Showing papers in "Journal of Convergence Information Technology in 2013"
TL;DR: A perfect combination of cloud computing and internet of things can promote fast development of agricultural modernization, realize smart agriculture and effectively solve the issues concerning agriculture, countryside and farmers.
Abstract: Issues concerning agriculture, countryside and farmers have been always hindering China’s development. The only solution to these three problems is agricultural modernization. However, China's agriculture is far from modernized. The introduction of cloud computing and internet of things into agricultural modernization will probably solve the problem. Based on major features of cloud computing and key techniques of internet of things, cloud computing, visualization and SOA technologies can build massive data involved in agricultural production. Internet of things and RFID technologies can help build plant factory and realize automatic control production of agriculture. Cloud computing is closely related to internet of things. A perfect combination of them can promote fast development of agricultural modernization, realize smart agriculture and effectively solve the issues concerning agriculture, countryside and farmers.
248 citations
TL;DR: Structural equation analysis results indicate that hedonic motivation, performance expectancy, social influence, and price value positively affect students’ mobile learning adoption.
Abstract: Although mobile learning in higher education has recently received considerable attention, the fact remains that much of the scholarly effort has been limited to the notions of instrumentality. Drawing on UTAUT2 and extant literature on learning behavior, an adoption model that reflects the determinants of undergraduate students’ mobile learning acceptance in a consumer context was developed and empirically tested against data collected from 182 undergraduate students in China. Structural equation analysis results indicate that hedonic motivation, performance expectancy, social influence, and price value positively affect students’ mobile learning adoption. Surprisingly, self-management of learning was found to have both direct and indirect negative influences on undergraduate students’ adoption of mobile learning. Theoretical and practical implications of the findings are discussed.
96 citations
Journal Article•
TL;DR: This paper provides a qualitative analysis based on field experience using three games for entrepreneurship that shows that SGs have still to significantly evolve in order to become an effective and efficient tool that could be successfully and reliably used in HE.
Abstract: The potential of Serious Games (SGs) in education is widely recognized, and their adoption is significant in particular in children instruction. However, the deployment rate of SGs in higher education (HE) and their proper insertion in meaningful curricula is still quite low. This paper intends to make a first step in the direction of a better characterization of the pedagogical effectiveness of SGs in HE, by providing a qualitative analysis based on our field experience using three games for entrepreneurship, that we have studied in the light of two well established pedagogical paradigms, such as the Revised Bloom’s taxonomy and the Kolb’s Learning stages. In general, we observe that SGs address several goals of the Bloom’s taxonomy, in particular at the lower levels. Moreover, the cyclical nature of the business simulations can be directly mapped to the sequential steps described by Kolb. However, our analysis also shows that SGs have still to significantly evolve in order to become an effective and efficient tool that could be successfully and reliably used in HE. In the light of our experience, we also propose a schema for a proper integration of SGs by supporting different goals in different steps of a formal education process, Our study finally suggests directions for future research in the field.
27 citations
16 citations
TL;DR: A Semantic Interoperability for Data Integration-SIDI framework to integrate information from heterogeneous databases of difference providers in the same domain has been applied to the healthcare domain to enable semantic interoperability among independently developed health information system-HIS for integrating healthcare data.
Abstract: This paper proposes a Semantic Interoperability for Data Integration-SIDI framework to integrate information from heterogeneous databases of difference providers in the same domain. A framework is designed to incorporate with important procedures based on ontology and semantic web services technologies. The semantic web services annotation is imperative to cope with the semantic service discrepancies with the help of ontology. The research also proposes the ontology mapping technique to determine the correspondences between information concepts with semantic bridges description to automatically construct the semantic rule-based inference. As a result, the framework has been applied to the healthcare domain to enable semantic interoperability among independently developed health information system-HIS for integrating healthcare data.
15 citations
TL;DR: Some research directions of mobile cloud computing such as application partition, computation offloading, resource management and context-aware services as well as future research trends in brief are introduced.
Abstract: Mobile cloud computing introduces the cloud computing technology to the mobile Internet. It can greatly promote the development and application of cloud computing, and can promote the development and application of the Internet technology to a higher level. Mobile cloud computing system consists of mobile devices, wireless networks and cloud data centers. It combines cloud computing technology and mobile Internet technology. With the combination of cloud computing and mobile Internet, mobile cloud computing causes some new research issues belonging to the field of mobile cloud computing. This paper introduces some research directions of mobile cloud computing such as application partition, computation offloading, resource management and context-aware services as well as future research trends in brief.
13 citations
TL;DR: This paper will give a security threat analysis for the perception layer, the transport layer and the application layer according to the actual situation that the system is facing such as the mass nodes manager and heterogeneous network integration and so on.
Abstract: There are a lot of security threats during the development of the Internet of Things and the issues are needed to be resolved in the system development process. Establishing a threat model after security threats analysis is an essential step to build a security system. A perfect designed threat model can help designers to identify security threats that exist in the system quickly and make decision timely to protect the data security and normal operation of the system. In this paper, first, we will give a security threat analysis for the perception layer, the transport layer and the application layer according to the actual situation that the system is facing such as the mass nodes manager and heterogeneous network integration and so on. Then we will show the threat modeling process focusing on the perception layer with the method of threat tree model. At last, we will give the final threat tree model and corresponding security countermeasures. This model can provide a theoretical basis for making the follow-up security measure study and finishing the risk assessment work.
12 citations
TL;DR: A new field-weakening scheme based on the space-vector modulation technique that improves the utilization ratio of thespace-vector-pulse-width-modulation (SVPWM) inverter, but also achieves a smooth transition between the constant-torque mode below the base-speed and the Constant-power mode above the basespeed.
Abstract: We investigate the implementation of field-weakening control for interior permanent magnet synchronous motor (IPMSM), and analyze the algorithm of field-weakening control in d-q axes. To deal with the problem that the dc-link voltage is not fully utilized when the voltage regulation is employed, we propose a new field-weakening scheme based on the space-vector modulation technique. The duty-time of zero-voltage vector is used as the feedback signal to decide the switching of fieldweakening. To avoid the regulation lag in the q-axis component, we apply the lead-angle control during the field-weakening progress. The proposed scheme is validated with Matlab/Simulink tool. Simulation results show that the scheme is feasible. It not only improves the utilization ratio of the space-vector-pulse-width-modulation (SVPWM) inverter, but also achieves a smooth transition between the constant-torque mode below the base-speed and the constant-power mode above the basespeed.
11 citations
TL;DR: SAUS which is a measure for smartphone addiction was developed and tested to evaluate precedents of smartphone addiction and explores the phenomenon and problematic use in Korea.
Abstract: Smartphone addiction can be defined as a state of being enslaved to smartphone and its related service. This study explores the phenomenon and problematic use in Korea. Also SAUS which is a measure for smartphone addiction was developed and tested to evaluate precedents of smartphone addiction.
11 citations
11 citations
TL;DR: The use of the extremum method to determine the peak point of the pulse wave, then determined based on thepeak point out the location of the other features, the experiment proved that this method can increase the detection rate of feature points.
Abstract: Abstract The complete analysis of the pulse wave is in the collection of the pulse wave signal in the signal containing a small amount of noise and more clear, however vulnerable to a variety of the influence of interference, so that the extracted pulse wave contains a lot of noise, thus lowering noise handling is particularly necessary. At the same time, pulse wave contains human physiological and pathological information, different people will exhibit different characteristics, can be seen to determine the characteristic point of the pulse wave analysis of human physiological health makes sense. Method for signal denoising with wavelet transform and multi-resolution analysis, the method in the time domain and frequency domain can characterize the local signal information, and has a self-adaptive signal. The use of the extremum method to determine the peak point of the pulse wave, then determined based on the peak point out the location of the other features, the experiment proved that this method can increase the detection rate of feature points.
TL;DR: The improved ant colony algorithm is proposed, inspired from the ant foraging behavior and integrated multi-goal match of the secondary distribution, which will shorten the scheduling time, implement system load balancing at the same time and embed these scheduling algorithms into a visualization system.
Abstract: As a distributed parallel computing, cloud computing has an absolute advantage in accessing and processing of huge amount of data. How to assign all these virtual cloud computing resources to the user is a key technical issues, scholars have proposed greedy algorithm, FCFS, and other variety of algorithms to solve this problem. However, the algorithms just build a local optimal solution, there is no global allocation of resources in the cloud computing. In order to solve this problem, we are inspired from the ant foraging behavior and integrated multi-goal match of the secondary distribution, then, we proposed ant colony optimization algorithm. The improved ant colony algorithm combines the traditional ant colony algorithm and the greedy algorithm's advantage. Finally, we use the cloud computing simulation tools CloudSim to do the simulative experiments and embed these scheduling algorithms into a visualization system. From the comparison of the simulation results, it can be seen that the improved ant colony algorithm shorten the scheduling time, implement system load balancing at the same time.
TL;DR: A new knowledge based control algorithm for fault detection and diagnosis and recovery using fuzzy logic approach and challenge approach namely Fault Tolerance Fuzzy Knowledge based control in Wireless Sensor Networks (WSNs) to eliminate faulty communication behaviour nodes in the WSNs communication framework.
Abstract: In this paper, we present a new knowledge based control algorithm for fault detection and diagnosis and recovery using fuzzy logic approach and challenge approach namely Fault Tolerance Fuzzy Knowledge based control in Wireless Sensor Networks (WSNs). This FTFK algorithm diagnoses faulty communication between sensor nodes providing Fault Detection and Isolation (FDI) to eliminate faulty communication behaviour nodes in the WSNs communication framework. Our algorithm also monitors erroneous behaviour of nodes to ensure that faulty nodes sharing incorrect data under certain qualities can be tolerated in the network. We have conducted a simulation study for this FTFK algorithm using the Georgia Tech Network Simulator (GTNetS). Our simulation results show that FTFK scheme can improve performance and reliability of WSNs: it expenses little bit higher energy and examine time to achieve shorter average end to end delay and better packet success ratio when a number of cluster heads failures in the WSNs.
Journal Article•
TL;DR: Gamification approaches have been used widely by various industries such as government, manufacturing, education, health care, and military and are still being used today.
Abstract: Gamification approaches have been used widely by various industries such as government, manufacturing, education, health care, and military. There are...
TL;DR: A decision- making method with linguistic assessments is proposed based on expected values of trapezoidal hesitant fuzzy sets to solve the multicriteria decision-making problem in which the criteria weights are completely unknown.
Abstract: This paper extends hesitant fuzzy sets to trapezoidal hesitant fuzzy sets based on the combination of the concepts of trapezoidal fuzzy numbers and hesitant fuzzy sets and defines some operations on trapezoidal hesitant fuzzy sets. Then, a decision-making method with linguistic assessments is proposed based on expected values of trapezoidal hesitant fuzzy sets to solve the multicriteria decision-making problem in which the criteria weights are completely unknown and the criteria values for an alternative can be given by the linguistic values of trapezoidal fuzzy numbers provided by a group of decision makers to transform them into trapezoidal hesitant fuzzy sets. The criteria weights can be obtained by establishing a weight model based on the standard deviation of expected values from the trapezoidal hesitant fuzzy decision matrix. Then by an approach of weighted expected values for alternatives, the ranking order of all the alternatives can be determined and the best one can be easily identified as well. Finally, a practical example for the flexible manufacturing system is given to demonstrate the application of the proposed decision-making method. The numerical example shows that the proposed method is reasonable and applicable.
TL;DR: In this paper, the authors presented the water quality forecasting at the Nanjinguan water quality monitoring station of Yangtze River, China, using hybrid models consisting of Autoregressive Integrated Moving Average (ARIMA) models and Artificial Neural Network (ANNs) models.
Abstract: In this paper the water quality forecasting at the Nanjinguan water quality monitoring station of Yangtze River, China, is presented. The time series data used are weekly water quality data obtained directly from Nanjinguan station measurements over the course of five years. In order to forecast water quality, hybrid models consisting of Autoregressive Integrated Moving Average (ARIMA) models and Artificial Neural Network (ANNs) models were developed. The ARIMA models were first used to do water quality forecasting of the time series data and then with the obtained errors ANNs were built taking into account the nonlinear patterns that the ARIMA technique could not capture, in order to reduce potential errors. Once the hybrid models were developed 38 samples out of the data for the station were used to do the water quality forecasting and the results were compared with the ARIMA and the ANNs models worked separately. Statistical error measures such as the root mean square error (RMSE), the mean absolute percentage error (MAPE) and correlation coefficient (R) were calculated to compare the three methods. The results showed that the hybrid models predict the water quality with a higher accuracy than the ARIMA and ANNs models in the examined station.
TL;DR: In this paper, an expanded version of the Theory of Planned Behavior (TPB) containing separate measures of social norms and habit is employed to compare psychological predictors of the intention to use four travel modes: the traditional train, the electric multiple unit (EMU), the high speed railway (HSR), and the coach.
Abstract: This paper makes use of a sample of travelers in metropolitan area of Yangtze River Delta to compare psychological predictors of the intention to use four travel modes: the traditional train, the Electric Multiple Unit (EMU), the High Speed Railway (HSR), and the coach. An expanded version of the Theory of Planned Behavior (TPB) containing separate measures of social norms and habit is employed. The results demonstrate that attitude, subjective norm, and perceived behavioral control explained between 33% and 45% of the variance in intention to use various travel modes. In all cases, attitude and subjective norm are important factors and by adding descriptive norm to the original predictors in TPB, the explained variance increased by between 4% and 8%. Furthermore, introduction of habit in model results the much more explained variance in intention. This paper also reports the study which demonstrates the moderating effect of habit on the intention–behavior relationship. Results illustrate that the effect of habit as moderator of intention on behavior in intercity travel modes was weaker than that in in-city travel modes.
TL;DR: The empirical results show that the Markov-switching model can effectively depict fluctuating behavior of non-ferrous metal prices.
Abstract: Markov-switching model is a method applied to investigating the structural changes of nonlinear time series. This paper, by constructing three states Markov-switching model, studies the state transition behaviors in the price fluctuation of nonferrous metal from January 2001 to March 2011. Three different kinds of states of SHFE copper price fluctuation are observed: rising sharply, rising mildly and dropping sharply. Each state is characterized with different probability of transition as well as different average duration. The final part presents the causal analysis of the emergence of main state at each phase. The empirical results show that the Markov-switching model can effectively depict fluctuating behavior of non-ferrous metal prices.
TL;DR: This paper aims to discuss how the data mining and statistical algorithms can help to identify the fraudulent transactions’ characteristics and prevent the fraudulent Transactions in real-time.
Abstract: With the advance of internet technologies in recent years, online shopping is becoming a popular trend to make purchases compared to the traditional ways. There are many excellent benefits to both the consumers and business conducting online businesses. However, it could also cause great damage to the business due to the increasing number of fraudulent online transactions. In order to improve the online shopping experience, there are great needs to reduce and prevent the fraudulent activities. This paper aims to discuss how the data mining and statistical algorithms can help to identify the fraudulent transactions’ characteristics and prevent the fraudulent transactions in real-time.
TL;DR: Assessment of the mediation effects of satisfaction on the relationship between quality factors and performance showed that user satisfaction has a high significant mediation role between information, service quality and effectiveness in terms of performance.
Abstract: Web-Based Management Information System (WBMIS) is mainly concerned with supporting management functions including decision making, performance management and cost reduction in order to provide an effective management for organizations at different levels. For this reason the assessment of WBMIS is highly needed to justify the IT investment in terms of its impacts on performance, and especially on the employee performance. It is important to highlight that a very little research has been conducted to assess the influence of the two critical factors including information and service quality on the employee performance. For this purpose, this study focuses on the assessment of the mediation effects of satisfaction on the relationship between quality factors and performance. A sample of a total of 128 respondents was gathered in a reasonable scale study in order to test the validity and reliability of the adapted instrument as well as test the significance of the mediation effect of user satisfaction. The results of multiple regression showed that there are significant relationships between study factors (information quality, service quality, user satisfaction and task performance). Furthermore, hierarchical regression test indicated that user satisfaction has a high significant mediation role between information, service quality and effectiveness in terms of performance (Sig. < 0.01). Therefore, as the quality of information and e-services increased, the satisfaction with WBMIS increased which in turn leads to increase in the employee performance.