https://opus.lib.uts.edu.au/bitstream/10453/33344/4/A%20review%20on%20the%20occurrence%20of%20micropollutants%20in%20the%20aquatic%20environment%20and%20their%20fate%20and%20removal%20during%20wastewater%20treatment.pdf

A review on the occurrence of micropollutants in the aquatic environment and their fate and removal during wastewater treatment

Highway Capacity Manual改訂の動向--テイラ-教授の講演より

Review of iron-free Fenton-like systems for activating H2O2 in advanced oxidation processes

In the last few decades, pharmaceuticals, credited with saving millions of lives, have emerged as a new class of environmental contaminant. These compounds can have both chronic and acute harmful effects on natural flora and fauna. The presence of pharmaceutical contaminants in ground waters, surface waters (lakes, rivers, and streams), sea water, wastewater treatment plants (influents and effluents), soils, and sludges has been well doccumented. A range of methods including oxidation, photolysis, UV-degradation, nanofiltration, reverse osmosis, and adsorption has been used for their remediation from aqueous systems. Many methods have been commercially limited by toxic sludge generation, incomplete removal, high capital and operating costs, and the need for skilled operating and maintenance personnel. Adsorption technologies are a low-cost alternative, easily used in developing countries where there is a dearth of advanced technologies, skilled personnel, and available capital, and adsorption appears to be the most broadly feasible pharmaceutical removal method. Adsorption remediation methods are easily integrated with wastewater treatment plants (WWTPs). Herein, we have reviewed the literature (1990-2018) illustrating the rising environmental pharmaceutical contamination concerns as well as remediation efforts emphasizing adsorption.

Pharmaceuticals of Emerging Concern in Aquatic Systems: Chemistry, Occurrence, Effects, and Removal Methods.

Occurrences and removal of pharmaceuticals and personal care products (PPCPs) in drinking water and water/sewage treatment plants: A review

A review of the effects of emerging contaminants in wastewater and options for their removal

Development and characterization of novel charged surface modification macromolecule to polyethersulfone hollow fiber membrane with polyvinylpyrrolidone and water

Negatively charged polyethersulfone hollow fiber nanofiltration membrane for the removal of bisphenol A from wastewater

Traffic congestion in the urban area occurs more frequent than the past due to rapidly increasing on road vehicle usage rates. It could seriously hinder the development of urban area if a well management system has not being established. These scenarios necessitate the development of advance traffic management systems to increase the performance of signalized intersection. Traffic signal timing management (TSTM) system which comprise of genetic algorithm based optimization is proposed. Using a proper TSTM system, network traffic flow can be improved with considerably less cost than other infrastructural improvements. The proposed genetic algorithm based optimization approach allows signal timing parameters such as offset, cycle time, green split and phase sequence to be optimized with objective of minimum delay and better traffic fluency. The proposed GATSTM system has the ability to handle and manage the dynamic changes of the traffic networks condition by calibrating the system parameters accordingly.

Multiple intersections traffic signal timing optimization with genetic algorithm

Occurrences of traffic congestions within the urban traffic network are increasing in a rapid rate due to the rising traffic demands of the outnumbered vehicles on road. The effectiveness of management from traffic signal timing planner is the key solution to solve the traffic congestions, but unfortunately the current traffic light signal system is not fully optimized based on the dynamic traffic conditions on the road. Adaptable traffic signal timing plan system with ability to learn from their past experiences is needed to overcome the dynamic changes of the urban traffic network. The ability of Q-learning to prospect gains from future actions and obtain rewards from its past experiences allows Q-learning to improve its decisions for the best possible actions. A good valuable performance has been shown by the proposed learning algorithm that able to improve the traffic signal timing plan for the dynamic traffic flows within a traffic network.

/pdf/q-learning-based-traffic-optimization-in-management-of-20yjoe23yl.pdf

Nurmin Bolong

Papers

A review of the effects of emerging contaminants in wastewater and options for their removal

Development and characterization of novel charged surface modification macromolecule to polyethersulfone hollow fiber membrane with polyvinylpyrrolidone and water

Negatively charged polyethersulfone hollow fiber nanofiltration membrane for the removal of bisphenol A from wastewater

Multiple intersections traffic signal timing optimization with genetic algorithm

Q-Learning Based Traffic Optimization in Management of Signal Timing Plan