Abstract: Abstract Nowadays, university teaching can no longer rely solely on the pillar of traditional teaching, research on new teaching/learning methods is becoming more and more numerous, especially with the integration of new information and communication technologies, which play an important role in our daily lives. In the case of our university, all the algorithmic courses taught in the first year of computer science at our university are face-to-face; our research aims to present the improvements that online adaptive training can bring to the learning style of learners. In particular, in terms of learners’ subjective satisfaction and learning speed and performance. The objective of this research is to find the contribution that problem-based learning can make to the learner’s learning style within a social network. The technique proposed in this paper aims to personalize learning by applying Felder–Silverman’s model of learning styles and intelligent technologies, for example, such as ontology and data mining methods to improve the quality and sustainability of learning. The PBL process does not focus on problem solving with a defined solution, but takes into consideration the improvement of other attractive abilities and qualities. This will include learning, improved collaboration and group communication. PubDate: 2019-02-10 DOI: 10.1007/s12626-019-00032-6
Authors:Apantri Peungnumsai; Apichon Witayangkurn; Masahiko Nagai; Hiroyuki Miyazaki Pages: 21 - 45 Abstract: Abstract Taxis are considered one of the most convenient means of transportation, especially when people have to travel off-route, where public transportation is not a feasible option, and also when they need to reach a destination according to what is most convenient for them. However, many issues exist about taxi services, such as the problems of passengers who are unable to get taxi service at the location of their choice, or problems concerning when they need the taxi service to arrive. These problems may be due to the unavailability of the taxi at that particular location or due to the taxi driver not wanting to provide service. A taxi driver may not want to provide service to a potential passenger, because they may have preferences on the direction and areas they want to go or because of the different types of service zoning. Understanding the behaviors of taxi drivers and the characteristics of the trip/travel might be helpful to solving such issues. In this study, we conducted an analysis from a questionnaire survey and large-scale taxi probe data to understand taxi service behavior, travel characteristics, and to discover taxi service zoning characteristics. As a result, four types of taxi service zones including isolated zones, interactive zones, special service zones, and target zones were encountered. Travel characteristics were calculated and analyzed at different criteria, such as weekdays, weekends, and various time windows in a single day. The result of these characteristics was explained according to their similarities and dissimilarities in each type of zone. The discovery of the different zones and their respective definitions might be a good initiative for further development of a policy for taxi drivers to provide better service for passengers. PubDate: 2018-06-01 DOI: 10.1007/s12626-018-0019-4 Issue No:Vol. 12, No. 1 (2018)
Authors:Takeshi Morita; Kodai Nakamura; Hiroki Komatsushiro; Takahira Yamaguchi Pages: 71 - 96 Abstract: Abstract Although AI and service robot applications have become very popular in many domains recently, many of them are specific applications and it is still difficult to develop integrated intelligent applications such as a robot teahouse and teaching assistant robots. To develop such integrated intelligent applications, we need integrated intelligent application platforms that have AI integration and agile process facilities. From the above background, we are currently developing PRactical INTElligent aPplicationS (PRINTEPS), which is a platform for developing integrated intelligent applications by combining only five types of modules, namely knowledge-based reasoning, spoken dialogue, image sensing, motion management, and machine learning. This paper proposes a workflow editor in PRINETPS based on a service-oriented architecture and a Robot Operating System that enables real-time parallel processing for multiple robots and sensors by integrating the five types of modules. The editor also supports not only developers but also domain experts in updating workflows frequently. This paper also proposes a novel method to integrate signals acquired through image sensing with knowledge (ontologies and business rules) using C-SPARQL and Semantic Web Rule Language. To evaluate PRINTEPS, we developed a robot teahouse application including customer reception and guidance to table services using a humanoid robot with PRINTEPS. Through this case study, we demonstrated that the behaviors of the robot can be modified by changing the workflow, the ontology, and the rules. PubDate: 2018-06-01 DOI: 10.1007/s12626-018-0020-y Issue No:Vol. 12, No. 1 (2018)
Authors:Takeshi Morita; Shunsuke Akashiba; Chihiro Nishimoto; Naoya Takahashi; Reiji Kukihara; Misae Kuwayama; Takahira Yamaguchi Pages: 97 - 126 Abstract: Abstract To support elementary school teachers in teaching by encouraging active learning while maintaining the interest of pupils, this study focuses on supporting teaching, learning, and monitoring the progress of students through a Teacher–Robot collaboration lesson application using not only laptops and tablets, but also robots and sensors. Since developing a lesson application is time consuming for teachers, we have developed an integrated intelligent application development platform named PRactical INTElligent aPplicationS (PRINTEPS) to aid Teacher–Robot collaboration. However, several functions and interfaces for education are missing. Therefore, in this study, we extend several functions for education to PRINTEPS. In addition, since it is necessary in learning and monitoring the progress of students to present learning content suitable to each pupil’s level of understanding, we also have provided support through the use of a tablet quiz system based on ontologies and rule bases. In the case study, we developed a Teacher–Robot collaboration lesson application and conducted lessons for sixth-grade pupils at an elementary school. From the case study, we have confirmed the effectiveness of our platform and the application. PubDate: 2018-06-01 DOI: 10.1007/s12626-018-0021-x Issue No:Vol. 12, No. 1 (2018)
Abstract: Abstract This study investigates the determinant role of the cross-border movement of skilled labor in the expansion of service trade between the US, and both developed and developing countries. For this purpose, we employ the key concepts of network theory as an analytical framework and conduct panel data analysis and graphical modeling analysis for 31 countries from 1999 to 2008. In this decade, offshore outsourcing in the service trade took off worldwide. We use data for each country’s service exports to the US, number of H-1B visas issued, GNI per-capita, network readiness index, and an English dummy for the official language. We illustrate the trajectory and interactions between these factors. These analyses yield three observations. First, service trade with the US is more intensive among higher income countries. Second, the number of H-1B visas issued has a positive effect on service exports to the US. Third, individuals in lower income countries tend to desire H-1B visas and create intensive skilled labor networks with the US, the path through which developing countries such as India expanded their service exports to the US. PubDate: 2018-12-01 DOI: 10.1007/s12626-018-0028-3
Abstract: Abstract This article focuses on a new approach for personal identification by exploring the features of pedestrian behavior. The recent progress of a motion capture sensor system enables personal identification using human behavioral data observed from the sensor. Kinect is a motion sensing input device developed by Microsoft for Xbox 360 and Xbox One. Personal identification using the Microsoft Kinect sensor (hereafter referred to as Kinect) is presented in this study. Kinect is used to estimate body sizes and the walking behaviors of pedestrians. Body sizes such as height and width, and walking behavior such as joint angles and stride lengths, for example, are used as explanatory variables for personal identification. An algorithm for the personal identification of pedestrians is defined by a traditional neural network and by a support vector machine. In the numerical experiments, pictures of body sizes and the walking behaviors are captured from fifteen examinees through Kinect. The walking direction of pedestrians was specified as 0°, 90°, 180°, and 225°, and then the accuracies were compared. The results indicate that identification accuracy was best when the walking direction was 180°. In addition, the accuracy of the vector machine was better than that of the neural network. PubDate: 2018-12-01 DOI: 10.1007/s12626-018-0026-5
Abstract: Abstract Several academic social networks have emerged to help researchers who need to search for documents relevant to their interests. The recommendation has been adopted in many websites to suggest relevant documents to users according to their profiles. However, many academic social networks and digital libraries still lack recommendations. In this paper, we propose a new document recommendation approach for the academic social bookmarking website: Bibsonomy. In our method, we use a community detection technique to identify related users. Then, for each target user, the recommended documents are selected from their learning communities. Experimental results show that the proposed method performs better than state-of-the-art recommendation methods. PubDate: 2018-12-01 DOI: 10.1007/s12626-018-0024-7
Abstract: Abstract When a large-scale disaster hits a community, especially a water-related disaster, there is a scarcity of automobiles and a sudden increase in the demand for used cars in the damaged areas. This paper conducts a case study of a recent massive natural disaster, the Great East Japan Earthquake and Tsunami of 2011 to understand those car scarcities and demand in the aftermath of the catastrophe. We analyze the reasons for the increase in demand for used cars and how social media can predict people’s demand for used automobiles. In other words, this paper explores whether social media data can be used as a sensor of socio-economic recovery status in damaged areas during large-scale water-related disaster-recovery phases. For this purpose, we use social media communication as a proxy for estimating indicators of people’s activities in the real world. This study conducts both qualitative analysis and quantitative analysis. For the qualitative research, we carry out semi-structured interviews with used-car dealers in the tsunami-stricken area and unveil why people in the area demanded used cars. For the quantitative analysis, we collected Facebook page communication data and used-car market data before and after the Great East Japan Earthquake and Tsunami of 2011. By combining and analyzing these two types of data, we find that social media communication correlates with people’s activities in the real world. Furthermore, this study suggests that different types of communication on social media have different types of correlations with people’s activities. More precisely, we find that social media communication related to people’s activities for rebuilding and for emotional support is positively correlated with the demand for used cars after the Great East Japan Earthquake and Tsunami. On the other hand, communication about anxiety and information seeking correlates negatively with the demand for used cars. PubDate: 2018-12-01 DOI: 10.1007/s12626-018-0025-6
Abstract: Abstract Graph-based entropy, an index of the diversity of events in their distribution to parts of a co-occurrence graph, is proposed for detecting signs of structural changes in the data that are informative in explaining latent dynamics of consumers’ behavior. For obtaining graph-based entropy, connected sub-graphs are first obtained from the graph of co-occurrences of items in the data. Then, the distribution of items occurring in events in the data to these sub-graphs is reflected on the value of graph-based entropy. For the data on the position of sale, a change in this value is regarded as a sign of the appearance, the separation, the disappearance, or the uniting of consumers’ interests. These phenomena are regarded as the signs of dynamic changes in consumers’ behavior that may be the effects of external events and information. Experiments show that graph-based entropy outperforms baseline methods that can be used for change detection, in explaining substantial changes and their signs in consumers’ preference of items in supermarket stores. PubDate: 2018-12-01 DOI: 10.1007/s12626-018-0023-8
Abstract: Abstract In this study, we carry out an empirical analysis on how electronic word-of-mouth (hereinafter “e-WOM”) marketing on e-WOM websites and electronic-commerce websites on the Internet boosts consumption on a macro-level. In our analysis, we conduct a model analysis of consumer behavior using data composed of more than 30,000 questionnaire surveys and quantitatively find the elasticity coefficient of the boost to consumption by performing a two-step GMM (generalized method of moments), which uses instrumental variables. The results of the analysis show e-WOM significantly increased expenditures in six fields: computers, electrical appliances, etc.; music; hobbies; clothing, accessories, etc.; beauty products, etc.; and goods for everyday life, etc. Furthermore, there was no field that had a significantly negative value. These results showed that, in the majority of the target fields, e-WOM had not only the effect of winning customers from the competition, but also the effect of boosting consumption on a macro-level. In addition, even from people’s subjective evaluations, there were many in all the generational groups who said that e-WOM boosted expenditures. PubDate: 2018-12-01 DOI: 10.1007/s12626-018-0027-4
Abstract: Abstract This study examines the influence of the valence of online customer reviews on sales outcomes based on prospect theory. Numerous studies have revealed the importance of customer reviews in online marketing. However, only few studies have explored the impact of online customer reviews on sales outcomes in the dynamic process. Prior studies in behavioral economics literature have indicated that people differently value gains and losses and that losses have more emotional impact than an equivalent amount of gains. This study verifies whether prospect theory applies to the relation between online customer reviews and sales outcomes. Relevant data were collected from Amazon.co.jp, and three statistical models were employed to investigate the relation between the two factors. Major findings confirm that negative customer reviews considerably impact online sales than positive reviews. Furthermore, the findings indicate that the marginal effects of positive and negative reviews decrease with the increase in their volume. The results of this study will enable marketers to compare the relative sales effects of different types of customer reviews and improve the effectiveness of customer service management. PubDate: 2018-12-01 DOI: 10.1007/s12626-018-0022-9
Authors:Takahiro Nishigaki; Katsumi Nitta; Takashi Onoda Abstract: Abstract In this paper, we propose an interactive constrained independent topic analysis in text data mining. Independent topic analysis (ITA) is a method for extracting independent topics from document data using independent component analysis. In this independent topic analysis, the most independent topics between each topic are extracted. By extracting the independent topic, managing documents with a large number of text data is easy with document access support systems and document management systems. However, the topics extracted by ITA are often different from the topics a user requests. For the system to be of service to users, an interactive system that reflects the user’s requests is necessary. Thus, we propose an interactive ITA that works for the user. For example, if there are three topics, i.e., topic A, topic B, and topic C, and a user choose the content from topics A and B, a user can merge those topics into one topic D. In addition, if a user wants to analyze topic A in more detail, a user could separate topic A into topics E and topic F. To that end, we define Merge Link constraints and Separate Link constraints as user requests. The Merge Link constraint is a constraint that merges two topics into one topic. The Separate Link constraint is a constraint that separates two topics from one topic. In this paper, we propose a method for extracting a highly independent topic that meets these constraints. We conducted evaluation experiments on our proposed methods, and obtained results to show the effectiveness of our approach. PubDate: 2018-04-26 DOI: 10.1007/s12626-018-0018-5
Authors:Georgios Lappas; Amalia Triantafillidou; Anastasia Deligiaouri; Alexandros Kleftodimos Abstract: Abstract This paper analyzes the communication strategies used by Greek local governments through the utilization of Web 2.0 technologies, specifically Facebook, and the effectiveness of these strategies in relation to citizens’ online engagement. More specifically, it examines Facebook communication strategies and levels of citizens’ engagement. For this purpose, we conducted a content analysis on the active and official Facebook pages of local municipalities in Greece from January 2017 until the end of September 2017. Our results suggest a rise in the percentage of active Facebook pages maintained by local governments in comparison to our 2014 study. Our results also show that local governments in Greece are using Facebook in a predominantly top-down manner to promote events organized by the municipality and to push one-way information to citizens about their services and actions. Local authorities have, however, made significant progress in relation to posts that support transparency and accountability and that enhance or mobilize citizens’ participation. Our evaluation of local government Facebook strategies indicates that marketing the municipality to external public, such as tourists, and providing information about services are effective strategies that drive citizens’ online attitude expression (liking), engagement (commenting), and advocacy behavior (sharing). According to our analysis, local governments in Greece prefer the strategies that we found to be the least engaging. In addition, our study provides interesting details of how specific characteristics and modes of Facebook messages (photos, videos, URLs, hashtags, and mentions) impact on citizens’ engagement. Finally, our results provide valuable insights for social media managers in local government who aim to increase the impact of their municipal Facebook pages. PubDate: 2018-03-29 DOI: 10.1007/s12626-018-0017-6
Authors:Natsuki Sano; Yuki Mori; Tomomichi Suzuki Pages: 173 - 183 Abstract: Abstract In manufacturing industries, product inspection is automated and the use of image data is increasingly being employed for defect detection. A manufacturing company in Japan produces an item and inspects the produced products using image data. Reducing the error rate is important in product inspection because poor inspection of products might lead to the delivery of defective products to consumers (consumer’s risk) and strict inspection increases production cost (producer’s risk). To reduce the error rate, we highlighted fault points using a two-dimensional moving range filter and discriminated defect production through a unanimous vote among Mahalanobis classifiers for each color component. For results, we achieved a lower error rate than the current system. This research is an empirical study of how to use image data in defect detection. PubDate: 2017-12-01 DOI: 10.1007/s12626-017-0015-0 Issue No:Vol. 11, No. 2 (2017)
Authors:Xuanang Feng; Yi Zuo; Eisuke Kita; Fumiya Saito Pages: 201 - 215 Abstract: Abstract This article proposes a new approach to personal authentication by exploring the features of a person’s face and voice. Microsoft’s Kinect sensor is used for facial and voice recognition. Parts of the face including the eyes, nose, and mouth, etc., are analyzed as position vectors. For voice recognition, a Kinect microphone array is adopted to record personal voices. Mel-frequency cepstrum coefficients, logarithmic power, and related values involved in the analysis of personal voice are also estimated from the voices. Neural networks,support vector machines and principal components analysis are employed and compared for personal authentication. To achieve accurate results, 20 examinees were selected for face and voice data used for training the authentication models. The experimental results show that the best accuracy is achieved when the model is trained by a support vector machine using both facial and voice features. PubDate: 2017-12-01 DOI: 10.1007/s12626-017-0010-5 Issue No:Vol. 11, No. 2 (2017)
Authors:Masanari Oishi; Norihito Seki; Hiroki Kondo Abstract: Abstract The authors propose the effectiveness of Facebook functions in the promotion of career education. In recent years, career education in Japanese universities has differed slightly from that in other countries. Japanese students are trained to be competitive in the job-hunting process; they need to obtain the technical skills and knowledge necessary to pass a company entrance examination or a university oral interview. This practice is in stark contrast with the intrinsic meaning of vocational/career education, which is the process by which students acquire the abilities and independence required by a certain industry. This meaning is manifested in the purpose of the career education program of Hokkai-Gakuen University’s Faculty of Business Administration. The program’s purpose is to foster independence in its students rather than the acquisition of skills for the job-hunting process. The professional independence of every student is important to their career development after graduating from the university. On the other hand, it is known that e-portfolios generally encourage students to record and assess their activities. To promote the activities that students tackle in the program, we introduced an e-portfolio using Facebook. This study shows the characteristics and achievements of our e-portfolio. PubDate: 2017-11-13 DOI: 10.1007/s12626-017-0011-4
Hybrid journal (It can contain Open Access articles)
