Socio-economic baseline survey of the fishing communities of Lake Victoria, Uganda

The purpose of the Socio-economic Baseline Survey of the Fishing Communities was to provide information on the fish landing beaches, people involved in fisheries, their livelihood activities and facilities available to them.

Socio-economics of fishing communities on Uganda water bodies

Control and management of Uganda fishery resources has been hindered by among other factors the multispecies nature of the resource and the characteristic behaviour of the fishing communities. Fishermen have both genuine and uncompromising attitudes as to why they carry out certain fishing technologies.All fishing activities aim at maximizing the catches or profits while others may fish on a small scale for subsistence. Sensitizing the fisherfolk on the appropriate fishing technologies, importance of a well regulated fishery exploitation and their participation in control and management of the resource would enhance or lead to increased and sustainable fish production. Socio-economics of fishing technologies were therefore examined using prepared questionnaires and reasons why the fishing communities behave the way they do established

Invertebrate communities of Lake Nabisojjo

Invertebrates are organisms without a backbone on the basis of body size. Aquatic invertebrates can be divided into two broad categories: micro-and macro-invertebrates. The former commonly known as zooplankton, ranging in size from < 100um 10 ca.1500um and are mainly planktonic (i.e living suspended in the water column). The latter, also known as benthos, (bottom dwelling) are associated with bottom sediments(ie, living on sediment surface or burrowing in sediments), are much bigger organism greater than 1500um in body size.

Issues of HIV/AIDS/ health among the fisher communities of Lake Albert and Kyoga

The fisheries resources of Lakes Albert and Kyoga present a high potential for economic growth, food, employment and foreign earnings. However, livelihoods appear to be compromised with the emergence and rapid spread of HIV/AIDS in the fisher communities of L. Albert and Kyoga. HIV/AIDS is considered a silent epidemic that is unique, posing a great challenge to the fisheries managers, health service providers, development planners and the resource users themselves. Fishers have high HIV prevalence, as well as AIDS-related illnesses and mortality rates. The high HIV prevalence rates among the fishing communities in Uganda is between 10-40% compared to the national rates which lie between 6% and 7%. This indicates that the national programmes have not adequately addressed the plight of the fishing communities of Lakes Albert, and Kyoga and the consequences have been devastating. Men and women living in fishing villages across the world have been found to be between five and ten times more vulnerable to the disease than other communities (Tarzan et al 2005, FAO, 2007). The present prevalence rates among the fishing communities stands at 10 to 40 % (LVFO, 2008). Meanwhile the same fishing communities are the essential labour for the Lakes’ fishery industry which is thriving nationally and internationally. That resource potentially can alleviate poverty and the HIV/AIDS threat. Fishing communities are the hidden victims of the disease, mixing patterns with the general population could act as a reservoir of infection that could spill over into the general population to drive the epidemic. On L. Albert, a quarter of the fisher folk were HIV-positive by 1992 compared to 4% in a nearby Agricultural village. Since then, there have been no targeted studies to address or monitor the prevalence rates eight years later, yet the multiplicity factor is high. HIV/AIDS can be linked to unsustainable fisheries, as the labour force available would not go to deep waters to fish, instead would fish in the shallow waters as a coping mechanism. A further effect is the loss to National and local economies and reduced nutritional security for the wider population. HIV/AIDS remains a significant challenge that has created a mosaic of complexity in the fishery sector. This needs to be addressed. It is, therefore, paramount that a comprehensive study was under taken to address this pandemic and the phenomenon of HIV/AIDS based on the study objectives. 1. To determine the trend in HIV/AIDS infection among fishing communities and the factors affecting it 2. To assess the impacts of HIV/AIDS on fish production and the implications for fisheries management.

Knowledge, perceptions, impacts and roles of lakeside communities and institutions in the sustainable control of water hyacinth

The massive water hyacinth mats that covered water bodies in the 1990s had serious social and economic impacts. They affected fishing, transportation, water quality and health of fishing communities as well as production of goods and services of lake-based institutions (commercial establishments). At peak infestations, the communities and institutions were aware of and participated readily in control effort. However, after the major collapse of hyacinth in 1998, some of them relaxed in their control efforts. The status of knowledge, perception, impacts, preparedness and role of the lakeside communities and institutions to control the weed has, therefore, been monitored since the major resurgence of the weed to find out if the lakeside communities and institutions still perceive water hyacinth as a problem and the extent to which they are prepared to sustain control.

Comparative study of vision tracking methods for tracking of construction site resources

Vision tracking has significant potential for tracking resources on large scale, congested construction sites, where a small number of cameras strategically placed around the site could replace hundreds of tracking tags. The correlation of vision tracking 2D positions from multiple views can provide the 3D position. However, there are many 2D vision trackers available in the literature, and little information is available on which one is most effective for construction applications. In this paper, a comparative study of various vision tracker categories is carried out, to identify which one is most effective in tracking construction resources. Testing parameters for evaluating categories of trackers are identified, and benefits and limitations of each category are presented. The most promising trackers are tested using a database of construction operations videos. The results indicate the effectiveness of each tracker in relation to each parameter of the test, and the most suitable tracker needed to research effective 3D vision trackers of construction resources.

Automated Computation of the Fundamental Matrix for Vision-Based Construction Site Applications

Estimating the fundamental matrix (F), to determine the epipolar geometry between a pair of images or video frames, is a basic step for a wide variety of vision-based functions used in construction operations, such as camera-pair calibration, automatic progress monitoring, and 3D reconstruction. Currently, robust methods (e.g., SIFT + normalized eight-point algorithm + RANSAC) are widely used in the construction community for this purpose. Although they can provide acceptable accuracy, the significant amount of required computational time impedes their adoption in real-time applications, especially video data analysis with many frames per second. Aiming to overcome this limitation, this paper presents and evaluates the accuracy of a solution to find F by combining the use of two speedy and consistent methods: SURF for the selection of a robust set of point correspondences and the normalized eight-point algorithm. This solution is tested extensively on construction site image pairs including changes in viewpoint, scale, illumination, rotation, and moving objects. The results demonstrate that this method can be used for real-time applications (5 image pairs per second with the resolution of 640 × 480) involving scenes of the built environment.

Automated vision tracking of project related entities

Tracking of project related entities such as construction equipment, materials, and personnel is used to calculate productivity, detect travel path conflicts, enhance the safety on the site, and monitor the project. Radio frequency tracking technologies (Wi-Fi, RFID, UWB) and GPS are commonly used for this purpose. However, on large-scale sites, deploying, maintaining and removing such systems can be costly and time-consuming. In addition, privacy issues with personnel tracking often limits the usability of these technologies on construction sites. This paper presents a vision based tracking framework that holds promise to address these limitations. The framework uses videos from a set of two or more static cameras placed on construction sites. In each camera view, the framework identifies and tracks construction entities providing 2D image coordinates across frames. Combining the 2D coordinates based on the installed camera system (the distance between the cameras and the view angles of them), 3D coordinates are calculated at each frame. The results of each step are presented to illustrate the feasibility of the framework.

Testing in harsh conditions: Tracking resources on construction sites with machine vision

When tracking resources in large-scale, congested, outdoor construction sites, the cost and time for purchasing, installing and maintaining the position sensors needed to track thousands of materials, and hundreds of equipment and personnel can be significant. To alleviate this problem a novel vision based tracking method that allows each sensor (camera) to monitor the position of multiple entities simultaneously has been proposed. This paper presents the full-scale validation experiments for this method. The validation included testing the method under harsh conditions at a variety of mega-project construction sites. The procedure for collecting data from the sites, the testing procedure, metrics, and results are reported. Full-scale validation demonstrates that the novel vision tracking provides a good solution to track different entities on a large, congested construction site.

Machine vision based concrete surface quality assessment

Manually inspecting concrete surface defects (e.g., cracks and air pockets) is not always reliable. Also, it is labor-intensive. In order to overcome these limitations, automated inspection using image processing techniques was proposed. However, the current work can only detect defects in an image without the ability of evaluating them. This paper presents a novel approach for automatically assessing the impact of two common surface defects (i.e., air pockets and discoloration). These two defects are first located using the developed detection methods. Their attributes, such as the number of air pockets and the area of discoloration regions, are then retrieved to calculate defects’ visual impact ratios (VIRs). The appropriate threshold values for these VIRs are selected through a manual rating survey. This way, for a given concrete surface image, its quality in terms of air pockets and discoloration can be automatically measured by judging whether their VIRs are below the threshold values or not. The method presented in this paper was implemented in C++ and a database of concrete surface images was tested to validate its performance. Read More: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0000126?journalCode=jcemd4

Automated 3D Vision Tracking for Project Control Support

On-site tracking in open construction sites is often difficult because of the large amounts of items that are present and need to be tracked. Additionally, the amounts of occlusions/obstructions present create a highly complex tracking environment. Existing tracking methods are based mainly on Radio Frequency technologies, including Global Positioning Systems (GPS), Radio Frequency Identification (RFID), Bluetooth and Wireless Fidelity (Wi-Fi, Ultra-Wideband, etc). These methods require considerable amounts of pre-processing time since they need to manually deploy tags and keep record of the items they are placed on. In construction sites with numerous entities, tags installation, maintenance and decommissioning become an issue since it increases the cost and time needed to implement these tracking methods. This paper presents a novel method for open site tracking with construction cameras based on machine vision. According to this method, video feed is collected from on site video cameras, and the user selects the entity he wishes to track. The entity is tracked in each video using 2D vision tracking. Epipolar geometry is then used to calculate the depth of the marked area to provide the 3D location of the entity. This method addresses the limitations of radio frequency methods by being unobtrusive and using inexpensive, and easy to deploy equipment. The method has been implemented in a C++ prototype and preliminary results indicate its effectiveness