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One of Japan's largest distribution centres has introduced an automatic sorting system using voice input. The workforce has been halved.

As forestry contributes to the reduction of greenhouse gases by CO₂ fixation, in recent years, use of wood in buildings has attracted all over the world more attention. However, construction of large wood structures is almost inexistent within urban areas in Japan. This is due to the Japanese law on fire protection of wood buildings in cities, which is considered very strict with severe requirements. This paper aims to present a research work relative to the development of one-hour fire-resistant wood structural elements for buildings in cities. The developed elements are composed of three layers made of laminated timber.

These wood structural elements, made of glued laminated timber with self-charring-stop, have sufficient fire resistance during and after a fire and comply with the strict Japanese standard for wood structural elements, which stipulates that such elements have to withstand the whole dead-load of concerned buildings after fire. To comply with such requirements, new elements of glued laminated timber with self-charring-stop layer were developed, and their performance was confirmed. Several fire-resistant tests conducted on columns, beams, column-beam joints, connections between beams and walls and beams with holes were carried out.

All tests proved that the elements have sufficient fire resistance. No damage was found out at the load-bearing part of the elements after testing. As the developed elements have two layers protecting the load-bearing part, the temperature in the load-bearing part could be retained below 260°C (carbonization temperature) and provide the elements with a sufficient fire resistance for 1 h.

These wood structural elements have already been applied in six projects, where large-size wooden buildings were constructed in urban areas in Japan.

The proposed structural elements use a novel technique. Every wooden element is composed of three layers made of glued laminated timber. The elements have a typical performance of self-charring-stop after fire without need for water of firefighters. More technologies related to these elements, including column-beam joints and beams with holes and effect of crack, were also developed to design and construct safe wooden buildings.

Automated driving systems (ADSs) are being developed to avoid human error and improve driving safety. However, limited focus has been given to the fallback behavior of automated vehicles, which act as a fail-safe mechanism to deal with safety issues resulting from sensor failure. Therefore, this study aims to establish a fallback control approach aimed at driving an automated vehicle to a safe parking lane under perceptive sensor malfunction.

Owing to an undetected area resulting from a front sensor malfunction, the proposed ADS first creates virtual vehicles to replace existing vehicles in the undetected area. Afterward, the virtual vehicles are assumed to perform the most hazardous driving behavior toward the host vehicle; an adaptive model predictive control algorithm is then presented to optimize the control task during the fallback procedure, avoiding potential collisions with surrounding vehicles. This fallback approach was tested in typical cases related to car-following and lane changes.

It is confirmed that the host vehicle avoid collision with the surrounding vehicles during the fallback procedure, revealing that the proposed method is effective for the test scenarios.

This study presents a model for the path-planning problem regarding an automated vehicle under perceptive sensor failure, and it proposes an original path-planning approach based on virtual vehicle scheme to improve the safety of an automated vehicle during a fallback procedure. This proposal gives a different view on the fallback safety problem from the normal strategy, in which the mode is switched to manual if a driver is available or the vehicle is instantly stopped.

The purpose of this paper is to examine the efficacy of the Japanese ten-item personality inventory (TIPI-J), a short version of the big five (BF) questionnaire, on crowdsourcing. The BF traits are indicators of personality and are said to be an effective predictor of study performance in various occupations. BF can be used in crowdsourcing to predict crowd workers’ performance; however, it will be difficult to use in practice for two reasons like the time-and-effort issue and the bias issue. In this study, an empirical analysis is conducted on crowdsourcing to examine if TIPI-J can solve those issues.

To investigate the issues, two tasks are posted on a crowdsourcing provider. Both TIPI-J and full version BF are conducted before and after selecting crowd workers. Structural validity and convergence validity are tested with correlation analysis between before (TIPI-J) and after (full version BF) data to examine the bias issue. Additionally, those correlations are compared with previous study and significances are examined.

The correlations in “conscientiousness” is 0.45-0.50, respectively, compared with a previous study, those two correlations did not show significance. This indicates that no clear bias exists.

This is the first research to investigate the efficacy of TIPI-J on crowdsourcing and showed that TIPI-J can be a useful tool for predicting crowd workers’ performance and thus it can help to select appropriate crowd workers.