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This study aims to present a novel technique to localize the human position in a room, to manage people in a specified space.

In this study, a real-time human sensing detection and smart lighting control was designed within a single silicon core. The chip has been successfully realized within 1.5 mm² silicon area using TSMC 0.25 um process.

This chip can read the weak signal of pyroelectric infrared (PIR) sensor to find the position of human body in a dark room and then help control the smart lighting system for an intelligent surveillance system.

This chip presented the retriggering delay control to expand the LED lighting time infinitely to avoid lighting-off suddenly while users stay on a space. This function is very useful in a practical intelligent surveillance system that is mainly based on human detection to better reduce power dissipation and memory space.

Although numerous studies have examined factors that influence smartphone acceptance and use, few have analyzed cognitive age. This study aims to use the unified theory of acceptance and use of technology (UTAUT) to test two models to analyze the moderating effect of cognitive age. This research offers relevant suggestions among different cognitive age groups.

A questionnaire survey was conducted to collect research data in Taiwan and the UTAUT model was used. Model 1 ensures all four antecedent constructs among digital natives (those under 34 years old). Model 2 divides the digital immigrants into two groups to test the influence of cognitive age on the behaviors of smartphone use. This study tests Model 1 using AMOS 20 to examine the measurement and structural model and validates Model 2 using partial least squares (PLSs).

In Model 1, the digital natives have sufficient confidence to accept a new technology with ease and little effort owing to most educational resources and the widespread internet. Group 1 in Model 2 reveals that the behavior of digital immigrants is similar to that of digital natives. For Group 2 in Model 2, they tend to infer that skills or tasks they associate with having higher value are more difficult to learn.

This study provides another dimensional result for different cognitive age groups and it has to consider not only chronological age but also cognitive age in user behavior. The result can enrich the theoretical perspective on technology adoption and use behavior via cognitive age, which is a significant and important self-related factor that can help predict technology adoption and use behavior.

The Communist revolution in China has led to the appearance in this country of increasing numbers of Chinese books in Russian translation. The Chinese names in Cyrillic transcription have presented many librarians and students with a new problem, that of identifying the Cyrillic form of a name with the customary Wade‐Giles transcription. The average cataloguer, the first to meet the problem, has two obvious lines of action, and neither is satisfactory. He can save up the names until he has a chance to consult an expert in Chinese. Apart altogether from the delay, the expert, confronted with a few isolated names, might simply reply that he could do nothing without the Chinese characters, and it is only rarely that Soviet books supply them. Alternatively, he can transliterate the Cyrillic letters according to the system in use in his library and leave the matter there for fear of making bad worse. As long as the writers are not well known, he may feel only faintly uneasy; but the appearance of Chzhou Ėn‐lai (or Čžou En‐laj) upsets his equanimity. Obviously this must be entered under Chou; and we must have Mao Tse‐tung and not Mao Tsze‐dun, Ch'en Po‐ta and not Chėn' Bo‐da. But what happens when we have another . . . We can hardly write Ch'en unless we know how to represent the remaining elements in the name; yet we are loth to write Ch'en in one name and Chėn' in another.

Churn prediction is a very important task for successful customer relationship management. In general, churn prediction can be achieved by many data mining techniques. However, during data mining, dimensionality reduction (or feature selection) and data reduction are the two important data preprocessing steps. In particular, the aims of feature selection and data reduction are to filter out irrelevant features and noisy data samples, respectively. The purpose of this paper, performing these data preprocessing tasks, is to make the mining algorithm produce good quality mining results.

Based on a real telecom customer churn data set, seven different preprocessed data sets based on performing feature selection and data reduction by different priorities are used to train the artificial neural network as the churn prediction model.

The results show that performing data reduction first by self-organizing maps and feature selection second by principal component analysis can allow the prediction model to provide the highest prediction accuracy. In addition, this priority allows the prediction model for more efficient learning since 66 and 62 percent of the original features and data samples are reduced, respectively.

The contribution of this paper is to understand the better procedure of performing the two important data preprocessing steps for telecom churn prediction.

The purpose of this paper is twofold: first, to develop a conceptual model using the push-pull-mooring (PPM) framework to understand the switching behavior of small- and medium-size enterprises (SMEs) of batik from adopting traditional marketing to e-commerce; and, second, to test whether the PPM variables prevent or lead to the switching behavior of SMEs of batik to adopt e-commerce.

This study uses a hypothesis which is drawn from related literature, quantifiable measures variables with a 1–5 Likert scale, hypothesis testing and draws the inference about a phenomenon of switching the behavior of SMEs from traditional marketing to e-commerce from the sample of 100 owners of batik SMEs, which are located in Yogyakarta, Solo and Pekalongan. The study used partial least square with the aid of the SmartPLS software program to test the hypothesis.

The result of hypothesis testing indicates that two factors significantly influence the switching behavior of batik SMEs from physical store retailing to e-commerce. The first factor is the desire of SMEs to support the information searching behavior of their customers, and the second factor is the perception that adopting e-commerce can provide value for the SMEs. However, this study fails to prove that the attractiveness of e-commerce can significantly pull the switching behavior of batik SMEs from physical store retailing to e-commerce. Moreover, related to mooring factors, the results show that the computer self-efficacy of the SME owners as a moderating effect is not supported.

This study has several limitations. First, the samples were restricted to the SMEs of batik in three cities (Yogyakarta, Solo and Pekalongan). It is significant to conduct cross-sector, cross countries, cross-region or even cross-cultural investigations on this subject for better explanations of the results from a global perspective. Studies on cultural differences in switching behavior are supposed to accommodate to different individuals from the SME owner. Second, the study does not differentiate the sizes of enterprises; that is, no test was conducted for small-, medium- and large-size enterprises. The study only focuses on SMEs. Different empirical results may be obtained for different sizes because each enterprise size can have a different condition in e-commerce adoption. Second, this study pays more attention to the product categories of stamped batik and hand-drawn batik. Consumers can have dissimilar favorite channels to purchase other types of batik. Future research should also consider this issue.

Within all the opportunities available through e-commerce (support the information searching behavior, save the travel time and travel cost, better service quality to their customer, a lower price to their customer as well, and increase their sales), the SMEs need to enhance e-commerce activities and put it in their strategy for moving forward. On the other side, the government should have a strong interest in helping and supporting the SME through several activities.

The research confirms that e-commerce adoption may benefit SMEs. It may encourage more SMEs to move from the traditional physical store retailing to e-commerce.

Although this study uses the conceptual model from the study of Chang et al. (2017), significant differences exist between the two studies. This study uses the PPM framework in the context of the seller migratory decision, whereas in most studies, the PPM framework is used in the context of the consumer migratory decision. Moreover, most studies about the adoption of e-commerce by owners of SMEs use the theory of reasoned action, theory of planned behavior, technology acceptance model, technology, organization and environment, and unified theory of acceptance and use of technology as the framework.

Data collection from inbound tourists is a repetitive activity. This paper's main purpose is to show that, unless something useful about the nature of change is being established, repetitious collection of data from, for example, inbound visitors results in ineffective accumulation of data. The paper also aims to elucidate what it means for data to be ineffective for practical application or theory development.

The approach was to examine three years of data from inbound visitors to Taiwan to consider what would make data collection more effective.

Collecting many specific variables relating to travel by inbound tourists can result in recognizing segments and other matters important for applied research or theory development. Analysis shows detailed information can have limited use and high cost when different details apply to different segments. After identifying segments to study, effective information collection can require segment specific questioning, special sampling and segment specific studies.

While various countries conduct special studies, annual collection of a wide variety of information from inbound tourists is a common practice. This research provides new perspectives on why some data collection practices should be modified.

This study examines how professional technicians' teaching styles and students' learning readiness affect cooking skills performance in culinary inheritance.

This study constructed a learning performance model from the situated cognition perspective using a sample of students at universities and vocational colleges on a professional technician course. A total of 4,000 questionnaires were mailed to students, of which 2,018 were returned.

Students regard technical professors as teaching experts and expect them to care for their learning, while professional technicians' knowledge sharing significantly increases students' learning performance. The findings provide insight into professional technicians' teaching styles for academics.

This study focuses on the situated cognition perspective and its correlation with students' learning performance and discusses professional technicians' knowledge sharing as an important influencing factor.

The purpose of this paper is to conceptualise a framework that integrates information quality, system quality, function quality, and social influence based on the information system (IS) success model, to explore the relationship among these factors, which might be the key determinants of Facebook educational usage intention.

An internet survey was conducted to collect empirical data from 221 Facebook users on their experiences of using Facebook. This study applied structural equation modeling (SEM) to demonstrate the proposed model’s construct relations and multiple group analysis.

The results of this study show that social influence and information quality are critical and direct determinants that affect users’ continuous intention to use Facebook in learning; social influence also indirectly affect Facebook usage intention through the mediating effect of information quality. Except the path between social influence and usage intention in age subgroups, the relationships among these determining factors in the proposed model are stable, and there were no significant differences among gender subgroups and age subgroups examined using the multiple group comparison test.

The findings provide a better understanding of the IS success model that influences the Facebook educational usage intention for researchers and practitioners.

The study integrated understanding by design-Internet of Things (UbD-IoT) education with design thinking and computational thinking to plan and design an IoT course. Cross-domain application examples were employed to train students in problem-understanding, deep thinking and logical design for IoT applications.

In this study, the UbD model was integrated with design thinking and computational thinking in the planning and design of an IoT course. The examples of cross-domain applications were used to train students to understand a problem by engaging themselves in deep thinking and helping them think and design logically for an IoT application.

The UbD-IoT learning design greatly decreased students' overall cognitive load. UbD-IoT learning has a significant impact on the performance of computational thinking in problem-solving and problem-understanding. The impact of UbD-IoT learning on logical thinking and program learning cognition in students needs to be verified.

The results of this study have shown that the UbD model is effective in reducing the cognitive load of a learning course and also strengthens T-competencies in the lateral skills of computational thinking, critical problem-solving, logical thinking and creative thinking.

The post-pandemic recognises changes are required; universities need to rethink their e-servicescapes strategies by offering different approaches to enhance students’ learning. This study aims to draw on learning self-efficacy trajectories and propose a conceptual model for exploring the predictive validity of satisfaction. In addition, it explores the mediating role of e-servicescapes and the moderating relationship effect of mature and younger students.

Learning self-efficacies is incorporated into the design of the model in an attempt to understand student cognition. The influences of e-servicescape on adopting online preferences and satisfaction are also examined. The model was empirically validated by surveying 266 respondents. Structural equation modelling and multi-group analysis were used to analyse the data.

The results of this study show learning self-efficacies has no significant influence on satisfaction. Yet, they showed a significant influence on e-servicescapes. E-servicescapes positively influenced satisfaction and preference for adopting online learning. E-servicescapes also had a mediating effect between self-efficacy to complete a course and satisfaction, as well as self-efficacy to interact with instructors and satisfaction. It had a negative suppressed effect on social interaction.

The research makes the following contributions. Firstly, the conceptualised model identifies an association between learning self-efficacies and e-servicescapes, suggesting universities as service providers can maximise the value offerings of their customer assets. Secondly, e-servicescapes demonstrate a full mediating effect between self-efficacies and satisfaction, indicating that if universities are to compete successfully in dynamic markets, they should co-create value in their e-servicescapes domain to increase satisfaction. Thirdly, the study recognises the need for a hybrid system of both face-to-face and online delivery because the multi-group analysis shows mature age preference for online learning is required to make this transformation successful.