commonwealth in a Post-Brexit Era Creator An entity primarily responsible for making the resource Robert Ebo Hinsonn . Description An account of the resource n this chapter, the discussion revolves around Africa’s engagement with the new Europe in a post-Brexit era – which, like AfCFTA, also became effective on 1 January 2021. The chapter discusses, on a broader level, Europe–Africa relations in the creative industries. Specific examples are drawn from the Commonwealth Agenda, and the France/German/Dutch relations at both the public and private spheres. Publisher An entity responsible for making the resource available Emerald Publishing Limited Date A point or period of time associated with an event in the lifecycle of the resource 2022 Source A related resource from which the described resource is derived https://www.emerald.com/insight/content/doi/10.1108/978-1-80071-302-420211004/full/html Language A language of the resource English https://www.repository.gctu.edu.gh/files/original/db6e2ce6febd4afd6e82bfb0b41ab3e7.pdf 9a7a09c1d07c8d013817b39532994ff6 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty of IT Business Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource HIV/AIDS scourge and economic growth in sub-Sahara Africa Creator An entity primarily responsible for making the resource S Twumasi-Ankrah, JT Ashaolu, Isaac Ankrah Description An account of the resource This study examines the impact of HIV/AIDS scourge on economic growth of some selected Sub-Sahara African countries. The three sub-Sahara African regions (Southern, West and Eastern) are categorized into lowest and highest HIV prevalence rate, using the global report of the UNAIDS 2012 data. In each region, the lowest and the highest HIV prevalence rate countries are selected respectively. Thus, we consider a panel of three countries in each category over a period from 1995–2012. We used these data to estimate the cross-country level regressions of these two categories, using panel data models. Thus, our results are in twofold: For lowest HIV prevalence rate category, the pooled OLS model was the “best” model. This pooled OLS model indicated that, for one unit increase in HIV prevalence rate, the gross domestic product per capita of countries is expected to decrease by US $23.46, holding all other variables constant. Again for highest HIV prevalence rate category, the fixed effect model was the “best” model. The fixed effect model revealed that, one unit increase in HIV prevalence rate will cause the gross domestic product per capita of countries to decrease by US $9.98, holding all other variables constant. Generally, for a unit increase in HIV prevalence rate, the impact of HIV on the economy is two-thirds larger in lowest HIV prevalence rate countries than that of the highest HIV prevalence rate countries. Publisher An entity responsible for making the resource available Universal Journal of Public Health Date A point or period of time associated with an event in the lifecycle of the resource 2015 Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=qSyX_i8AAAAJ&citation_for_view=qSyX_i8AAAAJ:d1gkVwhDpl0C Language A language of the resource English https://www.repository.gctu.edu.gh/files/original/bae4121a9e48a30bdd1bd4404a8d1fd9.pdf 7ff0f08de31bad1163b280533a4a63ea Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty of Computing and Information Systems Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Investigating Dense Cnn Architectures: A Case Study of Facial Emotional Recognition Systems Creator An entity primarily responsible for making the resource Emmanuel Kyei, Peter Appiahene, Mighty Abra Ayidzoe, Obed Appiah, Justice Asare, Emmanuel Freeman, William Brown-Acquaye Description An account of the resource In recent years, Facial Emotional Recognition (FER) has garnered significant attention for its pivotal role across various applications, including human-computer interaction, healthcare, and sentiment analysis. This study is motivated by the need to enhance the accuracy and efficiency of FER systems, with a particular focus on leveraging Convolutional Neural Networks (CNNs) featuring dense architectures. Charles Darwin's groundbreaking work on facial expressions as indicators of human emotional states inspires this research, which aims to elevate FER systems for applications spanning therapy, human-machine interactions, and diverse domains like healthcare, education, and entertainment. While previous studies have recognized CNNs' ability to improve FER accuracy through intricate feature extraction, the evolving nature of the field calls for exploring novel CNN architectures and techniques to further enhance precision and efficiency. In this study, we develop and implement a deep learning model capable of classifying images into seven discrete emotion categories, representing universal human emotions. This objective is achieved by implementing a five-block CNN-based learning algorithm consisting of 44 layers designed to progressively capture complex facial features and expressive patterns. The CNN model performed well on FER and FERG datasets, with accuracy rates of 0.97 and 0.98, showcasing proficiency in facial expression classification. Comparative analysis highlighted its competitive accuracy, emphasizing the importance of feature extraction and architecture design. This research advances facial emotion recognition … Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=rQvaaoMAAAAJ&cstart=20&pagesize=80&citation_for_view=rQvaaoMAAAAJ:Wp0gIr-vW9MC Language A language of the resource English Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty of Computing and Information Systems Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Improved Residue Number System Reverse Conversion Algorithm for [[Equation]] Three Moduli Set Implementation in Sensor Networks Creator An entity primarily responsible for making the resource PRINCE MODEY, Gaddafi Adbdul-Salaam, Alimatu Sadia Shirazu, Mohammad Hossein Anisi, Emmanuel Freeman Description An account of the resource Residue Number System (RNS) is a number system providing borrow-free subtraction, carry-free addition, parallel operations, and one-step multiplication. These capabilities make RNS applications in Digital Signal Processing and Wireless Networks a good choice. Although RNS has proven to solve the problem of carry propagation in binary number systems, it has the problem of reverse conversion, which limits its implementation in digital systems likewise sensor nodes. In this paper, we proposed an RNS reverse converter based on the moduli set {[[EQUATION]]} and the residue number [[EQUATION]]. The proposed scheme re-grouped the moduli set into two sub-moduli sets with their corresponding residue representations. The proposed method in this study requires [[EQUATION]] bit hardware resources for its implementation and also imposed [[EQUATION]] delay in its performance. The proposed RNS reverse converter needs lesser hardware resources for its implementation compared to other state of the art, making it suitable for hardware implementation in sensor networks. The proposed scheme demonstrates reliable and secure data transmission in Wireless Sensor Networks (WSNs) by using the RRNS QC encoder/decoder scheme. Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=rQvaaoMAAAAJ&cstart=20&pagesize=80&citation_for_view=rQvaaoMAAAAJ:dhFuZR0502QC Language A language of the resource English https://www.repository.gctu.edu.gh/files/original/e156f5ce520295d87dafb1fc60254f35.pdf adc9a35e99000b0dfdd8b1345ea2e186 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty of Computing and Information Systems Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Informatics in Medicine Unlocked Creator An entity primarily responsible for making the resource Isaac Baffour Senkyire, Kashala Kabe Gedeon, Emmanuel Freeman, Benjamin Ghansah, Zhe Liu Description An account of the resource Automatic pancreas segmentation of CT scans enables physicians to identify and monitor the abnormalities in the pancreas. This facilitates intraoperative assistance, surgical planning, prognosis, and diagnosis. Nonetheless, the size and location of the pancreas in the CT image input data present a significant challenge for automatic segmentation, and the intricacy of the background region confounds deep segmentation networks. To solve this difficulty, we propose the Encoder-Corollary Atrous Spatial Pyramid Pooling-Decoder Network (EcD-Net) for locating and segmenting the pancreas. This two-tiered method begins with a coarse segmentation stage for locating the pancreas within the overall CT image. Using the detected image from the first tier, a fine segmentation network based on U-Net is applied to segment the target organ (pancreas). A novel Saturated Multiview Dense Module (SMD-Module) is presented to enhance information gradient flow for the stability of the training process and easier convergence at the fine stage. A novel Corollary Atrous Spatial Pyramid Pooling Module (CASPP-Module) is proposed to simultaneously capture low-level details and high-level global context information to enhance the pancreas segmentation accuracy, extract global and local spatial data, and detect the pancreas at varied scales. On the publicly available National Institute of Health (NIH) pancreas dataset, our proposed EcD-Net surpasses previous state-of-the-art methods with a mean Dice Similarity Coefficient (DSC) of 88.84%, mean Precision (PRE), Recall (REC), and Intersection over Union (IoU) of 91.85%, 88.21%, and 89.94% respectively … Date A point or period of time associated with an event in the lifecycle of the resource 2024 Source A related resource from which the described resource is derived https://www.researchgate.net/profile/Benjamin-Ghansah-2/publication/385323071_EcD-Net_Encoder-Corollary_Atrous_Spatial_Pyramid_Pooling-Decoder_Network_for_Automated_Pancreas_Segmentation_of_2D_CT_Images/links/672b2cc277f274616d5eeb25/EcD-Net-Encoder-Corollary-Atrous-Spatial-Pyramid-Pooling-Decoder-Network-for-Automated-Pancreas-Segmentation-of-2D-CT-Images.pdf?__cf_chl_tk=w.nKPPDQX976.WVdYddVY05V2Jyar6C34yuuacFRMX4-1741103602-1.0.1.1-Wf2eFlbEa6zXih_DPuzs32K2hnghe4vR_vCrGwYG2OI Language A language of the resource English https://www.repository.gctu.edu.gh/files/original/640a564915c1c5155ebef212183d1b71.pdf 02fa0130efd91591d257be1b3dd4f9a3 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty of Computing and Information Systems Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource An Assessment of E-commerce Adoption in the Banking Industry of Ghana Creator An entity primarily responsible for making the resource Patrick Baah-Acquah, Emmanuel Freeman Publisher An entity responsible for making the resource available The International Journal of Business & Management Date A point or period of time associated with an event in the lifecycle of the resource 2016 Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=rQvaaoMAAAAJ&cstart=20&pagesize=80&citation_for_view=rQvaaoMAAAAJ:Zph67rFs4hoC Language A language of the resource English Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty of IT Business Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Country Level Case Studies Creator An entity primarily responsible for making the resource Robert Ebo Hinson Description An account of the resource This chapter provides insights into country-level case studies on the creative sub-sectors such as the Domestic Tourism Development Strategy in Nigeria and the Year of the Return initiative in Ghana – showcasing architectural feats and innovative cultural artefacts. This chapter also features Burkina Faso (film), Djibouti (Animation and sustainable tourism), Kenya (animation and Arts), Nigeria (photography, film), Ghana, Mozambique, South Africa, Zambia and Zimbabwe. Citation Publisher An entity responsible for making the resource available Emerald Publishing Limited Date A point or period of time associated with an event in the lifecycle of the resource 2022 Source A related resource from which the described resource is derived https://www.emerald.com/insight/content/doi/10.1108/978-1-80071-302-420211008/full/html Language A language of the resource English