This paper addresses the system design for virtual network services, particularly focusing on virtual machine (VM) services. The VM service requires users to define a substantial number of specifications, such as CPU resources and latency bounds, as a prerequisite. This process is challenging for nonprofessional users and inefficient even for professional users. Users need to clearly understand the specifications they need and report their requirements to the service manager, which demands a high level of knowledge and experience of a system engineer. To make the system more accessible to users, we propose a framework that enables interaction with the virtual network service through natural language (NL) inputs from the users. The framework employs NL models to interpret user requests in NL format into service specifications to determine the specificationdependent optimal virtual network allocation. We demonstrated the effectiveness of the proposed framework through numerical experiments, which show that the user requests in NL are accurately interpreted and incorporated into the virtual network allocation.

This paper addresses the design of an assistance control system that enables safe and flexible operation while facilitating operator upskilling. A key factor in upskilling is increasing opportunities for operators to attempt control actions. To this end, we design an assistance system that reduces intervention frequency and promotes operator freedom. We particularly focus on designing a human assistance system for water level control in a tank system. Then, we characterize the set of admissible control actions for the human operator in order to design assistance control logic that ensures the safety of the overall system. Finally, we conduct a human-in-the-loop simulation of the tank system. Through the simulation, we verify that the proposed assistance system ensures the safety of the overall system with minimal intervention, demonstrating its potential as a foundational technology for effective operator upskilling.

Gig work is a work style in which freelancers undertake one-off jobs based on their own convenience. One can see that the gig work system is a management system that matches one-off jobs with registrant freelancers under their free decision-making. This paper addresses a systematic design of the gig work system. To this end, first, we model the decision-making by the freelancers and the evolutions in remaining workloads. We express the probability that at least one of the registrant freelancers gets opportunities of one-off jobs based on their utility. Next, we design a model-based controller, which matches one-off jobs with them. Finally, the effectiveness of the proposed work management system is verified in numerical experiments.

Prevention of pedestrians traffic accidents has become an important issue in intelligent transportation system. Pedestrian to vehicle communication, in which pedestrians send their position information to surrounding vehicles, is effective in reducing accidents when pedestrians are out of sight of vehicles. However, in urban canyons, the precision of pedestrian positioning via GPS may be significantly degraded due to obstructions and reflections of roadside buildings. To solve this problem, our previous work has suggested using vehicles as anchors for pedestrian positioning, and estimating pedestrian-vehicle distance from instantaneous channel state information (CSI), by using Support Vector Regression (SVR). In this paper, based on the fact that pedestrian-vehicle distance changes continuously, we propose to estimate the distance from a CSI sequence by using an LSTM (Long short-term memory) model, and solve the problem of packet loss that may affect the CSI collection. Simulations using 3D ray tracing show that the proposed method reduces the distance error and the horizontal positioning error by 24.8 % and 41.7%, respectively, compared to the previous method using SVR.

One of the typical autonomous driving systems is a human-machine cooperative system that intervenes in the driver operation. The autonomous driving needs to make consideration of the driver individuality in addition to safety. This paper considers a human-machine cooperative system balancing safety with the driver individuality using the Human-In-The-Loop System (HITLS) for rear-wheel steering control. This paper assumes that it is safe for HITLS to follow the target side-slip angle and target angular velocity without conflicts between the controller and driver operations. We propose HITLS using the primal-dual algorithm and the internal model control (IMC) type I-PD controller. In HITLS, the signal expander delimits the human-selectable operating range and the controller cooperates stably the human operation and automated control in that range. The primal-dual algorithm realizes the driver and the signal expander. Our outcomes are the making of the rear-wheel steering system which converges to the target value while reflecting the driver individuality.

We will demonstrate some workshop space that we have designed for creating and sharing socially meaningful activities that transcend differences in culture and age. We argue for the importance of: 1. Sharing at multiple levels: bodily/sensory, emotional, intellectual, and social levels. 2. Connecting these levels by introducing technologies in response to socially shared meanings. In our demonstration, we will show some activities incorporating Scratch/Cricket technologies to enhance sharing and connecting these levels.

This workshop aims increase understanding through experience the style of a traditional Japanese art. The idea is to develop growing "images" from the impressions gotten from the paintings on the "Byo-bu (Folding screen)", and then to re-create with the others a "New story" coming from these "images". Thus, we would like to think about a collaborative creation based on individual or common ideas and the process of creative thinking that were raised by Byo-bu.

Decorated characters are widely used in various documents. Practical optical character reader is required to deal with not only common fonts but also complex designed fonts. However, since the appearances of decorated characters are complicated, most general character recognition systems cannot give good performances on decorated characters. In this paper, an algorithm that can extract character's essential structure from a decorated character is proposed. This algorithm is applied in preprocessing of character recognition. The proposed algorithm consists of three procedures: global structure extraction, interpolation of structure and smoothing. By using multiscale images, topographical features, such as ridges and ravines are detected for structure extraction. Ridges are used for extracting global structure and ravines are used for interpolation. Experimental results show character structures can be clearly extracted from very complex decorated characters.

Decorated characters are widely used in various documents. Practical optical character reader is required to deal with not only common fonts but also complex designed fonts. However, since appearances of decorated characters are complicated, most general character recognition systems cannot give good performances on decorated characters. In this paper, an algorithm that can extract character's essential structure from a decorated character is proposed. This algorithm is applied in preprocessing of character recognition. The proposed algorithm consists of three parts: global structure extraction, interpolation of structure, and smoothing. By using multi-scale images, topographical features such as ridges and ravines are detected for structure extraction. Ridges are used for extracting global structure, and ravines are used for interpolation. Experimental results show clear character structures are extracted from very complex decorated characters.