Search results for: online model identification

Authors: Nafise Fareghzadeh

Abstract:

Service identification is one of the main activities in the modeling of a service-oriented solution, and therefore errors made during identification can flow down through detailed design and implementation activities that may necessitate multiple iterations, especially in building composite applications. Different strategies exist for how to identify candidate services that each of them has its own benefits and trade offs. The approach presented in this paper proposes a selective identification of services approach, based on in depth business process analysis coupled with use cases and existing assets analysis and goal service modeling. This article clearly emphasizes the key activities need for the analysis and service identification to build a optimized service oriented architecture. In contrast to other approaches this article mentions some best practices and steps, wherever appropriate, to point out the vagueness involved in service identification.

Keywords: SOA, service identification, service taxonomy, service layer.

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Authors: Amalia Triantafillidou, Georgios Lappas, Prodromos Yannas, Alexandros Kleftodimos

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In this paper, an experiment was conducted to assess the impact of online deliberation on citizens’ attitudes. Specifically, this research compared pre and post deliberation opinions of participants who deliberated online via an asynchronous platform regarding the issue of political opinion polls. Results indicate that online deliberation had a positive effect on citizens’ attitudes since it was found that following deliberation participants changed their views regarding public opinion polls. Specifically, online deliberation improved discussants perceptions regarding the reliability of polls, while suppressing their negative views about the misuse of polls by media, polling organizations and politicians.

Keywords: Online deliberation, attitudes change, opinion polls, e-democracy.

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Authors: Suman Senapati, Goutam Saha

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Real world Speaker Identification (SI) application differs from ideal or laboratory conditions causing perturbations that leads to a mismatch between the training and testing environment and degrade the performance drastically. Many strategies have been adopted to cope with acoustical degradation; wavelet based Bayesian marginal model is one of them. But Bayesian marginal models cannot model the inter-scale statistical dependencies of different wavelet scales. Simple nonlinear estimators for wavelet based denoising assume that the wavelet coefficients in different scales are independent in nature. However wavelet coefficients have significant inter-scale dependency. This paper enhances this inter-scale dependency property by a Circularly Symmetric Probability Density Function (CS-PDF) related to the family of Spherically Invariant Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain and corresponding joint shrinkage estimator is derived by Maximum a Posteriori (MAP) estimator. A framework is proposed based on these to denoise speech signal for automatic speaker identification problems. The robustness of the proposed framework is tested for Text Independent Speaker Identification application on 100 speakers of POLYCOST and 100 speakers of YOHO speech database in three different noise environments. Experimental results show that the proposed estimator yields a higher improvement in identification accuracy compared to other estimators on popular Gaussian Mixture Model (GMM) based speaker model and Mel-Frequency Cepstral Coefficient (MFCC) features.

Keywords: Speaker Identification, Log Gabor Wavelet, Bayesian Bivariate Estimator, Circularly Symmetric Probability Density Function, SIRP.

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Authors: P. Georgieva, S. Feyo de Azevedo

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This paper is focused on issues of process modeling and two model based control strategies of a fed-batch sugar crystallization process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. Two control alternatives are considered – model predictive control (MPC) and feedback linearizing control (FLC). Adequate ANN process models are first built as part of the controller structures. MPC algorithm outperforms the FLC approach with respect to satisfactory reference tracking and smooth control action. However, the MPC is computationally much more involved since it requires an online numerical optimization, while for the FLC an analytical control solution was determined.

Keywords: artificial neural networks, nonlinear model control, process identification, crystallization process

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Authors: Shanshan Qi, Rob Law, Dimitrios Buhalis

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The fast technology and economic growth in China has attracted global attention in its tourism development. This study makes an effort on investigating China-s online tourism market and the Chinese online travelers- perceptions of hotel websites. The findings are expected to better understand Chinese customers- online preference and identified the differences among online travelers from different regions in the country. Empirical findings showed online reservation information is the most important factor to Chinese customers, and tourists from different regions of China have perception difference on user-friendly factor. The findings benefit hoteliers from understanding their websites development and formulating more appropriate online strategies to meet the requirements of Chinese travelers.

Keywords: Chinese online travelers, Hotel websites, Regions of China, Website usefulness

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Authors: Chummanond Natchaya, Rotchanakitumnuai Siriluck

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The objective of this study is to identify the factors that influence the online purchasing loyalty for Thai herbal products. Survey research is used to gather data from Thai herb online merchants to assess factors that have impacts on enhancing loyalty. Data were collected from 300 online customers who had experience in online purchasing of Thai Herbal products. Prior experience consists of data from previous usage of online herbs, herb purchase and internet usage. E-Quality data consists of information quality, system quality, service quality and the product quality of Thai herbal products sold online. The results suggest that prior experience, Equality, attitude toward purchase and trust in online merchant have major impacts on loyalty. The good attitude and E-Quality of purchasing Thai herbal product online are the most significant determinants affecting loyalty.

Keywords: e-Commerce, Thai herb, E-Quality, satisfaction, loyalty.

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Authors: Munazza A. Mirza, Khawar Khurshid

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Individuals are generally associated with different learning styles, which have been explored extensively in recent past. The learning styles refer to the potential of an individual by which s/he can easily comprehend and retain information. Among various learning style models, VARK is the most accepted model which categorizes the learners with respect to their sensory characteristics. Based on the number of preferred learning modes, the learners can be categorized as uni-modal, bi-modal, tri-modal, or quad/multi-modal. Although there is a prevalent belief in the learning styles, however, the model is not being frequently and effectively utilized in the higher education. This research describes the identification model to validate teacher’s didactic practice and student’s performance linkage with the learning styles. The identification model is recommended to check the effective application and evaluation of the various learning styles. The proposed model is a guideline to effectively implement learning styles inventory in order to ensure that it will validate performance linkage with learning styles. If performance is linked with learning styles, this may help eradicate the distrust on learning style theory. For this purpose, a comprehensive study was conducted to compare and understand how VARK inventory model is being used to identify learning preferences and their correlation with learner’s performance. A comparative analysis of the findings of these studies is presented to understand the learning styles of tertiary students in various disciplines. It is concluded with confidence that the learning styles of students cannot be associated with any specific discipline. Furthermore, there is not enough empirical proof to link performance with learning styles.

Keywords: Learning style, VARK, sensory preferences, identification model, didactic practices.

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Authors: Hang-cheong Wong, Pak-kin Wong, Chi-man Vong, Zhengchao Xie, Shaojia Huang

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Automotive engine air-ratio plays an important role of emissions and fuel consumption reduction while maintains satisfactory engine power among all of the engine control variables. In order to effectively control the air-ratio, this paper presents a model predictive fuzzy control algorithm based on online least-squares support vector machines prediction model and fuzzy logic optimizer. The proposed control algorithm was also implemented on a real car for testing and the results are highly satisfactory. Experimental results show that the proposed control algorithm can regulate the engine air-ratio to the stoichiometric value, 1.0, under external disturbance with less than 5% tolerance.

Keywords: Air-ratio, Fuzzy logic, online least-squares support vector machine, model predictive control.

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Authors: Pui-Lai To, E-Ping Sung

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The purpose of this study is to investigate hedonic online shopping motivations. A qualitative analysis was conducted to explore the factors influencing online hedonic shopping motivations. The results of the study indicate that traditional hedonic values, consisting of social, role, self-gratification, learning trends, pleasure of bargaining, stimulation, diversion, status, and adventure, and dimensions of flow theory, consisting of control, curiosity, enjoyment, and telepresence, exist in the online shopping environment. Two hedonic motivations unique to Internet shopping, privacy and online shopping achievement, were found. It appears that the most important hedonic value to online shoppers is having the choice to interact or not interact with others while shopping on the Internet. This study serves as a basis for the future growth of Internet marketing.

Keywords: Internet Shopping, Shopping Motivation, Hedonic Motivation.

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Authors: Azah Kamilah Muda, Siti Mariyam Shamsuddin, Maslina Darus

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Writer identification is one of the areas in pattern recognition that attract many researchers to work in, particularly in forensic and biometric application, where the writing style can be used as biometric features for authenticating an identity. The challenging task in writer identification is the extraction of unique features, in which the individualistic of such handwriting styles can be adopted into bio-inspired generalized global shape for writer identification. In this paper, the feasibility of generalized global shape concept of complimentary binding in Artificial Immune System (AIS) for writer identification is explored. An experiment based on the proposed framework has been conducted to proof the validity and feasibility of the proposed approach for off-line writer identification.

Keywords: Writer identification, generalized global shape, individualistic, pattern recognition.

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Authors: Prakash Vel, Jocelyn Rodrigues

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Luxury is an identity, a philosophy and a culture which requires understanding before the adoption of e-business practices because of its intricacies and output are essentially different from other types of goods. Factors such as culture, personal characteristics, website quality, and vendor characteristics influence the online purchasing behavior of consumers thus making it a complex area of study. This paper explores the scope of e-retail for luxury consumption in the U.A.E. by identifying what motivates and de-motivates online purchase behavior of U.A.E. consumers and necessary hypotheses have been drawn to reflect behavior between online luxury preference consumers and non-online luxury preference consumers.

Keywords: e-Retail, Luxury brands, U.A.E. consumer.

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Authors: Bojan Korizma, Zeljko Panian

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Online auctions are not very popular in Croatia. The main reason for this is a very limited number of services which can be used by Croatian users. Until recent times, even selling through the most popular online auction site eBay wasn't possible because PayPal services could not make payment to bank or debit card accounts in Croatia. Furthermore, many foreign sellers do not offer delivery of their products to Croatia which means that large quantities of goods initially offered on such sites are not available. With that in mind, it is necessary to analyze the buying and selling habits of Croatian users and existing online auction sites, both Croatian and foreign, and create a model for new domestic site. This site will have to exploit every positive aspect of existing models and neutralize every negative perception indicated by users in the survey so that, hopefully, it would attract new users.

Keywords: online auction, eBay, safe payment, product delivery

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Authors: Heejin Yun, Juanjuan Zang

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This study aims to analyze the text terms posted on an online community of people from the same hometown and to understand the topic and trend of nostalgia composed online. For this purpose, this study collected 144 writings which the natives of Yeongjong Island, Incheon, South-Korea have posted on an online community. And it analyzed association relations. As a result, online community texts means that just defining nostalgia as ‘a mind longing for hometown’ is not an enough explanation. Second, texts composed online have abstractness rather than persons’ individual stories. This study figured out the relationship that had the most critical and closest mutual association among the terms that constituted nostalgia through literature research and association rule concerning nostalgia. The result of this study has a characteristic that it summed up the core terms and emotions related to nostalgia.

Keywords: Nostalgia, cultural memory, data mining, online community.

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

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Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: Energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning.

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R²).

Keywords: Time series modelling, stochastic processes, ARIMA model, Karkheh River.

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Authors: Ke He, Wumaier Parezhati, Haruka Yamashita

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Recently, online marketplaces in the e-commerce industry, such as Rakuten and Alibaba, have become some of the most popular online marketplaces in Asia. In these shopping websites, consumers can select purchase products from a large number of stores. Additionally, consumers of the e-commerce site have to register their name, age, gender, and other information in advance, to access their registered account. Therefore, establishing a method for analyzing consumer preferences from both the store and the product side is required. This study uses the Doc2Vec method, which has been studied in the field of natural language processing. Doc2Vec has been used in many cases to analyze the extraction of semantic relationships between documents (represented as consumers) and words (represented as products) in the field of document classification. This concept is applicable to represent the relationship between users and items; however, the problem is that one more factor (i.e., shops) needs to be considered in Doc2Vec. More precisely, a method for analyzing the relationship between consumers, stores, and products is required. The purpose of our study is to combine the analysis of the Doc2vec model for users and shops, and for users and items in the same feature space. This method enables the calculation of similar shops and items for each user. In this study, we derive the real data analysis accumulated in the online marketplace and demonstrate the efficiency of the proposal.

Keywords: Doc2Vec, marketing, online marketplace, recommendation system.

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Authors: Ginalber L. O. Serra

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This work proposes a recursive weighted ELS algorithm for system identification by applying numerically robust orthogonal Householder transformations. The properties of the proposed algorithm show it obtains acceptable results in a noisy environment: fast convergence and asymptotically unbiased estimates. Comparative analysis with others robust methods well known from literature are also presented.

Keywords: Stochastic Systems, Robust Identification, Parameter Estimation, Systems Identification.

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Authors: B. Chandra, P. Paul Varghese

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Crypto System Identification is one of the challenging tasks in Crypt analysis. The paper discusses the possibility of employing Neural Networks for identification of Cipher Systems from cipher texts. Cascade Correlation Neural Network and Back Propagation Network have been employed for identification of Cipher Systems. Very large collection of cipher texts were generated using a Block Cipher (Enhanced RC6) and a Stream Cipher (SEAL). Promising results were obtained in terms of accuracy using both the Neural Network models but it was observed that the Cascade Correlation Neural Network Model performed better compared to Back Propagation Network.

Keywords: Back Propagation Neural Networks, CascadeCorrelation Neural Network, Crypto systems, Block Cipher, StreamCipher.

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Authors: Afef Badri

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Metaphorical creativity does not constitute a static property of discourse. It is an interactive dynamic process created online. There has been a lack of research concerning online produced metaphorical creativity. This paper intends to account for metaphorical creativity in online talk-in-interaction as a dynamic process that emerges as discourse unfolds. It brings together insights from the emergentist approach to the study of metaphor in verbal interactions and insights from conceptual blending approach as a model for analysing online metaphorical constructions to propose a model for studying metaphorical creativity in interactive talk. The model is based on three focal points. First, metaphorical creativity is a dynamic emergent and open-to-change process that evolves in real time as interlocutors constantly blend and re-blend previous metaphorical contributions. Second, it is not a product of isolated individual minds but a joint achievement that is co-constructed and co-elaborated by interlocutors. The third and most important point is that the emergent process of metaphorical creativity is tightly shaped by contextual variables surrounding talk-in-interaction. It is grounded in the framework of interpretation of interlocutors. It is constrained by preceding contributions in a way that creates textual cohesion of the verbal exchange and it is also a goal-oriented process predefined by the communicative intention of each participant in a way that reveals the ideological coherence/incoherence of the entire conversation.

Keywords: Communicative intention, conceptual blending, contextual variables, the emergentist approach, ideological coherence, metaphorical creativity, textual cohesion

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Authors: C. Perez, O. Reinoso, N. Garcia, J. M. Sabater, L. Gracia

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For high-speed control of robots, a good knowledge of system modelling is necessary to obtain the desired bandwidth. In this paper, we present a cartesian robot with a pan/tilt unit in end-effector (5 dof). This robot is implemented with powerful direct drive AC induction machines. The dynamic model, parameter identification and model validation of the robot are studied (including actuators). This work considers the cartesian robot coupled and non linear (contrary to normal considerations for this type of robots). The mechanical and control architecture proposed in this paper is efficient for industrial and research application in which high speed, well known model and very high accuracy are required.

Keywords: Robot modelling, parameter identification and validation, AC servo-motors.

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Authors: Pongsatorn Tantrabundit, Lersak Phothong, Ong-art Chanprasitchai

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Due to the emergence of the Internet, it has extended the traditional Word-of-Mouth (WOM) to a new form called “Electronic Word-of-Mouth (eWOM).” Unlike traditional WOM, eWOM is able to present information in various ways by applying different components. Each eWOM component generates different effects on online consumer behavior. This research investigates the effects of Webcare (responding message) from product/ service providers on negative eWOM by applying two types of products (search and experience). The proposed conceptual model was developed based on the combination of the stages in consumer decision-making process, theory of reasoned action (TRA), theory of planned behavior (TPB), the technology acceptance model (TAM), the information integration theory and the elaboration likelihood model. The methodology techniques used in this study included multivariate analysis of variance (MANOVA) and multiple regression analysis. The results suggest that Webcare does slightly increase Thai online consumer’s perceptions on perceived eWOM trustworthiness, information diagnosticity and quality. For negative eWOM, we also found that perceived eWOM Trustworthiness, perceived eWOM diagnosticity and quality have a positive relationship with eWOM influence whereas perceived valence has a negative relationship with eWOM influence in Thai online consumers.

Keywords:

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Authors: Chiao-Chen Chang, Yang-Chieh Chin

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This study examines the issue of recommendation sources from the perspectives of gender and consumers- perceived risk, and validates a model for the antecedents of consumer online purchases. The method of obtaining quantitative data was that of the instrument of a survey questionnaire. Data were collected via questionnaires from 396 undergraduate students aged 18-24, and a multiple regression analysis was conducted to identify causal relationships. Empirical findings established the link between recommendation sources (word-of-mouth, advertising, and recommendation systems) and the likelihood of making online purchases and demonstrated the role of gender and perceived risk as moderators in this context. The results showed that the effects of word-of-mouth on online purchase intentions were stronger than those of advertising and recommendation systems. In addition, female consumers have less experience with online purchases, so they may be more likely than males to refer to recommendations during the decision-making process. The findings of the study will help marketers to address the recommendation factor which influences consumers- intention to purchase and to improve firm performances to meet consumer needs.

Keywords: Recommendation sources, Online purchaseintentions, Gender differences, Perceived risk.

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Authors: Yu Wang

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Nowadays, Internet enables its users to share the information online and to interact with others. Facing with numerous information, these Internet users are confused and begin to rely on the opinion leaders’ recommendations. The online opinion leaders are the individuals who have professional knowledge, who utilize the online channels to spread word-of-mouth information and who can affect the attitudes or even the behavior of their followers to some degree. Because utilizing the online opinion leaders is seen as an important approach to affect the potential consumers, how to identify them has become one of the hottest topics in the related field. Hence, in this article, the concepts and characteristics are introduced, and the researches related to identifying opinion leaders are collected and divided into three categories. Finally, the implications for future studies are provided.

Keywords: Online opinion leaders, user attributes analysis, text mining analysis, network structure analysis.

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Authors: Masoud Sadeghian, Alireza Fatehi

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One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameter were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement rotary kiln by using nonlinear identification technique on the Locally Linear Neuro- Fuzzy (LLNF) model. For the first time, a simulator model as well as a predictor one with a precise fifteen minute prediction horizon for a cement rotary kiln is presented. These models are trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. At the end, the characteristics of these models are expressed. Furthermore, we presented the pros and cons of these models. The data collected from White Saveh Cement Company is used for modeling.

Keywords: Cement rotary kiln, nonlinear identification, Locally Linear Neuro-Fuzzy model.

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Authors: Carol Shepherd, Madelon Alpert, Marilyn Koeller

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In order to provide and maintain effective pedagogy for the burgeoning virtual reality community, it is vital to have trained faculty in the institutions of higher education who will teach these courses and be able to make full use of their academic knowledge and expertise. As the number of online courses continues to grow, there is a need for these institutions to establish mentoring programs that will support the novice online instructor. The environment in which this takes place and the factors that ensure its success are critical to the adoption of the new instructional delivery format taught by both seasoned educators and adjunct instructors. Effective one-on-one mentoring promotes a professional, compassionate and collegial faculty who will provide a consistent and rigorous academic program for students online.

Keywords: Mentoring seasoned faculty, staff development, online pedagogy, online andragogy.

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Authors: Hamed Zolfaghari, Mojtaba Kord

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Project planners and controllers are frequently faced with the challenge of inadequate software for the preparation of automatic project progress reports based on actual project information updates. They usually make dashboards in Microsoft Excel, which is local and not applicable online. Another shortcoming is that Microsoft project does not store the data in database, so the data cannot automatically be imported from Microsoft Project into Microsoft Excel. This study aimed to propose a model for the preparation of reports on automatic online project progress based on actual project information updates by the integration of Primavera P6, SQL database, and Power BI (Business Intelligence) for a construction project. The designed model could be applicable to project planners and controller agents by enabling them to prepare project reports automatically and immediately after updating the project schedule using actual information. To develop the model, the data were entered into P6, and the information was stored on the SQL database. The proposed model could prepare a wide range of reports, such as earned value management, Human Resource (HR) reports, and financial, physical, and risk reports automatically on the Power BI application. Furthermore, the reports could be published and shared online.

Keywords: Primavera P6, SQL, Power BI, Earned Value Management, Integration Management.

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Authors: Keuk Jong Yu, Sang Hee Kang, Sung Chang You

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In Korea, the technology of a load fo nuclear power plant has been being developed. automatic controller which is able to control temperature and axial power distribution was developed. identification algorithm and a model predictive contact former transforms the nuclear reactor status into numerically. And the latter uses them and ge manipulated values such as two kinds of control ro this automatic controller, the performance of a coperation was evaluated. As a result, the automatic generated model parameters of a nuclear react to nuclear reactor average temperature and axial power the desired targets during a daily load follow.

Keywords: axial power distribution, model reactor temperature, system identification

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Authors: Nidhi Gadura

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Given the increase in the number of students and administrators asking for online courses the author developed two partially online courses. One was a biology majors at genetics course while the other was a non-majors at biology course. The student body at Queensborough Community College is generally underprepared and has work and family obligations. As an educator, one has to be mindful about changing the pedagogical approach, therefore, special care was taken when designing the course material. Despite the initial concerns, both of these partially online courses were received really well by students. Lessons learnt were that student engagement is the key to success in an online course. Good practices to run a successful online course for underprepared students are discussed in this paper. Also discussed are the lessons learnt for making the eLearning environment better for all the students in the class, overachievers and underachievers alike.

Keywords: Partially online course, pedagogy, student engagement, community college.

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Authors: Waralak Vongdoiwang Siricharoen

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One of object oriented software developing problem is the difficulty of searching the appropriate and suitable objects for starting the system. In this work, ontologies appear in the part of supporting the object discovering in the initial of object oriented software developing. There are many researches try to demonstrate that there is a great potential between object model and ontologies. Constructing ontology from object model is called ontology engineering can be done; On the other hand, this research is aiming to support the idea of building object model from ontology is also promising and practical. Ontology classes are available online in any specific areas, which can be searched by semantic search engine. There are also many helping tools to do so; one of them which are used in this research is Protégé ontology editor and Visual Paradigm. To put them together give a great outcome. This research will be shown how it works efficiently with the real case study by using ontology classes in travel/tourism domain area. It needs to combine classes, properties, and relationships from more than two ontologies in order to generate the object model. In this paper presents a simple methodology framework which explains the process of discovering objects. The results show that this framework has great value while there is possible for expansion. Reusing of existing ontologies offers a much cheaper alternative than building new ones from scratch. More ontologies are becoming available on the web, and online ontologies libraries for storing and indexing ontologies are increasing in number and demand. Semantic and Ontologies search engines have also started to appear, to facilitate search and retrieval of online ontologies.

Keywords: Software Developing, Ontology, Ontology Library, Artificial Intelligent, Protégé, Object Model.

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Authors: Andreas Ahrens, Jelena Zascerinska

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Emotions are crucial in online classes in adult education. Despite that, a little attention was devoted to the emotional experience of being an online teacher in the field of andragogy, and the online teacher’s emotional perspectives in ever changing environments have to be analysed. The paper aims at the analysis of teachers’ emotional experience in online classes in adult education in selected European countries. The research tends to propose implications for training of teachers who work in online classes in adult education. The survey was conducted in April 2022. In the selected European countries 78 respondents took part in the study. Among them, 30 respondents represented Germany, 28 respondents Greece, and 20 respondents were from Italy. The theoretical findings allow defining teacher emotional experience. The analysis of the elements of the respondents’ emotional experience allows concluding that teachers’ attitude to online classes has to be developed. The key content for teacher training is presented. Directions of further work are proposed.

Keywords: Adult education, online classes, teacher emotional experience, European countries.

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