Image enhancement is one of the key techniques in processing quality of images in systems. The main purpose of image enhancement is to bring out detail that is hidden in an image or to increase contrast in a low contrast image. This technique provides a multitude of choices for improving the visual quality of images. This is the main reason that image enhancement is used in a huge number of applications with important challenges such as noise reduction, degradations, blurring etc. This paper focuses on three contrast enhancement techniques for image enhancement which are: Histogram Equalization (HE), Adaptive Histogram Equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) which are then compared with the help of the eight (8) quality image measurement metrics which are: i.e.

The Knapsack Problems are among the simplest integer programs which are NP-hard. Problems in this class are typically concerned with selecting from a set of given items, each with a specified weight and value, a subset of items whose weight sum does not exceed a prescribed capacity and whose value is maximum. The classical 0-1 Knapsack Problem arises when there is one knapsack and one item of each type. This paper considers the application of classical 0-1 knapsack problem with a single constraint to computer memory management. The goal is to achieve higher efficiency with memory management in computer systems. This study focuses on using simulated annealing and genetic algorithm for the solution of knapsack problems in optimizing computer memory. It is shown that Simulated Annealing performs better than the Genetic Algorithm for large number of processes.

The objective of the experiment was to investigate the influence of organic (poultry) manure, inorganic manure (N.P.K) and their combination on the growth and yield of sweet pepper in the transitional zone of Ghana. The experiment was conducted at the research field of the College of Agriculture Education, University of Education Winneba, Mampong campus in 2017. The experiment was laid out in randomized complete block design (RCBD) which consisted of four treatments with 4 replications. The treatment groups were: Control (no soil amendment), 10 t/ha PM, 300 kg/ha N.P.K, and 5 t/ha PM + 150 kg/ha N.P.K. All the treatments were given fair and equal attention in terms of watering, weeding and disease and pest control. The result showed that 10 t/ha PM recorded (P=.05) the tallest plant height, greater number of leaves and leaf area per plant, days taken for 50% bud appearance and flowering, the highest number of flowers per plant and the minimum days to fruit set, highest number of fruit set minimum days to harvesting with the control been the least in all traits. Similarly, 10 t/ha PM recorded (P=.05) had the highest number of fruits per plant, average fruit weight and fruit yield while the control treatment recorded the least in all traits. This study concludes that the application of poultry manure improves the productivity of sweet pepper. This study recommends that 10 t/ha PM is an ideal for maximum vegetative growth and yield of sweet pepper.

Since organizational decisions are vital to organizational development, customers' views and feedback are equally important to inform good decisions. Given this relevance, this paper seeks to automate a sentiment analysis system -SentDesk-that can aid tracking sentiments in customers' reviews and feedback. The study was contextualised in some business organisations in Ghana. Three business organizational marketers were made to annotate emotions and as well tag sentiments to each instance in the corpora. Kappa and Krippendoff coefficients were computed to obtain the annotation agreement in the corpora. The SentDesk system was evaluated in the environment alongside comparing the output to that of the average sentiments tagged by the marketers. Also, the SentDesk system was evaluated in the environment by the selected marketers after they had tested the platform. By finding the average kappa value from the corpora (CFR + ISEAR), the average kappa coefficient was found to be 0.40 (40%). The results of evaluating the SentDesk system with humans shows that the system performed as better as humans. The study also revealed that, while annotating emotions and sentiments in the datasets, counsellor's own emotions influences their perception of emotions.

Aim: This study was conducted to investigate small holder farmers’ awareness of climate-smart agricultural practices and challenges to climate change adoption in the semi-deciduous zone of Ghana. Study Design: A descriptive research design was used for the study. Place of study: The study was conducted within the Sekyere South district in the Ashanti Region of Ghana. Methodology: Questionnaire was the main tool for data collection. Statistical Package for Social Science [SPSS], version 20 was used for data analysis. Pearson Product Correlation was used to determine the correlation between variables and CSA at 0.05 significant level. Results: Results from the study revealed that agroforestry (52.0%) and rainwater harvesting techniques (80.0%) were never known among majority of the respondents’ as CSA strategy. Besides, farmers were moderately aware of fire and pest management (48.0%) and crop rotation (36.0%) strategies as CSA approach (48%), as well as, minimum tillage which farmers testify of having a considerable idea on it (52%). Nonetheless, respondents often used improved seed variety (64%) and also resorted to residue management and usage (52%) as CSA options in crop productivity. The study further revealed that a higher segment of the farmers attested that no proper training/education, no governmental support, lack of finance, lack of climate information and non-availability of extension field officers, representing 64%, 76%, 84%, and 76% respectively were the major challenges faced by farmers in adopting and practicing climate-smart agriculture. Conclusion: Farmers little knowledge on climate change impeded the successful adoption of CSA practices.