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One of the ultimate goals of the learning process is the success of student learning. Using data and students' achievement with machine learning to predict the success of student learning will be a crucial contribution to everyone involved in determining appropriate strategies to help students perform. The selected 11 research articles were chosen using the inclusion criteria from 2753 articles from the IEEE Access and Science Direct database that was dated within 2019-2021 and 285 articles that were research articles. This study found that the classification machine learning algorithm was most often used in predicting the success of students' learning. Four algorithms that were used most often to predict the success of students' learning are ANN, Naïve Bayes, Logistic Regression, SVM and Decision Tree. Meanwhile, the data used in these research articles predominantly classified students' success in learning into two or three categories which are pass/fail; or fail/pass/excellent.

In recent years, neural networks have attracted much attention in the machine learning and the deep learning technologies. Bio-inspired functions and intelligence are also expected to process efficiently and improve existing technologies. In the visual pathway, the prominent features consist of nonlinear characteristics of squaring and rectification functions observed in the retinal and visual cortex networks, respectively. Further, adaptation is an important feature to activate the biological systems, efficiently. Recently, to overcome short-comings of the deep learning techniques, orthogonality for the weights in the networks has been developed for the signal propagation and the efficient optimization of the learning. In this paper, bio-inspired asymmetric networks with nonlinear characteristics are proposed, which are derived from the retinal networks in the biological visual pathway. The asymmetric network proposed here was verified to detect the movement of the object, efficiently in our previous studies. This paper shows a new characteristic of the adaptive orthogonality in the asymmetric networks. First, it is shown that the asymmetric network with nonlinear characteristics is effective for generating orthogonality. Second, the proposed asymmetric network with Gabor filters is compared with the conventional energy model from the point of the orthogonality characteristics. Finally, the asymmetric networks with nonlinear characteristics can generate the extended orthogonal bases in independent subspaces, which are useful for classification and efficient learning.

XYZ is a company engaged in the port sector. To support the company’s business processes, XYZ uses two applications to carry out operational activities, namely the CARTOS application to manage invoices and the Finance application to record company costs and revenues. To produce a cost accounting report, XYZ is still processing and visualizing it manually with data sources from the two applications mentioned earlier. This resulted in quite a long time processing data into information. So that reporting to management cannot be done in real time. Therefore XYZ needs a system that can help management to analyze and manage data into information in real time. The Business Intelligence (BI) method is one of the solutions for company needs, especially in analyzing and providing access to data to help make better decisions. This study discusses the design and implementation of business intelligence solutions ranging from architecture, data warehouse, ETL processes and visualization in the form of a dashboard in accordance with the needs of XYZ. The method used in developing business intelligence dashboards refers to the executive information system life cycle method which consists of justification, planning, business analysis, design, construction, and dissemination. The results of this research are dashboard visualization using the Power BI tool that displays information and knowledge needed in the monitoring process and becomes material to produce management decisions related to cost accounting reports.

Implications of sensor technology on new product introduction requires critical decisions on divergent marketing and operational aspects. In this paper, we employed the Bass model for a new product that used the sensor technology diffusion from the perspective of the Wagner-Whitin lot-sizing model which discusses this matter related to suitability of sensor technology on the market and operational dimensions. The objective of this study is to propose an uncertain fuzzy approach to specify the new product that applied the sensor technology introduction’s optimum time, price, production scheduling, and rate simultaneously. This model will be applied to analyze the impact of sensor technology diffusion on the market acceptance and some operational parameters, for instance, total customer population, price elasticities, startup and maintenance costs, the unit’s variable cost and research and development costs on optimized benefit, and the product’s optimized lifespan. In this experiment, we have inspiration from the version of the Sale et al. (2017) model which considers uncertainty by using fuzzy triangular numbers and performing the alpha cut method. Moreover, in this research, variable cost is considered as a Cobb-Douglas function. Initially, in Research Methodology, mathematical modeling is applied, wherein utilizing simulation and the experimental design method, data were generated. Eventually, using LINGO optimization software, the problem was solved, and for further examinations considering the existence of various parameters, design of experiment (DoE) by Design-Expert 8 software and response surface methodology was adopted to analyze and optimize the problem’s parameters. The results indicated that the objective function’s climax occurs when the higher limit of alpha being 0.7 is assumed; hence, the optimum state of demand belongs to this amount of alpha.

This study is aimed to analyze success of the Enterprise Resource Planning (ERP) System Merging in Chemical Company Singapore that acquired two companies. The success component of ERP system success is using DeLone and McLean success model with qualitative method. The research methodology used detail interview with project implementation team, ERP consultants (8 informants) to get more detail from ERP system merging with information and collected supporting data from the ERP system itself. The result shows that ERP System Merging succeed to increase the system quality of Chemical Company which acquired two companies into one ERP system. It was depicted by the increment of easiness on using the system. The information much more integrated and accurate after the ERP system merging. Meanwhile service quality was increased because of all incidents now monitored in one efficient log system and handled by experienced IT application support team.

Generation of useful variables and features is an important issue throughout the machine learning, artificial intelligence, and applied fields for their efficient computations. In this paper, the nearest neighbor relations are proposed for the minimal generation and the reduced variables of the functions in the threshold networks. First, the nearest neighbor relations are shown to be minimal and inherited for threshold functions and they play an important role in the iterative generation of the Chow parameters. Further, they give a solution for the Chow parameters problem. Second, convex cones are made of the nearest neighbor relations for the generation of the reduced variables. Then the edges of convex cones are compared for the discrimination of variables. Finally, the reduced variables based on the nearest neighbor relations are shown to be useful for documents classification.

The rapid proliferation of smartphone-mounted multiple sensors has been accompa-nied by the increasing utilization of participatory sensing, which is a type of crowdsourcing by which many users effectively share sensing data. Privacy protection is important for this purpose because the sensing data often contain private infor-mation about the users. Existing privacy protection methods do not enable effective and precise data restoration in this application when there is a large number of choices and few data. In this study, we developed a method for addressing this issue. The randomized response method and negative survey method are used to conceal private information contained in individual data by the addition of random noise to the data. Moreover, the proposed method utilizes a novel procedure whereby the transmission is repeated multiple times when selecting one option from multiple options. The pro-posed method was evaluated by simulation and was found to be more effective than existing methods.

The illegal dumping of garbage, flooding, and embankment and bridge failures are some of the common problems related to rivers. To be able to tackle these issues effectively, it is necessary to understand and respond to them with speed. In addition, future measures are required. However, since river basins can be very large, it is difficult for the river management staff to notice and respond to all river-related issues promptly. In order to improve the system used in Japan for monitoring the areas around rivers, we collaborated with the Ministry of Land, Infrastructure and Transport Chubu Regional Development Bureau Shonai River Office. In particular, to enable river administrators to quickly understand the issues occurring around rivers and to help them resolve these issues quickly, we developed a River Information Management System (RIMS) that promotes information sharing by the local residents through smartphones. This RIMS consists of a River Information Application (RIA) and a Post Management System (PMS). The RIA is an application for posting river-related problems using a smartphone. On the other hand, the PMS can be used by the river administrators to view the problems posted and respond to them. The developed system was tested successfully by the river ad-ministrators and patrol staff of the river office in the Shonai River basin.

In this paper, we analyzed and examined review data which is in various languages of foreign visitors to a local city where is Hamamatsu city, Shizuoka prefecture, Japan. Target data were in the categories of "hotel" and "tourist spots" in multilingual in Chinese and English. And the word appearance frequency and the result of emotion analysis were obtained from review data by using NLPIR which is a morphological analysis tool. By conducting knowledge discovery, the characteristics and differences of foreign travelers visiting local cities by nationality are clarified. By the method used in this study, local cities can increase the marketing ability to attract foreign tourists.

The implementation of an information system that supports company goals is the main strategy of an organization. But aligning business strategies with information system(IS) and information technology(IT) is not as easy as it seems, because there are several gaps of strategies between upper level and practical level. Often the focus in system development is only on the architecture of the future system, even though the study says that the engineering model of needs is the most important thing in the process of developing the company’s system. PT. SBS is a distributor and supplier company. Along with the development of its business, business processes also become more complex. The information system that was originally felt to be sufficient is considered to be no longer optimal so that it often results in delays in delivery with a fairly large percentage. Therefore, an Enterprise Resources Planning(ERP) system will be developed but it must be ensured that the business processes used are oriented towards organizational goals. The purpose of this study is to introduce and explain the stages of the Organization Goal-Oriented Requirement Engineering (OGORE) method as a requirement engineering method in a company’s business processes that focuses on organizational goals. The research method was done by collecting business process data and defining key performance indicators(KPIs) in a small discussion group with stakeholders in the company. The results of this method were Goal Tree Model (GTM) diagrams which was then used as a reference in describing new business processes and in preparing the requirements specification documents. The conclusion obtained that the stages of the OGORE method are able to eliminate needs according to the organization’s goals. It is also recommended to use the OGORE method as one of the requirements management steps in the Enterprise Architecture method to create new method as an agenda for the future.

Generation of useful variables in the features spaces is an important issue throughout the neural networks, the machine learning and artificial intelligence for their efficient and discriminative computations. In this paper, the nearest neighbor relations are proposed for the minimal generation and the reduced variables for the feature spaces. First, the nearest neighbor relations are shown to be minimal independent and inherited for the construction of the feature space. For the analysis, convex cones are made of the nearest neighbor relations, which are independent vectors for the generation of the reduced variables. Then, edges of convex cones are compared for the discrimination of variables. Finally, feature spaces with the reduced variables based on the nearest neighbor relations are shown to be useful for the real documents classification.

The security system in monitoring the room or something suspicious activity that can cause crimes in the field of information and technology as in private homes is indispensable. Aims to keep valuables from theft and loved ones like babies from kidnapping or reducing the risk of an accident in an unguarded infant activity. The use of CCTV still has constraints because some functions are still done manually such as should always move the record of the CCTV data every day to different memory so that there is waste in using memory. Moreover, the position of the camera can not be adjusted freely in the placement so that it can easily be destroyed by irresponsible people, and also ordinary CCTV needs electricity that is considerable in its use. This research is done to improve and facilitate the process of monitoring of baby activity and the room where the baby is called sleep or rest, all monitoring activities can be done using only a Web browser that can be accessed by a smartphone or desktop. The monitoring system is created using a program called RPi Cam that is installed on the Raspberry Pi with a Raspberry Camera module as a monitoring camera and a DHT22 sensor module as a room temperature monitor.

Introduction : Social Big data is generated by interactions of connected users on social network. Sharing of opinions and contents amongst users, reviews of users for products, result in Social Big data. If any user intends to select product such as movies, books etc. from e-commerce sites or view any topic or opinion on social networking sites, there are a lot of options and these options result in information overload. Case Description : Social recommendation systems assist users to make better selection as per their likings. Recent research works have improved recommendation systems by using matrix factorization, social regularization or social trust inference. Furthermore, these improved systems are able to alleviate cold start and sparsity but not efficient for scalability. Discussion and Evaluation: The main focus of this paper is to improve scalability and provide better recommendations to users with large-scale data in less response time. We have partitioned social big graph and distributed it on different nodes based on Mahout and PowerGraph like system. Conclusion : In our approach, partitioning is based on direct as well as indirect trust between users and comparison with state-of-the-art approaches proves that statistically better partitioning quality is achieved using our approach. In our proposed approach ScaleRec, hyperedge and transitive closure are used to enhance social trust amongst users. Experiment analysis on standard datasets proves that better locality and recommendation accuracy is achieved by using our proposed approach.

Tourist movement studies have been carried out for understanding tourists decisions for visiting and sightseeing. Knowing tourist interests and wayfinding decision-making affect tourists routes and facilities since the planners and hotel facilities will do planning their hospitality and every service plans using their information. To make the model of the tourist movements, an effective mathematical description will be expected for their systematic analysis. In this paper, Markov process model of the tourist movements are newly developed using information theory. Then, it is shown that the order of Markov process of the movements is estimated using conditional entropies, efficiently and the shuffling operation of Markov process is newly proposed to verify conditional entropies of the Markov process. The stochastic simulation model based on the analysis is useful for the verification of the Markov process with the estimated order of the behavior of tourists movement.

This study discusses the importance of networking, venue, and tourism resources of the destination in international convention. This study also considers differences between international and domestic attendees. To clarify the research objective, the questionnaire survey was conducted at the 8th International Congress on Advanced Applied Informatics at Toyama International Conference Center on July 7-12, 2019 and the 13th International Meeting on Electrochromism at Chiba University on Aug 27-31, 2018. The target population in the present study consists of attendees of two international conventions. During the international conventions, researchers collected 237 questionnaires. Totally, the mean score of international attendees is higher than that of domestic attendees, so international attendees are looking forward to having networking, venue and tourism resource in Japan. In the binary regression analysis, there are clear differences between international and domestic attendees in networking. The results of the binary logistic regression analysis show that international attendees regard ‘welcome reception party’, ‘coffee break’, and ‘excursion’ as places where the attendees exchange each other. On the other hand, domestic attendees prefer farewell reception party’ to welcome reception party’, ‘coffee break’, and ‘excursion.

This study aims to assist resource management and the project controller at Port Harbor Company. Port Harbor Company is an IT Consulting. Problems that often occur in IT Consulting are related to the project cost, resource management and control of each project. Problems that occur at the Port Harbor Company are poor resource management, spending costs that exceed a predetermined budget and how to see the status of ongoing projects. Using Business Intelligence and the dashboard as a front end will help the project controller and resource management manage resources, manage project costs and monitor ongoing projects. In this study, the development and implementation of Business Intelligence and dashboards using the ASAP method are expected to be more structured and can solve the Port Harbor Company problem.

Tourist movement studies have been carried out for understanding tourists decisions for visiting and sightseeing. Knowing tourist interests and wayfinding decision-making affect tourists routes and facilities since the planners and hotel facilities will do planning their hospitality and every service plans using their information. To make the model of the tourist movements, an effective mathematical description will be expected for their systematic analysis. In this paper, Markov process model of the tourist movements are newly developed using information theory. Then, it is shown that the order of Markov process of the movements is estimated using conditional entropies, efficiently and the shuffling operation of Markov process is newly proposed to verify conditional entropies of the Markov process. The stochastic simulation model based on the analysis is useful for the verification of the Markov process with the estimated order of the behavior of tourists movement.

Purpose This paper aims to present a preliminary experimental result on a large-scale experiment on a cyber-physical hybrid discussion support environment in a panel discussion session in an international conference. Design/methodology/approach In this paper, the authors propose a hybrid (cyber-physical) environment in which people can discuss online and also offline simultaneously. The authors conducted a large-scale experiment in a panel discussion session in an international conference where participants can discuss by using their online discussion support system and by physical communications as usual. Findings The authors analyzed the obtained date from the following three viewpoints: participants’ cyber-physical attention, keywords cyber-physical linkage and cyber-physical discussion flow. These three viewpoints indicate that the methodology of the authors can be effective to support hybrid large-scale discussions. Originality/value Online large-scale discussion has been focused as a new methodology that enable people to discuss, argue and make consensus in terms of political issues, social complex problems (like climate change), city planning and so on. In several cases, the authors found that online discussions are very effective to gather people opinions and discussions so far. Moreover, this paper proposes a hybrid (cyber-physical) environment in which people can discuss online and also offline simultaneously.

Revitalization of local cities is one of the major issues for Japan. The international convention can attract foreign participants to the venue and increase the local economic ripple effect. Therefore, by questionnaires investigation for the interests and expectations of participants, we clarify the needs of participants and present it to local cities / bureaus as reference for planning and developing international conference venues. The results show that respondents are interested in sightseeing local tourist sites, so local government should play an important role in making strategy for repeat visitation of foreign visitors.

International conferences have a great economic ripple effect. International conferences can also attract many foreign participants to the area where the conference is held. In terms of the amount of consumption for one trip to Japan, the participants in the international conference are about twice. Furthermore, the participants of the international conference will stay more days than general foreign tourists. Under such circumstances, it is known that the attraction of international conferences is intensifying the competition of attraction with foreign countries and cities. In order to win such competition, analysis was tried from the marketing point of view. In this paper, we conducted an awareness survey using questionnaires to participants in the international conference and analyzed it. As a result, the purpose of the conference participation was clarified. Then, participants with high sense of purpose were extracted from all participants, and social events and meeting places expected were clarified. Also, by analyzing the foreign participants' motivation for visiting Japan, we clarified the expectations and motivations of the foreign participants.

This paper proposes new visualization based on distance between persons, which are defined with Normalized Restricted Dynamic Time Warping. In the visualization persons are located based on their distances that are defined by their movement histories with t-SNE. In experiments we visualize academic conference participants with our proposed method and confirm that the proposed method helps us to find participants moving together.

This paper trying to create something new regarding the online game marketplace for producing an integrated marketplace with several combined genre and categories of games. The primary purpose of this research is to develop e-commerce for online games and explain the benefit that people can get from it. This research focuses on building an online marketplace based on a website that can provide an opportunity to do it transaction related to a specific game. Mainly, the online games marketplace quality will be based on user satisfaction and user recommendation from the previous research. Meanwhile, these satisfaction level include four dimensions that decide the perceived value of the user reason for purchasing an online games item, which are functional value, emotional value, monetary value, and social value. From that information, we build a marketplace for online games item to satisfy the user requirement and also benefiting with its advantages. We also provide the difference between e-commerce mainly with our proposed e-commerce for online games item. The results will be a full-fledged web-based application for online games item marketplace. This paper will be an opportunity to further development of online games marketplace for the growth of online games transaction.

Discussions related to the Digital Banking (DB) transformation has become the main issues in the industry nowadays. Digital disruption has changed the way peoples do business and perform transactions. However, the bankers still found many problems when performing DB transformation. Main issues on DB transformation are that many banks still assume that digital transformation is about workflows and systems rather than focus on customer experience. Nowadays, Artificial Intelligence (AI) and Big Data Analytics (BDA) have risen and played as an important role in the new banking era. The recent trend of AI and BDA enable banking to be more customer-centric based on data driven. Personalization service becoming an important strategy for leveraging the existing customer engagement, and attracting potential customer become new customers. This study explores the application of AI and BDA in banking for leveraging customer experience. This study used literature review and interviews to gather the data. We interview more than some persons in Indonesia banking industry to get the insight on the implementation of AI and BDA in Indonesia. The paper reveals best practices of the global banking and Indonesian banking, in the implementation of AI & BDA. The contributions of this study are proposed enterprise architecture and recommended digital innovation in AI and BDA that enables banking institutions to leverage customer experiences.

This study is to clarify what kinds of factors are important to attract international conventions for Japanese researchers. Moreover, this study discusses the differences between those who have hosted international convention and those who are willing to host international convention in the future by using machine learning. Even though Japanese government has begun MICE promotion activities, researches on MICE industry are still limited and just get started in Japan. In analysis of the data, respondents are classified into 2 groups; those who have hosted international convention as experienced group and those who are willing to host international convention in the future as non-experienced group. A machine learning was used to analyze the difference of perspectives on the importance of site selection criteria between those who have hosted international convention and those who are willing to host international convention in the future. The results of machine learning show the differences between those who have hosted international conventions and those who are willing to host international conventions in the future.

From industrial viewpoint, the international conference has a significant economic impact for the region where the conference takes place. Participants at international conferences will spend more days than tourists or visitors for other purposes. Many different stakeholders are involved in the convention industry as it is an basic factor in promoting inbound tourism in Japan. Japanese governmental agency JNTO takes an important role of promoting to attract international conference. In this paper, 2427 samples are collected for evaluation effective elements to number of participants, which is include the name of the conference, venue, prefecture / city, the number of participants, etc., then, the chi-square test was adopted to clarify the relationship with participants. From the perspective of attracting international conferences, we analyzed the cities and venues where many foreign participants are coming. As a result, it become clear that there was an association among the participants, the venue and the host city. For international conference organizers, the choice of a venue and a host city is one of the most important factors for the success of the conference. Furthermore, it was found that the other factors considered were hardly related. On the other hand, it has also become clear that certain venues may exhibit outstanding performance.

The issues that relate with the automatics and intelligent tracing of the transaction and banking customer become the main issues nowadays. Whereas most of transaction that already moved to digital and online transaction that needed more intelligent features on the Predictive Analyst. The rise of predictive analytics (PA) is one of the biggest disruptions in financial services. In the last years, PA methods grew sharply to give the baseline of data driven decision-making process for forecasting future business situation. PA uses various algorithms to discover different patterns in the big data environment that might create more value for businesses including in financial institutions. The potential implementation of data science in financial industry is still to be explored. In this paper, we summarize work done on PA at financial industry. We also explore the potential application of PA and investigating how data science and big data is going to be used in financial institutions in the future.

Neural networks researches are developed for the recent machine learnings. To improve the performance of the neural networks, the biological inspired neural networks are often studied. Models for motion processing in the biological systems have been used, which consist of the symmetric networks with quadrature functions of Gabor filters. This paper proposes a model of the bio-inspired asymmetric neural networks, which shows excellent ability of the movement detection. The prominent features are the nonlinear characteristics as the squaring and rectification functions, which are observed in the retinal and visual cortex networks. In this paper, the proposed asymmetric network with Gabor filters and the conventional energy model are analyzed from the orthogonality characteristics. It is shown that the biological asymmetric network is effective for generating the orthogonality function using the network correlation computations. Further, the asymmetric networks with nonlinear characteristics are able to generate independent subspaces, which will be useful for the creation of features spaces and efficient computations in the learning.

Programming languages are vital components of the computer industry in the world today. There are many different programming languages which do not address which language performs the best and more efficiency than the other programming languages. In this paper we present a couple of different algorithms which we tested with a couple of different programming languages. This helps us out by a functional standpoint on which language is the better one. We report the results of the experiment by comparing the results that we have gotten from each of the programming languages. Our results show which programming language is the better suited for each of the algorithms that we tested.

Convention industry produces great economic impact because, when a conference held, delegates stay longer than pleasure travelers with other purposes. Many different stakeholders are involved in convention industry as it is an essential factor in promoting inbound tourism in Japan. This study focuses on the evaluation of convention bureau, taking into account its regional characteristics and convention facilities. The questionnaire survey was conducted at the 24th international Meetings Expo (IME 2014) held on December 9-10, 2014, at the Tokyo International Forum, Japan. Researchers distributed questionnaires directly to the convention bureaus during the IME 2014. The respondents' evaluation about their region and convention center was measured and also, the binary logistic regression was adopted to clarify how the duration of service affect their evaluation. This model is utilized in the case of a situation where mainly two possible results are expected. The results showed that there were some significant difference in duration of service.

To get more benefit, most of all organizations gather and analyze various data. Especially, these systems work well in profit-making organizations. In recent years, universities which are permanently voluntary organizations became active in order to know themselves. However, there are no such systems in temporary voluntary organizations. Therefore, these organizations cannot always decide something correctly. In this paper, we not only design a mechanism to solve this problem occurred in temporary voluntary organizations but also simulate this mechanism by using simple example.

In this paper we explain about lobbying and its agent-based simulations in agent field that hasn’t been done in social sciences and engineering. Lobbying research is studied in political science and has been provided a lot of contributions in social science, however these are not analyzed by computational methods. Thus, we show our conducted simulation and show the process of persuading and persuasion in lobbying the interaction and the changing of opinion of group the process of persuasion at Lobbying. We analyze the process of changing of agents’ thoughts and believes when they make interactions with each other in lobbying. To clarify the background in lobbying research, we introduce several existing contributions and discuss them in each research field including cultural research, organizational research, sociological research, political science research, and social psychological research, respectively.

Convention industry is classified as four categories: the acronym, 'MICE' (Meetings, Incentives, Convention/Congress, and Exhibition/Event). MICE industry has been acknowledge as helping destinations gain a better tourism image and produce economic impact. According to Japan Tourism Agency, economic ripple impact which convention industry produces in 2015 is 590.5 billion in 2015. Among the stakeholders, convention bureaus play an important role to attract convention business in Japan. Since researches on convention industry and especially convention bureaus are still limited and just get started in Japan, this study is to clarify what kinds of factors are important to attract international conventions for Japanese researchers. Moreover, this study discusses the differences between those who have hosted international convention and those who are willing to host international convention in the future. The questionnaire survey for the current research was conducted by online. In method, each respondents' evaluation was analyzed in descriptive statistics and then respondents are classified into 2 groups. Respondents who are willing to host international convention tend to place importance on all sorts of domains. Therefore, convention bureaus need to offer information and support their preparation to host international convention thoroughly.

Revitalization of local cities is one of the major issues for Japan. Recently foreign tourists visiting Japan have increased, and its economic ripple effect is great. However, in big cities and local cities, there is a big difference in the inbound market. To solve the problem, it is necessary to think about the marketing of regional origin. In order to attract foreign tourists to local cities, review data on the Internet was collected and analyzed by the text mining method to clarify the characteristics and differences of each nationality. As a result, we have discovered the difference between Chinese and Taiwanese preferences, for example. This knowledge enables optimal products/services to be provided by customer groups, and can be developed to other areas/cities.

We study an advertisement transaction market which is considering a value of advertisement in addition to monetary value. This paper proposes a novel model for advertisement transactions which employs two stages auctions. To improve an advertisement value for advertisers, it is important to consider not only advertisement sizes and its allocations but also its combinations for the advertisers’ marketing strategies. The two stages auction aims to improve the advertisement value and seller’s revenue. The concept of our model is that the advertisers can consider own marketing strategies for the auction. The first auction winner can choose some preferred other advertisers to make a second auction, and also he/she can reject inconvenient advertisers. The first auction winner can consider the marketing strategy by making a convenient bidders set in the second auction.

Development of cloud computing applications has increased as the cloud has become more popular over the last few years. Developers and researchers are interested in software development methodologies that are created specifically for cloud application development. This paper investigates how the Agile methodology can be applied to cloud computing with a focus on what basic principles of Agile are best suited for cloud applications. Using the twelve Agile principles as a guideline, a case study will be performed to develop a cloud application that uses Dropbox API to create an application with cloud storage. The results show that seven of the twelve principles were successful with positive outcomes from using them during development. The remaining five were unsuccessful.

Every year, the government can make smarter decisions to help developing countries if they have access to relevant data on citizens who wish to donate or invest to promote development. Aiddata.org [1] provides data to visualize and analyze data on $40 trillion in financing for development and maintains development finance related activities. Using the Donation Database Data from AidData.org we can successfully analyze the Business Process data. The analysis starts with Data Profiling [5], identifying the analytical themes and understanding the business story about the data. We implemented a Hadoop [4] data mart to analyze aspects such as Number of Donations a country or a sector made in a particular year and the results are displayed using Tableau tool [9].

A recommendation system provides an individual with personalized service. This paper describes our research conducted to develop and implement a Movie Recommendation engine in the form of a Web Application using two simple approaches: (1) Non-Personalized Recommendation, (2) Content based recommendation techniques using a machine-learning algorithm. The former is achieved by Bayesian Estimation and the latter is derived based on Term Frequency and Inverse Rating Frequency(TF-IRF) Approach coupled with the Cosine Similarity Measuring Technique. Our results indicate that the proposed approach Bayesian Estimation and TF-IRF approach is efficient in terms of calculating the prediction and recommendation factor for a movie with a minimum webpage loading time, when compared to the existing methods such as Aggregate Opinion Mining and Product Association.

This paper describes a novel model of education program and curricula in higher engineering to be employed in ASEANs and its related countries. Our investigation and research program consists of 10 universities including University of Brunei Darussalam, Institute of Technology at Cambodia, Institute of Technology at Bandung, National University of Laos, University of Technology in Malaysia, Yangon Technological University, De La Salle University at Philippines, Nanyang Technological University, Vietnam National university, and Advanced Institute of Industrial Technology in Japan. Our team made an MOU to conduct investigation to create a standard model of higher education program for engineering professions between 2015 to 2017. In this paper, we propose and introduce our invented education program and curricula, example of course in information technology and mechanical engineering, evaluation through questionnaires in external organizations. The proposed program consists 9 years program through high school to graduate school, but students can join in each school based on their needs. The contribution of this paper includes these three points; the proposed model is related with a human capitals development model to complement the existing engineering professional education; schools provide professional education program to execute effective learning; and the proposed model enables to be employed in current various schools easily.

Developing a popular mobile application which is suitable to the users based on the input that users have given with their feedback is very challenging. There are many new mobile applications with high user feedback but few download rates. Moreover, some users of the application are unwilling to give their feedbacks. This abrupt state is caused by the carelessness of mobile application developers in noticing the importance of user feedback and user behavior. In this paper, we will state several steps and options that could be taken by mobile application developers to popularize their mobile application. This solution is mainly focused on the utilization of user feedback and user behavior, which also include proper use of feedback loop, great advertising, and behavioral change. The objectives of this analysis are to change unpopular mobile applications with high user feedback to become popular mobile application with high user download rate, as well as to encourage users to properly express their opinion regarding the application by giving out their feedback to the mobile application developers.

In the tourism industry, convention industry is emerging as one of the most important sections and is diversifying at a rapid pace because of direct and indirect impacts on an economy. Various stakeholders are concerned in convention industry for the reason that it is an essential factor in promoting inbound tourism in Japan. Convention bureaus play an important role to attract convention business in Japan, so this study focuses on convention bureaus perception about destination characteristics and public relation activities and discusses the differences between non-experienced and experienced convention bureaus. The questionnaire was conducted at the 25th international Meetings Expo (IME 2015) held on December 9-10, 2015, at the Tokyo International Forum, Japan. In method, descriptive statistics of questionnaire items and binary logistic regression which examined the differences between experienced and non-experienced group were adopted. In descriptive statistics, the findings indicate that presence or absence of a structure for cooperation among convention bureaus, facility staff and hotel staff to attract international conventions showed an exclusively high mean score. In logistic regression, the experienced tend to have higher awareness of accommodation, price, cooperative structure, and unique culture than non-experienced.

In existing convention management research and its business research, the results of analyses of surveys using answer of questionnaire clarify the motivation of participation, satisfactions and expectation to attend conference for convention attendees. These contributions help event planners and several other stakeholders to design and prepare the conference. Convention is one of good functions to provide networking opportunity for attendees. In this paper, we clarify the characteristics of attendees whose motivation to attend conventions are networking. We show attendees' expectations to the conference for attendees, who think that the networking is important purpose to attend the conference. The number of attendee and rate of highly show-up people are important to enhance their satisfaction. Thus, we implemented a conference attendee management system and introduce it.

A lot of data are collected through various kind of sensors and devices and can be used to make business strategy. These are sometimes used in business and marketing. In existing convention management research and its business research, most of contributions provide the result of analyses of surveys using answer of questionnaire or interviews from convention attendees, event planners and several other stakeholders. If we can know attendees' behavior, perception, and thinking by collecting data from sensors, digital voice recorders and cameras, the management and business design can be designed based on the analysis in order to improve the quality of service and attendee's satisfaction. In this paper, we explain what convention attendees expect to attend the conventions. We show our preliminary experiments to collect attendees' behavior data in a convention. Then, we propose an improved design on experiment environment to acquire attendees' data in convention. We propose a refined model of convention management research and business process in the end of this paper. In our proposed research and business process on convention management, a lot of types acquired data from sensors set in convention facility and can promise to design an improved service to enhance attendees' satisfaction in convention.

A structure of the Internet advertisement is that the service providers decide order of placement of many advertisements and advertising fees by auctions when advertisers offer their promotions. It is known that Generalized Second Price Auction (GSP) mechanism is the most efficient auction mechanism of the advertisement auction. Searching engine companies employ GSP mechanism basically. There are a lot of researches on GSP in order to analyze and clarify its feature and advantages. However, these researches assume that traded advertisements are mutually independent. That is means that each advertisement does not influence other advertisements. Also these researches do not consider a value of advertisement, which means some criterions of a name value of a company, effectiveness and an importance, that is dependently each other. This paper proposes a new advertisement auction mechanism based on GSP with considering the value of advertisement. The authors analyze the auctioneer’s profit in comparison between normal GSP, normal VCG (Vickrey-Clarke-Groves Mechanism) and their proposed mechanism. An Approach to Co-Dependent Value Based Internet Advertisement Auction

This paper discusses the agent-based lobbying where agents persuade others before/after discussion. In the lobbying, person persuade to people in order to change their mind. When an agent is persuaded successfully, his/her favor of view about decision is changed from supported thinking to unsupported thinking. In this paper, we define the strength of persuasion and acceptance and assume some rules. We show our conducted simulation of lobbying based on our defined rules and assumptions. Results of simulations show the group's solidarity is strengthened if each agent in the group has both high strength of persuasion and acceptance. When there is not difference of the strength of persuasion and acceptance between agents, the group which has a lot of opportunities to persuade has an advantage to be changed the other agent's favor of view about decision.

Most of all organizations try to get more benefit by gathering and analyzing various data. These systems work well in profit-making organizations especially, In recent year, permanent voluntary organizations such as universities become to be active in order to know themselves. However, temporary voluntary organizations hardly have any such systems. Therefore, such organizations can not always make their right decision. In this paper, we design a mechanism to solve this problem for temporary voluntary organizations. We also show calculative simulations by using simple examples.

Convention industry produces great economic impact and is rapidly diversifying. Many different stakeholders are concerned in convention industry for the reason that it is an essential factor in promoting inbound tourism in Japan. This study focuses on convention bureaus and discusses the differences between non-experienced and experienced convention bureaus with regards to the regional characteristics that each region has. The questionnaire was conducted at the 24th international Meetings Expo (IME 2014) held on December 9-10, 2014, at the Tokyo International Forum, Japan. Researchers distributed questionnaires directly to the convention bureaus during IME 2014. In method, binary logistic regression was adopted. Logistic binary regression is used for two value response. This model is utilized in the case of a situation where mainly two possible results are expected. The results showed that the experienced tended to have a high awareness of providing local information, while the non-experienced tended to have a high awareness of providing the best service as hospitality in the local area.

Service science research has been developing rapidly in this decade and provided a lot of contribution to enhance value of information systems. Most of IT engineers and scientists are promoting researches based on the concept what information systems make an effective, an optimal, and comfortable society. Since the e-services are provided to users, we need to define their values on user-friendliness, sustainability, economical efficiencies, effectiveness, satisfaction, and some other viewpoints. In this talk, I introduce the service fit model to realize what the users utilities are enhanced by e-services. The former half, we discuss the irrational issues of human activity and thinking. Even though some splendid services are provided by the information systems, people sometimes do not think the service is valuable because their thinking and services are not matched. In latter half, I introduce some examples and actual cases where the systems provide smart services and functions. IT solutions in tourism industry and semiconductors industry are introduced in end of this talk.

In designing a new teaching system, a challenging issue is how the system intelligently supports learners. This paper describes a methodology and a system design on the intelligent instruction support for software engineering education. For information science courses at a university, software engineering subjects are usually compulsory and students study dominant conceptions of implementation like software architecture, and the methodology of software design in software engineering lectures. To enhance learners’ understanding, the authors design a novel instructional model based on the analogical thinking theory. The analogical thinking-based instruction consists of concrete teaching methods like analogy dropping method, self role-play method, and the anthropomorphic thinking method. Questionnaires for learners after the instructions give results of effective education in an actual trial. The contribution of this paper is to provide a new instruction theory, the way of educational practice method, and implementation of the system.

In this paper, we introduce a case study of digital textbook-based education in professional school to educate nursing and care. Digital textbook is utilized on digital textbook viewer software installed on the table computer. In professional education, using digital textbook is one of promising field to enhance its quality since the detailed description can be easily understood. Further, instructors can know students' condition of learning viewing recorded log of their learning and users history. The latter half of this paper discusses our challenges of use of digital textbook in actual professional education. In nursing education, digital textbook-based instruction and study is not familiar with instructor and students. However, we achieve a measure of our goal of instruction using digital textbook in nursing school.