PAPER making! FROM THE PUBLISHERS OF PAPER TECHNOLOGY INTERNATIONAL Volume 7, Number 3, 2021
an important role in their application. The technologies applied, the level of reduction in water consumption and the extent of water recycling are different for each mill, since the quality of whitewater and wastewater varies depending on the raw materials and products. The maintenance of the balance between partial equilibria of process variables such as water flowrates, pulp consistency, physiochemical, thermal and microbiological properties through water management is important for maintaining efficient water use and lowering the need for consumption of additional fresh water. “ Monitoring of papermaking wastewater treatment processes using t-distributed stochastic neighbor embedding ”, Xiaobo Ma, Yuchen Zhang, Fengshan Zhang & Hongbin Liu, Journal of Environmental Chemical Engineering , Vol.9(6), 2021, 106559. A combination of t-distribution stochastic neighbor embedding with a Gaussian mixture model (t-SNE-GMM) is proposed for sensor fault detection in wastewater treatment processes. The proposed method can be used to handle the non-Gaussian and nonlinear characteristics of wastewater treatment processes simultaneously. The t-SNE method is first used to reduce the dimension of process data, and then GMM only uses the normal process data to accomplish fault detection. With manifold learning, the hybrid model can reduce computation complexity and improve detection accuracy. Two methods that combined GMM with principal component analysis (PCA-GMM) and kernel PCA-GMM (KPCA-GMM) are used for comparing with t-SNE-GMM. The fault detection performance was verified by simulating sensor faults in the wastewater treatment process. Among them, the fault detection rates of bias fault, drifting fault, and complete failure fault using t- SNE-GMM are increased by 67.8%, 5%, and 109.52%, respectively, compared with KPCA-GMM. Although the improvement of the fault detection rate of drifting faults is not obvious, it has an excellent performance in the false alarm rate. The combined method has the capability of detecting the sensor faults in the wastewater treatment process. WOOD PANEL “ Recent applications of nanoparticles in wood-based panels ”, Nadir Ayrilmis, Machines. Technologies. Materials . Vol.15(7), pp.287-290, pp.287-290, (2021). Nanocellulose applications in the wood-based panels have gained a great deal in the scientific researches and industrial applications. Utilization of natural and synthetic nanoparticles as reinforcement in the wood-based panels has considerably increased in the last two decades due to their unique properties. The main property of the nanocellulose is its very high surface area. Hereby, the very small use of nanoparticles such as 1-2 wt% in the composites is enough at a relatively low-cost. Nanoparticles are presently considered to be high-potential reinforcing fillers for the enhancement of the physical, mechanical, electrical/electronic properties, thermal resistivity, fire, durability properties of wood-based panels such as particleboard, fibreboard, oriented strandboard, and plywood. The nanoparticles are applied to wood based panels during the manufacture and after production. The raw materials such as wood or resin can be treated with nanoparticles or the finished panels can be treated with nanoparticles. In this study, the recent developments in the nano particles, their applications in the wood based panels, and their effects on the panel properties were reviewed “ Structural Insulation Materials from Plant Resources for Building ”, Aung Htut Thu & Alexander I. Zakharov, Macromolecular Symposia , online. Nowadays, researchers are focusing on the methods of using recycled industrial/agricultural wastes as raw materials, which are not only economically but also environmentally useful. In the recent years, many scholars have conducted research on the rational use of rice husks (RHs) and found that RHs are rich in inorganic/organic components and used in combination with
Technical Abstracts
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