Neuro-symbolic Reasoning System for Modeling Complex Behaviours.

A neuro-symbolic reasoning strategy for modelling a complex system is presented in which the aim is to forecast, in real time, the physical parameter values of a dynamic environment: the ocean. In situations in which the rules that determine a system are unknown the prediction of the parameter values that determine the characteristic behaviour of the system can be a problematic task. In such a situation it has been found that a case-based reasoning system, in combination with an artifical neural network, can provide a more effective means of performing such predictions than other connectionist or symbolic techniques. The case-based reasoning system incorporates a radial basis function artificial neural network for the case adaptation. The results obtained from experiments, in which the system operated in real time in the oceanographic environment, are presented

Hybrid Instance-bsed system for predicting ocean temperatures

An instance-based problem solving model is presented in which the aim is to forecast, in real time, the physical parameter values of a complex and dynamic environment: the ocean. The situations in which the rules that determine a system are unknown, the prediction of the parameter values that determine the characteristic behaviour of the system can be a problematic task. In such a situation it has been found that an instance-based reasoning system can provide a more effective means of performing such predictions than other connectionist or symbolic techniques. The instance-based reasoning system incorporates a radial basis function artificial neural network for the instance adaptation. The results obtained from experiments, in which the system operated in real time in the oceanographic environment, are presented

A CBP agent for monitoring the carbon dioxide exchange rate from satellite images

This work presents a multiagent system for evaluating automatically the interaction that exists between the atmosphere and the ocean surface. Monitoring and evaluating within the Ocean CO2 exchange process is a function requiring working with a great amount of data: satellite images and in-situ vessel’s data. The system presented in this work focuses on Ambient Intelligence (AmI) technologies since the vision of AmI assumes seamless, unobtrusive, and often invisible but also controllable interactions between humans and technology. The work presents the construction of an open multiagent architecture which, based on the use of deliberative agents incorporating case-based planning (CBP) systems, offers a distributed model for such an interaction. This work also presents an analysis and design methodology that facilitates the implementation of CBR agent based distributed artificial intelligent systems. Moreover, the architecture takes into account the fact that the working environment is dynamic and therefore it requires autonomous models that evolve over time. In order to resolve this problem an intelligent environment has been developed, based on the use of CBP-CBR agents, which are capable of handling several goals, constructing plans from the data obtained through satellite images and research vessels, acquiring knowledge and of adapting to environmental changes, are incorporated. The artificial intelligence system has been successfully tested in the North Atlantic Ocean, and the results obtained will be presented within this work

IBR retrieval method based on topology preserving mappings

Case-based reasoning systems, in general, and instance-based reasoning systems, in particular, are used more and more in industrial applications nowadays. During the last few years, researchers have been working in the development of techniques to automate the reasoning stages identified in this methodology. This paper presents a method for automating the retrieval stage and indexation of instance-based reasoning systems. This method is based on a modification of a new type of topology preserving map that can be used for scale invariant classifica- tion. The scale invariant map is an implementation of the negative feedback network to form a topology-preserving mapping. Maximum/minimum likelihood learning is applied in this paper to the scale invariant map and its possibilities are explored. This method automates the organization of cases and the retrieval stage of case-based reasoning systems. The proposed methodology groups instances with similar struc- ture, identifying clusters automatically in a data set in an unsupervised mode. The method has been successfully used to completely automate the reasoning process of an oceanographic forecasting system and to improve its performance

Evaluating the air-sea interactions and fluxes using an instance-based reasoning system.

The interaction of the atmosphere and the ocean has a profound effect on climate, while the uptake by the oceans of a major fraction of atmospheric CO2 has a moderating influence. By improving accuracy in the quantification of the ocean's CO2 budget, a more precise estimation can be made of the terrestrial fraction of global CO2 budget and its subsequent effect on climate change. An instance-based reasoning system, which incorporates a novel neural-based clustering and retrieval method has been developed for estimating the CO2 budget. This paper reviews the problem of measuring the ocean's CO2 budget, presents the model developed to resolve it and presents the obtained results

The Vehicle, 1969, Vol. 11 no. 2

Vol. 11, No. 2 Table of Contents Short Story: The TripCharles Whitepage 4 PhotoDale Huberpage 5 A NightRoger Zulaufpage 6 Sixteen-year-old Students...NBpage 6 LostJim Biropage 6 The AmateurRoger Zulaufpage 7 ManRoger Zulaufpage 7 My CamelotRonald Garnerpage 7 The Rose and the BriarKenneth L. Folkertspage 9 Who Am I?Frank McKennedypage 10 PhotoDale Huberpage 11 Mr. Samuel ClemensLarry A. Millerpage 11 Lock OutAra Childspage 12 Excuse MeRoger Zulaufpage 12 On Shadows from a Candle \u2767Michael G. McKeepage 12 beginning of an endCaryl Dagropage 12 DrawingMADpage 13 We Ain\u27t Un HurJames Birchlerpage 13 Genesis II, 18 \u2767Michael G. McKeepage 13 Short Story: A Patent Leather PaleEleanor Aikenpage 14 hungry childRoger Zulaufpage 15 DrawingRoger Zulaufpage 15 PhotoRoger Digglepage 16 Do You Like The Rain?Linda Boltmanpage 17 Seasons ChangePerry J. Carterpage 17 PhotoDale Huberpage 19 Whistling TreesPam McKinneypage 19 PostscriptThomas W. Reapage 20 PhotoDale Huberpage 20https://thekeep.eiu.edu/vehicle/1020/thumbnail.jp

The Vehicle, 1969, Vol. 11 no. 2

Vol. 11, No. 2 Table of Contents Short Story: The TripCharles Whitepage 4 PhotoDale Huberpage 5 A NightRoger Zulaufpage 6 Sixteen-year-old Students...NBpage 6 LostJim Biropage 6 The AmateurRoger Zulaufpage 7 ManRoger Zulaufpage 7 My CamelotRonald Garnerpage 7 The Rose and the BriarKenneth L. Folkertspage 9 Who Am I?Frank McKennedypage 10 PhotoDale Huberpage 11 Mr. Samuel ClemensLarry A. Millerpage 11 Lock OutAra Childspage 12 Excuse MeRoger Zulaufpage 12 On Shadows from a Candle \u2767Michael G. McKeepage 12 beginning of an endCaryl Dagropage 12 DrawingMADpage 13 We Ain\u27t Un HurJames Birchlerpage 13 Genesis II, 18 \u2767Michael G. McKeepage 13 Short Story: A Patent Leather PaleEleanor Aikenpage 14 hungry childRoger Zulaufpage 15 DrawingRoger Zulaufpage 15 PhotoRoger Digglepage 16 Do You Like The Rain?Linda Boltmanpage 17 Seasons ChangePerry J. Carterpage 17 PhotoDale Huberpage 19 Whistling TreesPam McKinneypage 19 PostscriptThomas W. Reapage 20 PhotoDale Huberpage 20https://thekeep.eiu.edu/vehicle/1020/thumbnail.jp

Second-look PET-CT following an initial incomplete PET-CT response to (chemo)radiotherapy for head and neck squamous cell carcinoma

OBJECTIVES: The limited positive predictive value of an incomplete response on PET-CT following (chemo)radiotherapy for head and neck squamous cell carcinoma (HNSCC) means that the optimal management strategy remains uncertain. The aim of the study is to assess the utility of a 'second-look' interval PET-CT. METHODS: Patients with HNSCC who were treated with (chemo)radiotherapy between 2008 and 2017 and underwent (i) baseline and (ii) response assessment PET-CT and (iii) second-look PET-CT following incomplete (positive or equivocal scan) response were included. Endpoints were conversion rate to complete response (CR) and test characteristics of the second-look PET-CT. RESULTS: Five hundred sixty-two patients with HNSCC underwent response assessment PET-CT at a median of 17 weeks post-radiotherapy. Following an incomplete response on PET-CT, 40 patients underwent a second-look PET-CT at a median of 13 weeks (range 6-25) from the first response PET-CT. Thirty-four out of 40 (85%) patients had oropharyngeal carcinoma. Twenty-four out of 40 (60%) second-look PET-CT scans converted to a complete locoregional response. The primary tumour conversion rate was 15/27 (56%) and the lymph node conversion rate was 14/19 (74%). The sensitivity, specificity, positive predictive value and negative predictive value (NPV) of the second-look PET-CT were 75%, 75%, 25% and 96% for the primary tumour and 100%, 92%, 40% and 100% for lymph nodes. There were no cases of progression following conversion to CR in the primary site or lymph nodes. CONCLUSIONS: The majority of patients who undergo a second-look PET-CT convert to a CR. The NPV of a second-look PET-CT is high, suggesting the potential to avoid surgical intervention. KEY POINTS: • PET-CT is a useful tool for response assessment following (chemo)radiotherapy for head and neck squamous cell carcinoma. • An incomplete response on PET-CT has a limited positive predictive value and optimal management is uncertain. • These data show that with a 'second-look' interval PET-CT, the majority of patients convert to a complete metabolic response. When there is doubt about clinical and radiological response, a 'second-look' PET-CT can be used to spare patients unnecessary surgical intervention