33 10 3131 https://repository.gctu.edu.gh/files/original/0c23721498e26ed67550e1a5c830163f.pdf cda7119035e5a136d44af1a895ef1277 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 Applicability and Usefulness of the HFACS-GMI Creator An entity primarily responsible for making the resource Theophilus Joe-Asare, E Stemn, N Amegbey Description An account of the resource To present information such as causes of accidents and their consequences on the Ghanaian mining industry in the safety literature, classification schemes for incident analysis within the safety literature were studied. Human Factor Analysis and Classification Scheme (HFACS) emerged suitable for incident analysis. Base on its suitability for incident analysis within the Ghanaian Mining Industry (GMI), a derivative of the HFACS, namely HFACS-GMI, was proposed. This research seeks to study the usefulness and the applicability of the HFACS-GMI. Collectively, 56 incident investigation reports were obtained from an open cast gold mine in Ghana and analysed using the HFACS-GMI. Two cases, an equipment damage incident and an injury incident, were used to demonstrate the coding processing in identifying the causal factors. The analysis shows that most mishaps are associated with adverse workplace/operator conditions (151 references), with the physical environment (72.2%) being cited as the major causal code under the tier. Management decision showed a major contribution (74.1%) to mishap under the causal codes. Most cases were attributed to mistake error (57.4%) followed by the contravention (51.1%) of set rules and procedures with the operator's act tiers. Inadequate work standards (27.8%) and failure to ensure competency (24.1%) under the operational process and leadership flaw causal codes, respectively, were identified as the most cited nanocode. Management decision is critical in a mishap and should be given much attention in developing accident prevention strategies. The study has demonstrated that HFACS-GMI is … Date A point or period of time associated with an event in the lifecycle of the resource 2021 Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=4--inMwAAAAJ&citation_for_view=4--inMwAAAAJ:Y0pCki6q_DkC Language A language of the resource English https://repository.gctu.edu.gh/files/original/dd55546a8b09b3087479aba00d244e5c.pdf 5d5feac995c89593efc86d6a9af8650c 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 Food Science 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 Applicability of the melanger for chocolate refining and Stephan mixer for conching as small-scale alternative chocolate production techniques Creator An entity primarily responsible for making the resource Michael Hinneh, Davy Van de Walle, Julie Haeck, Enoch Enorkplim Abotsi, Ann De Winne, Arifin Dwi Saputro, Kathy Messens, Jim Van Durme, Emmanuel Ohene Afoakwa, Luc De Cooman, Koen Dewettinck Description An account of the resource Conventional dark chocolate production methods that are applied in the industry consist of several steps, which require equipment with big investment costs. There are however few cost-effective alternatives suggested for small-scale production. Meanwhile, knowledge on these alternative equipment/techniques are insufficient to promote miniature production of high quality chocolates, either for research purposes in an industrial context, or for producers in developing countries, where the cost of investing in conventional equipment seems to be an impediment. The aim of this study was two-fold; first, to assess the feasibility of utilizing the ECGC-12SLTA CocoaTown melanger as an alternative to the conventional 3-roll refiner at different settings and fat content. Thereafter, one optimal setting was selected for each equipment for further investigation on the impact of the refining on some quality attributes of the final … Publisher An entity responsible for making the resource available Elsevier Date A point or period of time associated with an event in the lifecycle of the resource 2019 Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=EZuX1N8AAAAJ&pagesize=80&citation_for_view=EZuX1N8AAAAJ:W1ZWpF0a3GIC Language A language of the resource English https://repository.gctu.edu.gh/files/original/9fec837ddfe25b4e56a27579fe290e5b.pdf ff440c7ce97891aa661bd884146b52a6 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 Application of BCG as a strategic planning tool to assess the sustainability and growth of university programs in a competitive market Creator An entity primarily responsible for making the resource Stephen Owusu Afriyie, Yusheng Kong, Michael Owusu Akomeah, Kingsley Appiah, Patrick Obeng Danso Description An account of the resource With regards to the competitive environment for consumer demand, it is imperative for organizations to utilize reputed models for tactical resource allocation to different strategic business units and products. The work describes and explains the BCG portfolio matrix model to assess five Ghanaian university programs. Effective implementation of the BCG model helps the institution of higher education to achieve the finest status from the viewpoint of competitive positions in the market. The model helps institutions choose which markets and business units to finance on the basis of two features-competitiveness and market attractiveness; with the fundamental drivers for these factors being market share and growth rate respectively. Therefore, for the survival and growth of the product, the firm needs to adopt some effective and operative strategies, and also invests in areas like research and development which will enhance new ideas. Of course, the technological and innovative aspects should also not be disregarded. These strategies will enhance an innovative brand in the existing market which will help the product gain a competitive advantage. This paper attempts to analyse the business model, BCG and how it can seek to promote sustainability and growth of the university programs in a competitive market. Date A point or period of time associated with an event in the lifecycle of the resource 2018 Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=TbSlw38AAAAJ&citation_for_view=TbSlw38AAAAJ:eQOLeE2rZwMC 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 Engineering 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 Application of Classical Multiplicative Decomposition Time Series Predictive Model for the Forecast of Domestic Electricity Demand and Supply: A Ghanaian Context. Creator An entity primarily responsible for making the resource Ruhiya Abubakar, Amevi Acakpovi, Michael Agyare, Samuel Afoakwa Description An account of the resource In modern technology and systems modeling, electric energy forecast is extremely vital for the attainment of effective application of energy policies. This model is formulated after a thorough study of the power load conditions of Ghana and the factors that affect domestic electricity demand and supply in the country was conducted. In Ghana, the Long-range Energy Alternatives Planning (LEAP) forecast model is officially applied for electricity demand and projection of power supply which comes with forecasting errors. Thus, there exists a crucial need to develop a forecasting model for the best energy policies formulation and consequent minimization of overall forecasting error compared to the LEAP model. A step-by-step mathematical approach of forecasting time series data of all the domestic electricity demand areas of Accra, namely: Mallam, Achimota and Accra East 9-year data was applied in the forecasting … 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://scholar.google.com/citations?view_op=view_citation&hl=en&user=AhSMvB8AAAAJ&cstart=20&pagesize=80&citation_for_view=AhSMvB8AAAAJ:GnPB-g6toBAC Language A language of the resource English https://repository.gctu.edu.gh/files/original/3f629962b36d70a96ad9e1f618c9862b.pdf c0247ecb851411cd677f995e2a2c45ab 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 Application of FPGA to Real‐Time Machine Learning: Hardware Reservoir Computers and Software Image Processing.(2018) Creator An entity primarily responsible for making the resource Piotr, Antonik Subject The topic of the resource SOFTWARE ENGINEERING ( Real-Time Software And Systems) Publisher An entity responsible for making the resource available Springer Date A point or period of time associated with an event in the lifecycle of the resource 2018 Format The file format, physical medium, or dimensions of the resource pdf Language A language of the resource English https://repository.gctu.edu.gh/files/original/85b55ba3c0cf570396535ba2a424ab23.pdf 785084a1d9cb8563ac63e9208ed39757 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 Application of Frederick Herzberg’s Two-Factor theory in assessing and understanding employee motivation at work: a Ghanaian Perspective Creator An entity primarily responsible for making the resource Kwasi Dartey-Baah, George Kofi Amoako Description An account of the resource This paper critically examines Frederick Herzberg’s two-factor theory and assesses its application and relevance in understanding the essential factors that motivate the Ghanaian worker. The two-factor theory of motivation explains the factors that employees find satisfying and dissatisfying about their jobs. These factors are the hygiene factors and motivators. The hygiene factors when absent can lead to dissatisfaction in the work place but when fully catered for in the work environment on their own are not sufficient to satisfy workers whereas the motivators referring to the nature of the job, provide satisfaction and lead to higher motivation. This paper adds to the understanding of what motivates the Ghanaian worker most and creates the platform for a re-evaluation of the thinking and viewpoint that workers rate motivator factors higher than the hygiene factors in the work setting. Date A point or period of time associated with an event in the lifecycle of the resource 2011 Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=hXmr_bYAAAAJ&citation_for_view=hXmr_bYAAAAJ:u-x6o8ySG0sC 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 Food Science 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 Application of ISO 22000 in comparison with HACCP on industrial processing of milk chocolate. Creator An entity primarily responsible for making the resource EO Afoakwa, H Mensah-Brown, GK Crentsil, K Frimpong, F Asante Description An account of the resource Hazard analysis was conducted to identify critical control points (CCPs) during cocoa processing and milk chocolate manufacture and applied into a hazard analysis and critical control point (HACCP) plan. During the process, the different biological, physical and chemical hazards identified at each processing stage in the hazard analysis worksheet were incorporated into the HACCP plan to assess the risks associated with the processes. Physical hazards such as metals, stones, fibres, plastics and papers; chemical hazards such as pesticide residues, mycotoxins and heavy metals; and microbiological hazards such as Staphyloccous aureus, coliforms, Salmonella, Aspergillus and Penicillium were identified. ISO 22000 analysis was conducted for the determination of some pre-requisite programmes (PrPs) during the chocolate processing and compared with the HACCP system. The ISO 22000 Analysis worksheet … Date A point or period of time associated with an event in the lifecycle of the resource 2013 Source A related resource from which the described resource is derived https://scholar.google.com/citations?view_op=view_citation&hl=en&user=EZuX1N8AAAAJ&cstart=100&pagesize=100&citation_for_view=EZuX1N8AAAAJ:1qzjygNMrQYC Language A language of the resource English https://repository.gctu.edu.gh/files/original/002a289a5a1837673e1aa7e6788a7a67.pdf cd39d148949ab373ba8036cd5438eb18 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 Application of machine learning approach for iron deficiency anaemia detection in children using conjunctiva images Creator An entity primarily responsible for making the resource Justice Williams Asare, William Leslie Brown-Acquaye, Martin Mabeifam Ujakpa, Emmanuel Freeman, Peter Appiahene Description An account of the resource Iron deficiency is commonly referred to as anaemia which is a general public health problem that normally occurs as a result of a reduction in red blood cells which is common in developing countries such as Africa. In this study, machine learning algorithms such as CNN, k-NN, Naïve Bayes, Decision Tree and SVM were utilized for the study to detect anaemia in children using conjunctiva images. The images were segmented into their various CIELAB colour space components and the ROI from each image was retrieved. The dataset was split randomly into 70:10:20, which were then used to train, validate, and test the models, as appropriate. The CNN achieved the highest accuracy (98.45 %). The findings of this study demonstrate that non-invasive techniques are essential for detecting anaemia in children. This study deploys a cost-effective mechanism, and result-orientated, to detect anaemia in developing … Publisher An entity responsible for making the resource available Elsevier 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://scholar.google.com/citations?view_op=view_citation&hl=en&user=rQvaaoMAAAAJ&citation_for_view=rQvaaoMAAAAJ:_kc_bZDykSQC Language A language of the resource English https://repository.gctu.edu.gh/files/original/4bfa73336b1eea9964ced17a46348b92.pdf 49c3f4108adf641ef5938029e08d00c6 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 Application of machine learning approach for iron deficiency anaemia detection in children using conjunctiva images Creator An entity primarily responsible for making the resource Justice Williams Asare, William Leslie Brown-Acquaye, Martin Mabeifam Ujakpa, Emmanuel Freeman, Peter Appiahene Description An account of the resource Iron deficiency is commonly referred to as anaemia which is a general public health problem that normally occurs as a result of a reduction in red blood cells which is common in developing countries such as Africa. In this study, machine learning algorithms such as CNN, k-NN, Naïve Bayes, Decision Tree and SVM were utilized for the study to detect anaemia in children using conjunctiva images. The images were segmented into their various CIELAB colour space components and the ROI from each image was retrieved. The dataset was split randomly into 70:10:20, which were then used to train, validate, and test the models, as appropriate. The CNN achieved the highest accuracy (98.45 %). The findings of this study demonstrate that non-invasive techniques are essential for detecting anaemia in children. This study deploys a cost-effective mechanism, and result-orientated, to detect anaemia in developing … Publisher An entity responsible for making the resource available Elsevier 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://scholar.google.com/citations?view_op=view_citation&hl=en&user=rQvaaoMAAAAJ&citation_for_view=rQvaaoMAAAAJ:_kc_bZDykSQC Language A language of the resource English https://repository.gctu.edu.gh/files/original/f203e5f1bac8dc30edef66a69e00bbe0.pdf 18cd7741f6d7ad1d935d3f057fcc3529 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 Application of Macrobenthic Faunal Indices in Assesssing the Ecological Quality Status of Laloi Lagoon of Ghana Creator An entity primarily responsible for making the resource Rita Esi Ampiaw, Martin Owusu Amoamah, Iddrisu Wahab Abdul, Joseph Dadzie Description An account of the resource The aim of this study was to assess the macrobenthic fauna structure and use its indices as a tool for characterizing the ecological state of the Laloi lagoon. Thus, a field assessment of the benthos in the Laloi lagoon was carried in January 2012. Four replicate samples were taken at each station contained in three zones and analysed for their structure and composition. Twenty-one (21) species of macrobenthos belonging to 19 genera were identified. The highest number of species belonged to Polychaetes (15 species) followed by Bivalves (6 species) and 1 species of Gastropod. The grain size of sediments and total organic matter as essential factors in distribution and population diversity of macrobenthos communities were also analysed. The results showed that all of the stations were characterized by medium sand to very fine sand. Shannon-Wiener index (H'), species richness (S) and Pielou’s evenness were calculated and they revealed a high species diversity with variability in abundance within stations. The ecological indices, such as (AMBI, M-AMBI, BENTIX and H’) were also applied to the available benthic species data to determine the ecological status of the lagoon. AMBI, M-AMBI, H'and BENTIX gave different results regarding the boundaries for High, Good and Moderate and it was worse when applying H'and BENTIX. However, the index AMBI provided a more suitable evaluation of EcoQS corresponding to ‘slightly polluted’lagoons in compliance with univariate community indices. 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=ECTxVnYAAAAJ&cstart=20&pagesize=80&citation_for_view=ECTxVnYAAAAJ:qjMakFHDy7sC Language A language of the resource English