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To mitigate the challenges that Flash Event (FE) poses to IP-Traceback techniques, this paper presents an IP Traceback scheme for detecting the source of a DoS attack based on Shark Smell Optimization Algorithm (SSOA). The developed model uses a discrimination policy with the hop-by-hop search. Random network topologies were generated using the WaxMan model in NS2 for different simulations of DoS attacks. Discrimination policies used by SSOA-DoSTBK for the attack source detection in each case were set up based on the properties of the detected attack packets. SSOA-DoSTBK was compared with a number of IP Traceback schemes for DoS attack source detection in terms of their ability to discriminate FE traffics from attack traffics and the detection of the source of Spoofed IP attack packets. SSOA-DoSTBK IP traceback scheme outperformed ACS-IPTBK that it was benchmarked with by 31.8%, 32.06%, and 28.45% lower FER for DoS only, DoS with FE, and spoofed DoS with FE tests respectively, and 4.76%, 11.6%, and 5.2% higher performance in attack path detection for DoS only, DoS with FE, and Spoofed DoS with FE tests, respectively. However, ACS-IPTBK was faster than SSOA-DoSTBK by 0.4%, 0.78%, and 1.2% for DoS only, DoS with FE, and spoofed DoS with FE tests, respectively.

Noise from transportation systems is unavoidable in urban areas and can be harmful to human health. The noise generated by selected transportations systems in Ilorin, an urban area in central Nigeria, was studied by direct measurements and the use of questionnaires. Measurements were taken at the airport, train station and different locations for vehicular traffic. Questionnaires were also administered on residents of these areas to elicit information on the perception of transportation noise in the areas. The results show that all the studied locations produced maximum noise levels in excess of the 85-dBA acceptable tolerable limit for humans. The train station produced the highest stepwise noise levels due to the motion and horning of the locomotive engines. The study also established distances in which the sound level is safe over a specific period of time for each of the studied noise sources. These are of 18.84 m, 161.21 m, 13.85 m and 15.08 m for aircraft take-off, movement and horning of railway locomotive engine and vehicular traffic inside and outside town respectively. Suggested solutions were that residential buildings, academic areas and hospitals should not be located too close to sources of transportation noise and the need for enforcement of relevant noise control laws is to be pursued.

This paper presents the development of unit and storm hydrographs for Rivers Moro, Asa and Oyun catchmem. Snyder's method was used to develop the unit hydrographs; while the SCS Curve Number method was used to estimate excess rainfall values from rainfall depth of different return periods. The design storm hydrographs corresponding to the excess rainfall values were determined based on the unit hydrograph ordinates established through convolution. The design storm hydrograph obtained for Moro River catchment based on 5-yr, 20-yr, 50-yr, 100-yr and 200-yr return period ranged between 245.29 m3/s and 685.84 m3/s. Thai of Asa River catchment varied from 301.34 m3/s to 846.46 m3/s and the design storm hydrograph flows obtained for Oyun River catchment varied from 257.29 m3/s to 723.56m3/s. The design storm hydrograph flows obtained can be recommended for sizing hydraulic structures within Kwara State drainage network.