A Multilayer Perceptron Artificial Neural Network Study of Fatal Road Traffic Crashes

This paper examines the relationship between fatal road traffic accidents and potential predictors using multilayer perceptron artificial neural network (MLANN) models. The initial analysis employed twelve potential predictors, including traffic volume, prevailing weather conditions, roadway characteristics and features, drivers’ age and gender, and number of lanes. Based on the output of the model and the variables’ importance factors, seven significant variables are identified and used for further analysis to improve the performance of models. The model is optimized by systematically changing the parameters, including the number of hidden layers and the activation function of both the hidden and output layers. The performances of the MLANN models are evaluated using the percentage of the achieved accuracy, R-squared, and Sum of Square Error (SSE) functions.

Assessment of Municipal Solid Waste Management in the Farmgate Area of Dhaka North City Corporation

This investigation is focused on conducting a thorough analysis of Municipal Solid Waste Management (MSWM). MSWM encompasses a range of interdisciplinary measures that govern the various stages involved in managing unwanted or non-utilizable solid materials, commonly known as rubbish, trash, junk, refuse, and garbage. These stages include generation, storage, collection, recycling, transportation, handling, disposal, and monitoring. The waste materials mentioned in this context exhibit a wide range of items, such as organic waste from food and vegetables, paper, plastic, polyethylene, iron, tin cans, deceased animals, byproducts from demolition activities, manure, and various other discarded materials. This study aims to provide insights into the possibilities of enhancing solid waste management in the Farmgate area of Dhaka North City Corporation (DNCC). To accomplish this objective, the research examines the conventional waste management methods employed in this area. It conducts extensive field surveys, collecting valuable data through interviews with local residents and key individuals involved in waste management, such as waste collectors, dealers, intermediate dealers, recyclers, and shopkeepers. The results indicate that significant amounts of distinct waste categories are produced daily. These include food and vegetable waste, which amount to 52.1 tons/day;polythene and plastic, which total 4.5 tons/day;metal and tin-can waste, which amounts to 1.4 tons/day;and paper waste, which totals 5.9 tons/day. This study highlights the significance of promoting environmental consciousness to effectively shape the attitudes of urban residents toward waste disposal and management. It emphasizes the need for collaboration between authorities and researchers to improve the current waste management system.

Vibrational Spectroscopy of Pain Relievers: Traditional and Remote Raman Techniques

The application of vibrational spectroscopy in the pharmaceutical industry is widely investigated, from the quality assurance of the product during the production process control to the final products’ quality control and the authentication of products on the markets. This study focuses on non-contact and noninvasive detection and identification of pain-relievers at 1-5 meters standoff distances. The specimens analyzed include standard laboratory-grade active ingredients and commercially available pain relievers in powder, solid and liquid forms. All the remote measurements captured revealed the Raman signatures of the specimens, with varying peak intensities. To correlate the band intensities captured with the standoff distances between the laser source and the specimens, the intensity ratios of the two prominent peaks of the laboratory grade reference active ingredient (1607 and 1319 cm-1) normalized with 1319 cm-1 are used. The results of the study suggest the viability of standoff Raman spectroscopy for routine monitoring and identification of pharma-ceuticals, including counterfeit pain relievers.

Recycled Aggregates:Production,Properties and Value-added Sustainable Applications

Part of an extensive research undertaken by the Concrete and Masonry Research Group at Kingston University-London was reported to demonstrate through scientific research and full-scale site trials,that quality recycled concrete aggregates can be produced and can be used successfully in a range of concrete applications.The effects of up to 100% coarse recycled concrete aggregate（RCA） on fresh,engineering and durability related properties were established and assessed its suitability for use in a rage of sustainable applications.

Physico-Chemical Characterization of Novel Epoxy Matrix System Reinforced with Recycled Short Milled Carbon Fibre

As received recycled short milled carbon fiber (SMCF) reinforced diglycidal ether of bisphenol-A (DGEBA) epoxy matrix materials have been developed by ultra-sonication mixing of SMCF in epoxy then curing at room temperature for nine days. The SMCF with mean diameter 7.5 μm, and length 100 - 300 μm, was used at different loadings i.e. 1, 2, 3, 5 and 10 wt%. Elemental analysis, surface chemistry and crystallography of SMCF were examined using X-ray fluorescence, X-ray photoelectron spectroscopy and X-ray diffraction. Fourier Transform IR spectroscopy confirmed that both in unmodified and SMCF-modified epoxies, 99% curing was achieved. Surface microhardness study showed a slight increase with 5% and 10% SMCF addition. Raman study confirms no structural change in SMCF after incorporation in epoxy. Also, a numerical modelling is implemented to correlate the density of the modified epoxy and SMCF volume fraction/distribution uniformity.