Generic optimization environment and knowledge-based guided evolutionary algorithms for automated transmission calibration – Method to generate a knowledge base through impact analysis of parameters a...

2020 ◽  
pp. I-355-I-384
Author(s):  
T. Korb ◽  
M. Nussbaumer ◽  
S. Rinderknecht
2021 ◽  
Author(s):  
Marciane Mueller ◽  
Rejane Frozza ◽  
Liane Mählmann Kipper ◽  
Ana Carolina Kessler

BACKGROUND This article presents the modeling and development of a Knowledge Based System, supported by the use of a virtual conversational agent called Dóris. Using natural language processing resources, Dóris collects the clinical data of patients in care in the context of urgency and hospital emergency. OBJECTIVE The main objective is to validate the use of virtual conversational agents to properly and accurately collect the data necessary to perform the evaluation flowcharts used to classify the degree of urgency of patients and determine the priority for medical care. METHODS The agent's knowledge base was modeled using the rules provided for in the evaluation flowcharts comprised by the Manchester Triage System. It also allows the establishment of a simple, objective and complete communication, through dialogues to assess signs and symptoms that obey the criteria established by a standardized, validated and internationally recognized system. RESULTS Thus, in addition to verifying the applicability of Artificial Intelligence techniques in a complex domain of health care, a tool is presented that helps not only in the perspective of improving organizational processes, but also in improving human relationships, bringing professionals and patients closer. The system's knowledge base was modeled on the IBM Watson platform. CONCLUSIONS The results obtained from simulations carried out by the human specialist allowed us to verify that a knowledge-based system supported by a virtual conversational agent is feasible for the domain of risk classification and priority determination of medical care for patients in the context of emergency care and hospital emergency.


Author(s):  
Sarah Bouraga ◽  
Ivan Jureta ◽  
Stéphane Faulkner ◽  
Caroline Herssens

Knowledge-Base Recommendation (or Recommender) Systems (KBRS) provide the user with advice about a decision to make or an action to take. KBRS rely on knowledge provided by human experts, encoded in the system and applied to input data, in order to generate recommendations. This survey overviews the main ideas characterizing a KBRS. Using a classification framework, the survey overviews KBRS components, user problems for which recommendations are given, knowledge content of the system, and the degree of automation in producing recommendations.


1990 ◽  
Vol 80 (6B) ◽  
pp. 1833-1851 ◽  
Author(s):  
Thomas C. Bache ◽  
Steven R. Bratt ◽  
James Wang ◽  
Robert M. Fung ◽  
Cris Kobryn ◽  
...  

Abstract The Intelligent Monitoring System (IMS) is a computer system for processing data from seismic arrays and simpler stations to detect, locate, and identify seismic events. The first operational version processes data from two high-frequency arrays (NORESS and ARCESS) in Norway. The IMS computers and functions are distributed between the NORSAR Data Analysis Center (NDAC) near Oslo and the Center for Seismic Studies (Center) in Arlington, Virginia. The IMS modules at NDAC automatically retrieve data from a disk buffer, detect signals, compute signal attributes (amplitude, slowness, azimuth, polarization, etc.), and store them in a commercial relational database management system (DBMS). IMS makes scheduled (e.g., hourly) transfers of the data to a separate DBMS at the Center. Arrival of new data automatically initiates a “knowledge-based system (KBS)” that interprets these data to locate and identify (earthquake, mine blast, etc.) seismic events. This KBS uses general and area-specific seismological knowledge represented in rules and procedures. For each event, unprocessed data segments (e.g., 7 min for regional events) are retrieved from NDAC for subsequent display and analyst review. The interactive analysis modules include integrated waveform and map display/manipulation tools for efficient analyst validation or correction of the solutions produced by the automated system. Another KBS compares the analyst and automatic solutions to mark overruled elements of the knowledge base. Performance analysis statistics guide subsequent changes to the knowledge base so it improves with experience. The IMS is implemented on networked Sun workstations, with a 56 kbps satellite link bridging the NDAC and Center computer networks. The software architecture is modular and distributed, with processes communicating by messages and sharing data via the DBMS. The IMS processing requirements are easily met with major processes (i.e., signal processing, KBS, and DBMS) on separate Sun 4/2xx workstations. This architecture facilitates expansion in functionality and number of stations. The first version was operated continuously for 8 weeks in late-1989. The Center functions were then transferred to NDAC for subsequent operation. Later versions will be distributed among NDAC, Scripps/IGPP (San Diego), and the Center to process data from many stations and arrays. The IMS design is ambitious in its integration of many new computer technologies, but the operational performance of the first version demonstrates its validity. Thus, IMS provides a new generation of automated seismic event monitoring capability.


Author(s):  
Samir Rohatgi ◽  
James H. Oliver ◽  
Stuart S. Chen

Abstract This paper describes the development of OPGEN (Opportunity Generator), a computer based system to help identify areas where a knowledge based system (KBS) might be beneficial, and to evaluate whether a suitable system could be developed in that area. The core of the system is a knowledge base used to carry out the identification and evaluation functions. Ancillary functions serve to introduce and demonstrate KBS technology to enhance the overall effectiveness of the system. All aspects of the development, from knowledge acquisition through to testing are presented in this paper.


Author(s):  
Ming Dong ◽  
Jianzhong Cha ◽  
Mingcheng E

Abstract In this paper, we realize knowledge-based discrete event simulation model’s representation, reasoning and implementation by means of object-oriented(OO) frame language. Firstly, a classes library of simulation models is built by using the OO frame language. And then, behaviours of simulation models can be generated by inference engines reasoning about knowledge base. Lastly, activity cycle diagrams can be used to construct simulation network logic models by connecting the components classes of simulation models. This kind of knowledge-based simulation models can effectively solve the modeling problems of complex and ill-structure systems.


Big Data ◽  
2016 ◽  
pp. 711-733 ◽  
Author(s):  
Jafreezal Jaafar ◽  
Kamaluddeen Usman Danyaro ◽  
M. S. Liew

This chapter discusses about the veracity of data. The veracity issue is the challenge of imprecision in big data due to influx of data from diverse sources. To overcome this problem, this chapter proposes a fuzzy knowledge-based framework that will enhance the accessibility of Web data and solve the inconsistency in data model. D2RQ, protégé, and fuzzy Web Ontology Language applications were used for configuration and performance. The chapter also provides the completeness fuzzy knowledge-based algorithm, which was used to determine the robustness and adaptability of the knowledge base. The result shows that the D2RQ is more scalable with respect to performance comparison. Finally, the conclusion and future lines of the research were provided.


2011 ◽  
Vol 1 (3) ◽  
pp. 39-55 ◽  
Author(s):  
Ingi Runar Edvardsson ◽  
Gudmundur Kristjan Oskarsson

This paper reports on empirical work recently conducted on outsourcing among knowledge-based and other service firms in Iceland. The results show that knowledge-based firms outsource on a larger scale and more human resource functions than other service firms. However, they do not have a more strategic vision towards outsourcing, nor do they outsource more low knowledge-based activities than other firms. The study gives support to the resource-based view of the firm, and is in line with former studies of knowledge-based firms. The firms in the survey tend to keep their core competencies and employees in-house, and at the same time they outsource other functions that they consider non-core, such as peripheral and administrative tasks, or IT that requires technical specialization. The more innovative firms rely on outsourcing from best in class suppliers regarding training and counselling. The contribution of this study to the theory of outsourcing is that the non-routine tacit knowledge base related to firms’ core competencies is not limited to knowledge-based firms, but to a large portion of service firms as well.


2010 ◽  
Vol 113-116 ◽  
pp. 1256-1260
Author(s):  
Jun Luo ◽  
Wei Guo Zhang ◽  
Bing Shan Wu

Unsuitable development of wetland area will cause serious environmental problems. Thus, wetland development and environmental protection has become an issue of national emphasis for the environmental management in the world. There is a demand for planning and decision strategies in this complex area. Because of the complexity and the enormous amount of relevant data, the decision makers need effective support for their decisions. The use of a knowledge-based approach is a solution for reducing this complexity. Accordingly, this study adopts knowledge management techniques and information technology to acquire and retain all kind of knowledge needed for the decision making process, and discusses the development of knowledge-based environmental information system promote the sustainable development wetland. The aim of this paper is to develop knowledge base system integrate with the existing information database and improve the knowledge base associated with environmental decision processes to help the sustainable development of wetland.


Robotica ◽  
1991 ◽  
Vol 9 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Dae-Won Kim ◽  
Bum-Hee Lee ◽  
Myoung-Sam Ko

SUMMARYIn this paper, an approach to modelling of a robotic assembly cell is proposed and a method for managing the cell operation is described using a knowledge base. Since the modelling structure is based on the concept of the state variable, the relationships between states are described by the state transition map (STM). The knowledge-bases for state transition and assembly job information are obtained from the STM and the assembly job tree (AJT), respectively. Using the knowledge-base, the System structure is discussed in relation to both managing the cell operation and evaluating the performances. Finally, a simulation algorithm is presented with the simulation results to show the significance of the proposed modelling approach.


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