Switching Machine Improvisation Models by Latent Transfer Entropy Criteria (original) (raw)
A framework for Anticipatory Machine Improvisation and Style
2006
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Relations between Performers/parameters and Level of Automation
IFAC workshop on manufacturing modelling, management and control, 2007
Manufacturing companies struggles with the fact that costumers are becoming more and more aggressive in demanding new products and services within a short period of time. A result of this is that companies have to find the most effective manufacturing for their products. This means finding new tactics to decrease the time-and costparameters in a system i.e. cycle-time, ramp-up time, investments etc. It is a challenge to find the best solution for this when it comes to flexibility, robustness and efficiency. This paper presents some of the parameters that exist in a manufacturing system and the relationship between them. This is done to be able to identify the parameters that is the most important when it comes to simulate and visualise different Levels of Automation (LoA).
Entropy as a measure of operational flexibility
European Journal of Operational Research, 2005
As competition among firms is being based more and more on the level of service, there is a great interest in using a measure of flexibility to indicate a firm's capability to respond to customer demands. Entropy is proposed as a measure of flexibility for manufacturing operations. The properties of entropy that make it a suitable measure of flexibility are outlined. A computer simulation of a job shop was used to test the measure through a number of different scenarios using a discrete-event stochastic simulator. Results showed that entropy succeeded in measuring flexibility when the relative demand for the fabrication of products changed. Entropy was also used to monitor process flexibility as time progressed.
Machine Improvisation with Variable Markov Oracle
Computers in Entertainment, 2016
In this article, we describe the Variable Markov Oracle and how it can be used in stylistic machine music improvisation scenarios. A Variable Markov Oracle is a data structure capable of identifying repeated subsequences within a multivariate time series. A Variable Markov Oracle symbolizes a time series by maximizing an information theoretic measure. After symbolizing the time series, repetitive structures can be extracted and used for music improvisation. We present a machine improvisation framework, using a Variable Markov Oracle, that is capable of generating novel audio content for either real-time or stored audio input. This work focuses on guided improvisation and structured improvisation.
Advances in Markov-Switching Models
2002
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On Quantifying Manufacturing Flexibility: An Entropy Based Approach
2015
In this research, an entropy based evaluation is adapted for the quantification of manufacturing flexibility. The aim is to evaluate the manufacturing flexibility in scope of a job shop model and to reach a single numeric value that would represent the overall flexibility level of operations performed in that manufacturing unit. The model proposed is applied to a job shop in which manufacturing is characterized by type of machinery, number and type of operations and routing for each product as well as time spend for operations, machine set up activities and material handling. In the paper, the flexibility level of the job shop is found and the association between the total entropy value and flexibility level is discussed.
Machine Improvisation With Formal Specifications
Proceedings of the SMC Conferences, 2014
We define the problem of machine improvisation of music with formal specifications. In this problem, one seeks to create a random improvisation of a given reference melody that however satisfies a "specification" encoding constraints that the generated melody must satisfy. We consider the scenario of generating a monophonic Jazz melody (solo) on a given song harmonization. The music is encoded symbolically, with the improviser generating a sequence of note symbols comprising pairs of pitches (frequencies) and discrete durations. Our approach can be decomposed roughly into two phases: a generalization phase, that learns from a training sequence (e.g., obtained from a human) an automaton generating similar sequences, and a supervision phase that enforces a specification on the generated sequence, imposing constraints on the music in both the pitch and rhythmic domains. The supervision uses a measure adapted from Normalized Compression Distances (NCD) to estimate the divergence between generated melodies and the training melody and employs strategies to bound this divergence. An empirical evaluation is presented on a sample set of Jazz music. 1 Inharmonic and aperiodic sounds are beyond the scope of this paper.
An Examination of Variability and Its Basic Properties for a Factory
IEEE Transactions on Semiconductor Manufacturing, 2005
Variability is a key performance index of a factory. In order to characterize variability of a factory, definitions of bottleneck, utilization, and variability of a single machine are reexamined and clarified. The clarification leads to the introduction of a detail expression for the relationship between cycle time and work-in-progress. In order to quantify variability for factories, the author uses a single machine system to gauge the behaviors, and subsequently derives an explicit expression for the variability, of a simple factory, making use of analogy and the clarified definitions. The obtained results can be applied to many subjects in the field of manufacturing management, such as factory performance analysis, capacity planning, and cycle time reduction. With the derived results, properties of variability for a simple factory in the aspects of utilization versus throughput bottlenecks and nonthroughput bottlenecks, gap effects, and bounds on variability, are examined in detail to shed light on the insights of the stochastic behaviors of a complex factory.
Flexibility has long been recognized as a manufacturing capability that has the potential to impact mainly the competitive position of an organization. The entropy approach, which was extended from information theory, fell in handling problems with incomplete and uncertain data, because it depicts only the stochastic aspects included with measured observations. In order to get a global view, this work proposes a new approach based on fuzzy entropy concept. The development of the fuzzy model results in a set of nonlinear constrained problems to be solved using a metaheuristics method. The applicability of our approach is illustrated through a flexible manufacturing cell. By adopting such framework, both dimensions of uncertainty in system modeling, expressed by stochastic variability and imprecision, can be taken into consideration.