佐々木 史織

Semantic computing is an important and promising approach to semantic analysis for various environmental phenomena and changes in real world. This paper presents a new semantic computing method with multi-spectrum images for analyzing and interpreting environmental phenomena and changes occurring in the physical world. We have already presented a concept of "Semantic Computing System" for realizing global environmental analysis. This paper presents a new semantic computing method to realize semantic associative search for the multiple-colours-spectrum images in the multi-dimensional semantic space, that is "multi-spectrum semantic-image space" with semantic projection functions. This space is created for dynamically computing semantic equivalence, similarity and difference between multi-spectrum images and environmental situations. We apply this system to global environmental analysis as a new platform of environmental computing. We have already presented the 5D World Map System, as an international research environment with spatio-temporal and semantic analysers. We also present several new approaches to global environmental-analysis for multi-spectrum images in "multi-spectrum semantic-image space."

This paper presents the analysis and visualization of river-water quality in 25 rivers in Thailand by using 5D World Map system. Water pollution is analyzed by using Water Quality Index (WQI) and Metal Index (MI), which focus on Ping, Nan and Chao Phraya River (the important rivers of Thai). The WQI indicator was used to evaluate water quality by conductivity, NO3-N, NO2-N, NH3-N, Cd, Cr, Mn, Ni, Pb, Zn and As. The MI indicator was used to estimate concentration of metal in the river. The results on 5D World Map System show that several actual values assigned to water-quality parameters are shown in snapshots. The results of Water Quality Index (WQI) show the WQI levels 32.697 at Chaophraya river (Bangkok, 2004) and 38.534 at Ping river (Nakhonsawan, 2014) for Irrigation and Aquatic life respectively, and can be classified into categories of quality-levels for Irrigation and Aquatic life. The results of Metal Index (MI) show that the MI level reaches 92.902 at Ping River (Nakhonsawan, 2014) and 1803.303 at Ping River (Nakhonsawan, 2014) for Irrigation and Aquatic life respectively.

This paper presents a low-cost and portable water quality monitoring system for a researcher, consumer and also drinking water distribution systems. This system consists of main controller unit based on Commercial off-the-shelf (COTS) single board computer and equipped with LCD touch screen to display data information, the central measurement unit is interfaced to the multi-parameter sensor array to collect data from environment and communication unit that bring connection from the sensor device to The Internet. The dimension of portable water monitoring system are 38cm x 12.8cm x 8cm, and the weight is 658gr. The device also supports for modularity. From experiment we measured that the reliability delay for processing data is 1 second and delay for communication is only 2 seconds with 3.1Mbps Internet connection.

Nowadays, UAV is widely used in several research and industrial fields. One of the highly beneficial features is that it is able to be utilized to capture aerial images in high-resolution for environmental study or detecting disaster phenomena quickly. This paper presents a multispectral image analysis system for aerial images that captured by multispectral camera, which are mounted on an unmanned autonomous vehicle (UAV) or Drone, and discusses an application of semantic computing system for agricultural health condition monitoring and analysis. In our experiments, we analyze multispectral images to detect healthy and unhealthy conditions of agricultural area and interpret the keyword of plant health conditions for user. We also propose the SPA process for real-time farming area management. As a case study, we conducted an experiment on rye fields in Latvia.

This paper deals with event-based feature extraction to analyze the incubation time of coral under two stressor: temperature and light intensity. The study is conducted in Kho Sichang Island, Thailand during hot season. The method for extracting the important events is Hilbert Huang Transform (HHT). The event as a result of Empirical Mode Decomposition (EMD) and Instantaneous Frequency (IF) are confirmed with the time duration of first symptom appearance in Acrophora Hummilis coral. The result shows variation of incubation time of coral disease under different event combination. The important finding in this research is incubation time of coral disease under different situation. It is important for early warning in coral damage.

Nowadays, deforestation activity still occurs despite having huge impact for human being. The different causes of deforestation are relatively brings different effect on nature, while forest fire and illegal logging are two major deforestation activities. In this paper, we proposed a new method to represent semantic analysis of deforestation effect based on its cause. We proposed idea to interpret reflected "substances (material)" of deforestation area in spectrum domain into human language. The objectives of this paper are to (1) Detect deforestation area, (2) Detect the type activity that cause deforestation (whether it is logging or forest fire), (3) measuring the degree of deforestation effect for soil by considering the soil properties, (4) identify and present important nature changes occurring in soils that affect post deforestation management. Riau has been selected as the study area, where the data was acquired by using Landsat Satellite images between 2013 and 2014; where there is a big forest fire occurs. The experimental result produces new semantic analysis matrices to determining the soil condition after deforestation in different context.

This paper presents the analysis and visualization of river-water quality in 25 rivers in Thailand by using 5D World Map system. Water pollution is analyzed by using Water Quality Index (WQI) and Metal Index (MI), which focus on Ping, Nan and Chao Phraya River (the important rivers of Thai). The WQI indicator was used to evaluate water quality by conductivity, NO3-N, NO2-N, NH3-N, Cd, Cr, Mn, Ni, Pb, Zn and As. The MI indicator was used to estimate concentration of metal in the river. The results on 5D World Map System show that several actual values assigned to water-quality parameters are shown in snapshots. The results of Water Quality Index (WQI) show the WQI levels 32.697 at Chaophraya river (Bangkok, 2004) and 38.534 at Ping river (Nakhonsawan, 2014) for Irrigation and Aquatic life respectively, and can be classified into categories of quality-levels for Irrigation and Aquatic life. The results of Metal Index (MI) show that the MI level reaches 92.902 at Ping River (Nakhonsawan, 2014) and 1803.303 at Ping River (Nakhonsawan, 2014) for Irrigation and Aquatic life respectively.

Semantic computing is an important and promising approach to semantic analysis for various environmental phenomena and changes in real world. This paper presents a new semantic computing method with multi-spectrum images for analyzing and interpreting environmental phenomena and changes occurring in the physical world. We have already presented a concept of "Semantic Computing System" for realizing global environmental analysis. This paper presents a new semantic computing method to realize semantic associative search for the multiple-colours-spectrum images in the multi-dimensional semantic space, that is "multi-spectrum semantic-image space" with semantic projection functions. This space is created for dynamically computing semantic equivalence, similarity and difference between multi-spectrum images and environmental situations. We apply this system to global environmental analysis as a new platform of environmental computing. We have already presented the 5D World Map System, as an international research environment with spatio-temporal and semantic analysers. We also present several new approaches to global environmental-analysis for multi-spectrum images in "multi-spectrum semantic-image space."

Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts's road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts's road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

Dengue fever disease had threatens more than 4 billion people worldwide. Current studies in this disease focus on the relation between environmental data and dengue cases directly without considering the stage of the mosquito's life. In fact, dengue case is associated with different dominant stages under different circumstances. Therefore, it is important to analyze and select the dominant stage of mosquito for different situation to select an adequate strategy for disease-spreading prevention. In this research, we introduce the new system to select the stage based on context-dependency by using Mathematical Model of Meaning ( MMM). The feature of this research is in calculating the similarity pattern analysis between environmental data with disease stage. The objective of the research is to build effective prevention system due to dominant mosquito's stage that possible to trigger dengue case. In this study, we focus on abiotic contexts with features such as rainfall, temperature, humidity, sunshine duration, CO2 and wind speed. This model consist of ( a) subspace creation based on stage classification from ecological model of dynamic energy budget, ( b) context-similarity calculation by using MMM, and ( c) matching-prediction by Hilbert Transform. Through this system, we can determine an effective strategy to prevent dengue case in every different situation. Therefore, this system can contribute to reduce environmental damage and probability of health problem caused by an improper strategy of disease prevention. In this research, we employ real weather data of Surabaya from 2007 to 2011. The result shows that the dominant stage in wet season and dry season is different, also in specific case such as disaster, the dominant stage also different.

This paper presents a collaborative knowledge sharing system called 5D World Map System and its applications in the field of multidisciplinary environmental research and education. In this paper, by presenting two case studies related to more than 20 Asia-Pacific countries, we demonstrate the feasibility of our analytical visualization and knowledge sharing method with 5D World Map System for the study of hot energy issues. 5D World Map System enables semantic, temporal and spatial analysis of multimedia, integrates and visualizes the analysed results as a 5-dimentional dynamic historical atlas. The main feature of this system is to create various context-dependent patterns of environmental/historical/cultural stories according to a user's viewpoint dynamically. This system generates multiple views of semantic and temporal-spatial relationships among multimedia of the cross-cutting issues, and provides high visibility of semantic correlations between multimedia in time series variation with multi-geographical spaces. The objective to create this system is to combine real and cyber spaces to share knowledge not only in technological systems/mechanisms but also social rules/phenomena in the field of environmental research. The main contribution of this research is proposing a method to re-create, visualize and objectivize the analysed results of both engineering and political studies by using a real-time knowledge sharing system with multimedia, spatiotemporal information and global overview.

Visual information such as pictorial symbols, icons and images capture our imagination. In our paper, we discuss icons and images in the context of cross-cultural communication. The authors present their own viewpoints to the subject. We discuss about communication in the multi-cultural world and analyze icons in cross-cultural context. Two professional application domains for icons will be presented. A Kansei-based cross-cultural multimedia computing system and a cross-cultural image communication system are described. Icons are a good means for communication within a certain application domain and in a certain context. © 2014 The authors and IOS Press.

To maintain and uplift the motivation for doing exercise which is tend to be too simple in rehabilitation and ergotherapy, doing exercise with music is one of the good solutions. In this paper, we confirm that doing exercise with music is fun. Next, we design five types of musical features which relate to exercises. These features are evaluated by doing five types of exercises with listening to the tunes. Based on the results obtained from the experiments, we found many new things, for example, tempo has the adjustment limitation based on how well the user knows the tune. In this paper, we report the latest results from the experiments and explain the way to progress of this research.

Currently, floods are not only occurred in the outskirts of the river course, but also in the urban area, especially in the big city. The main problem of urban flood is the fact that it occurs in highly populated areas. It is a global phenomenon that causes widespread devastation, economic damages and loss of human lives. All the strategies basically are good for long term mitigation but not appropriate for solving the real problems when a disaster happens, because it is static and not real time. To overcome, two main points should be developed: sociocultural knowledge on floods and flood prevention infrastructure development. Both are correlated to build the settlement of flood problem. Therefore, it is essential to build an integrated system combining Cyber-Physical-Human. The proposed system includes (1) physical layer that consist of sensors rainfall and river water levels and satellite sensors, (2) abstract layer consist of flood modelling (3) interaction with human. Mitigation system based Cyber - Physical - Human will be very useful for agencies related to flood control and as a decision making tool for the government and society at large. Surabaya is chosen as study area

This paper presents an explorative cultural-image analyzer and its application to comparative analyses of cultural arts and crafts. The goal of this system is to provide a new image-exploration environment that reflects the diversity of humans' sense of color and the breadth of cultural human knowledge by detecting and visualizing characteristic historical color-trends within cultural-image data sets. The primary components of this system are the two explorative analysis methods with feature estimation and evaluation of culture-dependent colors: (a) image-group exploration and (b) color exploration. The system visualizes the distinct differences among image groups aggregated by the attributes such as author, era, region, etc. and provides notable images for users through the image-group exploration method. In addition, the system visualizes the subtle differences of colors in images and provides a key to analyze cultural art works by the color-exploration method, with a zooming function for color distributions and cultural-color name estimation. By utilizing the existing annotations and attributes that are available for most images, the system analyzes the differences of colors among image-groups defined by statistical analysis and visualizes the representations of each image-group on an overview map. This system enables a user to analyze the characteristics of a collection of cultural art works by browsing the representative images of each image-group, exploring the specified culture-dependent colors with high accuracy, and observing subtle differences of colors among image-groups according to culture-dependent color names at a glance.

The aim of this research is to construct a new collaborative mashup system, named Web-based Environmental Education (WEE), for global environmental monitoring research and education in which all participants could associatively organize multimedia data about physical environments and visually monitor various environmental topics based on time-series multi-geographical views. The main features of this system are: (1) collaborative multimedia database creation using "social sensors", (2) information aggregation from Web resources, (3) content-based image and document retrieval, and (4) big-picture visualization with spatiotemporal view controllers and content-based image, document retrieval. In this paper, a new designed usage of social network services as an educational tool and a new method for gathering environmental information from Web resources are presented. We also present three promising educational scenarios to examine the applicability of the system.

This paper includes five contributions on the topic of multimedia information systems for social, cross-cultural and environmental computing. Approaches, models, and methods for Web Semantization, Cross-cultural Image Computing, Information Modelling and Data Mining, Mobile Information Systems for Ubiquitous Society, and Multimedia Systems for Cross-cultural and Environmental Computing are introduced and discussed. This paper is based on the contributions presented in the panel discussion of EJC 2012 Conference.

This paper presents a Web-based nature sound ensemble learning system that allows students to create a narrative-episode with "visual", "auditory", and "experimental" effects. Main component of our system is implemented in the Web environment and can be easily introduced to PCs in a classroom for nature sound ensemble lessons among remote learners, classes, and schools. In this study, we show the feasibility of our Web-based ensemble learning system, where several learners actually participate in the remote nature sound ensemble lessons using example "narrative-episode" with pictures and nature sounds. © 2013 Springer-Verlag.

A bird-world image-map system is a new geographical system with spatiotemporal and color analysis functions. This System is like a "Multimedia Encyclopedia", which makes it possible for users to share comprehensive birds' knowledge, such as the name, habitat, migration and activity period of birds, by creating birds' database from users' input and fragment data on cyberspace and visualizing the datasets on a set of chronologically-ordered world-maps. Because of the rapid progress in multimedia, mobile and GIS technology, various kinds of information resources about natural environments of the real world can be accessed in a cyber space. In this situation, it is important to support users to acquire valuable knowledge that expresses user's fragmentary information about the real world and adequate information on the cyber space. In order to provide and collect birds' information in the world and create digital maps, this system realizes the functions for identifying a bird contained in a picture image input by a user through the global analysis of temporal, spatial and color information of images within a selected domain. In addition, this system makes it possible for users to share comprehensive birds' knowledge, such as the habitat, migration and the activity period of birds by creating birds' database from users' input and fragment data on cyberspace and visualizing the datasets on a set of chronologically-ordered world-maps. This system is also applicable for natural environment analysis by visual observation of ecological form, distribution, history and change of living-things, such as global habitats and migration.

Over the past decade, the rapid progress of multimedia data management technology has realized the large scale of media data transfer and resource-accumulation in the world. The multimedia computing technology has also been creating new information provision environments in the world-wide scope. Innovative integrations of large scale multimedia data management and computing technology will lead to a new information society. In the design of multimedia systems, one of the most important issues is how to search and analyze media data (images, music, movies and documents), according to impressions and contexts. We have proposed and introduced a "Kansei" and semantic associative search method based on our "Mathematical Model of Meaning (MMM) [11], [13], [14]". The concept of "Kansei" includes several meanings on sensitive recognition, such as "impression", "human senses", "feelings", "sensitivity", "psychological reaction" and "physiological reaction". This model realizes "Kansei" processing and semantic associative search for media data, according to user's impressions and contexts. This model is applied to compute semantic correlations between keywords, images, music and documents dynamically in a context-dependent way. The main feature of this model is to realize semantic associative search in the 2000 dimensional orthogonal semantic space with semantic projection functions. This space is created for dynamically computing semantic equivalence or similarity between keywords and media data. We have constructed "Cross-Cultural Multimedia Computing Systems" for sharing and analyzing different cultures with semantic associative functions applied to "cultural &amp multimedia data," as a new platform of cross-cultural collaborative environments. This environment enables to create a remote, interactive and real-time cultural and academic research exchange among different countries and cultures. © 2012 Springer-Verlag Berlin Heidelberg.

It is a significant research area in computer-assisted music learning to develop interactive learning materials to cultivate learner's performing abilities of musical instruments. Especially in the ensemble lesson at school, it is pointed out that not only the progress of playing technique is important, but also the development of each learner's abilities in collaboration and creativity in expression should be focused on. In this paper, we present a prototype of Web-based music learning system with "visual", "auditory", and "experimental" effects. The feature of our system is the Web-based playing functions, which are designed for ensemble lessons among remote learners, classes, and schools. In addition to the feasibility of our learning system, we present practical lesson scenarios using our prototype system. © 2011 IEEE.

Purpose – The purpose of this paper is to present the design and implementation of music courseware that features a music search system that uses impression keywords. The paper applies the courseware to Kansei (sensibility) development for elementary and junior high school students. The objectives of this courseware are to cultivate children's sensitivity to the mood of a music selection an understanding of the effects of tonality on the mood of the music and) an ability to appreciate and express music through activities such as searching, selecting, and listening while also utilizing information about musical impression. The courseware is also designed to support teachers who do not specialize in music education. Design/methodology/approach – Music courseware is designed containing the following three components: a semantic associative search engine that enables the retrieval of media data related to impression keywords selected by users interfaces and tools for music retrieval and learning, which support users as they study the mood of the music in an easy-to-understand format using basic music teaching scenarios and basic music teaching scenarios that are designed and created by elementary school teachers to encourage student understandings of the tonality and mood of the music in a practical manner. Findings – The results of several qualitative and quantitative experiments show that this courseware assists children in independently learning musical elements by feeling, understanding, and expressing music impressions using words from the courseware that are extracted automatically from musical elements, such as key, rhythm, tempo, pitch, melody, and harmony. Research limitations/implications – Additional applications in various elementary and junior high school settings are needed to address a variety of practical, real-life teaching scenarios. Social implications This courseware have the potential to support enrichment programs not only in ordinary schools but also in a wide range of non-educational settings, such as welfare care, disability care, and cross-cultural communication. Originality/value – The main feature of this courseware is its multimedia database technology, which applies Kansei to music education, thereby enabling students to understand the mood and structure of music based on their own subjective impressions using an objective framework. © 2010, Emerald Group Publishing Limited