Toward further enhancement of the fifth generation (5G) mobile communication system, referred to as 5G Evolution (5GE), more stable high data-rate transmission should be required even in high-mobility environments such as high-speed trains. By using 28 GHz-band experimental equipment with beamforming and beam tracking, a 5GE experimental trial had been conducted in the actual high-speed bullet train running at a speed of 283 km/h. However, it is important to evaluate transmission performances and robustness against the higher mobile speed in sub-6 GHz band in addition to millimeter-wave band. Thus, we conducted 4.85 GHz-band 5GE experimental trial aboard Shinkansen test train running at 360 km/h, which is the fastest experiment trial in Japan. This trial deployed two base station antennas along the Shinkansen railways, and a mobile station was mounted in the rolling stock of the Shinkansen test train. This paper introduces 4.85 GHz-band 5GE experimental equipment, an overview of the experimental trial, and measured transmission performances.

In order to further utilize the high frequency band represented by millimeter wave, it is one of the issues to construct an economical indoor area. One of the solutions is to efficiently bring the radio waves from outdoor base stations to indoors. In this study, we have confirmed that the indoor radio wave strength can be significantly improved by using three elemental technologies: (1) radio wave transmission structure design technology (FSS technology), (2) metasurface technology (radio wave aggregation technology), and (3) relay stations.

Users often obtain recipes from culinary websites when they are cooking. In this case, various recipes for the same dish are displayed. Therefore, users compare each recipe and decide which one they want to use. We believe that it would be easier to select a recipe if we extract the point of uniqueness of each recipe and present it in the search results. In this paper, we propose a method of extracting the uniqueness of a recipe by analyzing the ingredients and procedures used. Specifically, we reference a basic recipe that describes the standard cooking methods of a dish and extract the differences between it and other recipes to ascertain the points of uniqueness of the recipe using procedures' importance and correspondence. As a result of implementing the proposed method with several recipes, we confirmed that the proposed method is able to extract the uniqueness.

This paper presents outdoor field experimental results in the 28-GHz frequency band of a 5G radio access system where base stations (BSs) are installed on buildings to deploy a 5G trial area in the Tokyo Odaiba waterfront area. This is an early field trial assessment of key 5G features such as BS and mobile station (MS) beam tracking, being deployed in dense urban areas. In the trial area, a variety of key 5G technologies and conditions are evaluated such as BS and MS massive multiple-input multiple-output (MIMO) antennas, beamforming and tracking, use of the high 28-GHz frequency, the wide frequency bandwidth of 400 MHz, intra-baseband unit (BBU) hand over (HO), and a coverage area in a realistic urban deployment with four different trial courses. Experimental results show that throughput exceeding 1 Gbps is achieved in the experiment area, and approximately 200 Mbps is achieved at 500 m away from the BS. We confirm that beam tracking and intra-BBU HO operate effectively while compensating for high path loss in the 28-GHz band to achieve a coverage area of 500 m. On the other hand, line of sight (LoS) and Non-LoS conditions are critical to 5G performance in the 28-GHz band, and we find that 5G connections may drop behind trees, buildings, and/or under a footbridge. The trial results show that the downlink throughput exceeds 50 Mbps in 85%, 50%, 70%, and 33% of the four different trial courses, respectively.

This paper proposes 28-GHz band compatible vehicle glass mounted antenna that actualizes cellular-V2X communications and report on the downlink performance when distributing that antennas on the glass surfaces in high mobility environments up to 100 km/h. The antennas can be installed on vehicle glass surfaces without affecting the vehicle design. Based on measurement results when utilizing a distributed antenna installation on the glass surfaces, we confirmed proper beam selection according to the vehicle position. We also achieved the maximum throughput of approximately 8 Gbps while moving at high speeds of approximately 100 km/h, and achieved the maximum throughput of approximately 11 Gbps at a speed of approximately 30 km/h. We confirmed the feasibility of high-speed in-vehicle communications using a 28-GHz band compatible vehicle glass mounted antenna.

This paper presents outdoor field experimental results in the 28-GHz frequency band of a 5G radio access system where base stations (BSs) and a core network are installed on buildings to deploy a 5G trial area in the Tokyo Odaiba waterfront area as a 5G trial site. This is the first report of a 5G trial in a realistic urban deployment in an approximate 1 square kilometer area using a single 5G network. In this trial area, a variety of key 5G technologies are evaluated such as the peak data rate and throughput performance, 5G coverage area, BS and mobile station (MS) massive multiple-input multiple-output antennas for beamforming and tracking, intra- and inter-baseband unit handover employing the high frequency of 28 GHz, and the wide frequency bandwidth of 400 MHz in a realistic urban deployment. Results show that coverage is provided for 88% of the assessed drive route and the downlink throughput of 650 Mbps is achieved for 80% of the route. As indicated when buildings block the radio signal, line of sight (LoS) or non-LoS (NLoS) conditions are critical for signal propagation in the 28-GHz frequency band. To improve coverage in NLoS areas, a portable BS using a wireless backhaul system is installed in the trial area. With the portable BS, the corresponding coverage area is increased from 50% to 83% along the assessed drive route resulting in improved downlink throughput from 600 Mbps to 660 Mbps, and 250 Mbps to 280 Mbps in the uplink.

This paper presents a method of searching for modified maps that are similar to a user's query. Although there are many different reasons for using maps, a similarity search method can support user decision-making. Modified maps are simplified maps that have been changed in some way. They are useful for reflecting a user's specific purpose; however, there is no existing method for searching for modified maps. In this paper, we propose a system that suggests a list of similar modified maps by analyzing the features of a modified map input by the user.

Recent years have witnessed a rapid increase in the use of car navigation systems, which provide drivers with directions to their destinations. However, such systems do not always recommend a route that perfectly matches a driver's intent. Even when drivers intentionally change the driving route from the recommended one to another, most car navigation systems keep recommending or lead them back to the original recommended route. Such recommendations may not adequately reflect a driver's intent. We previously proposed a route recommendation method based on the estimation of a driver's intent by comparing the characteristics of a route selected by a driver and a route not selected by the driver but recommended by the car navigation system. In this study, we propose a method that can consider multiple costs and learn a driver's concept of the values for each cost; in brief, it represents an effective method for learning drivers' route selection preferences. In addition, we describe experimental evaluation results of our proposed method for driving route recommendations and learning drivers' route selection preferences.

In recent years, the importance of information on tourism is increasing because inbound tourists have a beneficial economic effect on regions that attract them. In general, the most popular method of obtaining tourism information is through guidebooks, which often consider only famous sightseeing spots. However, attractive spots are not available only in guidebooks. I consider that finding attractive spots on one's own would satisfy tourists. Therefore, I propose an extraction method for finding attractive Anaba (implying well-kept secret) spots based on users' evaluation and number of visitors. I define Anaba spots because they have low name recognition and high evaluation. In this study, I developed a prototype system by using a photo-sharing site to calculate name recognition and user's evaluation, and evaluated the proposed method.

Our paper proposes a method for extracting feature terms expressing feelings regarding the use of a product from customer reviews on e-commerce sites, based on content-based recommendation. Considering previous research indicating that negative events and impressions have a greater impact than positive ones, we define terms relating to factors over which customers argue the pros and cons in reviews as features related to feelings regarding the use of a product.

Various TV programs, such as travel and educational programs, often introduce tourist spots, or historical places. However, viewers find it difficult to grasp the surroundings of these spots or places, how the locations are related, and distances between them, when instantaneously moving between the scenes by switching video streams. Therefore, we built an interface using the geographical metadata of the video streams, called TV-Milan, that automatically presents geographic contents (i.e., maps, photos, Street View, etc.) synchronized with the TV program.

We propose a recommendation method of geographical information for mobile devices based on user search operations using local services such as Yelp. We presume that we can estimate the search conditions using user operations for a region and category by analyzing the user operations. There are four operations, changing the region, selecting the categories, viewing the objects, and selecting an object. We use the user operations to extract important factors attached to the user. At this time, we think that users have the requirement that there be an appropriate number of displayed objects. Thus, we propose a recommendation method with an automatic adjusting search property to satisfy the constrained condition for the number of displayed objects. We aim for intelligent interaction such as optimizing the search properties to estimate the user requirements from realizable operations on a general interface. In this paper, we discuss an adjusting method and developed prototype system.

We present a method of automatically generating learning channels by using the semantic relations that implicitly exist in slides of a lecture that has accompanying recorded video. These days, many lecture videos with presentation files are shared over the Web from many universities through their own public sites. Although these materials are useful and valuable to many potential students, their use of sequential static media for self-learning purposes means there is still a lack of support for self-learners seeking learning channels suitable for various levels of understanding. Our newly generated learning channels let users easily focus on either highly detailed slides or introductory slides without needing to examine all of the data. We describe a prototype system supported by this learning-channel construction method.

When we want information on current events, we often view news programs on TV or news streams on Web sites. A news video stream consists of several scenes, and viewers often gain a broad understanding of the news by viewing scenes in the given order. Since a viewer's opinion of a news topic depends on the scene order, we have developed a method for extracting blog entries expressing a particular point of view regarding news topics where we use a form of evaluation and categorization similar to that based on news scene order. In this paper, we describe our method of news evaluation based on news scene order, and explain how a blog search can be done using a news stream