Beijing University of Technology

About: Beijing University of Technology is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: Microstructure & Computer science. The organization has 31929 authors who have published 31987 publications receiving 352112 citations. The organization is also known as: Běijīng Gōngyè Dàxué & Beijing Polytechnic University.

A Self-Organizing Fuzzy Neural Network Based on a Growing-and-Pruning Algorithm

Abstract: A novel growing-and-pruning (GP) approach is proposed, which optimizes the structure of a fuzzy neural network (FNN). This GP-FNN is based on radial basis function neurons, which have center and width vectors. The structure-learning phase and the parameter-training phase are performed concurrently. The structure-learning approach relies on the sensitivity analysis of the output. A set of fuzzy rules can be inserted or reduced during the learning process. The parameter-training algorithm is implemented using a supervised gradient decent method. The convergence of the GP-FNN-learning process is also discussed in this paper. The proposed method effectively generates a fuzzy neural model with a highly accurate and compact structure. Simulation results demonstrate that the proposed GP-FNN has a self-organizing ability, which can determine the structure and parameters of the FNN automatically. The algorithm performs better than some other existing self-organizing FNN algorithms.

Suppressing Nitrite-oxidizing Bacteria Growth to Achieve Nitrogen Removal from Domestic Wastewater via Anammox Using Intermittent Aeration with Low Dissolved Oxygen.

Abstract: Achieving nitrogen removal from domestic wastewater using anaerobic ammonium oxidation (anammox) has the potential to make wastewater treatment energy-neutral or even energy-positive. The challenge is to suppress the growth of nitrite-oxidizing bacteria (NOB). This study presents a promising method based on intermittent aeration with low dissolved oxygen to limit NOB growth, thereby providing an advantage to anammox bacteria to form a partnership with the ammonium-oxidizing bacteria (AOB). The results showed that NOB was successfully suppressed using that method, with the relative abundance of NOB maintained between 2.0–2.6%, based on Fluorescent in-situ Hybridization. Nitrogen could be effectively removed from domestic wastewater with anammox at a temperature above 20 °C, with an effluent total nitrogen (TN) concentration of 6.6 ± 2.7 mg/L, while the influent TN and soluble chemical oxygen demand were 62.6 ± 3.1 mg/L and 88.0 ± 8.1 mg/L, respectively.

Porous Co3O4 nanowires and nanorods: Highly active catalysts for the combustion of toluene

Abstract: Porous Co 3 O 4 nanowires and nanorods (Co 3 O 4 -HT, Co 3 O 4 -HT-PEG, Co 3 O 4 -HT-CTAB, and Co 3 O 4 -ME-CTAB, respectively) have been fabricated via the hydrothermal or microemulsion route in the absence and presence of polyethylene glycol (PEG) or cetyltrimethylammonium bromide (CTAB), respectively. Physicochemical properties of the materials were characterized by means of numerous techniques, and their catalytic activities for toluene combustion were evaluated. It is shown that Co 3 O 4 -HT-PEG and Co 3 O 4 -HT-CTAB displayed a porous nanowire-like morphology, whereas Co 3 O 4 -ME-CTAB exhibited a porous nanorod-like shape. The porous Co 3 O 4 samples (surface area = 47–52 m 2 /g) possessed much higher surface oxygen adspecies concentrations and much better low-temperature reducibility than the nonporous counterpart. The Co 3 O 4 -HT-CTAB sample showed the highest catalytic performance ( T 50% = 195 and T 90% = 215 °C at a space velocity of 20,000 mL/(g h)). It is concluded that the excellent catalytic performance of Co 3 O 4 -HT-CTAB was associated with its higher surface area and surface oxygen species concentration, and better low-temperature reducibility.