MUSIC SOFTWARE DEVELOPMENT FOR GHANAIAN MUSIC EDUCATORS IN TERTIARY INSTITUTIONS.

During the 20th Century, the field of education witnessed dramatic changes in pedagogical strategies engendered by information and communication technology (ICT). Computer-assisted instruction has, in some instances, replaced the student-instructor interaction in the teaching and learning environment.  Arts educators, who, for a long time, adopted the apprenticeship approach to teaching, where the master artistes teach the novices, have also embraced the computer-assisted interactive approach. Since the year 2000, Departments of Music in Ghanaian Universities have been exposed to innovative teaching in which ICT is employed. However, in the area of music instructional technology, little has been done by Ghanaian music educators, especially in the area of music software development.  The purpose of this paper therefore is to encourage music educators in tertiary institutions to acquire skills in the development of music software and utilize them for the enhancement of teaching and learning

Certainty and Fragility: reassessing the role of automatically generated aids to the making process

This paper considers the role of automatically generated guides, supports and other material that are intended to aid the making process. Increasingly, work and even daily life are supported by systems that automatically create text, lines, images and other forms as an aid for numerous types of activity. These include the auto-suggestions of search engines and messaging apps, and the guides and supports generated by graphics and 3D modelling software. This study focuses on the role of these assistants in the production of media artefacts. It revaluates the temporary creations which support creative processes but which are rarely considered at great length beyond their originally intended purpose. This paper will discuss how a repurposed 3D printer has been used to reinvent the support material generated by 3D slicer software as drawings and images in their own right. In doing so it describes how the transition from digital proposition to analog realisation often traverses a line between certainty and fragility. It will reflect on what this might reveal about the perceived relationship between human and machine, and between the manmade and the mechanically produced. This in turn invites a reassessment and rebalancing of these roles

Fungal Biosorption, An Innovative Treatment for the Decolourisation and Detoxification of Textile Effluents

Textile effluents are among the most difficult-to-treat wastewaters, due to their considerable amount of recalcitrant and toxic substances. Fungal biosorption is viewed as a valuable additional treatment for removing pollutants from textile wastewaters. In this study the efficiency of Cunninghamella elegans biomass in terms of contaminants, COD and toxicity reduction was tested against textile effluents sampled in different points of wastewater treatment plants. The results showed that C. elegans is a promising candidate for the decolourisation and detoxification of textile wastewaters and its versatility makes it very competitive compared with conventional sorbents adopted in industrial processes

MODELLING COLOUR ABSORPTION OF UNDERWATER IMAGES USING SFM-MVS GENERATED DEPTH MAPS

Abstract. The problem of colour correction of underwater images concerns not only surveyors, who primarily use images for photogrammetric purposes, but also archaeologists, marine biologists, and many other domains experts whose aim is to study objects and lifeforms underwater. Different methods exist in the literature; some of them provide outstanding results but works involving physical models that take into account additional information and variables (light conditions, depths, camera to objects distances, water properties) that are not always available or can be measured using expensive equipment or calculated using more complicated models. Some other methods have the advantages of working with basically all kinds of dataset, but without considering any geometric information, therefore applying corrections that work only in very generic conditions that most of the time differs from the real-world applications.This paper presents an easy and fast method for restoring the colour information on images captured underwater. The compelling idea is to model light backscattering and absorption variation according to the distance of the surveyed object. This information is always obtainable in photogrammetric datasets, as the model utilises the scene's 3D geometry by creating and using SfM-MVS generated depth maps, which are crucial for implementing the proposed methodology. The results presented visually and quantitatively are promising since they are an excellent compromise to provide a straightforward and easily adaptable workflow to restore the colour information in underwater images

Personalized Photo Enhancement Using Artificial Neural Network

Artificial Neural Network (ANN) is applied to create a photo enhancement program that automatically adjusts image parameters on the face based on the preference of its own user. Viola Jones algorithm was used for face detection, and a Graphical User Interface (GUI) is created to enable users to edit the photos easily. Input data sets are essential in the learning progress of ANN. Variety of users inputted their respective image data into the program for training the neural network. Regression plot developed will be used to determine the performance of the system. The authors would relate the consistency of the users in editing their photos to the produced regression plot. On the other hand, actual tests were conducted to determine the time spent editing the photos manually and the amount of time the system automatically adjusted the photo. There is a difference in editing time between average manual adjustment and automatic adjustment by the ANN

Methods for the automatic alignment of colour histograms

Colour provides important information in many image processing tasks such as object identification and tracking. Different images of the same object frequently yield different colour values due to undesired variations in lighting and the camera. In practice, controlling the source of these fluctuations is difficult, uneconomical or even impossible in a particular imaging environment. This thesis is concerned with the question of how to best align the corresponding clusters of colour histograms to reduce or remove the effect of these undesired variations. We introduce feature based histogram alignment (FBHA) algorithms that enable flexible alignment transformations to be applied. The FBHA approach has three steps, 1) feature detection in the colour histograms, 2) feature association and 3) feature alignment. We investigate the choices for these three steps on two colour databases : 1) a structured and labeled database of RGB imagery acquired under controlled camera, lighting and object variation and 2) grey-level video streams from an industrial inspection application. The design and acquisition of the RGB image and grey-level video databases are a key contribution of the thesis. The databases are used to quantitatively compare the FBHA approach against existing methodologies and show it to be effective. FBHA is intended to provide a generic method for aligning colour histograms, it only uses information from the histograms and therefore ignores spatial information in the image. Spatial information and other context sensitive cues are deliberately avoided to maintain the generic nature of the algorithm; by ignoring some of this important information we gain useful insights into the performance limits of a colour alignment algorithm that works from the colour histogram alone, this helps understand the limits of a generic approach to colour alignment

RRS James Cook cruise JC166-167, 19 June – 6 July 2018. CLASS – Climate-linked Atlantic System Science Haig Fras Marine Conservation Zone AUV habitat monitoring, Equipment trials and staff training

Expedition JC166-167 combined a number of science and technical objectives in order to deliver a comprehensive programme for the UK marine science sector. The expedition supported the NERC National Capability programme CLASS (Climate-Linked Atlantic Sector Science, grant no NE/R015953/1), which aims to increase our understanding of the Atlantic Ocean system, in order to support evidence-based ocean management. More specifically, JC166-167 was part of the Fixed Point Observations Underpinning Activity, where repeated observations and surveys of Marine Protected Areas (MPAs) and their surroundings provide insight into the development and recovery of benthic ecosystems following natural and/or anthropogenic impacts. The target location for JC166-167 was the Greater Haig Fras Marine Conservation Zone (MCZ), west of Cornwall, which was surveyed by NOC, using Autosub AUVs, in 2012 and 2015. The 2018 expedition continued that time series, and expanded the study by also looking at differences in benthic community observed between day and night. Haig Fras is the only rocky reef on the Celtic Shelf, and was protected in 2016. In parallel with these science objectives, JC166-167 included an extensive series of equipment trials, combined with training for staff members of the Marine Autonomous and Robotic Systems group at NOC. The robotic and autonomous systems tested included the Isis ROV, HyBIS vehicle, the Autosub6000 AUV, a deep glider, a wave glider, a C-worker 4 USV and a drone. Some of the trials were carried out in the shallow waters around Haig Fras, while others required greater depths, for which we visited the Whittard Canyon system along the Celtic Margin. Wherever possible, trials and training were carried out in a way that the resulting data would help address CLASS science objectives, including objectives related to the sustained observations in the Canyons MCZ