Abstract: A platform assembly for attachment to a tree includes a platform, an integrally formed post coupled to the platform and operable to pivot relative to the platform about a pivot axis, and a standoff extending outward from the post proximate to the first end. The post extends from a first end to a second end along a length of the post that is substantially perpendicular to the pivot axis.

Abstract: An injection-molded climbing stick includes a first step, a second step, and a post extending from the first step to the second step along a length of the post and comprising a plurality of fibers that includes every fiber that is disposed within the post. The plurality of fibers includes a sub-plurality of fibers. Each fiber in the sub-plurality of fibers is elongated in a lengthwise direction of the fiber and oriented such that the lengthwise direction is substantially parallel to the length of the post, and the sub-plurality of fibers includes a majority of the fibers in the plurality of fibers.

Abstract: A tree saddle includes a first panel having first and second ends with a body portion disposed therebetween, and a second panel having first and second ends with a body portion disposed therebetween. One or more connecting members operably couple the first and second panels to one another. A magnetic coupling system includes a first magnetic array disposed on the first panel, and a second magnetic array disposed on the second panel. The first magnetic array is magnetically coupled to the second magnetic array when the tree saddle is in a coupled condition. The first magnetic array is uncoupled from the second magnetic array when the tree saddle is in an uncoupled condition. The tree saddle includes a first profile when the tree saddle is in the uncoupled condition that is greater than a second profile of the tree saddle when the tree saddle is in the coupled condition.

Abstract: A platform assembly for attachment to a tree includes a platform and a post. The platform has an outer perimeter that bounds an interior structure of the platform that is horizontally-inboard of the outer perimeter. The outer perimeter includes a rear portion, a first wing portion coupled to the rear portion at a first wing portion rear corner and including an outboard-most portion of the outer perimeter in a first lateral direction, a front portion coupled to the first wing portion, and a second wing portion coupled to the front portion. The post is coupled to the platform and pivots relative to the platform about a pivot axis.

Abstract: A tree saddle includes a first panel having first and second ends with a body portion disposed therebetween, and a second panel having first and second ends with a body portion disposed therebetween. One or more connecting members operably couple the first and second panels to one another. A magnetic coupling system includes a first magnetic array disposed on the first panel, and a second magnetic array disposed on the second panel. The first magnetic array is magnetically coupled to the second magnetic array when the tree saddle is in a coupled condition. The first magnetic array is uncoupled from the second magnetic array when the tree saddle is in an uncoupled condition. The tree saddle includes a first profile when the tree saddle is in the uncoupled condition that is greater than a second profile of the tree saddle when the tree saddle is in the coupled condition.

Abstract: A system and method of implementing an intuitive search interface for tactically searching one or more annotated utterance corpora in a machine learning-based dialogue system includes identifying an utterance corpus query for searching one or more annotated utterance corpora of a machine learning-based dialogue system; interpreting the utterance corpus query by translating the utterance corpus query into one or more search expressions recognizable to an utterance sample retrieval program searchably interfacing with the one or more annotated utterance corpora of the machine learning-based dialogue system; retrieving one or more annotated utterance samples from the one or more annotated utterance corpora based on the interpretation of the utterance corpus query; and returning the one or more annotated utterance samples to an intuitive utterance corpus search interface.

Abstract: A system and method of implementing an intuitive search interface for tactically searching one or more annotated utterance corpora in a machine learning-based dialogue system includes identifying an utterance corpus query for searching one or more annotated utterance corpora of a machine learning-based dialogue system; interpreting the utterance corpus query by translating the utterance corpus query into one or more search expressions recognizable to an utterance sample retrieval program searchably interfacing with the one or more annotated utterance corpora of the machine learning-based dialogue system; retrieving one or more annotated utterance samples from the one or more annotated utterance corpora based on the interpretation of the utterance corpus query; and returning the one or more annotated utterance samples to an intuitive utterance corpus search interface.

Abstract: Systems and methods for intelligently training a subject machine learning model includes identifying new observations comprising a plurality of distinct samples unseen by a target model during a prior training; creating an incremental training corpus based on randomly sampling a collection of training data samples that includes a plurality of new observations and a plurality of historical training data samples used in the prior training of the target model; implementing a first training mode that includes an incremental training of the target model using samples from the incremental training corpus as model training input; computing performance metrics of the target model based on the incremental training; evaluating the performance metrics of the target model against training mode thresholds; and selectively choosing based on the evaluation one of maintaining the first training mode and automatically switching to a second training mode that includes a full retraining of the target model.

Abstract: Systems and methods for constructing an artificially diverse corpus of training data includes evaluating a corpus of utterance-based training data samples, identifying a slot replacement candidate; deriving distinct skeleton utterances that include the slot replacement candidate, wherein deriving the distinct skeleton utterances includes replacing slots of each of the plurality of distinct utterance training samples with one of a special token and proper slot classification labels; selecting a subset of the distinct skeleton utterances; converting each of the distinct skeleton utterances of the subset back to distinct utterance training samples while still maintaining the special token at a position of the slot replacement candidate; altering a percentage of the distinct utterance training samples with a distinct randomly-generated slot token value at the position of the slot replacement candidate; and constructing the artificially diverse corpus of training samples based on a collection of the percentage of

Abstract: Systems and methods for synthesizing training data for multi-intent utterance segmentation include identifying a first corpus of utterances comprising a plurality of distinct single-intent in-domain utterances; identifying a second corpus of utterances comprising a plurality of distinct single-intent out-of-domain utterances; identifying a third corpus comprising a plurality of distinct conjunction terms; forming a multi-intent training corpus comprising synthetic multi-intent utterances, wherein forming each distinct multi-intent utterance includes: selecting a first distinct in-domain utterance from the first corpus of utterances; probabilistically selecting one of a first out-of-domain utterance from the second corpus and a second in-domain utterance from the first corpus; probabilistically selecting or not selecting a distinct conjunction term from the third corpus; and forming a synthetic multi-intent utterance including appending the first in-domain utterance with one of the first out-of-domain utteranc

Abstract: Systems and methods for constructing an artificially diverse corpus of training data includes evaluating a corpus of utterance-based training data samples, identifying a slot replacement candidate; deriving distinct skeleton utterances that include the slot replacement candidate, wherein deriving the distinct skeleton utterances includes replacing slots of each of the plurality of distinct utterance training samples with one of a special token and proper slot classification labels; selecting a subset of the distinct skeleton utterances; converting each of the distinct skeleton utterances of the subset back to distinct utterance training samples while still maintaining the special token at a position of the slot replacement candidate; altering a percentage of the distinct utterance training samples with a distinct randomly-generated slot token value at the position of the slot replacement candidate; and constructing the artificially diverse corpus of training samples based on a collection of the percentage of

Abstract: Systems and methods for synthesizing training data for multi-intent utterance segmentation include identifying a first corpus of utterances comprising a plurality of distinct single-intent in-domain utterances; identifying a second corpus of utterances comprising a plurality of distinct single-intent out-of-domain utterances; identifying a third corpus comprising a plurality of distinct conjunction terms; forming a multi-intent training corpus comprising synthetic multi-intent utterances, wherein forming each distinct multi-intent utterance includes: selecting a first distinct in-domain utterance from the first corpus of utterances; probabilistically selecting one of a first out-of-domain utterance from the second corpus and a second in-domain utterance from the first corpus; probabilistically selecting or not selecting a distinct conjunction term from the third corpus; and forming a synthetic multi-intent utterance including appending the first in-domain utterance with one of the first out-of-domain utteranc

Abstract: Systems and methods for synthesizing training data for multi-intent utterance segmentation include identifying a first corpus of utterances comprising a plurality of distinct single-intent in-domain utterances; identifying a second corpus of utterances comprising a plurality of distinct single-intent out-of-domain utterances; identifying a third corpus comprising a plurality of distinct conjunction terms; forming a multi-intent training corpus comprising synthetic multi-intent utterances, wherein forming each distinct multi-intent utterance includes: selecting a first distinct in-domain utterance from the first corpus of utterances; probabilistically selecting one of a first out-of-domain utterance from the second corpus and a second in-domain utterance from the first corpus; probabilistically selecting or not selecting a distinct conjunction term from the third corpus; and forming a synthetic multi-intent utterance including appending the first in-domain utterance with one of the first out-of-domain utteranc

Abstract: Embodiments herein disclose a debugging framework that employs a mode in the processor (for example, a processor using x86 architecture), to transparently study armored malware. Embodiments herein perform stealthy debugging by leveraging System Management Mode (SMM) to transparently debug software on bare-metal.

Abstract: Embodiments herein disclose a debugging framework that employs a mode in the processor (for example, a processor using x86 architecture), to transparently study armored malware. Embodiments herein perform stealthy debugging by leveraging System Management Mode (SMM) to transparently debug software on bare-metal.

Abstract: Methods of treating B2-bradykinin receptor mediated angioedema in a subject by administering a composition containing a 8-(heteroarylmethoxy)quinolone compound, a 8-(arylmethoxy)quinoline compound, or a salt, a stereoisomer, a hydrate, or a solvate thereof. Oral formulations containing a 8-(heteroarylmethoxy)quinolone compound, a 8-(arylmethoxy)quinoline compound, or a salt, a stereoisomer, a hydrate, or a solvate thereof for the treatment of B2-bradykinin receptor mediated angioedema. Use of a composition containing a 8-(heteroarylmethoxy)quinolone compound, a 8-(arylmethoxy)quinoline compound, or a salt, a stereoisomer, a hydrate, or a solvate thereof for the manufacture of a medicament for the treatment and/or prevention of a B2-bradykinin receptor mediated angioedema.