Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring)

Symbol Emergence in Robotics: A Survey

Humans can learn the use of language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form a symbol system and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted on the construction of robotic systems and machine-learning methods that can learn the use of language through embodied multimodal interaction with their environment and other systems. Understanding human social interactions and developing a robot that can smoothly communicate with human users in the long term, requires an understanding of the dynamics of symbol systems and is crucially important. The embodied cognition and social interaction of participants gradually change a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER is a constructive approach towards an emergent symbol system. The emergent symbol system is socially self-organized through both semiotic communications and physical interactions with autonomous cognitive developmental agents, i.e., humans and developmental robots. Specifically, we describe some state-of-art research topics concerning SER, e.g., multimodal categorization, word discovery, and a double articulation analysis, that enable a robot to obtain words and their embodied meanings from raw sensory--motor information, including visual information, haptic information, auditory information, and acoustic speech signals, in a totally unsupervised manner. Finally, we suggest future directions of research in SER.Comment: submitted to Advanced Robotic

Spatial Aspects of Metaphors for Information: Implications for Polycentric System Design

This dissertation presents three innovations that suggest an alternative approach to structuring information systems: a multidimensional heuristic workspace, a resonance metaphor for information, and a question-centered approach to structuring information relations. Motivated by the need for space to establish a question-centered learning environment, a heuristic workspace has been designed. Both the question-centered approach to information system design and the workspace have been conceived with the resonance metaphor in mind. This research stemmed from a set of questions aimed at learning how spatial concepts and related factors including geography may play a role in information sharing and public information access. In early stages of this work these concepts and relationships were explored through qualitative analysis of interviews centered on local small group and community users of geospatial data. Evaluation of the interviews led to the conclusion that spatial concepts are pervasive in our language, and they apply equally to phenomena that would be considered physical and geographic as they do to cognitive and social domains. Rather than deriving metaphorically from the physical world to the human, spatial concepts are native to all dimensions of human life. This revised view of the metaphors of space was accompanied by a critical evaluation of the prevailing metaphors for information processes, the conduit and pathway metaphors, which led to the emergence of an alternative, resonance metaphor. Whereas the dominant metaphors emphasized information as object and the movement of objects and people through networks and other limitless information spaces, the resonance metaphor suggests the existence of multiple centers in dynamic proximity relationships. This pointed toward the creation of a space for autonomous problem solving that might be related to other spaces through proximity relationships. It is suggested that a spatial approach involving discrete, discontinuous structures may serve as an alternative to approaches involving movement and transportation. The federation of multiple autonomous problem-solving spaces, toward goals such as establishing communities of questioners, has become an objective of this work. Future work will aim at accomplishing this federation, most likely by means of the IS0 Topic Maps standard or similar semantic networking strategies

A Survey on Semantic Processing Techniques

Semantic processing is a fundamental research domain in computational linguistics. In the era of powerful pre-trained language models and large language models, the advancement of research in this domain appears to be decelerating. However, the study of semantics is multi-dimensional in linguistics. The research depth and breadth of computational semantic processing can be largely improved with new technologies. In this survey, we analyzed five semantic processing tasks, e.g., word sense disambiguation, anaphora resolution, named entity recognition, concept extraction, and subjectivity detection. We study relevant theoretical research in these fields, advanced methods, and downstream applications. We connect the surveyed tasks with downstream applications because this may inspire future scholars to fuse these low-level semantic processing tasks with high-level natural language processing tasks. The review of theoretical research may also inspire new tasks and technologies in the semantic processing domain. Finally, we compare the different semantic processing techniques and summarize their technical trends, application trends, and future directions.Comment: Published at Information Fusion, Volume 101, 2024, 101988, ISSN 1566-2535. The equal contribution mark is missed in the published version due to the publication policies. Please contact Prof. Erik Cambria for detail

Finding and Using Moving Images in Context

Using selected moving images from Northeast Historic Film, this project will take a team approach to achieve open access with a metadata system incorporating emerging standards for discovery. We will emphasize contextualization, building tools to provide access to articles, scene-by-scene notes, both item-level and collection-level descriptive records, and we will integrate this information with new curriculum materials through easy-to-use interfaces. Partners are Primary Source and China Source, Maine Historical Society's Maine Memory Network, MIC, and the University of Maine's Windows on Maine. Three China scholars associated with Primary Source are committed to the project. We will digitize and put online unique footage of China,1928-1936, with rights to reuse, and we will ensure that researchers can easily find, identify, understand, and use the moving images. Teachers will participate in evaluation, informing decisions regarding follow-up initiatives

Coastal Biophysical Inventory Database for the Point Reyes National Seashore

The Coastal Biophysical Inventory Database is the repository of the data gathered from a rapid assessment of approximately 161 km of the intertidal habitat managed by the Point Reyes National Seashore and Golden Gate National Recreation Area. The Coastal Biophysical Inventory Database is modeled after the “Alaska Coastal Resources Inventory and Mapping Database” and CoastWalker program of Glacier Bay National Park and Preserve. The protocol and database were adapted for this effort to represent the features of the Point Reyes National Seashore and Golden Gate National Recreation Area located along the northern central coast of California. The database is an integration of spatial data and observation data entered and browsed through an interface designed to complement the methods of the observation protocol. The Coastal Biophysical Inventory (CBI) and Mapping Protocol is the methodology to collect and store repeatable observations of the intertidal zone to create a baseline of information useful for resource management and potentially assist damage assessment in the event of an oil spill. The inventory contributes to the knowledge needed for the conservation of coastal resources managed in the public’s trust. The Coastal Biophysical Inventory Database is a Microsoft Access 2003 format relational database with a customized data entry interface programmed in Microsoft Access Visual Basic for Applications. The interface facilitates the entry, storage and relation of substrate, biology, photographs, and other field observations. Data can be browsed or queried using query tools common to the Microsoft Access software or using custom spatial query tools built into the interface with ESRI MapObjects LT 2.0 ActiveX COM objects. The Coastal Biophysical Inventory’s GIS data set is useful for collecting, analyzing and reporting field observations about the intertidal zone. The GIS data set is linked to the observation data set through a unique number, the Segment ID, by using the relate tools found in ArcGIS (9.2-10). The Segment ID is a non-repeating number that references a section of coastline that is delineated by the type and form of the substrate observed. The Segment ID allows connection to the biological observations and other observation records such as photos or the original data sheets. Through ArcGIS connections to the observation database using the Segment ID, summaries of biodiversity or habitat can be made by location. The Coastal Biophysical Inventory has completed its initial goals to assess the coastline of two National Parks. The data set collected provides a snapshot of information and the database allows for future observations to be recorded. It provides coastal resource managers a broad insight and orientation to the intertidal resources managed by the National Park Service