Taxi-demand prediction is an important application of machine learning that enables taxi-providing facilities to optimize their operations and city planners to improve transportation infrastructure and services. However, the use of sensitive data in these systems raises concerns about privacy and security. In this paper, we propose the use of federated learning for taxi-demand prediction that allows multiple parties to train a machine learning model on their own data while keeping the data private and secure. This can enable organizations to build models on data they otherwise would not be able to access. Evaluation with real-world data collected from 16 taxi service providers in Japan over a period of six months showed that the proposed system can predict the demand level accurately within 1\% error compared to a single model trained with integrated data.

Have you ever wondered why some insects like cockroaches prefer to stay or decrease movement in darkness? Some may tell you it's called photophobia, a habit deeply coded in their genes. A further question would be whether we can correct this habit of cockroaches, that is, moving in the darkness just as they move in bright backgrounds. Scientists from Osaka University may have answered this question by converting a cockroach into a cyborg. They published their research in the journal Cyborg and Bionic Systems.

The large amount of data collected in buildings makes energy management smarter and more energy efficient. This study proposes a design and implementation methodology of data-driven heating, ventilation, and air conditioning (HVAC) control. Building thermodynamics is modeled using a symbolic regression model (SRM) built from the collected data. Additionally, an HVAC system model is also developed with a data-driven approach. A model predictive control (MPC) based HVAC scheduling is formulated with the developed models to minimize energy consumption and peak power demand and maximize thermal comfort. The performance of the proposed framework is demonstrated in the workspace in the actual campus building. The HVAC system using the proposed framework reduces the peak power by 16.1\% compared to the widely used thermostat controller.

A tweak to a popular text-to-image-generating artificial intelligence allows it to turn brain signals directly into pictures. The system requires extensive training using bulky and costly imaging equipment, however, so everyday mind reading is a long way from reality. Several research groups have previously generated images from brain signals using energy-intensive AI models that require fine-tuning of millions to billions of parameters. Now, Shinji Nishimoto and Yu Takagi at Osaka University in Japan have developed a much simpler approach using Stable Diffusion, a text-to-image generator released by Stability AI in August 2022. Their new method involves thousands, rather than millions, of parameters.

A tweak to a popular text-to-image-generating artificial intelligence allows it to turn brain signals directly into pictures. The system requires extensive training using bulky and costly imaging equipment, however, so everyday mind reading is a long way from reality. Several research groups have previously generated images from brain signals using energy-intensive AI models that require fine-tuning of millions to billions of parameters. Now, Shinji Nishimoto and Yu Takagi at Osaka University in Japan have developed a much simpler approach using Stable Diffusion, a text-to-image generator released by Stability AI in August 2022. Their new method involves thousands, rather than millions, of parameters.

You can't move a pharmaceutical scientist from a lab to a kitchen and expect the same research output. Enzymes behave exactly the same: They are dependent upon a specific environment. But now, in a study recently published in ACS Synthetic Biology, researchers from Osaka University have imparted an analogous level of adaptability to enzymes, a goal that has remained elusive for over 30 years. Enzymes perform impressive functions, enabled by the unique arrangement of their constituent amino acids, but usually only within a specific cellular environment. When you change the cellular environment, the enzyme rarely functions well--if at all.

Overview of the proposed method. An image of the current landscape is acquired by the mobile terminal and sent to the server PC. The server detects the target building and generates a mask. The area to be complemented is set from the mask image, and the input image is automatically altered based on the features around the target area. The output image based on the digital completion is sent to the mobile terminal as a future landscape after demolition to be displayed on the DR display.

For thousands of years, philosophers have pondered the question of whether humans are born with a'moral compass', or if we learn one as we grow older. Now, researchers have found that young babies can make moral judgements and punish antisocial behaviour – suggesting we're'inherently good' from birth. In experiments, the Japanese experts used eye-tracking technology to give eight-month-olds the power to punish a human-like blob on a computer screen. The babies were more inclined to give a punishment after they had seen it being violent towards a victim, the researchers found. Results suggest the motivation to give a punishment when it's due is intrinsic – something that we're born with – as opposed to learned.

In the young discipline of robotics-inspired biology, robots replace experimental animals, allowing researchers to learn about animals under a wider range of conditions than exist in nature or the laboratory. What is the secret behind the steady but oh-so-elegant way in which cats move? That's the subject of a study in Frontiers in Neurorobotics by scientists from Osaka University, who built a novel, 47cm-long and 7.6kg-heavy robotic cat. Based on previous research on the gait of real domestic cats, the authors deduced that key to the cats' sleek movement must lie in a previously unknown reflex circuit, which they call the "reciprocal excitatory circuit between hip and knee extensors". According to their hypothesis, this reflex circuit has two essential features.

Would you like to stay up to date with the latest robotics & AI research from top roboticists? The IEEE/RSJ IROS2020 (International Conference on Intelligent Robots and Systems) recently released their Plenary and Keynote talks in the IEEE RAS YouTube channel. Abstract: Computational modeling of cognitive development has the potential to uncover the underlying mechanism of human intelligence as well as to design intelligent robots. We have been investigating whether a unified theory accounts for cognitive development and what computational framework embodies such a theory. This talk introduces a neuroscientific theory called predictive coding and shows how robots as well as humans acquire cognitive abilities using predictive processing neural networks.