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                <text>Application of BCG as a strategic planning tool to assess the sustainability and growth of university programs in a competitive market</text>
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                <text>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.</text>
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                <text>Application of Classical Multiplicative Decomposition Time Series Predictive Model for the Forecast of Domestic Electricity Demand and Supply: A Ghanaian Context.</text>
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                <text>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 …</text>
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                <text>Application of FPGA to Real‐Time Machine Learning: Hardware Reservoir Computers and Software Image Processing.(2018)</text>
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                <text>Piotr, Antonik</text>
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                <text>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.</text>
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                <text>Application of ISO 22000 in comparison with HACCP on industrial processing of milk chocolate.</text>
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                <text>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 …</text>
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                <text>Application of machine learning approach for iron deficiency anaemia detection in children using conjunctiva images</text>
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                <text>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 …</text>
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                <text>Application of machine learning approach for iron deficiency anaemia detection in children using conjunctiva images</text>
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                <text>Justice Williams Asare, William Leslie Brown-Acquaye, Martin Mabeifam Ujakpa, Emmanuel Freeman, Peter Appiahene</text>
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                <text>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 …</text>
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                  <text>Faculty of Computing and Information Systems</text>
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                <text>Application of Macrobenthic Faunal Indices in Assesssing the Ecological Quality Status of Laloi Lagoon of Ghana</text>
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                <text>Rita Esi Ampiaw, Martin Owusu Amoamah, Iddrisu Wahab Abdul, Joseph Dadzie</text>
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                <text>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.</text>
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                  <text>Faculty of IT Business</text>
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                <text>Application of Monetary Policy in Money Market - A comparative Study between Ghana and India</text>
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                <text>Richard Amponsah and Freda Quarshie Emmanuel Attah Kumah Amponsah, George Oppong Appaigyei Ampong, Stephen Owusu Afriyie, Michael Nana Owusu-Akomeah, Joseph Asare</text>
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                <text>Scientific Indexing Services (SIS), ADBC, Euro Pub, Directory of Research Journal Indexing (DRJI), Euro Pub, Publons, OCLC- WorldCat, Researcher Life....</text>
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                <text>Application of multiple component constraint mixture design for studying the effect of ingredient variations on the chemical composition and physico-chemical properties of soy …</text>
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                <text>FM Kpodo, Emmanuel Ohene Afoakwa, BB Amoa, FKS Saalia, AS Budu</text>
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                <text>Investigations were conducted employing a three-component constrained mixture design to formulate milk blends from soy milk, peanut milk and cow milk. Variations in chemical composition and physico-chemical properties of 10-soy-peanut-cow milk (SPCM) formulations were studied. Variations in soy-peanut-cow milk (SPCM) concentrations influenced to varying levels the chemical composition and physico-chemical properties of blends. SPCM formulations containing significant amounts of all three ingredients used (60-70% soy milk, 20-27% peanut milk and 7-20% cow milk) had high crude protein and fat values ranging from 2.20-2.51% and 5.00-6.35% respectively. Increasing soy concentrations caused relative increases in protein content while fat content increased with increasing peanut concentrations. SPCM formulations were high in the minerals Fe and Mn relative to cow milk which was high in Ca and Zn content. Trends in pH were contrary to titratable acidity and increased with increasing soy milk content but decreasing cow milk content. SPCM formulations demonstrated acceptable non-Newtonian behaviour and consistency indices.</text>
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                <text>Universiti Putra Malaysia, Faculty of Food Science &amp; Technology</text>
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                <text>2013</text>
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