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effect of leachate recycling and inoculation on the biochemical characteristics of municipal refuse in landfill bioreactors

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Journal of environmental Sciences 2002年第3期14卷 406-412页

作者： ShenDS her DepartmentofenvironmentandResource ZhejiangUniversityHangzhou310029China.E－mail：shends@*** DepartmentofenvironmentandResource ZhejiangUniversityHangzhou310029China.E－mail：shends@mail.hz.zj

Activity development of key groups of enzymes involved in municipal refuse decomposition was measured in laboratory landfill bioreactors with and without leachate recycling and inoculation for about 210 days. The results showed that the enzymes (amylase, protease, cellulase, lipase and pectinase) were present in fresh refuse but at low values and positively affected by leachate recycling and refuse inoculation. The total average of cellulase activity in digesters D3 operated with leachate recycling but no inoculation, D4 and D5 operated with leachate recycling and inoculation was much higher.than that in digesters D1 and D2 without leachate recycling and inoculation by 88%—127%, 117%—162% and 64%—98%. The total average of protease activity was higher.in digester D4 than that in digesters D1, D2, D3 and D5 by 63%, 39%, 24% and 24%, respectively, and the positive effect of leachate recycling and inoculation on protease activity of landfilled refuse mainly was at the first two months. The total average of amylase activity was higher.in digesters D3, D4 and D5 than that in digesters D1 and D2 by 83%—132%, 96%—148% and 81%—129%. During the early phase of incubation, the stimulatory effect of inoculation on lipase activity was measured, but refuse moisture was the main factor affecting lipase activity of landfilled refuse. The inoculation, initial and continuous inoculation of microorganisms existing in leachate, was the mainly stimulatory factor affecting pectinase activity of landfilled refuse.

关键词： municipal refuse landfill bioreactor leachate recycle inoculation enzyme activity biochemical characteristics

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A new protocol of wide use for e-mail with perfect forward secrecy

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Journal of Zhejiang University-Science C(Computers and electronics) 2010年第1期11卷 74-78页

作者： Tzung-her.CHeN Department of Computer Science and Information engineering National Chiayi University

Recently, Sun et al. (2005) highlighted the essential property of perfect forward secrecy (PFS) for e-mail protocols when a higher.security level is desirable. Further.ore, Sun et al. (2005)’s protocols take only a single e-mail server into account. Actually, it is much more common that the sender and the recipient register at different e-mail servers. Compared to existing protocols, the protocol proposed in this paper takes into account the scenario that the sender and the recipient register at different servers. The proposed protocol is skillfully designed to achieve PFS and end-to-end security as well as to satisfy the requirements of confidentiality, origin, integrity and easy key management. The comparison in terms of functionality and computational efficiency demonstrates the superiority of the present scheme.

关键词： e-mail protocol Perfect forward secrecy (PFS) Confidentiality end-to-end security

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Strain measurement of fiber optic sensor surface bonding on host material

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中国有色金属学会会刊：英文版 2009年第B09期19卷 143-149页

作者： Shiuh-Chuan her.Chang-Yu TSAI Department of Mechanical engineering Yuan Ze University

Fiber optic sensor has been widely used as a structural health monitoring device by either.embedding into or surface bonding onto the structures. The strain of optic fiber induced by the host material is strongly dependent on the bonding characteristics which include the protective coating, adhesive layer and the length of bonding. The strains between the fiber optics and host structure are not exact the same. The existence of the protective coating and adhesive layer would affect the strain measured by the surface bonding optic sensor. The analytical expression of the strain in the optic fiber induced by the host material was presented. The results were validated by the finite element method. The theoretical predictions reveal that the strain in the optical fiber is lower than the strain of host material. Parametric study shows that a long bonding length and high modulus of protective coating would increase the percentage of strain transferring into the optical fiber. experiments were conducted by using Mach-Zehnder interferometer to measure the strain of the surface bonding optic fiber induced by the host structure. Good agreements were observed in comparison with the experimental results and theoretical predictions.

关键词：光纤传感器主机结构应变测量粘接材料表面结构健康监测粘结长度光纤应变

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NONLINeAR NUMeRICAL ANALYSIS OF A FLeXIBLe ROTOR eQUIPPeD WITH SQUeeZe COUPLe STReSS FLUID FILM JOURNAL BeARINGS

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Acta Mechanica Solida Sinica 2007年第4期20卷 309-316页

作者： Cai-Wan Chang-Jian her.Terng Yau Department of Mechanical and Automation engineering I-Shou University Kaohsiung County 840 Taiwan China Department of electrical engineering Far-East College Tainan County 744 Taiwan China

This study performs a dynamic analysis of a rotor supported by two squeeze couple stress fluid film journal bearings with nonlinear suspension. The numerical results show that the stability of the system varies with the non-dimensional speed ratios and the dimensionless parameter l＊. It is found that the system is more stable with higher.dimensionless parameter l＊. Thus it can conclude that the rotor-bearing system lubricated with the couple stress fluid is more stable than that with the conventional Newtonian fluid. The modeling results thus obtained by using the method proposed in this paper can be used to predict the stability of the rotor-bearing system and the undesirable behavior of the rotor and bearing center can be avoided.

关键词： couple stress fluid rotor-bearing system bifurcation chaos squeeze

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examination of DMT-based methods for evaluating the liquefaction potential of soils

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Journal of Zhejiang University-Science A(Applied Physics & engineering) 2011年第11期12卷 807-817页

作者： Gordon Tung-Chin KUNG Der-her.Lee Pai-Hsiang TSAI Sustainable environment Research Center National Cheng Kung University Department of Civil engineering National Cheng Kung University

The flat dilatometer test （DMT） has the potential to be a useful tool in the evaluation of liquefaction potential of soils. In practice, it is necessary to carefully examine existing DMT-based methods for evaluating liquefaction potential. We con- ducted the DMT and cone penetration test （CPT） in high liquefaction potential areas to examine the existing DMT-based methods for liquefaction potential evaluation. Specifically, the DMT and CPT were conducted side-by-side at each of six in-situ sites, and thus it is feasible to utilize those test results to validate the existing DMT-based methods. The DMT parameter, horizontal stress index （KD）, is used as an indicator for estimating liquefaction resistance of soils in terms of cyclic resistance ratio （CRR）. The analysis results revealed that the existing KD-based liquefaction evaluation methods would overestimate the CRR of soils, which leads to overestimation of the factor of safety against liquefaction. Also, the estimations of DMT-KI~ values by using the CPT-qc as well as the correlation between DMT-KD and CPT-qc proposed by the previous studies would be significantly smaller than field measurements. The results reflected that further.validation of the existing DMT-based methods for liquefaction evaluation is desirable.

关键词： Liquefaction Flat dilatometer test (DMT) Horizontal stress index earthquake

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A Multimodel Transfer-Learning-Based Car Price Prediction Model with an Automatic Fuzzy Logic Parameter Optimizer

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Computer Systems Science & engineering 2023年第8期46卷 1577-1596页

作者： Ping-Huan Kuo Sing-Yan Chen her.Terng Yau Department of Mechanical engineering National Chung Cheng UniversityChiayi62102TaiwanChina Advanced Institute of Manufacturing with High-Tech Innovations(AIM-HI) National Chung Cheng UniversityChiayi62102TaiwanChina

Cars are regarded as an indispensable means of transportation in *** studies have indicated that the automotive industry has witnessed remarkable advances and that the market of used cars has rapidly *** this study,a price prediction system for used BMW cars was *** parameters of used cars,including their model,registration year,and transmission style,were *** data obtained were then divided into three *** first subset was used to compare the results of each *** predicted values produced by the two algorithms with the most satisfactory results were used as the input of a fully connected neural *** second subset was used with an optimization algorithm to modify the number of hidden layers in a fully connected neural network and modify the low,medium,and high parameters of the membership function(MF)to achieve model ***,the third subset was used for the validation set during the prediction *** three subsets were divided using k-fold cross-validation to avoid overfitting and selection *** conclusion,in this study,a model combining two optimal algorithms(i.e.,random forest and k-nearest neighbors)with several optimization algorithms(i.e.,gray wolf optimizer,multilayer perceptron,and MF)was successfully *** prediction results obtained indicated a mean square error of 0.0978,a root-mean-square error of 0.3128,a mean absolute error of 0.1903,and a coefficient of determination of 0.9249.

关键词： Used car price prediction transfer learning fuzzy logic machine learning optimization algorithm

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Dense-Structured Network Based Bearing Remaining Useful Life Prediction System

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Computer Modeling in engineering & Sciences 2022年第10期131卷 133-151页

作者： Ping-Huan Kuo Ting-Chung Tseng Po-Chien Luan her.Terng Yau Department of Mechanical engineering National Chung Cheng UniversityChiayi62102Taiwan Advanced Institute of Manufacturing with High-Tech Innovations(AIM-HI) National Chung Cheng UniversityChiayi62102Taiwan

This work is focused on developing an effective method for bearing remaining useful life *** method is useful in accurately predicting the remaining useful life of bearings so that machine damage,production outage,and human accidents caused by unexpected bearing failure can be *** study uses the bearing dataset provided by FeMTO-ST Institute,Besancon,*** study starts with the exploration of neural networks,based on which the biaxial vibration signals are modeled and *** paper introduces pre-processing of bearing vibration signals,neural network model training and adjustment of training *** model is trained by optimizing model parameters and verifying its performance through *** proposed model’s superiority is also confirmed through a comparison with other.*** this study,the neural network model is trained with various types of bearing data and can successfully predict the remaining useful *** algorithm proposed in this study achieves a prediction accuracy of coefficient of determination as high as 0.99.

关键词： Bearing neural network remaining useful life prediction machine learning

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SMOGN,MFO,and XGBoost Based excitation Current Prediction Model for Synchronous Machine

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Computer Systems Science & engineering 2023年第9期46卷 2687-2709页

作者： Ping-Huan Kuo Yu-Tsun Chen her.Terng Yau Department of Mechanical engineering National Chung Cheng UniversityChiayi62102TaiwanChina Advanced Institute of Manufacturing with High-Tech Innovations(AIM-HI) National Chung Cheng UniversityChiayi62102TaiwanChina

The power factor is the ratio between the active and apparent power,and it is available to determine the operational capability of the intended circuit or the *** excitation current of the synchronous motor is an essential parameter required for adjusting the power factor because it determines whether.the motor is under the optimal operating *** the excitation current should predict with the experimental devices,such a method is unsuitable for online real-time *** artificial intelligence algorithm can compensate for the defect of conventional measurement methods requiring the measuring devices and the model optimization is compared during the research *** this article,the load current,power factor,and power factor errors available in the existing dataset are used as the input parameters for training the proposed artificial intelligence algorithms to select the optimal algorithm according to the training result,for this algorithm to have higher.*** SMOGN(Synthetic Minority Over-Sampling Technique for Regression with Gaussian Noise)is selected for the research by which the data and the MFO(Moth-flame optimization algorithm)are created for the model to adjust and optimize the parameters *** addition to enhancing the prediction accuracy for the excitation current,the automatic parameter adjusting method also allows the researcher. not specializing in the professional algorithm to apply such application method more *** final result indicated that the prediction accuracy has reached“Mean Absolute error(MAe)=0.0057,Root Mean Square error(RMSe)=0.0093 andR2 score=0.9973”.Applying this method to themotor control would be much easier for the power factor adjustment in the future because it allows the motor to operate under the optimal power status to reduce energy consumption while enhancing working efficiency.

关键词： Synchronous machine power factor excitation current active power apparent power

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Review of MXenes as new nanomaterials for energy storage/delivery and selected environmental applications

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Nano Research 2019年第3期12卷 471-487页

作者： Byung-Moon Jun Sewoon Kim Jiyong Heo Chang Min Park Namguk her.Min Jang Yi Huang Jonghun Han Yeomin Yoon Department of Civil and environmental engineering University of South Carolina Columbia 300 Main Street SC 29208 USA Department of Civil and environmerttal engineering Korea Army Academy at Young-Cheon 495 Hogook-ro Kokyungmeon Young-Cheon Gyeongbuk 38900 Republic of Korea Department of environmental engineering Kyungpook National University 80 Daehak-ro Buk-gu Daegu 41566 Republic of Korea Department of environmental engineering Kwangwoon University 447-1 Wolgye-Dong Nowon-Gu Seoul 01897 Republic of Korea School of engineering Institute for Materials & Processes (IMP) The University of Edinburgh Colin Maclaurin Road Edinburgh EH9 3DW Scotland UK

energy and environmental issues presently attract a great deal of scientific attention. Recently, two-dimensional MXenes and MXene-based nanomaterials have attracted increasing interest because of their unique properties (e.g., remarkable safety, a very large interlayer spacing, environmental flexibility, a large surface area, and ther.al conductivity). In 2011, multilayered MXenes (Ti3C2Tx, a new family of two-dimensional (2D) materials) produced by etching an A layer from a MAX phase of Ti3AlC2, were first described by researcher. at Drexel University. The term “MXene” was coined to distinguish this new family of 2D materials from graphene, and applies to both the original MAX phases and MXenes fabricated from them. We present a comprehensive review of recent studies on energy and environmental applications of MXene and MXene-based nanomaterials, including energy conversion and storage, adsorption, membrane, photocatalysis, and antimicrobial. Future research needs are discussed briefly with current challenges that must be overcome before we completely understand the extraordinary properties of MXene and MXene-based nanomaterials.

关键词： MXenes MXene-based nanomaterials energy storage environment applications

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ensemble Model for Spindle Ther.al Displacement Prediction of Machine Tools

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Computer Modeling in engineering & Sciences 2023年第10期137卷 319-343页

作者： Ping-Huan Kuo Ssu-Chi Chen Chia-Ho Lee Po-Chien Luan her.Terng Yau Department of Mechanical engineering National Chung Cheng UniversityChiayi62102Taiwan Advanced Institute of Manufacturing with High-Tech Innovations(AIM-HI) National Chung Cheng UniversityChiayi62102Taiwan

Numerous factors affect the increased temperature of a machine tool, including prolonged and high-intensity usage,tool-workpiece interaction, mechanical friction, and elevated ambient temperatures, among other.. Consequently,spindle ther.al displacement occurs, and machining precision suffers. To prevent the errors caused by thetemperature rise of the Spindle fromaffecting the accuracy during themachining process, typically, the factory willwarm up themachine before themanufacturing ***, if ther. is noway to understand the tool spindle’sther.al deformation, the machining quality will be greatly affected. In order to solve the above problem, thisstudy aims to predict the ther.al displacement of the machine tool by using intelligent algorithms. In the practicalapplication, only a few temperature sensors are used to input the information into the prediction model for realtimether.al displacement prediction. This approach has greatly improved the quality of tool ***,each algorithm has different performances in different environments. In this study, an ensemble model is used tointegrate Long Short-TermMemory (LSTM) with Support VectorMachine (SVM). The experimental results showthat the prediction performance of LSTM-SVM is higher.than that of other.machine learning algorithms.

关键词： Ther.al displacement ensemble model LSTM milling machine spindle

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