Dynamic learning of cases from data streams

This paper presents a dynamic adaptive framework for building a case library being able to cope with a data stream in the field of Case-Based Reasoning. The framework provides a three-layer architecture formed by a set of case libraries dynamically built. This Dynamic and Adaptive Case Library (DACL), can process in an incremental way a data stream, and can be used as a classification model or a regression model, depending on the predicted variable. In this paper, the work is focused on classification tasks. Each case library has a first layer formed by the dynamic clusters of cases, a second one formed by the meta-cases or prototypes of the cluster, and a third one formed by an incremental indexing structure. In our approach, some variant of k-d tres have been used, in addition to an exploration technique to get a more efficient retrieval time. This three-layer famework can be constructed in an incremental way. Several meta-case learning approaches are proposed, as well as some case learning strategies. The framework has been tested with several datasets. The experimental results show a very good performance in comparison with a batch learning scheme over the same data.Peer ReviewedPostprint (author's final draft

Environmental data stream mining through a case-based stochastic learning approach

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Environmental data stream mining is an open challenge for Data Science. Common methods used are static because they analyze a static set of data, and provide static data-driven models. Environmental systems are dynamic and generate a continuous data stream. Dynamic methods coping with the temporal nature of data must be provided in Data Science. Our proposal is to model each environmental information unit, timely generated, as a new case/experience in a Case-Based Reasoning (CBR) system. This contribution aims to incrementally build and manage a Dynamic Adaptive Case Library (DACL). In this paper, a stochastic method for the learning of new cases and management of prototypes to create and manage the DACL in an incremental way is introduced. This stochastic method works with two main moments. An evaluation of the method has been carried using a data stream of air quality of the city of Obregon, Sonora. México, with good results. In addition, other datasets have been mined to ensure the generality of the approach.Peer ReviewedPostprint (author's final draft

An approach for an architecture to embodied procedural reasoning

Some research in intelligent manufacturing systems summarizes the importance of developing new methods and techniques that should be more knowledge intensive, applied at the level of embedded devices. To bring a solution for this demand we propose an embedded architecture for micro-controllers based on the hypothesis is it possible to introduce intelligence in microcontrollers by applying some solutions from the area of Multiagent Systems and in particular Belief-Desires-Intentions (BDI) agents to model intelligent computational units that are physically embedded in the world. This approach was first formulated by Deepak Kumar and it is adopted as the basis of our research. This research is focused in the development of a BDI architecture which could provide flexible reasoning capabilities wich can cope with complicated tasks executed by an embodied system. The intelligent part is based in procedural reasoning -Belief, Desires and Intentions- (BDI).Postprint (published version

Bioinformatics: a promising field for case-based reasoning

Case Based Reasoning has been applied in different fields such as medicine, industry, tutoring systems and others, but in the CBR there are many areas to explore. Nowadays, some research works in Bioinformatics are attempting to use CBR like a tool for classifying DNA genes. Specially the microarrays have been applied increasingly to improve medical decision-making, and to the diagnosis of different diseases like cancer. This research work analyzes the Microarrays structure, and the initial concepts to understand how DNA structure is studied in the Bioinformatics' field. In last years the CBR has been related to Bioinformatics and Microarrays. In this report, our interest is to find out how the Microarrays technique could help in the CBR field, and specially in the Case-Based Maintenance policies.Postprint (published version

Case base maintenance: terms and directions

Since last years Case Base Reasoning (CBR) field has been growing, and Case Base Maintenance (CBM) is getting more important. Recent research has focused on case-base maintenance, addressing such issues as maintaining consistency, preserving competence, and controlling case-base grow. A set of dimensions for case-base maintenance proposed by Leake and Wilson, provides a framework for understanding and expanding CBM research. Taking this contribution into account, the aims of our work is to do a framework where the basics concepts of CBM are explained, and even more, as second objective we do a brief resume of some relevant contributions made by the scientific CBR community. Starting where Wilson and Leake research work ends.Postprint (published version

COVID-19 vaccine failure

COVID-19 affects the population unequally with a higher impact on aged and immunosuppressed people. Hence, we assessed the effect of SARS-CoV-2 vaccination in immune compromised patients (older adults and oncohematologic patients), compared with healthy counterparts. While the acquired humoral and cellular memory did not predict subsequent infection 18 months after full immunization, spectral and computational cytometry revealed several subsets within the CD8+ T-cells, B-cells, NK cells, monocytes and CD45RA+ CCR7- Tγδ cells differentially expressed in further infected and non-infected individuals not just following immunization, but also prior to that. Of note, up to 7 subsets were found within the CD45RA+ CCR7- Tγδ population with some of them being expanded and other decreased in subsequently infected individuals. Moreover, some of these subsets also predicted COVID-induced hospitalization in oncohematologic patients. Therefore, we hereby have identified several cellular subsets that, even before vaccination, strongly related to COVID-19 vulnerability as opposed to the acquisition of cellular and/or humoral memory following vaccination with SARS-CoV2 mRNA vaccines.This study has been funded through Programa Estratégico Instituto de Biología y Genética Molecular (IBGM Junta de Castilla y León. Ref. CCVC8485), Junta de Castilla y León (Proyectos COVID 07.04.467B04.74011.0) and the European Commission – NextGenerationEU (Regulation EU 2020/2094), through CSIC's Global Health Platform (PTI Salud Global; SGL21-03-026 and SGL2021-03-038)N

Bioinformatics: a promising field for case-based reasoning

Case Based Reasoning has been applied in different fields such as medicine, industry, tutoring systems and others, but in the CBR there are many areas to explore. Nowadays, some research works in Bioinformatics are attempting to use CBR like a tool for classifying DNA genes. Specially the microarrays have been applied increasingly to improve medical decision-making, and to the diagnosis of different diseases like cancer. This research work analyzes the Microarrays structure, and the initial concepts to understand how DNA structure is studied in the Bioinformatics' field. In last years the CBR has been related to Bioinformatics and Microarrays. In this report, our interest is to find out how the Microarrays technique could help in the CBR field, and specially in the Case-Based Maintenance policies

Dynamic learning of cases from data streams

This paper presents a dynamic adaptive framework for building a case library being able to cope with a data stream in the field of Case-Based Reasoning. The framework provides a three-layer architecture formed by a set of case libraries dynamically built. This Dynamic and Adaptive Case Library (DACL), can process in an incremental way a data stream, and can be used as a classification model or a regression model, depending on the predicted variable. In this paper, the work is focused on classification tasks. Each case library has a first layer formed by the dynamic clusters of cases, a second one formed by the meta-cases or prototypes of the cluster, and a third one formed by an incremental indexing structure. In our approach, some variant of k-d tres have been used, in addition to an exploration technique to get a more efficient retrieval time. This three-layer famework can be constructed in an incremental way. Several meta-case learning approaches are proposed, as well as some case learning strategies. The framework has been tested with several datasets. The experimental results show a very good performance in comparison with a batch learning scheme over the same data.Peer Reviewe

An approach for an architecture to embodied procedural reasoning

Some research in intelligent manufacturing systems summarizes the importance of developing new methods and techniques that should be more knowledge intensive, applied at the level of embedded devices. To bring a solution for this demand we propose an embedded architecture for micro-controllers based on the hypothesis is it possible to introduce intelligence in microcontrollers by applying some solutions from the area of Multiagent Systems and in particular Belief-Desires-Intentions (BDI) agents to model intelligent computational units that are physically embedded in the world. This approach was first formulated by Deepak Kumar and it is adopted as the basis of our research. This research is focused in the development of a BDI architecture which could provide flexible reasoning capabilities wich can cope with complicated tasks executed by an embodied system. The intelligent part is based in procedural reasoning -Belief, Desires and Intentions- (BDI)

Case base maintenance: terms and directions

Since last years Case Base Reasoning (CBR) field has been growing, and Case Base Maintenance (CBM) is getting more important. Recent research has focused on case-base maintenance, addressing such issues as maintaining consistency, preserving competence, and controlling case-base grow. A set of dimensions for case-base maintenance proposed by Leake and Wilson, provides a framework for understanding and expanding CBM research. Taking this contribution into account, the aims of our work is to do a framework where the basics concepts of CBM are explained, and even more, as second objective we do a brief resume of some relevant contributions made by the scientific CBR community. Starting where Wilson and Leake research work ends