596 research outputs found
The Complexity of Fixed-Height Patterned Tile Self-Assembly
We characterize the complexity of the PATS problem for patterns of fixed
height and color count in variants of the model where seed glues are either
chosen or fixed and identical (so-called non-uniform and uniform variants). We
prove that both variants are NP-complete for patterns of height 2 or more and
admit O(n)-time algorithms for patterns of height 1. We also prove that if the
height and number of colors in the pattern is fixed, the non-uniform variant
admits a O(n)-time algorithm while the uniform variant remains NP-complete. The
NP-completeness results use a new reduction from a constrained version of a
problem on finite state transducers.Comment: An abstract version appears in the proceedings of CIAA 201
An Expert System for Trouble Shooting - Auto Wire Bonder Machine
An expert system to trouble shoot auto Wire bonder machine has been
developed at Dpak product line, Motorola Semiconductor Sdn. Bhd., Seremban. This
expert system is to provide a systematic and analytical procedure to trouble shoot
Delvotec 6830 auto wire bonder. A rule-based expert system using backward
chaining method is developed to guide the user during trouble shooting wire bond
defect. The expert system collects information from the user on the wire bond defects
by asking various questions. When the expert system reached to a conclusion, the
recommend adjustment procedure and corrective action will be shown on the Pc.
This expert system, running on a personal computer (PC), is programmed using Vp-
Expert Shell, it captures the domain expert knowledge in wire bonding process into
the knowledge base. Knowledge for this system is elicited from the domain expert through interviews and discussion, other sources of knowledge are from
manufacturer operating manual, Total control Methodology CTCM) file and literature.
The aid of this expert system is to improve bonding quality by reducing production
yield loss
Ontologies and Information Extraction
This report argues that, even in the simplest cases, IE is an ontology-driven
process. It is not a mere text filtering method based on simple pattern
matching and keywords, because the extracted pieces of texts are interpreted
with respect to a predefined partial domain model. This report shows that
depending on the nature and the depth of the interpretation to be done for
extracting the information, more or less knowledge must be involved. This
report is mainly illustrated in biology, a domain in which there are critical
needs for content-based exploration of the scientific literature and which
becomes a major application domain for IE
Dynamic Acoustic Unit Augmentation With BPE-Dropout for Low-Resource End-to-End Speech Recognition
With the rapid development of speech assistants, adapting server-intended
automatic speech recognition (ASR) solutions to a direct device has become
crucial. Researchers and industry prefer to use end-to-end ASR systems for
on-device speech recognition tasks. This is because end-to-end systems can be
made resource-efficient while maintaining a higher quality compared to hybrid
systems. However, building end-to-end models requires a significant amount of
speech data. Another challenging task associated with speech assistants is
personalization, which mainly lies in handling out-of-vocabulary (OOV) words.
In this work, we consider building an effective end-to-end ASR system in
low-resource setups with a high OOV rate, embodied in Babel Turkish and Babel
Georgian tasks. To address the aforementioned problems, we propose a method of
dynamic acoustic unit augmentation based on the BPE-dropout technique. It
non-deterministically tokenizes utterances to extend the token's contexts and
to regularize their distribution for the model's recognition of unseen words.
It also reduces the need for optimal subword vocabulary size search. The
technique provides a steady improvement in regular and personalized
(OOV-oriented) speech recognition tasks (at least 6% relative WER and 25%
relative F-score) at no additional computational cost. Owing to the use of
BPE-dropout, our monolingual Turkish Conformer established a competitive result
with 22.2% character error rate (CER) and 38.9% word error rate (WER), which is
close to the best published multilingual system.Comment: 16 pages, 7 figure
Proceedings
Proceedings of the NODALIDA 2011 Workshop
Visibility and Availability of LT Resources.
Editors: Sjur Nørstebø Moshagen and Per Langgård.
NEALT Proceedings Series, Vol. 13 (2011), vi+32 pp.
© 2011 The editors and contributors.
Published by
Northern European Association for Language
Technology (NEALT)
http://omilia.uio.no/nealt .
Electronically published at
Tartu University Library (Estonia)
http://hdl.handle.net/10062/1697
Probabilistic grammatical model of protein language and its application to helix-helix contact site classification
BACKGROUND: Hidden Markov Models power many state‐of‐the‐art tools in the field of protein bioinformatics. While excelling in their tasks, these methods of protein analysis do not convey directly information on medium‐ and long‐range residue‐residue interactions. This requires an expressive power of at least context‐free grammars. However, application of more powerful grammar formalisms to protein analysis has been surprisingly limited. RESULTS: In this work, we present a probabilistic grammatical framework for problem‐specific protein languages and apply it to classification of transmembrane helix‐helix pairs configurations. The core of the model consists of a probabilistic context‐free grammar, automatically inferred by a genetic algorithm from only a generic set of expert‐based rules and positive training samples. The model was applied to produce sequence based descriptors of four classes of transmembrane helix‐helix contact site configurations. The highest performance of the classifiers reached AUCROC of 0.70. The analysis of grammar parse trees revealed the ability of representing structural features of helix‐helix contact sites. CONCLUSIONS: We demonstrated that our probabilistic context‐free framework for analysis of protein sequences outperforms the state of the art in the task of helix‐helix contact site classification. However, this is achieved without necessarily requiring modeling long range dependencies between interacting residues. A significant feature of our approach is that grammar rules and parse trees are human‐readable. Thus they could provide biologically meaningful information for molecular biologists
Smart Sensor Webs For Environmental Monitoring Integrating Ogc Standards
Sensor webs are the most recent generation of data acquisition systems. The research presented looks at the concept of sensor webs from three perspectives: node, user, and data. These perspectives are different but are nicely complementary, and all extend an enhanced, usually wireless, sensor network. From the node perspective, sensor nodes collaborate in response to environmental phenomena in intelligent ways; this is referred to as the collaborative aspect. From the user perspective, a sensor web makes its sensor nodes and resources accessible via the WWW (World Wide Web); this is referred to as the accessible aspect. From the data perspective, sensor data is annotated with metadata to produce contextual information; this is referred to as the semantic aspect. A prototype that is a sensor web in all three senses has been developed. The prototype demonstrates theability of managing information in different knowledge domains. From the low-level weather data, information about higher-level weather concepts can be inferred and transferred to other knowledge domains, such as specific human activities. This produces an interesting viewpoint of situation awareness in the scope of traditional weather data
The Road to General Intelligence
Humans have always dreamed of automating laborious physical and intellectual tasks, but the latter has proved more elusive than naively suspected. Seven decades of systematic study of Artificial Intelligence have witnessed cycles of hubris and despair. The successful realization of General Intelligence (evidenced by the kind of cross-domain flexibility enjoyed by humans) will spawn an industry worth billions and transform the range of viable automation tasks.The recent notable successes of Machine Learning has lead to conjecture that it might be the appropriate technology for delivering General Intelligence. In this book, we argue that the framework of machine learning is fundamentally at odds with any reasonable notion of intelligence and that essential insights from previous decades of AI research are being forgotten. We claim that a fundamental change in perspective is required, mirroring that which took place in the philosophy of science in the mid 20th century. We propose a framework for General Intelligence, together with a reference architecture that emphasizes the need for anytime bounded rationality and a situated denotational semantics. We given necessary emphasis to compositional reasoning, with the required compositionality being provided via principled symbolic-numeric inference mechanisms based on universal constructions from category theory. • Details the pragmatic requirements for real-world General Intelligence. • Describes how machine learning fails to meet these requirements. • Provides a philosophical basis for the proposed approach. • Provides mathematical detail for a reference architecture. • Describes a research program intended to address issues of concern in contemporary AI. The book includes an extensive bibliography, with ~400 entries covering the history of AI and many related areas of computer science and mathematics.The target audience is the entire gamut of Artificial Intelligence/Machine Learning researchers and industrial practitioners. There are a mixture of descriptive and rigorous sections, according to the nature of the topic. Undergraduate mathematics is in general sufficient. Familiarity with category theory is advantageous for a complete understanding of the more advanced sections, but these may be skipped by the reader who desires an overall picture of the essential concepts This is an open access book
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