Affective Computing for Emotion Detection using Vision and Wearable Sensors

The research explores the opportunities, challenges, limitations, and presents advancements in computing that relates to, arises from, or deliberately influences emotions (Picard, 1997). The field is referred to as Affective Computing (AC) and is expected to play a major role in the engineering and development of computationally and cognitively intelligent systems, processors and applications in the future. Today the field of AC is bolstered by the emergence of multiple sources of affective data and is fuelled on by developments under various Internet of Things (IoTs) projects and the fusion potential of multiple sensory affective data streams. The core focus of this thesis involves investigation into whether the sensitivity and specificity (predictive performance) of AC, based on the fusion of multi-sensor data streams, is fit for purpose? Can such AC powered technologies and techniques truly deliver increasingly accurate emotion predictions of subjects in the real world? The thesis begins by presenting a number of research justifications and AC research questions that are used to formulate the original thesis hypothesis and thesis objectives. As part of the research conducted, a detailed state of the art investigations explored many aspects of AC from both a scientific and technological perspective. The complexity of AC as a multi-sensor, multi-modality, data fusion problem unfolded during the state of the art research and this ultimately led to novel thinking and origination in the form of the creation of an AC conceptualised architecture that will act as a practical and theoretical foundation for the engineering of future AC platforms and solutions. The AC conceptual architecture developed as a result of this research, was applied to the engineering of a series of software artifacts that were combined to create a prototypical AC multi-sensor platform known as the Emotion Fusion Server (EFS) to be used in the thesis hypothesis AC experimentation phases of the research. The thesis research used the EFS platform to conduct a detailed series of AC experiments to investigate if the fusion of multiple sensory sources of affective data from sensory devices can significantly increase the accuracy of emotion prediction by computationally intelligent means. The research involved conducting numerous controlled experiments along with the statistical analysis of the performance of sensors for the purposes of AC, the findings of which serve to assess the feasibility of AC in various domains and points to future directions for the AC field. The AC experiments data investigations conducted in relation to the thesis hypothesis used applied statistical methods and techniques, and the results, analytics and evaluations are presented throughout the two thesis research volumes. The thesis concludes by providing a detailed set of formal findings, conclusions and decisions in relation to the overarching research hypothesis on the sensitivity and specificity of the fusion of vision and wearables sensor modalities and offers foresights and guidance into the many problems, challenges and projections for the AC field into the future

Detection of inconsistencies in concept classifications in a large dictionary — Toward an improvement of the EDR electronic dictionary —

The EDR electronic dictionary is a machine-tractable dictionary developed for advanced computer-based processing of natural language. This dictionary comprises eleven sub-dictionaries, including a concept dictionary, word dictionaries, bilingual dictionaries, co-occurrence dictionaries, and a technical terminology dictionary. In this study, we focus on the concept dictionary and aim to revise the arrangement of concepts for improving the EDR electronic dictionary. We believe that unsuitable concepts in a class differ from other concepts in the same class from an abstract perspective. From this notion, we first try to automatically extract those concepts unsuited to the class. We then try semi-automatically to amend the concept explications used to explain the meanings to human users and rearrange them in suitable classes. In the experiment, we try to revise those concepts that are the lower-concepts of the concept “human ” in the concept hierarchy and that are directly arranged under concepts with concept explications such as “person as defined by – ” and “person viewed from –. ” We analyze the result and evaluate our approach. 1

Ontology-based knowledge management for technology intensive industries

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Automatic Extraction and Assessment of Entities from the Web

The search for information about entities, such as people or movies, plays an increasingly important role on the Web. This information is still scattered across many Web pages, making it more time consuming for a user to find all relevant information about an entity. This thesis describes techniques to extract entities and information about these entities from the Web, such as facts, opinions, questions and answers, interactive multimedia objects, and events. The findings of this thesis are that it is possible to create a large knowledge base automatically using a manually-crafted ontology. The precision of the extracted information was found to be between 75–90 % (facts and entities respectively) after using assessment algorithms. The algorithms from this thesis can be used to create such a knowledge base, which can be used in various research fields, such as question answering, named entity recognition, and information retrieval

Space and Earth Sciences, Computer Systems, and Scientific Data Analysis Support, Volume 1

This Final Progress Report covers the specific technical activities of Hughes STX Corporation for the last contract triannual period of 1 June through 30 Sep. 1993, in support of assigned task activities at Goddard Space Flight Center (GSFC). It also provides a brief summary of work throughout the contract period of performance on each active task. Technical activity is presented in Volume 1, while financial and level-of-effort data is presented in Volume 2. Technical support was provided to all Division and Laboratories of Goddard's Space Sciences and Earth Sciences Directorates. Types of support include: scientific programming, systems programming, computer management, mission planning, scientific investigation, data analysis, data processing, data base creation and maintenance, instrumentation development, and management services. Mission and instruments supported include: ROSAT, Astro-D, BBXRT, XTE, AXAF, GRO, COBE, WIND, UIT, SMM, STIS, HEIDI, DE, URAP, CRRES, Voyagers, ISEE, San Marco, LAGEOS, TOPEX/Poseidon, Pioneer-Venus, Galileo, Cassini, Nimbus-7/TOMS, Meteor-3/TOMS, FIFE, BOREAS, TRMM, AVHRR, and Landsat. Accomplishments include: development of computing programs for mission science and data analysis, supercomputer applications support, computer network support, computational upgrades for data archival and analysis centers, end-to-end management for mission data flow, scientific modeling and results in the fields of space and Earth physics, planning and design of GSFC VO DAAC and VO IMS, fabrication, assembly, and testing of mission instrumentation, and design of mission operations center

24th International Conference on Information Modelling and Knowledge Bases

In the last three decades information modelling and knowledge bases have become essentially important subjects not only in academic communities related to information systems and computer science but also in the business area where information technology is applied. The series of European – Japanese Conference on Information Modelling and Knowledge Bases (EJC) originally started as a co-operation initiative between Japan and Finland in 1982. The practical operations were then organised by professor Ohsuga in Japan and professors Hannu Kangassalo and Hannu Jaakkola in Finland (Nordic countries). Geographical scope has expanded to cover Europe and also other countries. Workshop characteristic - discussion, enough time for presentations and limited number of participants (50) / papers (30) - is typical for the conference. Suggested topics include, but are not limited to: 1. Conceptual modelling: Modelling and specification languages; Domain-specific conceptual modelling; Concepts, concept theories and ontologies; Conceptual modelling of large and heterogeneous systems; Conceptual modelling of spatial, temporal and biological data; Methods for developing, validating and communicating conceptual models. 2. Knowledge and information modelling and discovery: Knowledge discovery, knowledge representation and knowledge management; Advanced data mining and analysis methods; Conceptions of knowledge and information; Modelling information requirements; Intelligent information systems; Information recognition and information modelling. 3. Linguistic modelling: Models of HCI; Information delivery to users; Intelligent informal querying; Linguistic foundation of information and knowledge; Fuzzy linguistic models; Philosophical and linguistic foundations of conceptual models. 4. Cross-cultural communication and social computing: Cross-cultural support systems; Integration, evolution and migration of systems; Collaborative societies; Multicultural web-based software systems; Intercultural collaboration and support systems; Social computing, behavioral modeling and prediction. 5. Environmental modelling and engineering: Environmental information systems (architecture); Spatial, temporal and observational information systems; Large-scale environmental systems; Collaborative knowledge base systems; Agent concepts and conceptualisation; Hazard prediction, prevention and steering systems. 6. Multimedia data modelling and systems: Modelling multimedia information and knowledge; Contentbased multimedia data management; Content-based multimedia retrieval; Privacy and context enhancing technologies; Semantics and pragmatics of multimedia data; Metadata for multimedia information systems. Overall we received 56 submissions. After careful evaluation, 16 papers have been selected as long paper, 17 papers as short papers, 5 papers as position papers, and 3 papers for presentation of perspective challenges. We thank all colleagues for their support of this issue of the EJC conference, especially the program committee, the organising committee, and the programme coordination team. The long and the short papers presented in the conference are revised after the conference and published in the Series of “Frontiers in Artificial Intelligence” by IOS Press (Amsterdam). The books “Information Modelling and Knowledge Bases” are edited by the Editing Committee of the conference. We believe that the conference will be productive and fruitful in the advance of research and application of information modelling and knowledge bases. Bernhard Thalheim Hannu Jaakkola Yasushi Kiyok

Crossing Experiences in Digital Epigraphy: From Practice to Discipline

Although a relevant number of projects digitizing inscriptions are under development or have been recently accomplished, Digital Epigraphy is not yet considered to be a proper discipline and there are still no regular occasions to meet and discuss. By collecting contributions on nineteen projects – very diversified for geographic and chronological context, for script and language, and for typology of digital output – this volume intends to point out the methodological issues which are specific to the application of information technologies to epigraphy. The first part of the volume is focused on data modelling and encoding, which are conditioned by the specific features of different scripts and languages, and deeply influence the possibility to perform searches on texts and the approach to the lexicographic study of such under-resourced languages. The second part of the volume is dedicated to the initiatives aimed at fostering aggregation, dissemination and the reuse of epigraphic materials, and to discuss issues of interoperability. The common theme of the volume is the relationship between the compliance with the theoretic tools and the methodologies developed by each different tradition of studies, and, on the other side, the necessity of adopting a common framework in order to produce commensurable and shareable results. The final question is whether the computational approach is changing the way epigraphy is studied, to the extent of renovating the discipline on the basis of new, unexplored questions

Optimizing Proactive Measures for Security Operations

Digital security threats may impact governments, businesses, and consumers through intellectual property theft, loss of physical assets, economic damages, and loss of confidence. Significant effort has been placed on technology solutions that can mitigate threat exposure. Additionally, hundreds of years of literature have focused on non-digital, human-centric strategies that proactively allow organizations to assess threats and implement mitigation plans. For both human and technology-centric solutions, little to no prior research exists on the efficacy of how humans employ digital security defenses. Security professionals are armed with commonly adopted "best practices" but are generally unaware of the particular artifacts and conditions (e.g., organizational culture, procurement processes, employee training/education) that may or may not make a particular environment well-suited for employing the best practices. In this thesis, I study proactive measures for security operations and related human factors to identify generalizable optimizations that can be applied for measurable increases in security. Through interview and survey methods, I investigate the human and organizational factors that shape the adoption and employment of defensive strategies. Case studies with partnered organizations and comprehensive evaluations of security programs reveal security gaps that many professionals were previously unaware of --- as well as opportunities for changes in security behaviors to mitigate future risk. These studies highlight that, in exemplar environments, the adoption of proactive security assessments and training programs lead to measurable improvements in organizations' security posture