Tatsuya Yamazaki

Quality of experience modeling with psychological effect for interactive Web services

Notion of the user-centered design (UCD) is requisite to improve user satisfaction. Matching the concept of UCD, Quality of Experience (QoE) is expected to become a paradigm shift from the existing operator-initiative network services. There are, however, several difficulties to realize practical communication services based on QoE. One difficulty is how to bridge QoE and Quality of Service (QoS) parameters relevant to system performance. Moreover, since QoE is based on the end-user subjective evaluation, flexible modeling corresponding to the end-user psychological status is needed. In this paper, an interactive Web service is considered and a QoE model with end-user psychological effect is derived by use of the Weber-Fechner law. Data of QoE and QoS parameter are collected through experiments and the mapping functions between QoE and QoS are estimated from the data.

QoE-driven bandwidth allocation method based on user characteristics

Network providers are nowadays facing with a big question in allocating network resources due to the constantly increasing of Internet services. While the network resource is not unlimited, users always desire the best quality of experience (QoE) with the huge information exchange. Therefore, finding a justice of network resource allocation based on the user experience is mandatory. In previous studies, network resources were allocated to all users by using a specific utility function without considering the user characteristics. In fact, the network resource consumptions are very different among individual users and directly depend on users behavior. For instance, the network demands of relax users are usually lower than those of busy users. Thus, allocating the same amount of resources to all users might not meet their expectations. In this paper, we propose two bandwidth allocation methods by classifying users into different groups based on their characteristics such as relax, short-time busy, and long-time busy users. To allocate the bandwidth in each group, specific utility functions are applied. By using these methods, the obtained results show that users get the different allocated bandwidth while they still experience the same level of QoE. On the other hand, the allocation considers users behavior to allocate suitable bandwidth based on the real resource consumption of users. As a result from these analyses, our proposal tends toward a fair allocation as well as an efficient management of the network resources.

Soil Moisture Sensing Experiments for Water Management in Pear Fields

Water management is one of the most important tasks in agriculture. However, the farmers rely on their intuition and experience to determine when and how much water should be provided. Sensing technologies have been highly developed and several test works were conducted. There are two types of sensors to measure soil moisture: soil moisture content and soil moisture tension sensors. The usage of these sensors can be different from each agricultural product and there is no validation test for pear cultivation. In this paper, we describe the validation experiment of these two types of sensors which are conducted in pear fields. After measuring the soil moisture during one-season pear cultivation, we have clarified the difference of two types of sensors. The soil moisture tension sensor can quantify the water-retaining power of soil, while the soil moisture content sensor can detect detailed fluctuation of the water content ratio in soil.

Urban Disaster Simulation Incorporating Human Psychological Models in Evacuation Behaviors

Building evacuation simulation provides us with various knowledge and suggestion before a real disaster happens. To date, however, evacuees were often modeled as homogeneous without individual motivation in a large-scale urban simulation model, which is rather different from real human behavior. In this paper, an evacuation simulation model with human psychological models is developed for urban disaster situation. Three psychological models are actually incorporated: normalcy bias, emotional contagion bias, and sympathy behavior bias. Normalcy bias is the initial evacuation delay caused by a belief that abnormal events rarely happen. Emotional contagion is the effect of one person’s emotional state on the emotional state of people around him/her both explicitly and implicitly. Simulated experimental results show that the proposed model provides accurate evacuation behaviors than the normal behavior model without psychological consideration.

Congestion field detection for Service Quality improvement using Kernel density estimation

Owing to proliferation of smart phones, communication services such as a video streaming service are common in a mobile situation. For these services, quality evaluation and communication control based on Quality of Experience (QoE), which is the degree of a users subjective satisfaction, is very important because the final goal of delivering high-quality service is improving users satisfaction. QoE tends to be affected by several factors including Quality of Service (QoS). Therefore, collecting QoS data from the users who use the mobile application has become one of promising schemes to meet the QoE, which is called the crowd sourcing data. The crowd sourcing data are, however, apt to be affected by sensing errors and low accuracy. In this study, we propose to estimate some densities just from the records of application use and its location information to remove the sensing errors and low accuracy. The Kernel density estimator is used to derive a continuous density function from discrete distributed sample data such as the collected QoS data. From the viewpoint of QoS, it is important to extract high-density fields of the application use to find out QoS degradation. After estimating the Kernel density estimator, we determine the borderline between the high-density field and the other field by using the reference value that can be determined from the observed data. Simulated experiments verify effectiveness of the proposed method.

Interactive Facial Expression Reader and Extension to First Impression Improver

Facial expression plays an important role as non-verbal information in dialogue communication. People complement verbal information with non-verbal information to hold a smooth conversation. To date, collaboration between information engineering and psychology has enabled development of human facial expression recognition technology. Most of the related studies, however, have ended up with a laboratory-based demonstration. In this paper, focusing on the facial expression database, we overview the facial expression recognition technology. Then we present a simple application using the current status of the facial expression recognition technology. Finally we show prospect of the technology with a more realistic application.