Case-based Maintenance Model for handling Relevant and Irrelevant Cases in Case-based Reasoning System

Case-based maintenance can be resource intensive and requires significant time and effort to collect and analyse all cases. This can lead to inefficiencies and high costs in the entire case-based reasoning system. Accordingly, the Relative Coverage Condensed Nearest Neighbour had been created to reduce the number of cases in a dataset by selecting a subset of representative cases, whereas maintaining the overall performance of the whole system. Besides, Footprint utility deletion is a type of case deletion algorithm that can remove redundant or irrelevant cases from a storage, though maintaining the system’s competency. Recently, Hybrid approach was given to ensure that the case-base remains up-to-date and relevant, while also reducing its size and complexity. However, the results from using these approaches seem to be improved for the better performance. Therefore, the proposed model is developed, which comprises two main phrases by using case-based reasoning and identifying relevant and irrelevant cases to provide better results. The reduction size of case-base is lower than the traditional studies approximately 1-9% and also gives higher percentage of solving problems about 1-7%, while the average problem-solving time is shorter than them nearly at most 8 times. &nbsp

Case-based maintenance : Structuring and incrementing the Case.

International audienceTo avoid performance degradation and maintain the quality of results obtained by the case-based reasoning (CBR) systems, maintenance becomes necessary, especially for those systems designed to operate over long periods and which must handle large numbers of cases. CBR systems cannot be preserved without scanning the case base. For this reason, the latter must undergo maintenance operations.The techniques of case base’s dimension optimization is the analog of instance reduction size methodology (in the machine learning community). This study links these techniques by presenting case-based maintenance in the framework of instance based reduction, and provides: first an overview of CBM studies, second, a novel method of structuring and updating the case base and finally an application of industrial case is presented.The structuring combines a categorization algorithm with a measure of competence CM based on competence and performance criteria. Since the case base must progress over time through the addition of new cases, an auto-increment algorithm is installed in order to dynamically ensure the structuring and the quality of a case base. The proposed method was evaluated through a case base from an industrial plant. In addition, an experimental study of the competence and the performance was undertaken on reference benchmarks. This study showed that the proposed method gives better results than the best methods currently found in the literature

Case Base Maintenance Approach.

International audienceCase base Maintenance is an active Case Based Reasoning research area. The main stream focuses on the method for reducing the size of the case-base while maintaining case-base competence. This paper gives an overview of these works, and proposes a case deletion strategy based on competence criteria using a novel approach. The proposed method, even if inspired from existing literature, combines an algorithm with a Competence Metric (CM). A series of tests are conducted using two standards data-sets as well as a locally constructed one, on which, three Case Base Maintenance approaches were tested. This experimental study shows how this technique compares favourably to more traditional strategies across two standard data-sets

Competence-Preserving Case-Deletion Strategy for Case-Base Maintenance.

International audienceThe main goal of a Case-Based Reasoning (CBR) system is to provide criteria for evaluating the internal behavior and task efficiency of a particular system for a given initial case base and sequence of a solved problems. The choice of Case Base Maintenance (CBM) strategies is driven by the maintainer's performance goals for the system and by constraints on the system's design and the task environment. This paper gives an overview of CBM works and proposes a case deletion strategy based on a competence criterion using a novel approach. The proposed method combines an algorithm with a Competence Metric (CM). Series of tests are conducted using four standard data-sets as well as a locally constructed one, on which, three case base maintenance approaches will be tested and evaluated by competence and performance criteria. Thereafter competence and performance experimental study shows how this method compares favorably to more traditional methods

Identification of a novel type of spacer element required for imprinting in fission yeast

Asymmetrical segregation of differentiated sister chromatids is thought to be important for cellular differentiation in higher eukaryotes. Similarly, in fission yeast, cellular differentiation involves the asymmetrical segregation of a chromosomal imprint. This imprint has been shown to consist of two ribonucleotides that are incorporated into the DNA during laggingstrand synthesis in response to a replication pause, but the underlying mechanism remains unknown. Here we present key novel discoveries important for unravelling this process. Our data show that cis-acting sequences within the mat1 cassette mediate pausing of replication forks at the proximity of the imprinting site, and the results suggest that this pause dictates specific priming at the position of imprinting in a sequence-independent manner. Also, we identify a novel type of cis-acting spacer region important for the imprinting process that affects where subsequent primers are put down after the replication fork is released from the pause. Thus, our data suggest that the imprint is formed by ligation of a not-fullyprocessed Okazaki fragment to the subsequent fragment. The presented work addresses how differentiated sister chromatids are established during DNA replication through the involvement of replication barriers

Deferred lightweight indexing for log-structured key-value stores

The recent shift towards write-intensive workload on bigdata (e.g., financial trading, social user-generated data streams)has pushed the proliferation of log-structured key-value stores, represented by Google's BigTable [1], Apache HBase [2] andCassandra [3]. While providing key-based data access with aPut/Get interface, these key-value stores do not support value-based access methods, which significantly limits their applicability in modern web and database applications. In this paper, we present DELI, a DEferred Lightweight Indexing scheme on the log-structured key-value stores. To index intensively updated bigdata in real time, DELI aims at making the index maintenance as lightweight as possible. The key idea is to apply an append-only design for online index maintenance and to collect index garbage at carefully chosen time. DELI optimizes the performance of index garbage collection through tightly coupling its execution with a native routine process called compaction. The DELI'ssystem design is fault-tolerant and generic (to most key-valuestores), we implemented a prototype of DELI based on HBasewithout internal code modification. Our experiments show that the DELI offers significant performance advantage for the write-intensive index maintenance