National Kaohsiung First University of Science and Technology

This paper describes a structured attempt to integrate flip teaching into language classrooms using a WebQuest active learning strategy. The purpose of this study is to examine the possible impacts of flipping the classroom on English language learners’ academic performance, learning attitudes, and participation levels. Adopting a quasi-experimental design, three different formats for flip teaching were developed in this study. The results indicate that the structured and semi-structured flip lessons were more effective instructional designs than the non-flip lessons. With a varying extent, both the structured and semi-structured flip lessons helped the students attain better learning outcomes, develop better attitudes toward their learning experiences, and devote more effort in the learning process. Given the positive results, this paper concludes with a call for more research into this promising pedagogy to contribute to its knowledge base across disciplines.

The conversion of organics in wastewaters into hydrogen gas could serve the dual role of renewable energy production and waste reduction. The chemical energy in a sucrose rich synthetic wastewater was recovered as hydrogen gas in this study. Using fractional factorial design batch experiments, the effect of varying pH (4.5-7.5) and substrate concentration (1.5-44.8 g COD/L) and their interaction on hydrogen gas production were tested. Mixed bacterial cultures obtained from a compost pile, a potato field, and a soybean field were heated to inhibit hydrogen-consuming methanogens and to enrich sporeforming, hydrogen-producing acidogens. It was determined that the highest rate (74.7 mL H2/(L*h)) of hydrogen production occurred at a pH of 5.5 and a substrate concentration of 7.5 g COD/Lwith a conversion efficiency of 38.9 mL H2/(g COD/L). The highest conversion efficiency was 46.6 mL H2/(g COD/L).

Family influence is central in Asian countries; however, little research exists regarding the effects of family ownership and corporate governance on corporate investment decisions. This article examines the relationships among family ownership, board independence, and R&D investment using a sampling of Taiwanese firms. The finding of the negative family ownership—R&D investment relationship suggests that family ownership may discourage risky long-term R&D investment. Such a finding may also suggest that firms with high family ownership may use R&D investment more efficiently and thus need less R&D in relation to firms with low family ownership. In addition, the interaction of family ownership and CEO duality/independent director ratio is negatively/positively related to R&D investment, suggesting that firms with high family ownership may increase R&D investment when the CEO—chair roles are separated or when more independent outsiders are included in the board.

In this paper, a hybrid Taguchi-genetic algorithm (HTGA) is proposed to solve global numerical optimization problems with continuous variables. The HTGA combines the traditional genetic algorithm (TGA), which has a powerful global exploration capability, with the Taguchi method, which can exploit the optimum offspring. The Taguchi method is inserted between crossover and mutation operations of a TGA. Then, the systematic reasoning ability of the Taguchi method is incorporated in the crossover operations to select the better genes to achieve crossover, and consequently, enhance the genetic algorithm. Therefore, the HTGA can be more robust, statistically sound, and quickly convergent. The proposed HTGA is effectively applied to solve 15 benchmark problems of global optimization with 30 or 100 dimensions and very large numbers of local minima. The computational experiments show that the proposed HTGA not only can find optimal or close-to-optimal solutions but also can obtain both better and more robust results than the existing algorithm reported recently in the literature.

Consumer habit, an important key to repetitive consumption, is an interesting yet puzzling phenomenon. Sometimes this consumption becomes obsessive--consumers will continue to act a certain way even when they feel it is not in their best interests. However, not all consumers develop such addictions. This study uses cyber-game addiction syndrome as an analogue to trace the possible causes of consumer addiction. Results from structure equation modeling show that repetition of favorite activities has a moderate effect upon addiction, which is in line with the assertion of rational addiction theory. However, flow experience--the emotional state embracing perceptional distortion and enjoyment--shows a much stronger impact on addiction. This suggests that consumers who have experienced flow are more likely to be addicted.

The pH and hydraulic retention time (HRT) of a chemostat reactor were varied according to a central composite design methodology with the aim of modeling and optimizing the conversion of starch into hydrogen by microorganisms in an anaerobic digested sludge. Experimental results from 23 runs indicate that a maximum hydrogen production rate of 1600 L/m(3)/d under the organic loading rate of 6 kg starch m(3)/d obtained at pH = 5.2 and HRT = 17 h. Throughout this study, the hydrogen percentage in the biogas was approximately 60% and no methanogenesis was observed. while the reactor was operated with HRT of 17 h, hydrogen was produced within a pH range between 4.7 and 5.7. Alcohol production rate was greater than hydrogen production rate if the pH was lower than 4.3 or higher than 6.1. Supplementary experiments confirm that the optimum conditions evaluated in this study were highly reliable; while a hydrogen production yield of 1.29 l H(2)/g starch-COD was obtained. An examination of the response surfaces, including hydrogen, volatile fatty acids (VFA) and alcohols production, led us to the belief that clostridium sp. predominated in the anaerobic hydrogen-producing microorganisms in this study. Experiment results obtained emphasize that the response of metabolites was a more useful indicator than hydrogenic activity for obtaining efficient hydrogen production. Furthermore, expressions of contour plots indicate that Response-Surface Methodology may provide easily interpretable advice on the operation of a hydrogen-producing bioprocess.

This study explored how social networking technology can be used to supplement face-to-face courses as a means of enhancing students' sense of community and, thus, to promote classroom communities of practice in the context of higher education. Data were collected from 67 students who enrolled in four face-to-face courses at two public universities in Taiwan. Findings indicated that the majority of participants developed strong feelings of social connectedness and expressed favorable feelings regarding their learning experiences in the classes where social networking sites were used as a supplementary tool. Learner difficulties and concerns of instructors about the educational use of social media are addressed with recommendations for future research and practice.

Abstract Web‐based technology has a dramatic impact on learning and teaching. A framework that delineates the relationships between learner control and learning effectiveness is absent. This study aims to fill this void. Our work focuses on the effectiveness of a technology‐mediated virtual learning environment (TVLE) in the context of basic information technology skills training. Grounded in the technology‐mediated learning literature, this study presents a framework that addresses the relationship between the learner control and learning effectiveness, which contains four categories: learning achievement, self‐efficacy, satisfaction, and learning climate. In order to compare the learning effectiveness under traditional classroom and TVLE, we conducted a field experiment. Data were collected from a junior high school of Taiwan. A total of 210 usable responses were analysed. We identified four results from this study. (1) Students in the TVLE environment achieve better learning performance than their counterparts in the traditional environment; (2) Students in the TVLE environment report higher levels of computer self‐efficacy than their counterparts in the traditional environment; (3) Students in the TVLE environment report higher levels of satisfaction than students in the traditional environment; and (4) Students in the TVLE environment report higher levels of learning climate than their counterparts in the traditional environment. The implications of this study are discussed, and further research directions are proposed.

Anthropogenic climate change, principally induced by the large volume of carbon dioxide emission from the global economy driven by fossil fuels, has been observed and scientifically proven as a major threat to civilization. Meanwhile, fossil fuel depletion has been identified as a future challenge. Lignocellulosic biomass in the form of organic residues appears to be the most promising option as renewable feedstock for the generation of energy and platform chemicals. As of today, relatively little bioenergy comes from lignocellulosic biomass as compared to feedstock such as starch and sugarcane, primarily due to high cost of production involving pretreatment steps required to fragment biomass components via disruption of the natural recalcitrant structure of these rigid polymers; low efficiency of enzymatic hydrolysis of refractory feedstock presents a major challenge. The valorization of lignin and cellulose into energy products or chemical products is contingent on the effectiveness of selective depolymerization of the pretreatment regime which typically involve harsh pyrolytic and solvothermal processes assisted by corrosive acids or alkaline reagents. These unselective methods decompose lignin into many products that may not be energetically or chemically valuable, or even biologically inhibitory. Exploring milder, selective and greener processes, therefore, has become a critical subject of study for the valorization of these materials in the last decade. Efficient alternative activation processes such as microwave- and ultrasound irradiation are being explored as replacements for pyrolysis and hydrothermolysis, while milder options such as advanced oxidative and catalytic processes should be considered as choices to harsher acid and alkaline processes. Herein, we critically abridge the research on chemical oxidative techniques for the pretreatment of lignocellulosics with the explicit aim to rationalize the objectives of the biomass pretreatment step and the problems associated with the conventional processes. The mechanisms of reaction pathways, selectivity and efficiency of end-products obtained using greener processes such as ozonolysis, photocatalysis, oxidative catalysis, electrochemical oxidation, and Fenton or Fenton-like reactions, as applied to depolymerization of lignocellulosic biomass are summarized with deliberation on future prospects of biorefineries with greener pretreatment processes in the context of the life cycle assessment.

A novel high step-up converter, which is suitable for renewable energy system, is proposed in this paper. Through a voltage multiplier module composed of switched capacitors and coupled inductors, a conventional interleaved boost converter obtains high step-up gain without operating at extreme duty ratio. The configuration of the proposed converter not only reduces the current stress but also constrains the input current ripple, which decreases the conduction losses and lengthens the lifetime of the input source. In addition, due to the lossless passive clamp performance, leakage energy is recycled to the output terminal. Hence, large voltage spikes across the main switches are alleviated, and the efficiency is improved. Even the low voltage stress makes the low-voltage-rated MOSFETs be adopted for reductions of conduction losses and cost. Finally, the prototype circuit with 40-V input voltage, 380-V output, and 1000-W output power is operated to verify its performance. The highest efficiency is 97.1%.

As with any other information system (IS), the success of online shopping depends largely on customer satisfaction and other factors that will eventually increase customers' loyalty intentions. This article integrates two major variables of technology acceptance model (TAM), trust, and fairness to construct a model for investigating the motivations behind customers' loyalty intentions towards online shopping. The hypothesised model is validated empirically using data collected from 311 customers of an online shopping store. The results indicated that distributive, procedural and interactional fairness were strong predictors of trust, which in turn influenced satisfaction. Distributive fairness and interactional fairness exhibited significant positive effects on satisfaction. Perceived usefulness and satisfaction influenced loyalty intention towards online shopping. Perceived ease of use acts indirectly on loyalty intention through the mediating effect of perceived usefulness. Implications for theory and practice and future research directions are discussed.

Two types of Class F fly ash with 4.6% and 7.8% loss on ignition were used for an experimental investigation dealing with concrete incorporating very high volumes of Class F fly ash (HVFA). A rational mix design method was developed for concrete with 20–80% fly ash replacement for cement. Tests were performed for fresh and hardened concrete properties. Test results indicated that the setting times and the air content of fly-ash concrete increased as the fly ash replacement level increased. The compressive and flexural strength of the HVFA concrete mixtures demonstrated continuous and significant improvement at late ages of 91 and 365 days. Relation was formulated for flexural and compressive strength for all grades of HVFA concrete. The concrete mixture containing low-LOI fly ash exhibited superior mechanical properties than those of the corresponding mixture containing high-LOI fly ash. These results confirm the feasibility that up to 80% of Class F fly ash can be suitably used as cement replacement in concrete by using a rational mixture proportions.

In this paper, a hybrid Taguchi-genetic algorithm (HTGA) is applied to solve the problem of tuning both network structure and parameters of a feedforward neural network. The HTGA approach is a method of combining the traditional genetic algorithm (TGA), which has a powerful global exploration capability, with the Taguchi method, which can exploit the optimum offspring. The Taguchi method is inserted between crossover and mutation operations of a TGA. Then, the systematic reasoning ability of the Taguchi method is incorporated in the crossover operations to select the better genes to achieve crossover, and consequently enhance the genetic algorithms. Therefore, the HTGA approach can be more robust, statistically sound, and quickly convergent. First, the authors evaluate the performance of the presented HTGA approach by studying some global numerical optimization problems. Then, the presented HTGA approach is effectively applied to solve three examples on forecasting the sunspot numbers, tuning the associative memory, and solving the XOR problem. The numbers of hidden nodes and the links of the feedforward neural network are chosen by increasing them from small numbers until the learning performance is good enough. As a result, a partially connected feedforward neural network can be obtained after tuning. This implies that the cost of implementation of the neural network can be reduced. In these studied problems of tuning both network structure and parameters of a feedforward neural network, there are many parameters and numerous local optima so that these studied problems are challenging enough for evaluating the performances of any proposed GA-based approaches. The computational experiments show that the presented HTGA approach can obtain better results than the existing method reported recently in the literature.

This article applies the dynamic conditional correlation model of Engle (2002 Engle, RF. 2002. Dynamic conditional correlation: a simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20: 339–50. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) with error correction terms in order to investigate the optimal hedge ratios of British and Japanese currency futures markets. For a comparison, the estimates of three other models -- traditional generalized autoregressive conditional heteroskedasticity (GARCH), ordinary least square (OLS) and error correction model (ECM) -- are also reported. Results show that the dynamic conditional correlation model yields the best hedging performance in both futures markets. Nonetheless, the traditional multivariate GARCH model (which exhibits constant conditional correlations and time-varying hedge ratios) performs the worst hedging effectiveness, even inferior to the time-invariant hedging methods (OLS and ECM). The inclusion of dynamic conditional correlations in the GARCH model can therefore better capture the frequent fluctuations in futures markets.

The continuous fractional Fourier transform (FRFT) performs a spectrum rotation of signal in the time-frequency plane, and it becomes an important tool for time-varying signal analysis. A discrete fractional Fourier transform has been developed by Santhanam and McClellan (see ibid., vol.42, p.994-98, 1996) but its results do not match those of the corresponding continuous fractional Fourier transforms. We propose a new discrete fractional Fourier transform (DFRFT). The new DFRFT has DFT Hermite eigenvectors and retains the eigenvalue-eigenfunction relation as a continous FRFT. To obtain DFT Hermite eigenvectors, two orthogonal projection methods are introduced. Thus, the new DFRFT will provide similar transform and rotational properties as those of continuous fractional Fourier transforms. Moreover, the relationship between FRFT and the proposed DFRFT has been established in the same way as the conventional DFT-to-continuous-Fourier transform.

Sixteen batch experiments were performed to evaluate the stability, kinetics, and metabolic paths of heat-shocked digester (HSD) sludge that transforms microcrystalline cellulose into hydrogen. Highly reproducible kinetic and metabolic data confirmed that HSD sludge could stably convert microcrystalline cellulose to hydrogen and volatile fatty acids (VFA) and induce metabolic shift to produce alcohols. We concluded that clostridia predominated the hydrogen-producing bacteria in the HSD sludge. Throughout this study the hydrogen percentage in the headspace of the digesters was greater than 50% and no methanogenesis was observed. The results emphasize that hydrogen significantly inhibited the hydrogen-producing activity of sludge when initial microcrystalline cellulose concentrations exceeded 25.0 g/L. A further 25 batch experiments performed with full factorial design incorporating multivariate analysis suggested that the ability of the sludge to convert cellulose into hydrogen was influenced mainly by the ratio of initial cellulose concentration (So) to initial sludge density (Xo), but not by interaction between the variables. The hydrogen-producing activity depended highly on interaction of So x (So/Xo). Through response surface analysis it was found that a maximum hydrogen yield of 3.2 mmol/g cellulose occurred at So = 40 g/L and So/Xo = 8 g cellulose/g VSS. A high specific rate of 18 mmol/(g VSS-d) occurred at So = 28 g/L and So/Xo = 9 g cellulose/g VSS. These experimental results suggest that high hydrogen generation from cellulose was accompanied by low So/Xo.

Automated writing evaluation (AWE) software is designed to provide instant computergenerated scores for a submitted essay along with diagnostic feedback.Most studies on AWE have been conducted on psychometric evaluations of its validity; however, studies on how effectively AWE is used in writing classes as a pedagogical tool are limited.This study employs a naturalistic classroom-based approach to explore the interaction between how an AWE program, MY Access!, was implemented in three different ways in three EFL college writing classes in Taiwan and how students perceived its effectiveness in improving writing.The findings show that, although the implementation of AWE was not in general perceived very positively by the three classes, it was perceived comparatively more favorably when the program was used to facilitate students' early drafting and revising process, followed by human feedback from both the teacher and peers during the later process.This study also reveals that the autonomous use of AWE as a surrogate writing coach with minimal human facilitation caused frustration to students and limited their learning of writing.In addition, teachers' attitudes toward AWE use and their technology-use skills, as well as students' learner characteristics and goals for learning to write, may also play vital roles in determining the effectiveness of AWE.With limitations inherent in the design of AWE technology, language teachers need to be more critically aware that the implementation of AWE requires well thought-out pedagogical designs and thorough considerations for its relevance to the objectives of the learning of writing.

A novel high step-up converter is proposed for a front-end photovoltaic system. Through a voltage multiplier module, an asymmetrical interleaved high step-up converter obtains high step-up gain without operating at an extreme duty ratio. The voltage multiplier module is composed of a conventional boost converter and coupled inductors. An extra conventional boost converter is integrated into the first phase to achieve a considerably higher voltage conversion ratio. The two-phase configuration not only reduces the current stress through each power switch, but also constrains the input current ripple, which decreases the conduction losses of metal-oxide-semiconductor field-effect transistors (MOSFETs). In addition, the proposed converter functions as an active clamp circuit, which alleviates large voltage spikes across the power switches. Thus, the low-voltage-rated MOSFETs can be adopted for reductions of conduction losses and cost. Efficiency improves because the energy stored in leakage inductances is recycled to the output terminal. Finally, the prototype circuit with a 40-V input voltage, 380-V output, and 1000- W output power is operated to verify its performance. The highest efficiency is 96.8%.

Purpose The purpose of this paper is to examine the effects of interactive and social features on users' online experiences and their purchase intention of virtual goods from a social network site. Design/methodology/approach A banner with a hyperlink that connected to the author's web survey was posted on the homepage of Facebook. Of the 258 responses returned, 176 were fully completed. Measurement items were adapted from previous literature. Structural equation modeling (SEM) was used to evaluate the research model and hypotheses testing. Findings The results of an empirical study supported the use of the stimuli‐organism‐response (S‐O‐R) model in a social networking site and showed how environmental features should be incorporated to enhance users' online experiences and purchase intentions. Specifically, social identity showed the strongest influence on involvement and flow. More specifically, affective involvement showed the greatest influence on purchase intention compared to flow and cognitive involvement. Practical implications The relative importance of both interactivity and social identity in platform features in shaping consumers' online experiences should not be ignored. The author suggests online games or apps. Additionally, platform providers should advance social identity features that show a strong positive impact on users' online experiences. Originality/value With the proliferation of online social gaming, there is growing evidence for virtual goods consumption; however, relatively few studies have discussed this phenomenon. This paper draws on hypotheses from environmental psychology; specifically, users' intentions to purchase are modeled on user responses to the online stimuli of a Web platform and the online experience that such an environment elicits.

Purpose – The purpose of this paper is to provide a better picture of factors influencing behavioral decisions in online shopping by identifying different targets of trust and discussing their antecedents and outcomes. Design/methodology/approach – Online survey data from 242 ihergo members were used to test the proposed model, and structural equation modeling with partial least squares was performed to analyze the measurement and structural models. Findings – The findings show that the four types of trust identified in this study are critical determinants of perceived risk and attitude. In addition, the majority of the antecedents are found to be associated with their respective types of trust. Research limitations/implications – The research extends the theory of reasoned action and prior research to discuss four types of consumer trust, as well as their respective antecedents and subsequent consequences. The result is a more descriptive model that better explicates consumers’ decision-making processes in online shopping. Practical implications – Given the intense competition between online shopping sites, web site managers should strive to provide a safe and user-friendly shopping environment. In addition, the vendor can enhance trust by encouraging satisfied customers to provide positive endorsements. Originality/value – This study is possibly the first of its kind, in identifying the four types of trust and their respective antecedents in the context of an online group-buying auction, and thus serves to enrich the existing literature concerning trust-building factors.