This study examined the relationships between the feelings about the purchase for others and the scene by using text mining, analyzing feelings by PLSA and, furthermore, the relationship among the feelings, purposes and the product genres by using a Bayesian network analysis for the review data of the sports product of Rakuten Ichiba. This study could understand what kind of communication was performed when a person purchased a product as a gift by analyzing the review data of the sportswear accessories and golf that there were particularly many products to purchase for others in sporting goods.

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In recent years, advanced driver-assistance systems (ADAS) and automated driving have been realized. These technologies work together with vehicles, traffic lights, roadside equipment, and network-connected center systems to realize safe and comfortable driving. It goes without saying that the reliability and security of the software in this system are important. On the other hand, in ADAS and autonomous driving technology, if information errors, information delays, or information shortages occur, even if the software functions correctly, deviation from the real world will occur, and accidents will occur. In particular, map data is the key data for software to make appropriate judgments, but it is difficult to perfectly match roads in the real world with map data in real time. Therefore, while considering the accuracy of information, ADAS and autonomous driving software must make decisions such as slowing down the vehicle, stopping it, and asking the driver to drive based on a fail-safe basis.

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As changes in the work environment associated with work-style reform and spread of the novel coronavirus, as well as reforms in business models in various industries associated with the recent progress and diffusion of digital technology, the style of project management in the system integration business also needs a reform. This document introduces a case study of a review of the system development process and project management to ensure QCD (quality, cost, and delivery) in the development and maintenance of financial system, where the author is engaged, amid the changes in the business and work environment.

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At present, the open architecture is widespread in various research areas. Especially, many open source software are used in the software engineering because of the standardization and cost reduction. In this research, we discuss the reliability learning and quality assessment obtained from software fault big data.

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Chikio Hayashi conceived of quantification to convert qualitative variables into quantitative variables, developed the necessary quantification theory systematically and independently, and took a leadership role in solving social problems supported by quantification theory. Quantification theory and survey design based on its application have taken root in all social analysis activities in industry, government, and academia in Japan as a method for analyzing and improving qualitative variables that are routinely collected and that are factors in behavior. Quantification theory has become a representative methodology for multivariate data analysis proposed by Japan, and has also made a pioneering contribution to the international community in the construction of Data Sciences. For these reasons, the Japanese Society of Applied Statistics recommends “Hayashi's Quantification Theory” for the Kototsukuri Collection.

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As people's needs and the business environment are constantly changing, the systems that support society must also continue to change to keep up with the world's trends. Autonomous decentralized information and control systems are a system concept that originated from the model of living organisms. It has been applied to many social infrastructure systems such as railways and steel, which require non-stop operation, flexibility, and maintainability, and supports sustainable system growth by realizing non-stop modification and gradual expansion.

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The Epidemic-Type Aftershock Sequence (ETAS) model proposed by Prof. Ogata is a point-process model representing a temporal or spatio-temporal pattern of earthquake occurrence. This model is widely recognized and applied in various scientific fields, such as medical science, social science, economics, and ecology, in addition to earth science. Forecasting systems for future earthquakes and crimes based on this model have been implemented and used in Japan, the United States, and Europe. Following the progress of point-process studies, particularly for a spatio-temporal point pattern, the ETAS model will be more widely used, and the forecasting through this model will impact our society.

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The Good Design Award is a design award system that originated in the Good Design Movement of the 1950s to educate the public about the importance of design, and was launched in 1957. Since then, regular consultations have been held with a variety of experts and related parties, and the award has continued to exist to this day, changing its aspect little by little, and has become an award that attracts a great deal of attention worldwide, especially in Asia.From the above, it can be inferred that the Good Design Award has made a significant contribution to the creation of a “Kototsukuri” in terms of raising public interest in design.

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With the development of science and technology, there is an urgent need to address the ethical, legal, and social issues (ELSI) associated with its embedding in society. In this paper, we discuss “digital trust” related to social media, which has a significant social impact.

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In this presentation, we will present a theoretical framework for describing multi-attribute decision making, explain computer simulations of typical decision strategies in multi-attribute decision making, and discuss which decision strategies can make better decisions with less cognitive effort and avoid worst-case decisions. Based on the simulation results, we will discuss which decision strategy requires less cognitive effort, can make better decisions, and can avoid worst-case decisions. Comparisons will also be made between psychological experiments and simulations to see how they differ.

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Along with the development of blockchain, there is an urgent need to respond to ethical, legal and social issues (ELSI). I would like to explore the social impact under the perspective that blockchain will change from centralized to decentralized autonomous corporations (DAC).

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Data sciencea are considered to be a system of methods to improve human, society, and the multidimensional values that surround them as quickly as possible through a series of processes such as data design and collection, structural modeling, and decision making based on statistical inferences. In this process, various value conflicts emerge within individuals, social groups, and through the relationship between humans and nature. As a result, ethical anf social aspects are inevitably introduced into data sciences. A prominent example is the decision-making arena of regulatory science, where data scientists seeking to minimize consumer risk and data scientists seeking to minimize producer risk coexist adversarial and where a mutually acceptable solution must be socially defined. Apart from the issue of Inhibition Ethics, which discourages intentional misrepresentation of data-based processes, this paper discusses the ethical and socialaspects that arise when data science professionals representing various positions do what they do best.

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