National Central University
  • Taoyuan City, Taiwan
Recent publications
Geophysical modelling performs to obtain subsurface structures in agreement with measured data. Freeware algorithms for geoelectrical data inversion have not been widely used in geophysical communities; however, different open-source modelling/inversion algorithms were developed in recent years. In this study, we review the structures and applications of openly Python-based inversion packages, such as pyGIMLi (Python Library for Inversion and Modelling in Geophysics), BERT (Boundless Electrical Resistivity Tomography), ResIPy (Resistivity and Induced Polarization with Python), pyres (Python wrapper for electrical resistivity modelling), and SimPEG (Simulation and Parameter Estimation in Geophysics). In addition, we examine the recovering ability of pyGIMLi, BERT, ResIPy, and SimPEG freeware through inversion of the same synthetic model forward responses. A versatile pyGIMLi freeware is highly suitable for various geophysical data inversion. The SimPEG framework is developed to allow the user to explore, experiment with, and iterate over multiple approaches to the inverse problem. In contrast, BERT, pyres , and ResIPy are exclusively designed for geoelectric data inversion. BERT and pyGIMLi codes can be easily modified for the intended applications. Both pyres and ResIPy use the same mesh designs and inversion algorithms, but pyres uses scripting language, while ResIPy uses a graphical user interface (GUI) that removes the need for text inputs. Our numerical modelling shows that all the tested inversion freeware could be effective for relatively larger targets. pyGIMLi and BERT could also obtain reasonable model resolutions and anomaly accuracies for small-sized subsurface structures. Based on the heterogeneous layered model and experimental target scenario results, the geoelectrical data inversion could be more effective in pyGIMLi, BERT, and SimPEG freeware packages. Moreover, this study can provide insight into implementing suitable inversion freeware for reproducible geophysical research, mainly for geoelectrical modelling.
CdIn 2 S 4 (CIS) has attracted widespread attention due to its structural stability and photoelectric properties, however, it is difficult to recycle when after usage. Carbon nanofibers (CNFs) as a suitable electron acceptor due to its stable physicochemical properties enhanced the mechanical properties and easily to recycle. There are also few reports on applying CIS/CNFs composite as photocatalyst in removing volatile organic compounds (VOCs). In this study, a novel CIS/CNFs composite was synthesized via a simple hydrothermal method. Various characterizations, such as X-ray diffraction, Scanning Electron Microscope, X-ray Photoelectron Spectroscopy and Transmission Electron Microscopy proved the successful synthesis of CIS/CNFs composite and revealed that CNFs grow on the surfaces of CIS connected with three-dimensional (3D) conductive network. Under visible light irradiation, degradation of toluene reached the optimal level of 86% as the CIS doped with 3% CNFs. Furthermore, 95% removal efficiency was achieved as 200 ppm ozone was added into the system and mineralization rate is also improved. The 3D network of CNFs can facilitate the effective separation and transfer of the photogenerated electron-hole pairs, protect CIS core from photo-corrosion and easily be recycled. Ultimately, plausible of ozone-enhanced photocatalytic mechanisms were proposed. Hence, this study presents a new photocatalyst with visible-light driven ozone-enhanced photocatalysis process toward VOCs.
Extensive research on the in-class synchronous learning aspect of the flipped classroom approach (FCA) has rendered favorable results the past decade. However, less attention has been placed on the out-of-class component of the FCA, specifically the drawbacks that may occur, such as low student accountability while watching the pre-assigned video lessons, thus coming to class unprepared, and not using the latest online technological to its full potential. This study addresses these issues by examining the impact of creating a more synchronous/collaborative online out-of-class flipped-class component. Using the latest online technology, a newly proposed flipped group (PFG) was created and then compared to a regular flipped group (RFG), and a traditional class (TC) over 14 weeks. Fifty-four undergraduate business students from a university in Taiwan participated in the study. Mock International English Language Testing System (IELTS) oral pre/post-tests were given to all participants to investigate which teaching approach is more effective. The results showed the PFG significantly improved overall on average, out-preforming the RFG. Surprisingly, the TC significantly performed better than the RFG. In addition, significant differences and correlations also occurred between the PFG and RFG students’ online learning behaviors and objective performances, such as the time spent online viewing the assigned video lessons and the effects on their quiz and final grade scores. This study’s findings support creating a more synchronous/collaborative online learning environment can enhance the out-of-class component of a FCA, and therefore help improve student’s overall oral/aural EFL learning.
This study investigates the impact of assimilating Formosat-7/COSMIC-II (FS7/C2) radio occultation (RO) refractivity data on predicting the heavy rainfall event that occurred in Taiwan on August 13, 2019. This event was characterized by heavy rainfall over the coastal region of central and southwestern Taiwan. Our investigation is performed using the Weather Research and Forecasting-Local Ensemble Transform Kalman Filter. Generally, assimilating the RO data increases the amount of moisture over the northern South China Sea (SCS) and the Pearl River area in southern China. It was expected that assimilating the RO data would improve low-level moisture analysis, given that more RO data are available for the lower atmosphere compared to those from Formosat-3/COSMIC-I. However, our results show that the experiment that does not include the RO data below 3 km facilitates better rainfall prediction over Taiwan in terms of the intensity and location of heavy rainfall. This heavy rainfall event can be attributed to moisture transport from the Pearl River area, where the RO data at the altitude of 3–5 km provide effective moisture enhancement to deepen the high-moisture layer. The experiment using the local spectral width (LSW) to conduct the quality control (QC) also helps improve rainfall prediction. However, such an LSW-based QC procedure tends to reject significant amounts of RO data 3 km above the land. Based on this case study, our results show that the QC procedure brings a larger impact to rainfall prediction than counterparts that adjust the observation error variance. A sophisticated QC procedure should be developed to optimize the impact of low-level RO data.
An earthquake swarm occurred in Haulien, Taiwan, from April 7 to August 31, 2021. The epicenters are in the range from 23°47′ N to 24°04′ N and from 121°25′ E to 121°42′ E. C q ( r ) and C q ( t ) are the generalized correlation integral of r and t , respectively. From the events with local magnitudes ≥ 3 and focal depths ≤ 25 km, C q ( r ) is calculated for the epicentral and hypocentral distribution (using the distance between two events, r ) and C q ( t ) for the time sequence (using the inter-event time between two events, t ). The multifractal dimension D q (q = 2, 3, …, 15) is the slope of the linear portion of the log–log plots of C q ( r ) versus r as well as C q ( t ) versus t . For the epicentral distribution, the linear pattern is in the range 0.5 ≤ log( r ) ≤ 1.3. The measured values of D q are all smaller than 2 that is the spatial dimension and monotonically decreases with increasing q . This indicates that the epicentral distribution of the swarm is multifractal. For the hypocentral distribution, a lack of a wide enough linear pattern on the log–log plot makes the hypocentral distribution be not multifractal. For the time sequence, the log–log plot of C q ( t ) versus t shows a linear pattern in the range 0.5 ≤ log( t ) ≤ 1.0. The values of D q are all smaller than 1 that is the time dimension and monotonically decreases with increasing q , thus suggesting multifractality of the time sequence when t is shorter than the maximum inter-event time.
FORMOSAT-3/COSMIC (F3/C) constellation of six micro-satellites was launched into the circular low-earth orbit at 800 km altitude with a 72-degree inclination angle on 15 April 2006, uniformly monitoring the ionosphere by the GPS (Global Positioning System) Radio Occultation (RO). Each F3/C satellite is equipped with a TIP (Tiny Ionospheric Photometer) observing 135.6 nm emissions and a TBB (Tri-Band Beacon) for conducting ionospheric tomography. More than 2000 RO profiles per day for the first time allows us globally studying three-dimensional ionospheric electron density structures and formation mechanisms of the equatorial ionization anomaly, middle-latitude trough, Weddell/Okhotsk Sea anomaly, etc. In addition, several new findings, such as plasma caves, plasma depletion bays, etc., have been reported. F3/C electron density profiles together with ground-based GPS total electron contents can be used to monitor, nowcast, and forecast ionospheric space weather. The S4 index of GPS signal scintillations recorded by F3/C is useful for ionospheric irregularities monitoring as well as for positioning, navigation, and communication applications. F3/C was officially decommissioned on 1 May 2020 and replaced by FORMOSAT-7/COSMIC-2 (F7/C2). F7/C2 constellation of six small satellites was launched into the circular low-Earth orbit at 550 km altitude with a 24-degree inclination angle on 25 June 2019. F7/C2 carries an advanced TGRS (Tri Gnss (global navigation satellite system) Radio occultation System) instrument, which tracks more than 4000 RO profiles per day. Each F7/C2 satellite also has a RFB (Radio Reference Beacon) on board for ionospheric tomography and an IVM (Ion Velocity Meter) for measuring ion temperature, velocity, and density. F7/C2 TGRS, IVM, and RFB shall continue to expand the F3/C success in the ionospheric space weather forecasting.
Six low Earth orbit (LEO) satellites were launched on June 25th, 2019 for a radio occultation (RO) mission for the FORMOSAT-7/COSMIC-2 (F7/C2) program. The GPS and GLONASS RO signals received by these F7/C2 satellites can be used to retrieve atmospheric and ionospheric parameter profiles for atmospheric and ionospheric research. In order to process the received RO signal, the processing system named Taiwan Radio Occultation Processing System (TROPS) is built. TROPS is developed by National Space Organization, Taiwan Analysis Center for COSMIC, and GPS Science and Application Research Center in Taiwan. The ionospheric products of TROPS are electron density profile, ionospheric scintillation index (S4 index), and absolute total electron content (TEC). S4 index has been calculated on board the satellites and other two products are retrieved by TROPS after the observation data downlink to ground. TEC is the linear integration of electron density along the signal propagation path. The electron density profile is retrieved from the relative TEC when the elevation angle of GNSS satellite is negative from F7/C2 satellite. The absolute TEC is the TEC from GNSS satellite to F7/C2 satellite. The difference between absolute and relative TEC is the TEC with/without differential code bias (DCB) correction. Currently, the data for the electron density profile and absolute TEC are provided by TROPS. Users can obtain the products freely from the internet. In this study, the retrieval method and the preliminary F7/C2 ionospheric TEC products retrieved by TROPS are presented in detail.
The opportunities and challenges of omnichannel in retail industry have been widely discussed, yet despite these benefits, the key elements that constitute an effective omnichannel and how customers respond to omnichannel retailing strategies remain unclear. This research conducted online surveys to test the effects of omnichannel elements on various brand experiences and customer retention, considering the moderating role of purchase behavior. The results indicate that omnichannel elements (integration, individualization, and interaction) are generally helpful in retaining customers, through omnichannel elements influence brand experiences differently. In addition, these omnichannel elements have different influences on customer retention due to different purchase behaviors. The findings suggest that retailers can use different omnichannel strategies to attract customers’ purchases and provide insights for practitioners who want to use omnichannel strategies to deliver superior experiences for customers.
This study aimed to develop a technique to chemically characterize odor issues in neighborhoods of designated industrial zones with pronounced emissions of volatile organic compounds (VOCs). Due to the elusive nature of odor plumes, speedy detection with sufficient sensitivity is required to capture the plumes. In this demonstration, proton-transfer-reaction mass spectrometry (PTR-MS) was used as the front-line detection tool in an industrial zone to guide sampling canisters for in-laboratory analysis of 106 VOCs by gas chromatography-mass spectrometry/flame ionization detector (GC-MS/FID). The fast but less accurate PTR-MS coupled with the slow but accurate GC-MS/FID method effectively eliminates the drawbacks of each instrument and fortifies the strength of both when combined. A 10-day PTR-MS field screening period was conducted to determine suitable trigger VOC species with exceedingly high mixing ratios that were likely the culprits of foul odors. Twenty canister samples were then collected, triggered by m/z 43, 61 (ethyl acetate, fragments, EA), m/z 73 (methyl ethyl ketone, MEK), or m/z 88 (morpholine) in all cases. Internal consistency was confirmed by the high correlation of critical species in the PTR-MS and trigger samples. Several long-lived halocarbons were exploited as the intrinsic internal reference for quality assurance. Oxygenated VOCs (OVOCs) accounted for 15%–75% of the total VOC mixing ratios in the triggered samples. However, EA and MEK, the most prominent OVOC species, did not appear to have common sources with morpholine, which presented with PTR-MS peaks incoherent with the other OVOCs. Nevertheless, these distinctive OVOC plumes were consistent with the multiple types of odor reported by the local residents. In contrast with the triggered sampling, random samples in the same industrial zone and roadside samples in a major metropolitan area were collected. The pronounced OVOC content in the triggered samples highlighted the advantage over random grab sampling to address odor issues.
A new innovative approach is essential for early and effective diagnosis of gastric cancer, using promoter hypermethylation of the tumor suppressor, SOCS-1, that is frequently inactivated in human cancers. We have developed an amplification-free fiber optic nanoplasmonic biosensor for detecting DNA methylation of the SOCS-1 human genome. The method is based on the fiber optic nanogold-linked sorbent assay of PCR-free DNA from human gastric tumor tissue and cell lines. We designed a specific DNA probe fabricated on the fiber core surface while the other probe is bioconjugated with gold nanoparticles in free form to allow percentage determination and differentiating the methylated and unmethylated cell lines, further demonstrating the SOCS-1 methylation occurs in cancer patients but not in normal cell lines. The observed detection limit is 0.81 fM for methylated DNA, and the detection time is within 15 min. In addition, our data were significantly correlated to the data obtained from PCR-based pyrosequencing, and yet with superior accuracy. Hence our results provide new insight to the quantitative evaluation of methylation status of the human genome and can act as an alternative to PCR with a great potential.
In recent years, building information modeling and artificial intelligence of things (BIM-AIOTs) in the construction industry have gained much attention. Construction engineers and researchers learn about BIM-AIOT and increase their professional knowledge through internet searches. However, the large amount of information on the internet makes it difficult to find specific information. Although some previous work of BIM-related searches exists, most still search with a combination of keywords or longer terms. This paper utilizes a machine learning model with natural language processing (NLP) technique of bidirectional encoder representations from transformers (BERT) integrated with a mobile chatbot as a question and answer (QnA) system. The dataset used for modeling contained 3334 text paragraphs that shortened to 10,002 questions. The result shows an F1 score of around 65% accuracy, which is acceptable for model prediction. Then, the system verifies to synchronize to the server and user interface. The system works well for information search and offers a supporting automation information system in the construction industry. This study achieved conversational machine understanding and a user-friendly BIM-AIOT integration information searches platform. The proposed system has a reliable research-based information source. It is verified as an effective and efficient way to produce fast decision-making. The system is deemed a future application for research-based problem-solving solutions in Architecture, Engineering, and Construction (AEC).
We report on the improved electrochemical performance of a high-voltage LiNi0.5Mn1.5O4 (LNMO) cathode using surface-modified carbon blacks (CBs) as conductive agents. Facile modifications of CBs were achieved using thermal, urea-based hydrothermal, and acid oxidation treatments. The material properties of the modified CBs, LNMO-based electrode surface, and electrolyte compositions were investigated and correlated. Based on the distribution of the decomposition deposits on the surface of the electrode, it is confirmed that CB, rather than the LNMO active material, dominates the electrolyte decomposition site at a high voltage, owing to its relatively high surface area for the reaction. Additionally, compared with the pristine CB, the hydrothermally treated N-doped CB (HCB) improves the electrochemical performance of the LNMO cathode, although the thermally treated sample exhibits the most adverse influence, followed by the oxidized one. The LNMO/HCB cathode attains optimum capacity retention (approximately 95%) for 100 cycles (1 C) and a high rate capability (70%, 5 C/0.2 C), corresponding to a lowered resistance at the cathode–electrolyte interface. Furthermore, HCB with a limited specific surface area and increased defects, as well as additional pyrrolic-N and pyridinic-N groups, substantially reduces the decomposition deposits on the surface of the electrode and the decomposition products in the electrolyte. These phenomena account for the improved electrochemical performance of the LNMO/HCB cathode.
Direct deposition of high-quality Ge film on Si substrate suitable for fabricating Ge/Si photodiodes was achieved by using plasma-enhanced chemical vapor deposition (PECVD) with GeCl4/H2 as precursors. A tensile-strained, impurity-free, monocrystalline Ge film with a surface roughness of < 1 nm and a threading-dislocation density on the order of 10⁴ cm⁻² could be grown at a rate of ca. 80 nm/min at a substrate temperature of 450 °C directly without the need of any kind of buffer layer or post-annealing. When applied to fabricate near-infrared (NIR) photodiodes, a low dark current density and a reasonably good responsivity for the employed photodiode architecture were attained, revealing the potential of this low-temperature fabrication method in monolithic integration of optoelectronic components with Si-based electronic circuits. The success of this technique may be attributed to an atomic-layer-deposition-like process for both nucleation and growth.
Background Corrosives substance in polluted air causes severe reliability issues for electronic devices. One of the critical purposes of a surface finishing layer on a printed circuit board is to increase the corrosion resistance of the conductive Cu layers. However, the currently available technologies for consumer products have difficulties meeting these requirements. Methods In this study, ultra-thin single layer Co, multilayer Co/Pd, and Co/Pd/Au are used to investigate the ability of corrosion resistance. The concentrations of the corrosive SO2 gas used higher than those of the conventional methodology (in ppb level) to intentionally from corrosion products that are sufficiently large for meaningful composition analyses. Significant findings The results show that a 200 nm Co, 200 nm Co/100 nm Pd, and 200 nm Co/100 nm Pd/100 nm Au can sustain a corrosive ambient environment with 150 ppm SO2. In an extremely high concentration of 1500 ppm SO2, the surface finishing layers failed to protect the Cu beneath. The failure analysis provides an understanding of the relationship between the microstructure and the atomic diffusion path. The corrosion mechanism is confirmed by electrochemical measurements. This study clearly confirms that Co is a promising alternative anti-corrosive material for the surface finishing layer of high-reliability devices.
Plain Language Summary As we drop a stone into the still water, the water piles up around the rock and induces ripples in the form of concentric circles that expand and travel away from the center point. A similar phenomenon happened in the atmosphere after the eruption of the Tonga underwater volcano (20.53°S, 175.38°W) at ∼04:15 UT on 15 January 2022. The Earth's atmosphere is a pond of air. The explosive eruption triggered prosperous waves, which is similar to dropping a stone into water. The waves, ripples, and disturbances in different spheres are fantastic due to the eruption (Figure S8 in Supporting Information S1). Besides the tsunamis, atmospheric concentric ripples, and ionospheric traveling disturbances, this study for the first time showed that the blast wave due to the eruption changed the dynamics of the ionosphere or thermosphere (upper atmosphere). It is well known that a significant volcanic eruption can release tremendous ashes and gases into the troposphere and stratosphere (lower atmosphere), which change the chemical and dynamic process there. The observations in this study surprisingly show that the eruption changed the dynamics of the upper atmosphere, where the volcanic cloud cannot reach.
The Tonga volcano eruption of 15 January 2022 unleashed a variety of atmospheric perturbations, coinciding with the recovery‐phase of a geomagnetic storm. The ensuing thermospheric variations created rare display of extreme poleward‐expanding conjugate plasma bubbles seen in the rate of total electron content index over 100–150°E, reaching ∼40°N geographic latitude. This is associated with fluctuations in FORMOSAT‐7/COSMIC‐2 (F7/C2) ion‐density measurements and spread‐F in ionograms. Preceding to this, an unusually strong pre‐reversal enhancement (PRE) occurred in the global ionospheric specification (GIS) electron density profiles derived from F7/C2 observations. The GIS also revealed a decrease of equatorial ionization anomaly (EIA) crest density due to the storm impact. Reduced E‐region conductivity by volcano‐induced waves and enhanced F‐region wind, further accelerated by reduced ion‐drag over the EIA, apparently intensified the PRE. Accompanied with the strong PRE, volcano‐induced seed perturbations triggered the super plasma bubble activity.
Continental outflows from peninsular Southeast Asia and East Asia dominate the widespread dispersal of air pollutants over subtropical western North Pacific during spring and autumn, respectively. This study analyses the chemical composition and optical properties of PM10 aerosols during autumn and spring at a representative high-altitude site, viz., Lulin Atmospheric Background Station (23.47°N, 120.87°E; 2862 m a.s.l.), Taiwan. PM10 mass was reconstructed and the contributions of major chemical components were also delineated. Aerosol scattering (σsp) and absorption (σap) coefficients were regressed on mass densities of major chemical components by assuming external mixing between them, and the site-specific mass scattering efficiency (MSE) and mass absorption efficiency (MAE) of individual components for dry conditions were determined. NH4NO3 exhibited the highest MSE among all components during both seasons (8.40 and 12.58 m² g⁻¹ at 550 nm in autumn and spring, respectively). (NH4)2SO4 and organic matter (OM) accounted for the highest σsp during autumn (51%) and spring (50%), respectively. Mean MAE (mean contribution to σap) of elemental carbon (EC) at 550 nm was 2.51 m² g⁻¹ (36%) and 7.30 m² g⁻¹ (61%) in autumn and spring, respectively. Likewise, the mean MAE (mean contribution to σap) of organic carbon (OC) at 550 nm was 0.84 m² g⁻¹ (64%) and 0.83 m² g⁻¹ (39%) in autumn and spring, respectively. However, a classification matrix, based on scattering Ångström exponent, absorption Ångström exponent, and single scattering albedo (ω), demonstrated that the composite absorbing aerosols were EC-dominated (with weak absorption; ω = 0.91–0.95) in autumn and a combination of EC-dominated and EC/OC mixture (with moderate absorption; ω = 0.85–0.92) in spring. This study demonstrates a strong link between chemical composition and optical properties of aerosol and provides essential information for model simulations to assess the imbalance in regional radiation budget with better accuracy over the western North Pacific.
This study highlighted the importance of software process tailoring (SPT) in modern software projects characterized by dynamic and evolutionary development. SPT is a collaborative practice, and the existing literature has focused on team-based knowledge aspects in performing SPT, whereas the quality of team interactions has rarely been discussed to address its conflictual nature. This study examined the teamwork quality (TWQ) framework with two team behavioral factors, namely team reflexivity and member autonomy, and developed a research model to explore how TWQ fits in the SPT’s conflicting context and how autonomy and reflexivity affect TWQ to promote SPT. The results showed that TWQ is essential for dealing with challenging tasks in SPT. The results also supported the evidence that reflexivity positively affects TWQ while member autonomy harms TWQ. When examining the mediating effect to see how TWQ operationalizes as an intermediate in the relationship between the two factors and SPT performance, this study found that reflexivity directly and indirectly boosts SPT performance. Member autonomy and SPT performance are independent when TWQ is the mediator. However, without TWQ, member autonomy negatively impacts SPT effectiveness and efficiency.
In this study, the characteristics of a strain wave gear (SWG) with a double-circular-arc with a common tangent (DCACT) profile were simulated using two-dimensional (2D) and three-dimensional (3D) finite element analysis (FEA). First, theoretically generated tooth profiles for the flexible spline (FS) and circular spline (CS) of an SWG were developed according to the theory of gearing. An automated mesh-generating computer program was developed in Visual C++ to establish 2D and 3D finite element models of the SWG based on its derived geometry. An FEA was then performed to explore the meshing characteristics, including the stress distribution, torsional angle, torsional stiffness, and number of engaged teeth, of the SWG. Continuous meshing of multiple tooth pairs between the FS and CS from the 2D FEA verified the conjugation of tooth profiles. The coning effect on the FS during assembly of the SWG was also predicted and discussed from the 3D FEA results. The 3D FEA produced more accurate and practical results than the 2D FEA did. Additionally, 3D FEAs of a modified (with longitudinal crowning) and unmodified (without longitudinal crowning) FS were performed and compared. Finally, a 3D FEA of a modified FS was successfully conducted to predict cyclic contact stress, root stress, and transmission error.
Given the huge demand for wire in today’s society, the quality of the wire is especially required. To control the quality of the produced wire, the industry has a great desire for automated optical inspection technology. This technology is a high-speed and highly accurate optical image inspection system that uses mechanical sensing equipment to replace the human eye as the inspection method and simulates manual operation by means of a robotic arm. In this paper, a high-performance algorithm for the automated optical inspection of wire color sequence is proposed. This paper focuses on the design of a high-speed wire color sequence detection that can automatically adapt to different kinds of wires and recognition situations, such as a single wire with only one color, and one or two wires covered with aluminum foil. To be further able to successfully inspect even if the wire is short in the screen and the two wires are close to each other, we calculate the horizontal gradient of the wires by edge detection and morphological calculation and identify the types and color sequences of the wires in the screen by a series of discriminative mechanisms. Experimental results show that this method can achieve good accuracy while maintaining a good computation speed.
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Wen-June Wang
  • Department of Electrical Engineering
Anthony Shiaw-Tseh Chiang
  • Department of Chemical & Materials Engineering
Chia Chu
  • Department of Civil Engineering
Yi-Hung Liu
  • Department of Chemical & Materials Engineering
Wen-Yih Chen
  • Department of Chemical & Materials Engineering
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Taoyuan City, Taiwan