Ensemble Sample Clauses
The "Ensemble" clause defines the group of parties or entities that are collectively involved in an agreement or contract. It typically specifies who constitutes the ensemble, such as a group of performers, companies, or stakeholders, and may outline their roles or responsibilities within the group. By clearly identifying all members of the ensemble, this clause ensures that obligations, rights, and expectations are properly allocated among the relevant parties, thereby reducing ambiguity and potential disputes about participation or accountability.
Ensemble. The terms “Ensemble,” “Ensemble member,” “member of the Ensemble,” “Artist engaged under an Ensemble contract” and “Ensemble Artist” shall include all persons who are engaged under Ensemble contracts and/or actually performing Ensemble work, as may be determined by AGMA.
Ensemble. This parameter controls the build-up of the reverb sound. These 3 characters allow for a very wide range of reverb sounds. This is an ensemble effect that originates from within the core structure that makes up the reverb effect. It modulates the pitch of the incoming sound, with a depth that increases throughout the duration of the reverb. Being a true, in-reverb effect, it can add richness to the sound without compromising the reverb’s spaciousness or clarity. At level “0” the Ensemble effect is off. At levels 1 to 5, it’s on, and at levels 6 to 10, it’s on with an additional modulation stage that creates an even more distinct sound. different listening spaces. Rev-A’s high quality processing ensures that at level 10, the reverb’s sound is pellucid, with high frequencies unattenuated. Controls
Ensemble. Crucial to the productivity of the rehearsal process as well as the dynamics of the performance is the cultivation of an ensemble among the company of actors and the production team. To that end the actor should endeavor to:
a) Maintain an environment where everyone feels free to explore, experiment, and take risks without fear of failure or ridicule. Support and, where possible, assist fellow actors in their efforts.
b) The actor should endeavor to keep an open mind and ▇▇▇▇▇▇ a willing attitude that allows for experimentation and exploration of the text and performance. Actors are subsequently expected to communicate when they don't understand something or are having difficulty making an interpretation work.
c) Any actor who's attitude within the rehearsal process is significantly disruptive to the progress or morale of the acting com pany will be dismissed from the company.
d) Throughout the early and middle stages of the production process, actors should strive to discover the most honest and compelling physical and vocal expression of their character's action and circumstances in rehearsal (as opposed to discussion). Show, don't tell.
e) The actor's discipline is to remain involved and engaged in rehearsal at all times even when not actively working. An actor should never “▇▇▇▇” through a rehearsal unless specifically instructed by the director or stage manager.
f) Listen! A successful actor's focus is ALWAYS external. It is never inward on the self, emotion, or the success of the performance. An actor’s focus is directed toward the subject of or obstacle to his or her objective-usually another character on stage.
Ensemble. This part exploits the classification results of the two models the DidaxTo (Figure 3) and The HyCoR (Figure 5). After experimentation on a set of datasets (Figure 6) the following decision tree (as seen in Figure 7) was created to implement the ensemble process.
Ensemble. Multiple instances of an application launched in parallel with different input data; each such instance may be a monolithic parallel code, itself running at extreme scale. These are now becoming part of highly complex data intensive workflows combining conventional HPC applications with machine learning and/or AI components, as well as for validation, verification and uncertainty quantification. This categorisation is not unique to CompBioMed, it is recognized widely in the HPC community as key “usage patterns”. It is worth mentioning that the Ensemble pattern is sometimes considered as two separate class: ensemble and complex workflows. In this document we discuss it as a single class. These patterns represent significant differences in the deployment strategy that should be taken into account when assessing scaling and performance as part of exascale readiness. In CompBioMed, and inheriting the characteristics of the computational medicine domain, we have applications falling under the three aforementioned patterns.