A CLIPS/X-window interface

The design and implementation of an interface between the C Language Integrated Production System (CLIPS) expert system development environment and the graphic user interface development tools of the X-Window system are described. The underlying basis of the CLIPS/X-Window is a client-server model in which multiple clients can attach to a single server that interprets, executes, and returns operation results, in response to client action requests. Implemented in an AIX (UNIX) operating system environment, the interface has been successfully applied in the development of graphics interfaces for production rule cooperating agents in a knowledge-based computer aided design (CAD) system. Initial findings suggest that the client-server model is particularly well suited to a distributed parallel processing operational mode in a networked workstation environment

Golden Rice and the Looming GMO Trade Debate: Implication for the Poor

The first generation of genetically modified crop varieties, currently most widespread in the maize and soybean sectors, sought to increase farmer profitability by improving agronomic traits. The next generation of biotech research is focusing also on breeding for attributes desired by consumers. Although not yet commercially available, a new variety of rice, known as ‘Golden Rice’, has been genetically engineered to contain a higher level of vitamin A. Thus in contrast with the current commercial applications of biotech crops, this new rice variety aims directly at benefiting consumers rather than producers. More specifically, it aims at improving the health of poor people in developing countries who rely on rice as their main staple food (or would be if it was cheaper) and whose diet is nutrient-deficient. This paper analyses empirically the potential economic effects of such an innovation in an environment of heated debates about the risks and benefits of these biotech developments. The emergence of genetically modified foods is generating policy reactions that are delaying the development and adoption of what promises to be a high-payoff technology, particularly for the world’s poor. These policy reactions may lead to trade disputes, in which case the way this GMO issue is addressed in the WTO’s dispute settlement body could have profound implications for poor households in developing countries.GMOs, golden rice, rice policy, WTO agreements, consumer preferences

Genetically Modified Rice Adoption: Implications for Welfare and Poverty Alleviation

The first generation of genetically modified (GM) crop varieties sought to increase farmer profitability through cost reductions or higher yields. The next generation of GM food research is focusing also on breeding for attributes of interest to consumers, beginning with ‘golden rice’, which has been genetically engineered to contain a higher level of vitamin A and thereby boost the health of poor people in developing countries. This paper analyses empirically the potential economic effects of adopting both types of innovation in Asia, including its impact on rice producers and other poor households. It does so using the global economy-wide computable general equilibrium model known as GTAP. The results suggest the very considerable farm productivity gains (even if extended beyond GM rice to include those from adopting other GM grains and oilseeds) could be exceeded by the welfare gains resulting from the potential health-enhancing attributes of golden rice, which would boost the productivity of unskilled workers among Asia’s poor.GMOs, golden rice, consumer preferences, nutritional attributes.

Genetically modified rice adoption : implications for welfare and poverty alleviation

The first generation of genetically modified (GM) crop varieties sought to increase producer profitability through cost reductions or higher yields, while the next generation of GM food research is focusing on breeding for attributes of interest to consumers. Golden Rice, for example, has been genetically engineered to contain a higher level of vitamin A and thereby boost the health of poor people in developing countries. This paper analyzes the potential economic effects of adopting both types of innovation in Asia, including its impact on rice producers and consumers. It does so using the global economy-wide computable general equilibrium model known as GTAP. The results suggest the farm productivity gains could be dwarfed by the welfare gains resulting from the potential health-enhancing attributes of golden rice, which would boost the productivity of unskilled workers among Asia's poor.Agricultural Research,Environmental Economics&Policies,Labor Policies,Crops&Crop Management Systems,Economic Theory&Research,Crops&Crop Management Systems,Environmental Economics&Policies,Agricultural Research,Economic Theory&Research,Drylands&Desertification

Using PVM to host CLIPS in distributed environments

It is relatively easy to enhance CLIPS (C Language Integrated Production System) to support multiple expert systems running in a distributed environment with heterogeneous machines. The task is minimized by using the PVM (Parallel Virtual Machine) code from Oak Ridge Labs to provide the distributed utility. PVM is a library of C and FORTRAN subprograms that supports distributive computing on many different UNIX platforms. A PVM deamon is easily installed on each CPU that enters the virtual machine environment. Any user with rsh or rexec access to a machine can use the one PVM deamon to obtain a generous set of distributed facilities. The ready availability of both CLIPS and PVM makes the combination of software particularly attractive for budget conscious experimentation of heterogeneous distributive computing with multiple CLIPS executables. This paper presents a design that is sufficient to provide essential message passing functions in CLIPS and enable the full range of PVM facilities

Semantically-Enhanced Information Extraction

Information Extraction using Natural Language Processing (NLP) produces entities along with some of the relationships that may exist among them. To be semantically useful, however, such discrete extractions must be put into context through some form of intelligent analysis. This paper1,2 offers a two-part architecture that employs the statistical methods of traditional NLP to extract discrete information elements in a relatively domain-agnostic manner, which are then injected into an inference-enabled environment where they can be semantically analyzed. Within this semantic environment, extractions are woven into the contextual fabric of a user-provided, domain-centric ontology where users together with user-provided logic can analyze these extractions within a more contextually complete picture. Our demonstration system infers the possibility of a terrorist plot by extracting key events and relationships from a collection of news articles and intelligence reports

IMMACCS: A Multi-Agent Decision-Support System

This report describes work performed by the Collaborative Agent Design Research Center for the US Marine Corps Warfighting Laboratory (MCWL), on the IMMACCS experimental decision-support system. IMMACCS (Integrated Marine Multi-Agent Command and Control System) incorporates three fundamental concepts that distinguish it from existing (i.e., legacy) command and control applications. First, it is a collaborative system in which computer-based agents assist human operators by monitoring, analyzing, and reasoning about events in near real-time. Second, IMMACCS includes an ontological model of the battlespace that represents the behavioral characteristics and relationships among real world entities such as friendly and enemy assets, infrastructure objects (e.g., buildings, roads, and rivers), and abstract notions. This object model provides the essential common language that binds all IMMACCS components into an integrated and adaptive decision-support system. Third, IMMACCS provides no ready made solutions that may not be applicable to the problems that will occur in the real world. Instead, the agents represent a powerful set of tools that together with the human operators can adjust themselves to the problem situations that cannot be predicted in advance. In this respect, IMMACCS is an adaptive command and control system that supports planning, execution and training functions concurrently. The report describes the nature and functional requirements of military command and control, the architectural features of IMMACCS that are designed to support these operational requirements, the capabilities of the tools (i.e., agents) that IMMACCS offers its users, and the manner in which these tools can be applied. Finally, the performance of IMMACCS during the Urban Warrior Advanced Warfighting Experiment held in California in March, 1999, is discussed from an operational viewpoint

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Big Data: Immediate Opportunities and Longer Term Challenges

The transformation of words, locations, and human interactions into digital data forms the basis of trend detection and information extraction opportunities that can be automated with the increasing availability of relatively inexpensive computer storage and processing technology. Trend detection, which focuses on what, is facilitated by the ability to apply analytics to an entire corpus of data instead of a random sample. Since the corpus essentially includes all data within a population there is no need to apply any of the precautions that are in order to ensure the representativeness of a sample in traditional statistical analysis. Several examples are presented to validate the principle that with increasing scale data quality becomes less important. Information extraction, which focuses on causality or why, is concerned with the automated extraction of meaning out of unstructured and structured data. This requires examination of the entities in the context of an entire document. While some of the relationships among the recognized entities may be preserved during extraction, the overall context of a document may not be preserved. The role of information representation in the form of an ontology, as a mechanism for facilitating the collection, extraction, organization, analysis, and retrieval of the semantic content of a sizeable data corpus is described with reference to past research findings

Perspective Models As a Means For Achieving True Representational Accuracy

Accurate and expressive representation of the subject matter over which a context-oriented, decision-support system operates is fundamental to the effectiveness and longevity of the resulting solution. Often taking the form of an ontology, such extensive representational models, by their very nature, are rich in both relationships and fine-grained objects. It is, however, these two strengths that can significantly increase complexity for its users in addition to adversely affecting system performance. Further, due to the multitude of compartmentalized facets (i.e., populations of distinct, reasoning agents) inherent in such software solutions, it is important to recognize that a single-minded omniscient set of domain descriptions representing a singular view of the world is not necessarily appropriate for every ontology user. In fact, in such highly expressive environments, it is critical to not only accept these distinctions in user perspective, but to, in fact, promote and exploit them. It is by acknowledging and supporting this perspective-based individuality that true representational accuracy and utility is achieved. Traditionally, software-based users comprising decision-support systems have operated over a singular, common representation, albeit a potential subset of the entire target modeling space. However, in the perspective model-enriched environment presented in this paper, ontology users are empowered with the ability to effectively perceive the world in accordance with individualized views. Architecturally, perspective models are integrated with one another via a central ontology. In this sense, perspective models act as satellites deriving certain aspects of their content from a central integration model. Exclusively operating over personalized perspective models, users are not only shielded from the broad-scoped complexities inherent in the more omniscient concerns of the central integration model but are also able to view and interact with the world in terms of their more familiar and expressive native representation. To be effective, the concept of perspective models must be partnered with a supportive model development process. In addition to an explanation of the concept of perspective models, this paper provides a discussion of a development process that supports effective development of both the potentially numerous set of perspective models in addition to the integration model that inter-connects them. The process offered in this paper effectively parcels the development of individual perspective models with the individuals possessing the necessary domain and use-case expertise. In this manner, the development process strives to significantly increase the involvement of the entire set of team members in the modeling activity, both capitalizing on user domain expertise in addition to increasing critical user understanding and acceptance of the representation over which their components are to operate