This study identified high-risk locations (hotspots) using geographic information systems (GIS) and spatial analysis. Five years of accident data (2013–2017) for the Lokoja-Abuja-Kaduna highway in Nigeria were used. The accident concentration analysis was conducted using the mean center analysis and Kernel density estimation method. These locations were further verified using Moran’s I statistics (spatial autocorrelation) to determine their clustering with statistical significance. Fishnet polygon and network spatial weight matrix approaches of the Getis–Ord Gi* statistic were used in the hotspot analysis. Hotspots exist for 2013, 2014, and 2017 with a significance level between 95–99%. However, hotspots for 2015 and 2016 have a low significance level and the pattern is random. The spatial autocorrelation analysis of the overall accident locations and the Moran’s I statistic showed that the distribution of the accidents on the study route is random. Thus, preventive measures for hotspot locations should be based on a yearly hotspot analysis. The average daily traffic values of 31,270 and 16,303 were obtained for the northbound and southbound directions of the Abaji–Abuja section. The results show that hotspot locations with high confidence levels are at points where there are geometric features.
High cost of building construction in the country has remained a major source of concern to successive government in the nation. Building materials constitute approximately 60-70% of the building cost. In view of this, the need for alternate building materials is imminent. This research work focuses on assessment of effect of different curing methods on the compressive strength of palm kernel shell aggregate concrete. All materials were collected at Ede, Osun state. The stages involved in this research are material collection, batching and mixing, casting of concrete cubes, slump test, curing, and compressive strength test. The tests carried out were x-ray fluorescence, slump test and compressive strength. Four different curing methods were used; water, air, salt water, and detergent to cure concrete with two mixing ratios of 1:2:4 and 1:1½:3. It can be observed that the Palm Kernel Shell (PKS) contains mainly Iron (Fe), Potassium (K), Calcium (Ca), Manganese (Mn) elements and other impurities. From the slump test results, it can be deduced that 1:1½:3 gave a better slump as expected. The compressive strength of cube ranges from 2.244 to 3.852N/mm2 Based on the results, the curing methods has a significant effect on the compressive strength of the PKS aggregate concrete.
Aggregates constitute more than 90% of concrete and significantly determine the strength of concrete. In this study, the shape characteristics such as flakiness and elongation were determined using elongation and thickness gauge. The aggregate used for the study is granite. Aggregate crushing value and aggregate impact value tests were performed on the aggregate while slump test, water absorption test, compressive strength test and flexural strength test were carried out on concrete. A total of one hundred and thirty-two concrete cubes were produced using 1:2:4 and 1:3:6 mix each for the compressive strength test and forty-eight reinforced concrete beams were produced for flexural strength test. The slump for all the samples tested was examined to be true. The compressive strength of the concrete cube was greatly affected by the shape of aggregate used and it was noted that; for lower percentage of flaky and elongated aggregate the compressive strength is moderately high compared to when the percentage is high. The highest obtained compressive strength, 15N/mm2 is in compliance with the concrete compressive strength of normal 1:2:4 mix as stipulated in ASTM C109, Also, with 30% of elongated aggregate and 30% of flaky, the flexural strength of 7.03 N/mm2 was obtained. This shows that aggregate shape is a very important property of coarse aggregate that must be put into consideration in production of quality concrete for construction works.
This paper assesses the operational data of a public transportation system, using the Bus Rapid Transit in Lagos State as a case study. Demographic data was collected through the administration of questionnaires to the commuters; this was carried out to observe variations in the population of the commuters from different perspectives. Some other categories of data were collected which include boarding and alighting, headway, arrival rate of commuters, waiting time of commuters and travel time data. These data were presented and analysed with MS Excel and Minitab statistical softwares. Results from the boarding and alighting data showed bus stops with high flux of commuters, these were at Ojota, Ketu, Mile 12, Costain, CMS and TBS. Probability distribution charts were prepared to analyze the remaining sets of data. This was carried out to study the distribution and consistency of the data. Coefficients of variation for the data were also estimated to study the variability of the data. From the study, the data followed normal distribution and they were consistent such that they can be used for further analysis of the system. It can be concluded that the distribution depicts the real situation at the study location. Thus, bus stops with high density of commuters should be provided with more buses so as to reduce the waiting time of commuters.
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