“Semantic space creation” and “distance-computing” are basic functions to realize semantic computing for environmental phenomena memorization, retrieval, analysis, integration and visualization. We have introduced “SPA-based (Sensing, Processing and Actuation) Multi-dimensional Semantic Computing Method” for realizing a global environmental system, “5-Dimensional World Map System”. This method is important to design new environmental systems with Cyber-Physical Space-integration to detect environmental phenomena occurring in a physical-space (real space). This method maps those phenomena to a multi-dimensional semantic-space, performs semantic computing, and actuates the semantic-computing results to the physical space with visualizations for expressing environmental phenomena, causalities and influences. As an actual system of this method, currently, the 5D World Map System is globally utilized as a Global Environmental Semantic Computing System, in SDG14, United-Nations-ESCAP: (https://sdghelpdesk.unescap.org/toolboxes). This paper presents a semantic computing method, focusing on “Time-series-Analytical Semantic-Space Creation and Semantic Distance Computing on 5D World Map System” for realizing global environmental analysis in time-series. This paper also presents the time-series analysis of actual environmental changes on 5D World Map System. The first analysis is on the depth of earthquakes Earthquake with time-series semantic computing on 5D World Map System, which occurred around the world during the period from Aug. 23rd to Aug. 28th, 2014, and Jan 7th to Jan. 13th, 2023. The second is the experimental analysis of the time-series difference extraction on glacier melting phenomena in Mont Blanc, Alps, during the period from 2013 to 2022, and Puncak Jaya (Jayawijaya Mountains), Papua, during the period from 1991 to 2020 as important environmental changes.

This paper presents an important application of 5D World Map System with a Risk-Resilience calculation and visualization method using time-series multilayered data for disasters and environmental change analysis to make appropriate and urgent solutions to global and local environmental phenomena in terms of short and long-term changes. This method enables the calculation of the current risk and resilience of a target region or city for disasters and rapid environmental changes, based on the analysis of past time-series changes of natural and socioeconomic factors’ distribution. This method calculates the total risk and resilience to disaster as a total aggregate value that reflects the amount of change in each variable in the past, by transforming multidimensional and heterogeneous variables into a form that allows comparative and arithmetic operations through geographical normalization and projection. As an implementation and experiments, we apply our method to assessing the role of forests in urban disaster resilience as an example, by analyzing time-series changes in vegetation and forest distribution and their relationships in urban areas. Specifically, using GIS, satellite data, demographic data, urban infrastructure data, and disaster data, we analyze the relationship among urban disaster occurrence and 1) population density, 2) urban infrastructure development, and 3) forest distribution and calculate “urban-forest-disaster risk/resilience”.

This paper describes about project “Data Sensorium” launched at the Asia AI Institute of Musashino University. Data Sensoriumis a conceptual framework of systems providing physical experience of content stored in database. Spatial immersive display is a key technology of Data Sensorium. This paper introduces prototype implementation of the concept and its application to environmental and architectural dataset.

It is significant to detect, estimate and predict “Human-health situations” and “a spread of transmitted disease” with past and current information of health-related phenomena. Temporal-transition and differential computing realizes semantic interpretations for situation changes in two phenomena with “temporal-length” in “specific situation”. The “temporal-length” in “specific situation” is used to compare two phenomena in multiple contexts in semantics. We present a new Temporal-transition Differential Computing Model for detecting, estimating and predicting “Human-health situations” and “a spread of transmitted disease.” This model defines “temporal-transition data structure” for expressing past and current information of health-related phenomena with temporal-axis, and two processes for Human-Health Semantic Space Creation and Semantic Computing with dimensional control mechanism.

The “SPA-based 5D World Map System” realizes Cyber-Physical-Space integration to detect changes of environmental phenomena with real data resources in a physical-space (real space), map them to the cyber-space to make knowledge bases and analytical computing, and actuate the computed results to the real space with visualization for expressing the causalities and influences. This paper presents an important application of 5D World Map System, adding “AI-Sensing” functions for “Global Environment-Analysis” to make appropriate and urgent solutions to global and local environmental phenomena in terms of short and long-term changes. Focusing on the ocean plastic garbage issues, this paper describes the methodology of AI-Sensing, the preliminary models and experiments on the accuracy of AI-Sensing and the substantiative experiments on the feasibility and effectiveness of AI-Sensing with real local data. In addition, the example outputs of the integration of AI-Sensing algorithm and SPA-based 5D World Map System and the future direction of a collaborative project for ocean plastic-garbage reduction are introduced.

Semantic space creation and computing are essentially significant to realize semantic interpretations of situations and symptoms in human-health. We have presented a semantic space creation and computing method for domain-specific research areas. This method realizes semantic space creation with domain-oriented knowledge and databases. This paper presents a semantic space creation and computing method for “Human-Health Database” with the implementation process for “Human-Health-Analytical Semantic Computing”. This paper also presents a new knowledge base creation method for personal health data for preventive care and potential risk inspection with global and geographical mapping and visualization in 5-Dimensional World Map System. This method focuses on the analysis of personal health and potential-risk inspection and realizes a set of semantic computing functions for semantic interpretations of situations and symptoms in human-health. This method is applied to “Human-Health-Analytical Semantic Computing” to realize world-wide evaluation for (1) multi-parameterized personal health data, such as various biomarkers, clinical physical parameters, lifestyle parameters, other clinical/physiological or human health factors, etc., for health monitoring, and (2) time-series multi-parameterized health data in the national/regional level for global analysis of potential cause of disease. This Human-Health-Analytical Semantic Computing method realizes a new multidimensional data analysis and knowledge sharing for a global-level health monitoring and disease analysis. The computational results are able to be visualized in the time-series difference of the values in each place, the difference between the values of multiple places in a focused area, and the time-series differences between the values of multiple places to detect and predict a potential-risk of diseases.

Cross-cultural religious tourism is computational to promote cross-cultural communication and understanding according to impression distance. Our motivation to implement semantic search with an emotion-oriented context into the proposed system is to realize global tourism recommendations expressed in different cultures. The objectives of this paper are (1) to find the religious places by using the tourist’s emotional distance, (2) to find similar religious places not only in the same culture but also in the different cultures with the tourist’s emotional distance calculations. Experimental results demonstrate the feasibility and applicability of this method.

This paper presents a new knowledge base creation method for personal/collective health data with knowledge of preemptive care and potential risk inspection with a global and geographical mapping and visualization functions of 5D World Map System. The final goal of this research project is a realization of a system to analyze the personal health/bio data and potential-risk inspection data and provide a set of appropriate coping strategies and alert with semantic computing technologies. The main feature of 5D World Map System is to provide a platform of collaborative work for users to perform a global analysis for sensing data in a physical space along with the related multimedia data in a cyber space, on a single view of time-series maps based on the spatiotemporal and semantic correlation calculations. In this application, the concrete target data for world-wide evaluation is (1) multi-parameter personal health/bio data such as blood pressure, blood glucose, BMI, uric acid level etc. and daily habit data such as food, smoking, drinking etc., for a health monitoring and (2) time-series multi-parameter collective health/bio data in the national/regional level for global analysis of potential cause of disease. This application realizes a new multidimensional data analysis and knowledge sharing for both a personal and global level health monitoring and disease analysis. The results are able to be analyzed by the time-series difference of the value of each spot, the differences between the values of multiple places in a focused area, and the time-series differences between the values of multiple locations to detect and predict a potential-risk of diseases.

This paper presents a 5D World Map System's application for disaster-resilience monitoring as "Environmental AI System" of each player's implementation of United Nation's SDG 9 and DGS 11 from global-level to regional-level, country-level, sub-regional-level and city-level. In Asia-Pacific, disaster risk is outpacing disaster resilience. The gap between risk and resilience-building is growing in those countries with the least capacity to prepare for and respond to disasters. Using the Sensing-Processing-Actuation (SPA) functions of 5D World Map System, a disaster risk analysis can be conducted in multiple contexts, including regional, national, and sub-national. At the regional, national and subnational levels, the analysis will focus on identifying disaster risk hotspots through incorporating existing multi-hazard disaster risk and socio-economic risk information. The system will further be used to assess future risks through integration of global climate scenarios downscaled to the region as well as countries. This paper presents the design of two new actuation functions of 5D World Map System: (1) Short-term warning with prediction and push alert and (2) Long-term warning with context-dependent multidimensional visualization, and examines the applicability of these functions by indicating that (1) will support both resident and those who are working at the operational level by being customized to disaster risk analysis for each target region/country/area, and (2) assist both policy-makers and sectoral ministries in target countries to use the analysis for evidence-based policy formulation, planning and investment towards building disaster-resilient society.

Metadata space creation for semantic associative search is an essential process for semantic searching for news article. We apply semantic computing methodology to realize an Environmental-News-Article Search System with Context-Oriented Interpretations. This paper presents a method for creating an environmental-news-article metadata space for applying semantic computing to environmental news-resources. Our creation process for realizing an environmental-news-article semantic space is (1)select news article regarding environment from news-resources, (2)extract news article that have keyword-tag “Global Warming” or “Warming” and set them as news article of “Global Warming,” (3)obtain all keyword-tag that news article of “Global Warming” have, (4)Count appearance frequency of each keyword-tag in news article of “Global Warming” and determine frequency thresholds of keyword-tag for composing metadata space, (5)create the environmental-news-article metadata space using the keyword-tag creamed off. We compared between several experiments with changed search phenomenon or search context for semantic associative search, and we made certain that our Environmental-News-Article Search System extracts the metadata space properly depending on the context and retrieves phenomena and documents semantically close to the search phenomenon or the search context. Our evaluation shows the effectiveness of the method for creating an environmental-news-article metadata space for applying semantic computing to environmental news-resources.

Semantic computing integration with deep-learning realizes a new artificial brain-memory system. We have presented a concept of “MMM: Semantic Computing System” for analyzing and interpreting environmental phenomena and changes occurring in the oceans and rivers in the world. We also introduce the concept of “SPA (Sensing, Processing and Analytical Actuation Functions)” for realizing a global environmental system, to apply it to Multi-dimensional World Map (5-Dimensional World Map) System. This concept is effective and advantageous to design environmental systems with Physical-Cyber integration to detect environmental phenomena as real data resources in a physical-space (real space), map them to cyber-space to make analytical and semantic computing, and actuate the analytically computed results to the real space with visualization for expressing environmental phenomena, causalities and influences. This paper presents integration and semantic-analysis methods for KEIO-MDBL-UN-ESCAP Joint system for global ocean-water analysis with Coral-Image Analysis in two environmental-semantic spaces with water-quality and image databases. We have implemented an actual space integration system for accessing environmental information resources with water-quality and image analysis. We clarify the feasibility and effectiveness of our method and system by showing several experimental results for environmental medical document data Environmental-semantic space integration realizes deep analysis environmental phenomena and situations. The essential computation in environmental study is context-dependent-differential computation to analyze the changes of various situations (air, water, CO2, places of livings, sea level, coral area, etc.). It is important to realize global environmental computing methodology for analyzing difference and diversity of nature and livings in a context dependent way with a large amount of information resources in terms of global environments. In the design of environment-analysis systems, one of the most important issues is how to integrate several environmental aspects and analyze environmental data resources with semantic interpretations. In this paper, we present an environmental-semantic computing system. Our environmental-semantic computing system realizes integration and semantic-search among environmental-semantic spaces with waterquality and image databases.

This paper presents an application of 5D World Map System with Context-Diversity-Responsive Semantic Associative Search for a large database of environmental news articles. By applying 5D World Map System to data describing social and natural phenomena, a new news-article subscription environment is realized by the dynamic combination of various semantic, temporal and spatial “context”. The new subscription environment enables to create, accumulate and visualize a series of analyzed results of semantic relations among phenomena as an interpreted social story. The system realizes the extraction of correlative and causal relations between phenomena which are potentially included in news articles. A semantic associative search method is applied to this system for realizing the concept that “semantics” of words, documents, and events/phenomena vary according to the “context”. The main feature of this system is to create various context-dependent patterns of social stories according to user's viewpoints and the diversity of context in phenomena dynamically. This system also provides an environment for analyzing the time-series change and spatial expansion of social and natural phenomena on a time-series multi-geographical space. In this paper, we show a prototype system applied for vast ten years of news-articles and several experiments about “global warming” to clarify the feasibility of the system.

This paper presents a global sharing analysis and visualization of water quality analysis by 5D World Map (5DWM) system. The data resources in this research collected from Sichang Island, Chonburi province, Thailand during 1990 to 2002 and 2010 to 2017. Six parameters of water quality were selected during 1990 to 2002 i.e. chlorophyll a, ammonia, nitrite, nitrate, phosphate and. The total locations sites were 21 stations which situated around Sichang Island. Otherwise, ten parameters were selected during 2010 to 2016 i.e. temperature, salinity, dissolved oxygen (DO), pH, ammonia, nitrite, nitrate, phosphate, silicate, and alkalinity. On the other hand, eight parameters were selected in February and July 2017 i.e. temperature, pH, oxidation reduction potential (ORP), conductivity, turbidity, dissolved oxygen (DO), TDS (Total Dissolved Solids), and salinity. All parameter of water quality was added and display by 5DWorld Map in order to visualize and sharing the water quality. Our results showed that 5DWorld Map can apply to environmental analysis and semantic computing. We apply the dynamic evaluation and mapping functions of multiple views of temporal-spatial metrics, and integrate the results of semantic evaluation to analyze environmental multimedia information resources. 5D World Map System for world-wide viewing for Global Environmental Analysis for water quality around Sichang Island, Thailand was reported in this study.

This research deals with the monitoring techniques using normal and multi-spectrum cameras to detect coral healthiness. The Acropora Corals were investigated in laboratory experiment. Parameter of investigation is Ammonia contamination from 0.01 ppm to 10.0 ppm. Under these conditions, the images of coral were captured and analyzed. An Entropy and coral indices of the obtained images were proposed. The important finding in this study is the feature extraction of coral healthiness: (1) event detection, (2) % degradation and (3) relationship between coral index and entropy. For event detection, the trends of water quality parameters such as temperature and salinity was considered. The obtained entropy values gave % degradation of coral. It was also found that GRCI index related with the relevant entropy values of coral images.

Environmental-semantic space integration is a promising approach to realize deep analysis environmental phenomena and situations. The essential computation in environmental study is context-dependent-differential computation to analyze the changes of various situations (air, water, CO2, places of livings, sea level, coral area, etc.). It is important to realize global environmental computing methodology for analyzing difference and diversity of nature and livings in a context dependent way with a large amount of information resources in terms of global environments. In the design of environment-analysis systems, one of the most important issues is how to integrate several environmental aspects and analyze environmental data resources with semantic interpretations. In this paper, we present an environmental-semantic computing system. Our environmental-semantic computing system realizes integration and semantic-search among environmental-semantic spaces with water-quality and image databases. We have already presented a concept of “Semantic Computing System” for analyzing and interpreting environmental phenomena and changes occurring in the oceans and rivers in the world. We also introduce the concept of “SPA (Sensing, Processing and Analytical Actuation Functions)” for realizing a global environmental system, to apply it to Multi-dimensional World Map (5-Dimensional World Map) System. This concept is effective and advantageous to design environmental systems with Physical-Cyber integration to detect environmental phenomena as real data resources in a physical-space (real space), map them to cyber-space to make analytical and semantic computing, and actuate the analytically computed results to the real space with visualization for expressing environmental phenomena, causalities and influences. This paper presents integration and semantic-analysis methods for two environmental-semantic spaces with water-quality and image databases. We have implemented an actual space integration system for accessing environmental information resources with water-quality and image analysis. We clarify the feasibility and effectiveness of our method and system by showing several experimental results for environmental medical document databases.

Three species of corals at Sichang Island i.e. Acropora sp. Goniopora sp. and Pavona sp. were subjected to a stress test with low salinity and normal salinity at concentration 10, 20 and 30 psu, respectively. Under water photograph and eye observation of coral activity were recorded at 12, 24 and 48 hours. The entropy or surface roughness and percent polyp activity were analyzed with comparison to eye observation of coral activity. The experiment was carried out under continuously water temperature and underwater light intensity controlled. The results indicated that “Healthy” entropy values for Acropora sp. are 1.57–1.62 and for Goniopora sp. are 4.26–4.46. In contrast, for Pavona sp., short polyp coral, there was no “Healthy” entropy value resulted from any photographic assessment in this study. The “Healthy” value of Acropora sp. evaluated from percent active polyp was more than 52.4. For conclusion, The Entropy and percent active polyp values were suitable tools for Acropora sp. and Pavona sp., a short polyp coral's healthy identification. Whereas the eye observation of coral activity both percent polyp extend and percent polyp long was suitable for Goniopora sp., a long polyp coral.

This paper presents a new analysis method and the functions for multi-dimensional sensing data, including multi-parameter sensor data and series of sensing images, for a collaborative knowledge creation system called 5D World Map System, and the applications in the field of multidisciplinary environmental researches. The main feature of 5D World Map System is to provide a platform of collaborative work for users to perform a global analysis for sensing data in a physical space along with the related multimedia data in a cyber space, on a single view of time-series maps based on the spatiotemporal and semantic correlation calculations. The concrete target data of the proposed new method and functions for world-wide evaluation is (1) multi-parameter sensor data such as water-quality, air-quality, soil-quality etc., and (2) multispectral and natural-color image data taken by moving cameras such as UAV/car-mounted cameras or mobile phones for environmental monitoring. The proposed world-wide evaluation functions enable multiple remote-users to acquire real-time sensing data from multiple sites around the world, perform analytical visualizations of the acquired sensing data by a selected world environmental standard to discover the incidental phenomena, and provide the analysed results to related users' terminal equipment automatically. These new functions realize a new multidimensional data analysis and knowledge sharing for a collaborative environment. Especially, in the world-wide evaluation function, applying the concept of “semantic computing” to determining the environmental-quality levels of multiple places around the world. The results are able to be analysed by the time-series difference of the value of each place, the differences between the values of multiple places in a focused area, and the time-series differences between the values of multiple places, and calculated as a “world ranking”, to detect and predict an environmental irregularity and incident. In our world-wide evaluation method, we define the environmental impacts as “semantics” of environmental condition. The originality of our method is in (1) an interpreter to convert the numerical environmental quality-level to the qualitative impacts/meanings by the sentence or a set of words that even non-specialists or ordinary people are able to understand, and (2) a visualizer to realize a global comparison and “world-ranking” with a semantic computing for targeting the multi-parameter sensing values of multiple sites around the world.

The global environmental analysis system is a new platform to analyze environmental multimedia data that acquired from nature resources. This system aims to realize and interpret environmental phenomena and changes occurring that happening in world wide scope. Semantic computing is important and promising approach to multispectral semantic-image analysis for various environmental aspects and contexts in physical world. In the previous study, we proposed a new system of agricultural monitoring and analysis based on semantic computing concept that it realizes the interpretation of agricultural health condition as human-level interpretation. In this paper, we propose a new analytical method for agriculture global comparisons to realize and recognize crop condition with several places in global scale. Multispectral semantic-image space for agricultural analysis can be utilized for global crop health monitoring by comparing crop conditions among different places. Our method applies semantic distance calculation to measure similarity among multispectral image data to realize the crop health condition as a ranking. According to our new proposed analytical method, we demonstrate a prototype implementation in the case of rye farm in Latvia and Finland. This prototype implementation shows an analysis in the case that image data have same crop type and conditions.

Human-microbiome-relations extraction is important for analyzing the effects on human gut microbiome from the difference of human attributes such as country, sex, age and so on. Human gut microbiome, a set of bacteria, provides various pathological and biological impacts on a hosting human body system. This paper presents a new analytical method for data resources that are difficult to understand such as human gut microbiome, by extracting the unknown relations with other adjunct metadata (e.g. human attributes data) with context-dependent clustering and semantic analysis. This method realizes the significant bacterial components acquisition for categorizing human attributes. The most important feature of our method is to analyze the unknown relations of human-microbiome with or without a correlation between a human attribute and bacteria that is found by related studies in bacteriology. With this method, an analyst is able to grasp the overview of bacteria data clustered by several clustering algorithms (k-means clustering / hierarchical clustering) using bacteria data selected by human attributes as a set of context. In addition, even without an association between a human attribute and bacteria as heuristic knowledge, an analyst is able to extract human-microbiome-relations focusing on a number of bacteria selected from all bacteria combinations by one-way analysis of variance (ANOVA) and our original criteria called the “degree of separation” of clustering. This paper also presents an experimental study about human-microbiome-relations extraction and the experimental results that show the feasibility and effectiveness of this method.

In the design of multimedia data mining systems, one of the most important issues is how to search and analyze media data, according to contexts. We have introduced a semantic associative search method based on our “Mathematical Model of Meaning (MMM) [1, 2, 3]”. This model is applied to compute semantic correlations between keywords, images, music and documents dynamically in a context-dependent way.

Dengue fever is a communicable disease that attacks more than 120 countries in the world during 50 years. Therefore, it is to make sense to say that collaboration among the countries, especially neighborhood countries, is one important key to combat the dengue. Currently, except a serological collaboration, collaboration in dengue is sporadic and temporal. This paper addresses the initiative to build vector-control strategy collaborative among Surabaya (Indonesia), Kuala Lumpur (Malaysia), and Bangkok (Thailand). Deriving the global policy from World Health Organization (WHO), we build the system that (1) extracting global feature from the local feature, (2) selecting the significant features, to determine ranking of importance of a feature, by weighting a feature, and (3) matching the pattern of data to the suitable strategy by measuring the similarity. We built the system from the real data of the Surabaya, Kuala Lumpur and Bangkok in 2012. We verified reliability of the system by comparing the data with the actual action in January 2012 The result shows that the system is system feasible to be implemented, however we still need more preparation to implement the system.

The multi-dimensional analysis is a promising approach to a new interpreting of environments by ground of the value-information and language-information on intellectual activities in various environment meanings to society. This paper presents a new analysis-system with semantic computing for environments in water-quality areas by integrating the fundamental important parameters of water-quality for creating the new meaning to society. The multi-water-parameter-analysis in a multi-dimensional space is important for current research issues in some water-quality research fields, which are based on the values and meanings of each parameter for obtaining the meaningful words in the category of agriculture, aquatic life, fish, drinking, industrial and irrigation. The multi-dimensional semantic space is significantly utilized for various interpretations related to the water-quality.

Multispectral image becomes widely used for environmental analysis to detect an object or phenomena that human eyes cannot capture. One of the main type of images acquired by remote sensing such as satellite or aircraft for earth observation. This paper presents a multispectral analysis for aerial images that captured by dual cameras (visible and infrared camera), which are mounted on an unmanned autonomous vehicle (UAV) or Drone. In our experiments, four spectral bands (three visible and one infrared band) were imaged, processed and analyzed to detect agricultural area and measure the health of vegetation. To interpret environmental phenomena and realize an environmental analysis, this study applies semantic analysis by creating a multispectral semantic image space, combined with three numerical indicators (the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI) and the soil adjusted vegetation index (SAVI)) that can be used to analyze plant health, photosynthetic activity and detect environmental object to determine an agricultural area. This paper also proposed the concept of multi-spectrum semantic-image space for agricultural monitoring by defining the correlation meaning from multi-dimensional parameters which related to agricultural analysis to realize and explain agriculture conditions. This paper presents the experimental study on a rice field, a cornfield, a salt farm and a coconut farm in Thailand.

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.

This paper presents real-time sensing, processing and actuating functions of a collaborative knowledge sharing system called 5D World Map System, and the applications in the field of multidisciplinary environmental research and education. The first objective is to integrate the analysis of sensing data into a knowledge sharing system with multimedia, based on the framework of Sensing-Processing-Actuation of Cyber-Physical Systems. The proposed real-time sensing, processing and actuating functions enable multiple remote-users to acquire real-time sensing data from multiple sites around the world, perform analytical visualizations of the acquired sensing data by the selected calculation methods on the system to discover the incidental phenomena, and provide the analysed results to related users' terminal equipment automatically. The second objective of the research is to realize a new multidimensional data analysis and knowledge sharing system for a collaborative environment by applying the concept of “differential computing” to the analysis of sensing data. Especially, in the processing function, the time-series difference of the value of each sensor, the differences between the values of multiple sensors in a selected area, and the time-series differences between the values of multiple sensors, are calculated, to detect an environmental incident and estimate the possibility of occurrence of the same kind of incident in the neighboring sites within the same area. By using 5D World Map System integrated with these functions, the users are able to perform a global analysis on the environmental sensing data along with the related multimedia data on a single view of time-series maps, based on the spatiotemporal and semantic correlation calculations.

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 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.

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: socio-cultural 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.

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.

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.

Specification of collaboration has neglected over a long period although collaboration is one of main conceptions in computer science and computer engineering. We distinguish between collaborations among systems and socio-technical collaboration. Database research has succeeded in developing approaches for collaboration among database systems that incorporate conceptual specification and allow to reason on systems at a far higher abstraction level. Conceptual modelling of socio-technical collaborating systems is however an open research issue. With the advent of web information systems systems became naturally socio-technical and collaborating. Therefore, we need a techniques for conceptual description of collaboration. Collaboration modelling may be based on models for communication, models for coordination, and models for cooperation. In socio-technical systems users work within their local environment and collaborate within the global world. Therefore, users inject their culture and their specific behaviour into collaboration. Users use information, communication, cooperation and coordination services. These services must be highly flexible and adaptable to the needs of users, to the circumstances and contexts of these users, and to the technical infrastructures used.

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.

Virtual communities rely primarily on ICT to connect their members to work together, and to share knowledge and practices. The importance of virtual collaborative work is increasing not only because of its economical and environmental benefits, but also due to its flexibility for establishing dynamically new cross-organizational and cross-cultural innovative teams. Virtual collaborative spaces should support their joint activities. In order to design and realize such spaces, an understanding of the tasks to be carried out by the virtual community is necessary, as well as an understanding of the related processes, contexts, and knowledge. In our paper, we introduce a reference model of a Cross-Cultural Cyber Space (CCS) for context-based knowledge creation and sharing between the members of the cross-cultural collaborative community. We also describe the prototype implementation of the CCS, a 3D cross-cultural art museum system.

Cultural computing is an emerging field of multidisciplinary computer science. In the near future, cultural computing will have several important applications in the fields of business, knowledge society, environmental issues, health care, education and research. Our paper is written in collaboration with the authors, who are also participants in the collaborative research project “Ubiquitous Cross-Cultural Multimedia Systems for Mobile Computing Societies/Ubiquitous Cross-Cultural Knowledge Space”. The issues discussed in our paper cover background knowledge related to cultural computing, general discussion of culture as a concept, an introduction to the concept and basic design of the Electronic Assistant for Cross-Cultural Communication, and an introduction to the design and implementation of the 3D Cross-Cultural Multimedia Museum" system and its applications. The 3D Cross-Cultural Multimedia Museum has been implemented as a prototype system of Cross-Cultural Cyber Space. The global changes caused not only by scientific and technological development, but by environmental issues as well, are our driving forces towards the era of cultural computing. Our paper is based on the presentations of the panel discussion at the EJC 2009 Conference.

This paper presents a design and implementation for the “4D World Map System,” a knowledge representation system which enables semantic, temporal and spatial analysis of documents, and integrates and visualizes the analyzed results as a 4-dimentional dynamic historical atlas (4D World Map Set). The main feature of this system is to create various context-dependent patterns of historical/cultural stories according to a user's viewpoints dynamically. This system generates multiple views of semantic and temporal-spatial relationships among documents of the humanities and social sciences. This system organizes the relationships among documents into various historical/cultural stories by a user's viewpoints. A semantic associative search method is applied to this system for realizing the concept that “semantics” of words, documents, and events vary according to the “context”. Semantically-evaluated and analyzed document data are also mapped dynamically onto a time-series multi-geographical space. This system provides high visibility of semantic correlations between documents in time series variation with geographic information. In this paper, we also show several experiments by using news articles and International Relations documents to clarify the feasibility of the system.

This paper presents a dynamic image-query creation and metadata extraction method with semantic correlation computation between color-combinations and impressions of multiple image data. The main features of our method are (1) to create an image-query which reflects user's intention dynamically according to the color-based combinations of images with common features selected by a user as context, (2) to extract appropriate impression by each image collection which cannot be easily extracted from a single image, (3) to provide users an image retrieval environment reflecting historical and cultural semantics and impression of color especially for cultural properties, and (4) to enable an image retrieval environment for the collection of images by time, culture, author e.t.c.. The queries are created by the combination of multiple image sets and operations, which are intersection, accumulation, average, difference of color elements of sample images. First, a set of multiple images with common features is set as sample data for a query creation. Second, color histograms are extracted from the image sets for creating feature vector of a query. Third, the correlations between an image-query vector and target image vectors are calculated on a space which represents the relationship between color and the impression according to historical and cultural semantics of color. This image-query creation method representing impression of color makes it possible to expand the range of image retrieval for a large number of image data of cultural property in digital archives, such as electronic library and electronic museum, automatically.