Talk to your semantic Web

Road traffic injuries are a major public health concern, these injuries place a heavy financial burden on global and national economies and the social cost of human suffering worldwide due to road crashes and injuries is incalculable. In response to this increasing problem, a number of governmental initiatives and working groups have been announced and many countries have published targets for reductions in road fatalities and injuries. The issue of driver distraction has received increasing attention from the media, public, government, industry and safety organisations. Initially much of the concern focussed on the use of mobile phones. This paper gives a brief description of the different types of driver distraction and how they relate to the driving task, standards and methods for measuring driver distraction are also discussed. The main focus of this paper is to review possible future automotive human machine interface (HMI) technologies and design techniques that may offer road safety benefits by reducing driver distraction when operating in-vehicle secondary controls.

This paper involves the review of papers related to an efficient ambulance management system in this project report we will be going through research papers related to similar topics and find information to improve the process of making an ambulance intelligent. India’s population is increasing as each day is passing. The increase in population puts a lot of strain and management of resources from medical, government services and many more. The strain on the resources results in citizens not getting proper help in the time of need. The main example of this process is ambulance management system which is the first line of help process in time of need. If a patient or a victim does not get an ambulance in time then the patient’s life is surely at risk. So there needs to be proper mechanism to handle this important resource and help patients in time. Latest technologies such as cloud computing, IoT, AI, ML and mobile computing can be used to improve the ambulance management and emergency help services. . Ambulance service is one of the crucial services that gets delayed. Sometimes on-sight doctors are not available, so the patient does not get medical attention immediately. In health monitoring system, the patient's vital health parameters such as ECG, Heart Rate and Body Temperature are monitored. These parameters are sent the hospital server using IoT and cloud technology. In the current era of technology, Artificial Intelligence (AI) is playing a vital role in the health care sector especially cardiac disease detection which is a major cause of sudden death. The work given here is a mini-project that is taken up as a part of the curriculum completed by electronics and communication engineering students in the second year of the electronics & communication engineering department at Dayananda Sagar College of Engineering in Bangalore.

The NCR Human Interface Technology Center (HITC) exists to meet its customers' business needs through the application of new human-interface technologies. The HITC designs and develops these user-interface solutions through a user-centered design (UCD) process, in which user needs and expectations guide all design and development decisions. The HITC consists of about 90 engineers and scientists with expertise in such areas as cognitive engineering, graphic design, image understanding, artificial intelligence, intelligent tutoring, database mining, and new I/O technologies. Established in 1988, the HITC is funded by work performed for its customers.

Current air traffic control and air traffic management systems are already working near their capacity limit. To meet future requirements resulting from an increase in air traffic worldwide, the development of new air traffic management concepts and technologies is needed. Validation and evaluation is a major part during the development process of new systems in order to ensure their suitability for real operation conditions. Simulation is a commonly used approach for testing and evaluating new technologies. This paper presents a modular aviation simulation environment at the Institute of Flight Guidance of the Technische Universitaet Braunschweig. The environment comprises two aircraft cockpit simulators, an air traffic controller working position and an airport traffic simulator. It is primarily used for the development of future augmentation systems including new human machine interface technologies. A software development framework is introduced that simplifies the communication between individual simulation modules as well as the integration of applications. Moreover, the paper presents two software projects that were developed within the scope of research activities and integrated into the simulation environment using the software framework. The first project deals with a concept of the visual presentation of wake vortex hazard zones in flight to improve the flight crew's situational awareness. The second one describes an onboard airport navigation application supporting the pilots during ground movement operations on aerodrome surfaces.

Because the ultimate purpose of the Semantic Web is to help users locate, organize, and process information, we strongly believe that it should be grounded in the information access method humans are most comfortable with—natural language. However, the Resource Description Framework (RDF), the foundation of the Semantic Web, was designed to be easily processed by computers, not humans. To render RDF friendlier to humans, we propose to augment it with natural language annotations, or metadata written in everyday language. We argue that natural language annotations are not only intuitive and effective, but can also accelerate the pace with which the Semantic Web is being adopted. We demonstrate the use of natural language annotations from within Haystack, an end user Semantic Web platform that also serves as a testbed for our ideas. In addition to a prototype SemanticWeb question answering system, we describe other opportunities for marrying natural language and Semantic Web technology.

EUROLAN, which has been held biennially since 1993, is one of the most significant European summer schools in the area of natural language processing. Each of the EUROLAN sessions has focused on an area of timely interest to researchers in the field; this year's EUROLAN involved students in tutorials and hands-on sessions concerned with semantic web technologies as applied to language processing, ontology creation and use, and consideration of the semantic web's potential and limitations.

The Web contains a lot of information but computers can't do very much with it. We have access to and a need for a lot of information (thanks to pervasive information devices such as mobile phones, PDAs, smart devices, TV, radio...) but we don't have time to find and make associations between information every time we want to. Given the need for quick, intuitive access to information, multimedia presentation is an effective form of communication - different media act as a better means to communicate dependant on the context, and synchronization (organisation of media in space and in time) can express non- verbally relationships between the content (e.g. linear presentation to represent a timeline of events). Appropriately delivering content in the form of synchronized multimedia is a complex task which needs to meet the requirements of the user, device, and actual context. This proves to be too complex to be fulfilled by manually authoring for all possibilities. This has lead to efforts in developing systems for (semi-)automatic multimedia generation. Knowledge representation techniques developed in earlier AI work are being applied to the World Wide Web. Through standards such as RDF and OWL, the so-called "Semantic Web" offers the potential of a large scale distributed knowledge repository built upon the existing Web infrastructure. This makes powerful amounts of knowledge available to Web-based applications as the basis for a new paradigm of Web-oriented services which are intelligent, dynamic, flexible and user-centred. Such services could find the information we need and present it to us in an effective manner. The current situation of Web content discovery and delivery displays significant disorder and inflexibility: natural language is problematically ambiguous and Web content is only adaptive to a limited extent. Using the Semantic Web, intelligent Web clients will be able to deliver the correct information every time by unambiguously understanding the meaning of queries and reasoning on them (through the knowledge available to them on the Web) to come to an answer. Likewise, Web resources will be described with metadata that supports their selection, adaptation and presentation to the needs of the client. Such a paradigm shift in Web-based systems (from content to knowledge-centred) requires a similar paradigm shift in system models, architectures, implementations and operations. This is equally the case for multimedia presentation systems. We propose a framework for a new type of multimedia presentation system in which the multimedia generation process is tightly integrated with the distributed knowledge of the Semantic Web. Unlike previous work in which knowledge is narrowly defined and used by the system, this approach is built with the scale and dynamics of the Web in mind. We name this framework SWeMPs - a Semantic Web-enabled Multimedia Presentation System. The key results of our research are the conceptual model for a multimedia presentation system and the generic rule base which interacts with that model (through querying, reasoning and deriving new knowledge) to realise individual multimedia generation tasks. These form the basis for an implementation of a multimedia presentation system which is fundamentally different from existing multimedia presentation systems in that it operates at the logical or conceptual level rather than the data or syntactic level. This reflects the reality that what users seek is information (knowledge about concepts) and effective communication of that information (respecting the relationships between concepts). It leverages the potential of the Semantic Web as a distributed, large scale, accessible repository of knowledge about the world of the user just as systems today use the Web as a repository of content. The implementation of this proposal serves as a 'proof of concept' and as a basis for the evaluation of the new approach through use cases.

<div><p><em> Machine Translation has been an area of linguistic research for almost more than two decades now. But it still remains a very challenging task for devising an automated system which will deliver accurate translations of the natural languages. However, great strides have been made in this field with more success owing to the development of technologies of the web and off late there is a renewed interest in this area of research. </em></p><p><em> Technological advancements in the preceding two decades have influenced Machine Translation in a considerable way. Several MT approaches including Statistical Machine Translation greatly benefitted from these advancements, basically making use of the availability of extensive corpora. Web technology web3.0 uses the semantic web technology which represents any object or resource in the web both syntactically and semantically. This type of representation is very much useful for the computing systems to search any content on the internet similar to lexical search and improve the internet based translations making it more effective and efficient.</em></p><p><em> In this paper we propose a technique to improve existing statistical Machine Translation methods by making use of semantic web technology. Our focus will be on Tamil and Tamil to English MT. The proposed method could successfully integrate a semantic web technique in the process of WSD which forms part of the MT system. The integration is accomplished by using the capabilities of RDFS and OWL into the WSD component of the MT model. The contribution of this work lies in showing that integrating a Semantic web technique in the WSD system significantly improves the performance of a statistical MT system for a translation from Tamil to English.</em></p></div><em> In this paper we assume the availability of large corpora in Tamil language and specific domain based ontologies with Tamil semantic web technology using web3.0. We are positive on the expansion and development of Tamil semantic web and subsequently infer that Tamil to English MT will greatly improve the disambiguation concept apart from other related benefits. This method could enable the enhancement of translation quality by improving on word sense disambiguation process while text is translated from Tamil to English language. This method can also be extended to other languages such as Hindi and Indian Languages.</em>

PowerAqua is a Question Answering system, which takes as input a natural language query and is able to return answers drawn from relevant semantic resources found anywhere on the Semantic Web. In this paper we provide two novel contributions: First, we detail a new component of the system, the Triple Similarity Service, which is able to match queries effectively to triples found in different ontologies on the Semantic Web. Second, we provide a first evaluation of the system, which in addition to providing data about PowerAqua's competence, also gives us important insights into the issues related to using the Semantic Web as the target answer set in Question Answering. In particular, we show that, despite the problems related to the noisy and incomplete conceptualizations, which can be found on the Semantic Web, good results can already be obtained.

Ontological indeterminacy (OI) involves incompatible conceptual systems being applicable to a domain with equal empirical adequacy; a phenomenon familiar in philosophy, but also present in the sciences and everyday life. This article presents arguments and a detailed use-case showing how OI causes problems for what seems to be a widespread, if implicit, understanding of how semantic Web (SW) terms refer or have meaning, namely: the referent/meaning of a SW term is established through precise definitions given in a formal ontology. We show that this account is incompatible with the key requirement that SW terms/statements be similar in meaning to corresponding natural language terms/statements. We present a new account, based on a “meaning as use” philosophy of language, that avoids these problems by formalizing the distinction between the intention to use a term in a customary manner and the decision to adopt a formal theory that explains or explicates that usage.

The main obstacle in the way of Semantic Web becoming a “democratic tool” is complexity of its standards. Therefore, a simple language, Notation3, is alternatively used in many communities. But Notation3 does not comply with “compositionality principle”, a characteristics of natural languages. Metalingua, described in this paper, is a counterpart of Notation3, which complies with this principle, can mediate the communication between humans speaking natural languages and Semantic Web, and be used for formalization of natural languages, including languages considered “difficult”, like Chinese. Metalingua is currently used in the projects of EstComputer, Inc. (www.estcomputer.com) for education and natural languages informatics.

For many software systems (e.g., computer aided design and computer aided software engineering tools), high-resolution graphical windowing interfaces are the appropriate user interface technology. However, for systems like a library database, inexpensive “dumb” terminals that accept natural language (NL) commands and that respond in natural language provide a much more usable interaction for those who care most about getting their data management tasks done quickly. Clearly, natural language processing systems augmented by reliable speech recognition systems will, in the near future, provide the most natural possible man-machine interface for low-bandwidth interactions.

While the Semantic Web is rapidly filling up, appropriate tools for searching it are still at infancy. In this paper we describe an approach that allows humans to access information contained in the Semantic Web according to its semantics and thus to leverage the specific characteristic of this Web. To avoid the ambiguity of natural language queries, users only select already defined attributes organized in facets to build their search queries. The facets are represented as nodes in a graph visualization and can be interactively added and removed by the users in order to produce individual search interfaces. This provides the possibility to generate interfaces in arbitrary complexities and access arbitrary domains. Even multiple and distantly connected facets can be integrated in the graph facilitating the access of information from different user-defined perspectives. Challenges include massive amounts of data, massive semantic relations within the data, highly complex search queries and users' unfamiliarity with the Semantic Web.

Summary form only given. In order to intelligently process vast information on the Web, we need to make computers understand the meaning of the Web contents and manipulate them taking account of their semantics. Since text is the major medium conveying information, it is thus natural and reasonable to set it as the immediate target that the computer understands the meaning, while there are other types of media such as picture, movie, etc. Toward this direction, the activity of the semantic Web is going on. It aims to establish a standardized machine-readable description format of meta-data. However, the meta-data are only fragments of the Web contents. Unlike the semantic Web, we aim to describe the concept meaning expressed in the whole natural language texts with a common format that the computer can understand. We have designed concept description language (CDL) as a vehicle for this end, and started its standardization activity in W3C. There are several levels of the meaning of the texts, ranging from shallow level to deep one. While it is still difficult to make a consensus on how to describe the deep meaning, we think that a certain consensus can be attained on a way of describing the shallow meaning of the texts, based on the research results accumulated in the field of natural language processing such as machine translation over the last several decades. In CDL, besides lexicons, 45 relations are predefined as being necessary and sufficient for denoting every semantic relation between entities (lexicons in a simple case). These CDL relations can be used universally, while the ontologies in the semantic Web are domain dependent and thus cause some problematic situations. Current issues of CDL are, among others, an easy semi-automatic way of converting natural language texts into the CDL description, and an effective mechanism of executing semantic retrieval on the CDL database. We believe that CDL contributes to build a framework of next-generation Web which provides the foundation for a variety of semantic computing. Also, CDL may contribute to overcome the language barrier among nations.

With the wide spread of Open Linked Data and Semantic Web technologies, a larger amount of data has been published on the Web in the RDF and OWL formats. This data can be queried using SPARQL, the Semantic Web Query Language. SPARQL cannot be understood by ordinary users and is not directly accessible to humans, and thus they will not be able to check whether the retrieved answers truly correspond to the intended information need. Driven by this challenge, natural language generation from SPARQL data has recently attracted a considerable attention. However, most existing solutions to verbalize SPARQL in natural language focused on English and Latin-based languages. Little effort has been made on the Arabic language which has different characteristics and morphology. This work aims to particularly help Arab users to perceive SPARQL queries on the Semantic Web by translating SPARQL to Arabic. It proposes an approach that gets a SPARQL query as an input and generates a query expressed in Arabic as an output. The translation process combines both morpho-syntactic analysis and language dependencies to generate a legible and understandable Arabic query. The approach was preliminary assessed with a sample query set, and results indicated that 75% of the queries were correctly translated into Arabic.