Search results for: Ying Deng
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 320

Search results for: Ying Deng

200 The Performance of PtSn/Al₂O₃ with Cylindrical Particles for Acetic Acid Hydrogenation

Authors: Mingchuan Zhou, Haitao Zhang, Hongfang Ma, Weiyong Ying

Abstract:

Alumina supported PtSn catalysts with cylindrical particles were prepared and characterized by using low temperature N2 adsorption/desorption and X-ray diffraction. Low temperature N2 adsorption/desorption demonstrate that the tableting changed the texture properties of catalysts. XRD pattern indicate that the crystal structure of supports had no change after reaction. The performances over particles of PtSn/Al2O3 catalysts were investigated with regards to reaction temperature, pressure, and H2/AcOH mole ratio. After tableting, the conversion of acetic acid and selectivity of ethanol and acetyl acetate decreased. High reaction temperature and pressure can improve conversion of acetic acid. H2/AcOH mole ratio of 9.36 showed the best performance on acetic acid hydrogenation. High pressure had benefits for the selectivity of ethanol and other two parameters had no obvious effect on selectivity.  

Keywords: acetic acid hydrogenation, cylindrical particles, ethanol, PtSn

Procedia PDF Downloads 287
199 Effective Retirement Planning: Exploring Financial Planning Behavior in Malaysia

Authors: Stanley Yap Peng Lok, Chong Wei Ying, Leow Hon Wei, Fatemeh Kimiyaghalam

Abstract:

Purpose: This paper examines how people treat on the importance of financial planning for their retirement. There is lack of standard instrument that enable us to access the retirement planning behavior. This paper studies the reliability and validity of a proposed scale for accessing this behavior. Design/methodology/approach: The Retirement Planning Behavior scale (RPB) is developed from the results of reviewing different papers on this topic. A total of 900 Malaysians from the age of 18 and above are used as the sample. Findings: Our results show, firstly, the RPB meets all criteria from the instrument reliability and validity which based on the theory of planned behavior. Second, our findings propose two components for this RPB scale; attitude toward planning for retirement and intention towards retirement planning behavior. Practical implication: An effective retirement planning achieves financial independence after the retirement. Our findings have important implications for the scope and significance of the retirement planning behavior measurement, especially for retirees. Originality/value: This study proposes a new approach to cater consumers’ needs for retirement planning. Therefore, consumers are able to achieve financial independence in their retirement age.

Keywords: retirement planning behavior (RPB) scale, reliability, validity, retirement planning, financial independence

Procedia PDF Downloads 376
198 Distributed Perceptually Important Point Identification for Time Series Data Mining

Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

Abstract:

In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

Procedia PDF Downloads 392
197 The Effect of General Corrosion on the Guided Wave Inspection of the Pipeline

Authors: Shiuh-Kuang Yang, Sheam-Chyun Lin, Jyin-Wen Cheng, Deng-Guei Hsu

Abstract:

The torsional mode of guided wave, T(0,1), has been applied to detect characteristics and defects in pipelines, especially in the cases of coated, elevated and buried pipes. The signals of minor corrosions would be covered by the noise, unfortunately, because the coated material and buried medium always induce a strong attenuation of the guided wave. Furthermore, the guided wave would be attenuated more seriously and make the signals hard to be identified when setting the array ring of the transducers on a general corrosion area of the pipe. The objective of this study is then to discuss the effects of the above-mentioned general corrosion on guided wave tests by experiments and signal processing techniques, based on the use of the finite element method, the two-dimensional Fourier transform and the continuous wavelet transform. Results show that the excitation energy would be reduced when the array ring set on the pipe surface having general corrosion. The non-uniformed contact surface also produces the unwanted asymmetric modes of the propagating guided wave. Some of them are even mixing together with T(0,1) mode and increase the difficulty of measurements, especially when a defect or local corrosion merged in the general corrosion area. It is also showed that the guided waves attenuation are increasing with the increasing corrosion depth or the rising inspection frequency. However, the coherent signals caused by the general corrosion would be decayed with increasing frequency. The results obtained from this research should be able to provide detectors to understand the impact when the array ring set on the area of general corrosion and the way to distinguish the localized corrosion which is inside the area of general corrosion.

Keywords: guided wave, finite element method, two-dimensional fourier transform, wavelet transform, general corrosion, localized corrosion

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196 Graphene-reinforced Metal-organic Framework Derived Cobalt Sulfide/Carbon Nanocomposites as Efficient Multifunctional Electrocatalysts

Authors: Yongde Xia, Laicong Deng, Zhuxian Yang

Abstract:

Developing cost-effective electrocatalysts for oxygen reduction reaction (ORR), oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) is vital in energy conversion and storage applications. Herein, we report a simple method for the synthesis of graphene-reinforced cobalt sulfide/carbon nanocomposites and the evaluation of their electrocatalytic performance for typical electrocatalytic reactions. Nanocomposites of cobalt sulfide embedded in N, S co-doped porous carbon and graphene (CoS@C/Graphene) were generated via simultaneous sulfurization and carbonization of one-pot synthesized graphite oxide-ZIF-67 precursors. The obtained CoS@C/Graphene nanocomposite was characterized by X-ray diffraction, Raman spectroscopy, Thermogravimetric analysis-Mass spectroscopy, Scanning electronic microscopy, Transmission electronic microscopy, X-ray photoelectron spectroscopy and gas sorption. It was found that cobalt sulfide nanoparticles were homogenously dispersed in the in-situ formed N, S co-doped porous carbon/Graphene matrix. The CoS@C/10Graphene composite not only shows excellent electrocatalytic activity toward ORR with high onset potential of 0.89 V, four-electron pathway and superior durability of maintaining 98% current after continuously running for around 5 hours, but also exhibits good performance for OER and HER, due to the improved electrical conductivity, increased catalytic active sites and connectivity between the electrocatalytic active cobalt sulfide and the carbon matrix. This work offers a new approach for the development of novel multifunctional nanocomposites for the next generation of energy conversion and storage applications.

Keywords: MOF derivative, graphene, electrocatalyst, oxygen reduction reaction, oxygen evolution reaction, hydrogen evolution reaction

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195 Effect of Si/Al Ratio on SSZ-13 Crystallization and Its Methanol-To-Olefins Catalytic Properties

Authors: Zhiqiang Xu, Hongfang Ma, Haitao Zhang, Weixin Qian, Weiyong Ying

Abstract:

SSZ-13 materials with different Si/Al ratio were prepared by varying the composition of aluminosilicate precursor solutions upon hydrothermal treatment at 150 °C. The Si/Al ratio of the initial system was systematically changed from 12.5 to infinity in order to study the limits of Al composition in precursor solutions for constructing CHA structure. The intermediates and final products were investigated by complementary techniques such as XRD, HRTEM, FESEM, and chemical analysis. NH3-TPD was used to study the Brønsted acidity of SSZ-13 samples with different Si/Al ratios. The effect of the Si/Al ratio on the precursor species, ultimate crystal size, morphology and yield was investigated. The results revealed that Al species determine the nucleation rate and the number of nuclei, which is tied to the morphology and yield of SSZ-13. The size of SSZ-13 increased and the yield decreased as the Si/Al ratio was improved. Varying Si/Al ratio of the initial system is a facile, commercially viable method of tailoring SSZ-13 crystal size and morphology. Furthermore, SSZ-13 materials with different Si/Al ratio were tested as catalysts for the methanol to olefins (MTO) reaction at 350 °C. SSZ-13 with the Si/Al ratio of 35 shows the best MTO catalytic performance.

Keywords: crystallization, MTO, Si/Al ratio, SSZ-13

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194 The Effects of Orientation on Energy and Plasticity of Metallic Crystalline-Amorphous Interface

Authors: Ehsan Alishahi, Chuang Deng

Abstract:

Commercial applications of bulk metallic glasses (BMGs) were restricted due to the sudden brittle failure mode which was the main drawback in these new class of materials. Therefore, crystalline-amorphous (C-A) composites were introduced as a toughening strategy in BMGs. In spite of numerous researches in the area of metallic C-A composites, the fundamental structure-property relation in these composites that are not exactly known yet. In this study, it is aimed to investigate the fundamental properties of crystalline-amorphous interface in a model system of Cu/CuZr by using molecular dynamics simulations. Several parameters including interface energy and mechanical properties were investigated by means of atomic models and employing Embedded Atom Method (EAM) potential function. It is found that the crystalline-amorphous interfacial energy weakly depends on the orientation of the crystalline layer, which is in stark contrast to that in a regular crystalline grain boundary. Additionally, the results showed that the interface controls the yielding of the crystalline-amorphous composites during uniaxial tension either by serving as sources for dislocation nucleation in the crystalline layer or triggering local shear transformation zones in amorphous layer. The critical resolved shear stress required to nucleate the first dislocation is also found to strongly depend on the crystalline orientation. Furthermore, it is found that the interaction between dislocations and shear localization at the crystalline-amorphous interface oriented in different directions can lead to a change in the deformation mode. For instance, while the dislocation and shear banding are aligned to each other in {0 0 1} interface plane, the misorientation angle between these failure mechanisms causing more homogeneous deformation in {1 1 0} and {1 1 1} crystalline-amorphous interfaces. These results should help clarify the failure mechanism of crystalline-amorphous composites under various loading conditions.

Keywords: crystalline-amorphous, composites, orientation, plasticity

Procedia PDF Downloads 263
193 Shock Isolation Performance of a Pre-Compressed Large Deformation Shock Isolator with Quasi-Zero-Stiffness Characteristic

Authors: Ji Chen, Chunhui Zhang, Fanming Zeng, Lei Zhang, Ying Li, Wei Zhang

Abstract:

Based on the synthetic principle of force, a pre-compressed nonlinear isolator with quasi-zero-stiffness (QZS) is developed for shock isolation of ship equipment. The proposed isolator consists of a vertical spring with positive stiffness and several lateral springs with negative stiffness. An analytical expression of vertical stiffness of the nonlinear isolator is derived and numerical simulation on the effect of the geometric design parameters is carried out. Besides, a pre-compressed QZS shock isolation system model is established. The stiffness characteristic of the system is studied and the effects of excitation amplitude and friction damping on shock isolation performance are discussed respectively. The research results show that in comparison with linear shock isolation system, the pre-compressed QZS shock isolation system could realize constant-force or approximately constant-force function and perform better anti-impact performance.

Keywords: quasi-zero-stiffness, constant-force, pre-compressed, large deformation, shock isolation, friction damping

Procedia PDF Downloads 643
192 Numerical Investigation on the Interior Wind Noise of a Passenger Car

Authors: Liu Ying-jie, Lu Wen-bo, Peng Cheng-jian

Abstract:

With the development of the automotive technology and electric vehicle, the contribution of the wind noise on the interior noise becomes the main source of noise. The main transfer path which the exterior excitation is transmitted through is the greenhouse panels and side windows. Simulating the wind noise transmitted into the vehicle accurately in the early development stage can be very challenging. The basic methodologies of this study were based on the Lighthill analogy; the exterior flow field around a passenger car was computed using unsteady Computational Fluid Dynamics (CFD) firstly and then a Finite Element Method (FEM) was used to compute the interior acoustic response. The major findings of this study include: 1) The Sound Pressure Level (SPL) response at driver’s ear locations is mainly induced by the turbulence pressure fluctuation; 2) Peaks were found over the full frequency range. It is found that the methodology used in this study could predict the interior wind noise induced by the exterior aerodynamic excitation in industry.

Keywords: wind noise, computational fluid dynamics, finite element method, passenger car

Procedia PDF Downloads 128
191 Architecture Performance-Related Design Based on Graphic Parameterization

Authors: Wenzhe Li, Xiaoyu Ying, Grace Ding

Abstract:

Architecture plane form is an important consideration in the design of green buildings due to its significant impact on energy performance. The most effective method to consider energy performance in the early design stages is parametric modelling. This paper presents a methodology to program plane forms using MATLAB language, generating 16 kinds of plane forms by changing four designed parameters. DesignBuilder (an energy consumption simulation software) was proposed to simulate the energy consumption of the generated planes. A regression mathematical model was established to study the relationship between the plane forms and their energy consumption. The main finding of the study suggested that there was a cubic function relationship between the depth-ratio of U-shaped buildings and energy consumption, and there is also a cubic function relationship between the width-ratio and energy consumption. In the design, the depth-ratio of U-shaped buildings should not be less than 2.5, and the width-ratio should not be less than 2.

Keywords: graphic parameterization, green building design, mathematical model, plane form

Procedia PDF Downloads 123
190 Automated Machine Learning Algorithm Using Recurrent Neural Network to Perform Long-Term Time Series Forecasting

Authors: Ying Su, Morgan C. Wang

Abstract:

Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

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189 Hierarchical Queue-Based Task Scheduling with CloudSim

Authors: Wanqing You, Kai Qian, Ying Qian

Abstract:

The concepts of Cloud Computing provide users with infrastructure, platform and software as service, which make those services more accessible for people via Internet. To better analysis the performance of Cloud Computing provisioning policies as well as resources allocation strategies, a toolkit named CloudSim proposed. With CloudSim, the Cloud Computing environment can be easily constructed by modelling and simulating cloud computing components, such as datacenter, host, and virtual machine. A good scheduling strategy is the key to achieve the load balancing among different machines as well as to improve the utilization of basic resources. Recently, the existing scheduling algorithms may work well in some presumptive cases in a single machine; however they are unable to make the best decision for the unforeseen future. In real world scenario, there would be numbers of tasks as well as several virtual machines working in parallel. Based on the concepts of multi-queue, this paper presents a new scheduling algorithm to schedule tasks with CloudSim by taking into account several parameters, the machines’ capacity, the priority of tasks and the history log.

Keywords: hierarchical queue, load balancing, CloudSim, information technology

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188 Adaptive Control of Magnetorheological Damper Using Duffing-Like Model

Authors: Hung-Jiun Chi, Cheng-En Tsai, Jia-Ying Tu

Abstract:

Semi-active control of Magnetorheological (MR) dampers for vibration reduction of structural systems has received considerable attention in civil and earthquake engineering, because the effective stiffness and damping properties of MR fluid can change in a very short time in reaction to external loading, requiring only a low level of power. However, the inherent nonlinear dynamics of hysteresis raise challenges in the modeling and control processes. In order to control the MR damper, an innovative Duffing-like equation is proposed to approximate the hysteresis dynamics in a deterministic and systematic manner than previously has been possible. Then, the model-reference adaptive control technique based on the Duffing-like model and the Lyapunov method is discussed. Parameter identification work with experimental data is presented to show the effectiveness of the Duffing-like model. In addition, simulation results show that the resulting adaptive gains enable the MR damper force to track the desired response of the reference model satisfactorily, verifying the effectiveness of the proposed modeling and control techniques.

Keywords: magnetorheological damper, duffing equation, model-reference adaptive control, Lyapunov function, hysteresis

Procedia PDF Downloads 341
187 Nanoarchitectures Cu2S Functions as Effective Surface-Enhanced Raman Scattering Substrates for Molecular Detection Application

Authors: Yu-Kuei Hsu, Ying-Chu Chen, Yan-Gu Lin

Abstract:

The hierarchical Cu2S nano structural film is successfully fabricated via an electroplated ZnO nanorod array as a template and subsequently chemical solution process for the growth of Cu2S in the application of surface-enhanced Raman scattering (SERS) detection. The as-grown Cu2S nano structures were thermally treated at temperature of 150-300 oC under nitrogen atmosphere to improve the crystal quality and unexpectedly induce the Cu nano particles on surface of Cu2S. The structure and composition of thermally treated Cu2S nano structures were carefully analyzed by SEM, XRD, XPS, and XAS. Using 4-aminothiophenol (4-ATP) as probing molecules, the SERS experiments showed that the thermally treated Cu2S nano structures exhibit excellent detecting performance, which could be used as active and cost-effective SERS substrate for ultra sensitive detecting. Additionally, this novel hierarchical SERS substrates show good reproducibility and a linear dependence between analyte concentrations and intensities, revealing the advantage of this method for easily scale-up production.

Keywords: cuprous sulfide, copper, nanostructures, surface-enhanced raman scattering

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186 Prediction and Analysis of Human Transmembrane Transporter Proteins Based on SCM

Authors: Hui-Ling Huang, Tamara Vasylenko, Phasit Charoenkwan, Shih-Hsiang Chiu, Shinn-Ying Ho

Abstract:

The knowledge of the human transporters is still limited due to technically demanding procedure of crystallization for the structural characterization of transporters by spectroscopic methods. It is desirable to develop bioinformatics tools for effective analysis of available sequences in order to identify human transmembrane transporter proteins (HMTPs). This study proposes a scoring card method (SCM) based method for predicting HMTPs. We estimated a set of propensity scores of dipeptides to be HMTPs using SCM from the training dataset (HTS732) consisting of 366 HMTPs and 366 non-HMTPs. SCM using the estimated propensity scores of 20 amino acids and 400 dipeptides -as HMTPs, has a training accuracy of 87.63% and a test accuracy of 66.46%. The five top-ranked dipeptides include LD, NV, LI, KY, and MN with scores 996, 992, 989, 987, and 985, respectively. Five amino acids with the highest propensity scores are Ile, Phe, Met, Gly, and Leu, that hydrophobic residues are mostly highly-scored. Furthermore, obtained propensity scores were used to analyze physicochemical properties of human transporters.

Keywords: dipeptide composition, physicochemical property, human transmembrane transporter proteins, human transmembrane transporters binding propensity, scoring card method

Procedia PDF Downloads 340
185 Planning of Construction Material Flow Using Hybrid Simulation Modeling

Authors: A. M. Naraghi, V. Gonzalez, M. O'Sullivan, C. G. Walker, M. Poshdar, F. Ying, M. Abdelmegid

Abstract:

Discrete Event Simulation (DES) and Agent Based Simulation (ABS) are two simulation approaches that have been proposed to support decision-making in the construction industry. Despite the wide use of these simulation approaches in the construction field, their applications for production and material planning is still limited. This is largely due to the dynamic and complex nature of construction material supply chain systems. Moreover, managing the flow of construction material is not well integrated with site logistics in traditional construction planning methods. This paper presents a hybrid of DES and ABS to simulate on-site and off-site material supply processes. DES is applied to determine the best production scenarios with information of on-site production systems, while ABS is used to optimize the supply chain network. A case study of a construction piling project in New Zealand is presented illustrating the potential benefits of using the proposed hybrid simulation model in construction material flow planning. The hybrid model presented can be used to evaluate the impact of different decisions on construction supply chain management.

Keywords: construction supply-chain management, simulation modeling, decision-support tools, hybrid simulation

Procedia PDF Downloads 174
184 Compact Dual-Band Bandpass Filter Based on Quarter Wavelength Stepped Impedance Resonators

Authors: Yu-Fu Chen, Zih-Jyun Dai, Chen-Te Chiu, Shiue-Chen Chiou, Yung-Wei Chen, Yu-Ming Lin, Kuan-Yu Chen, Hung-Wei Wu, Hsin-Ying Lee, Yan-Kuin Su, Shoou-Jinn Chang

Abstract:

This paper presents a compact dual-band bandpass filter that involves using the quarter wavelength stepped impedance resonators (SIRs) for achieving simultaneously compact circuit size and good dual-band performance. The filter is designed at 2.4 / 3.5 GHz and constructed by two pairs of quarter wavelength SIRs and source-load lines. By properly tuning the impedance ratio, length ratio and radius of via hole of the SIRs, dual-passbands performance can be easily determined. To improve the passband selectivity, the use of source-load lines is to increase coupling energy between the resonators. The filter is showing simple configuration, effective design method and small circuit size. The measured results are in good agreement with the simulation results.

Keywords: dual-band, bandpass filter, stepped impedance resonators, SIR

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183 Semi-Supervised Hierarchical Clustering Given a Reference Tree of Labeled Documents

Authors: Ying Zhao, Xingyan Bin

Abstract:

Semi-supervised clustering algorithms have been shown effective to improve clustering process with even limited supervision. However, semi-supervised hierarchical clustering remains challenging due to the complexities of expressing constraints for agglomerative clustering algorithms. This paper proposes novel semi-supervised agglomerative clustering algorithms to build a hierarchy based on a known reference tree. We prove that by enforcing distance constraints defined by a reference tree during the process of hierarchical clustering, the resultant tree is guaranteed to be consistent with the reference tree. We also propose a framework that allows the hierarchical tree generation be aware of levels of levels of the agglomerative tree under creation, so that metric weights can be learned and adopted at each level in a recursive fashion. The experimental evaluation shows that the additional cost of our contraint-based semi-supervised hierarchical clustering algorithm (HAC) is negligible, and our combined semi-supervised HAC algorithm outperforms the state-of-the-art algorithms on real-world datasets. The experiments also show that our proposed methods can improve clustering performance even with a small number of unevenly distributed labeled data.

Keywords: semi-supervised clustering, hierarchical agglomerative clustering, reference trees, distance constraints

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182 Improving Early Detection, Diagnosis And Intervention For Children With Autism Spectrum Disorder: A Cross-sectional Survey In China

Authors: Yushen Dai, Tao Deng, Miaoying Chen, Baoqin Huang, Yan Ji, Yongshen Feng, Shaofei Liu, Dongmei Zhong, Tao Zhang, Lifeng Zhang

Abstract:

Background: Detection and diagnosis are prerequisites for early interventions in the care of children with Autism Spectrum Disorder (ASD). However, few studies have focused on this topic. Aim: This study aims to characterize the timing from symptom detection to intervention in children with ASD and to identify the potential predictors of early detection, diagnosis, and intervention. Methods and procedures: A cross-sectional survey was conducted with 314 parents of children with ASD in Guangzhou, China. Outcomes and Results: This study found that most children (76.24%) were diagnosed within one year after detection, and 25.8% of them did not receive the intervention after diagnosis. Predictors to ASD diagnosis included ASD-related symptoms identified at a younger age, more serious symptoms, and initial symptoms with abnormal development and sensory anomalies. ASD-related symptoms observed at an older age, initial symptoms with the social deficit, sensory anomalies, and without language impairment, parents as the primary caregivers, family with lower income and less social support utilization increased the odds of the time lag between detection and diagnosis. Children whose fathers had a lower level of education were less likely to receive the intervention. Conclusions and Implications: The study described the time for detection, diagnosis, and interventions of children with ASD. Findings suggest that the ASD-related symptoms, the timing at which symptoms first become a concern, primary caregivers’ roles, father’s educational level, and the family economic status should be considered when offering support to improve early detection, diagnosis, and intervention. Helping children and their families take full advantage of support is also important.

Keywords: autism spectrum disorder, child, detection, diagnosis, intervention, social support

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181 Investigation of Wood Chips as Internal Carbon Source Supporting Denitrification Process in Domestic Wastewater Treatment

Authors: Ruth Lorivi, Jianzheng Li, John J. Ambuchi, Kaiwen Deng

Abstract:

Nitrogen removal from wastewater is accomplished by nitrification and denitrification processes. Successful denitrification requires carbon, therefore, if placed after biochemical oxygen demand (BOD) and nitrification process, a carbon source has to be re-introduced into the water. To avoid adding a carbon source, denitrification is usually placed before BOD and nitrification processes. This process however involves recycling the nitrified effluent. In this study wood chips were used as internal carbon source which enabled placement of denitrification after BOD and nitrification process without effluent recycling. To investigate the efficiency of a wood packed aerobic-anaerobic baffled reactor on carbon and nutrients removal from domestic wastewater, a three compartment baffled reactor was presented. Each of the three compartments was packed with 329 g wood chips 1x1cm acting as an internal carbon source for denitrification. The proposed mode of operation was aerobic-anoxic-anaerobic (OAA) with no effluent recycling. The operating temperature, hydraulic retention time (HRT), dissolved oxygen (DO) and pH were 24 ± 2 , 24 h, less than 4 mg/L and 7 ± 1 respectively. The removal efficiencies of chemical oxygen demand (COD), ammonia nitrogen (NH4+-N) and total nitrogen (TN) attained was 99, 87 and 83% respectively. TN removal rate was limited by nitrification as 97% of ammonia converted into nitrate and nitrite was denitrified. These results show that application of wood chips in wastewater treatment processes is an efficient internal carbon source. 

Keywords: aerobic-anaerobic baffled reactor, denitrification, nitrification, wood chip

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180 Alternating Expectation-Maximization Algorithm for a Bilinear Model in Isoform Quantification from RNA-Seq Data

Authors: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu

Abstract:

Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.

Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq

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179 Laser Welding Technique Effect for Proton Exchange Membrane Fuel Cell Application

Authors: Chih-Chia Lin, Ching-Ying Huang, Cheng-Hong Liu, Wen-Lin Wang

Abstract:

A complete fuel cell stack comprises several single cells with end plates, bipolar plates, gaskets and membrane electrode assembly (MEA) components. Electrons generated from cells are conducted through bipolar plates. The amount of cells' components increases as the stack voltage increases, complicating the fuel cell assembly process and mass production. Stack assembly error influence cell performance. PEM fuel cell stack importing laser welding technique could eliminate transverse deformation between bipolar plates to promote stress uniformity of cell components as bipolar plates and MEA. Simultaneously, bipolar plates were melted together using laser welding to decrease interface resistance. A series of experiments as through-plan and in-plan resistance measurement test was conducted to observe the laser welding effect. The result showed that the through-plane resistance with laser welding was a drop of 97.5-97.6% when the contact pressure was about 1MPa to 3 MPa, and the in-plane resistance was not significantly different for laser welding.

Keywords: PEM fuel cell, laser welding, through-plan, in-plan, resistance

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178 Factors Influencing the Use Intention of Unmanned Retail Stores

Authors: Yen-Ting Chiu, Chia-Ying Lin, Pei-Hsuan Ho

Abstract:

New technologies can help solve the problem of labor shortage and the decline of birthrate. Technologies can improve human’s life and reduce the burden on the staff and bring convenience to people. That’s why unmanned retail store X-Store was established in Taiwan to create more valuable services and shopping experiences based on smart retailing. The purpose of this study is to examine the impact of unmanned stores, X-Store, on customers’ behavioral intentions. It uses the Unified theory of acceptance and use of technology (UTAUT) model as a basis and adds a perceived value factor to explain customer willingness to use the X-Store. In addition, the study further divided the sample into gender and age groups to compare behavioral differences between different groups. The study collected 214 valid questionnaires through online questionnaires. Using SPSS as a statistical analysis tool, the results of the study show that effort expectancy, social influence, facilitating conditions, and perceived value have a significant impact on behavioral intention to use X-Store. However, performance expectancy is not significant. This research concludes with managerial implications and suggestions for retail practitioners.

Keywords: perceived value, smart retailing, unmanned store, UTAUT, X-Store

Procedia PDF Downloads 51
177 An Internet of Things-Based Weight Monitoring System for Honey

Authors: Zheng-Yan Ruan, Chien-Hao Wang, Hong-Jen Lin, Chien-Peng Huang, Ying-Hao Chen, En-Cheng Yang, Chwan-Lu Tseng, Joe-Air Jiang

Abstract:

Bees play a vital role in pollination. This paper focuses on the weighing process of honey. Honey is usually stored at the comb in a hive. Bee farmers brush bees away from the comb and then collect honey, and the collected honey is weighed afterward. However, such a process brings strong negative influences on bees and even leads to the death of bees. This paper therefore presents an Internet of Things-based weight monitoring system which uses weight sensors to measure the weight of honey and simplifies the whole weighing procedure. To verify the system, the weight measured by the system is compared to the weight of standard weights used for calibration by employing a linear regression model. The R2 of the regression model is 0.9788, which suggests that the weighing system is highly reliable and is able to be applied to obtain actual weight of honey. In the future, the weight data of honey can be used to find the relationship between honey production and different ecological parameters, such as bees’ foraging behavior and weather conditions. It is expected that the findings can serve as critical information for honey production improvement.

Keywords: internet of things, weight, honey, bee

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176 One Dimensional Reactor Modeling for Methanol Steam Reforming to Hydrogen

Authors: Hongfang Ma, Mingchuan Zhou, Haitao Zhang, Weiyong Ying

Abstract:

One dimensional pseudo-homogenous modeling has been performed for methanol steam reforming reactor. The results show that the models can well predict the industrial data. The reactor had minimum temperature along axial because of endothermic reaction. Hydrogen productions and temperature profiles along axial were investigated regarding operation conditions such as inlet mass flow rate and mass fraction of methanol, inlet temperature of external thermal oil. Low inlet mass flow rate of methanol, low inlet temperature, and high mass fraction of methanol decreased minimum temperature along axial. Low inlet mass flow rate of methanol, high mass fraction of methanol, and high inlet temperature of thermal oil made cold point forward. Low mass fraction, high mass flow rate, and high inlet temperature of thermal oil increased hydrogen production. One dimensional models can be a guide for industrial operation.

Keywords: reactor, modeling, methanol, steam reforming

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175 A Particle Swarm Optimal Control Method for DC Motor by Considering Energy Consumption

Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu

Abstract:

In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.

Keywords: comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control

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174 Mitochondrial Energy Utilization is Unchanged with Age in the Trophocytes and Oenocytes of Queen Honeybees (Apis mellifera)

Authors: Chia-Ying Yen, Chin-Yuan Hsu

Abstract:

The lifespans of queen honeybees (Apis mellifera) are much longer than those of worker bees. The expression, concentration, and activity of mitochondrial energy-utilized molecules decreased with age in the trophocytes and oenocytes of worker bees, but they are unknown in queen bees. In this study, the expression, concentration, and activity of mitochondrial energy-utilized molecules were evaluated in the trophocytes and oenocytes of young and old queen bees by biochemical techniques. The results showed that mitochondrial density and mitochondrial membrane potential; nicotinamide adenine dinucleotide (NAD+), nicotinamide adenine dinucleotide reduced form (NADH), and adenosine triphosphate (ATP) levels; the NAD+/NADH ratio; and relative expression of NADH dehydrogenase 1 and ATP synthase normalized against mitochondrial density were not significantly different between young and old queen bees. These findings reveal that mitochondrial energy utilization maintains a young status in the trophocytes and oenocytes of old queen bees and that trophocytes and oenocytes have aging-delaying mechanisms and can be used to study cellular longevity.

Keywords: aging, longevity, mitochondrial energy, queen bees

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173 Photo-Enhanced Catalytic Dry Reforming of Methane on Ni@SiO2 with High Resistance to Carbon

Authors: Jinrui Zhang, Tianlong Yang, Ying Pan

Abstract:

Methane and carbon dioxide are major greenhouse gases contributor. CO₂ dry reforming of methane (DRM) for syngas production is a promising approach to reducing global CO₂ emission and extensive utilization of natural gas. However, the reported catalysts endured rapid deactivation due to severe carbon deposition at high temperature. Here, CO₂ reduction by CH4 on hexagonal nano-nickel flakes packed by porous SiO₂ (Ni@SiO₂) catalysts driven by thermal and solar light are tested. High resistance to carbon deposition and higher reactive activity are demonstrated under focused solar light at moderate temperature (400-500 ℃). Furthermore, the photocatalytic DRM under different wavelength is investigated, and even IR irradiation can enhance the catalytic activity. The mechanism of light-enhanced reaction reactivity and equilibrium is investigated by Infrared and Raman spectroscopy, and the unique reaction pathway with light is depicted. The photo-enhanced DRM provides a promising method of renewable solar energy conversion and CO₂ emission reduction due to the excellent activity and durability.

Keywords: CO₂ emission reduction, methane, photocatalytic DRM, resistance to carbon deposition, syngas

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172 Smart Product-Service System Innovation with User Experience: A Case Study of Chunmi

Authors: Ying Yu, Wen-Chi Kuo, Tung-Jung Sung

Abstract:

The Product-Service System (PSS) has received widespread attention due to the increasing global competition in manufacturing and service markets. Today’s smart products and services are driven by Internet of things (IoT) technologies which will promote the transformation from traditional PSS to smart PSS. Although the smart PSS has some of technological achievements in businesses, it often ignores the real demands of target users when using products and services. Therefore, designers should know and learn the User Experience (UX) of smart products, services and systems. However, both of academia and industry still lack relevant development experience of smart PSS since it is an emerging field. In doing so, this is a case study of Xiaomi’s Chunmi, the largest IoT platform in the world, and addresses the two major issues: (1) why Chunmi should develop smart PSS strategies with UX; and (2) how Chunmi could successfully implement the strategic objectives of smart PSS through the design. The case study results indicated that: (1) the smart PSS can distinguish competitors by their unique UX which is difficult to duplicate; (2) early user engagement is crucial for the success of smart PSS; and (3) interaction, expectation, and enjoyment can be treated as a three-dimensional evaluation of UX design for smart PSS innovation. In conclusion, the smart PSS can gain competitive advantages through good UX design in the market.

Keywords: design, smart PSS, user experience, user engagement

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171 Energy Efficient Resource Allocation and Scheduling in Cloud Computing Platform

Authors: Shuen-Tai Wang, Ying-Chuan Chen, Yu-Ching Lin

Abstract:

There has been renewal of interest in the relation between Green IT and cloud computing in recent years. Cloud computing has to be a highly elastic environment which provides stable services to users. The growing use of cloud computing facilities has caused marked energy consumption, putting negative pressure on electricity cost of computing center or data center. Each year more and more network devices, storages and computers are purchased and put to use, but it is not just the number of computers that is driving energy consumption upward. We could foresee that the power consumption of cloud computing facilities will double, triple, or even more in the next decade. This paper aims at resource allocation and scheduling technologies that are short of or have not well developed yet to reduce energy utilization in cloud computing platform. In particular, our approach relies on recalling services dynamically onto appropriate amount of the machines according to user’s requirement and temporarily shutting down the machines after finish in order to conserve energy. We present initial work on integration of resource and power management system that focuses on reducing power consumption such that they suffice for meeting the minimizing quality of service required by the cloud computing platform.

Keywords: cloud computing, energy utilization, power consumption, resource allocation

Procedia PDF Downloads 303