scholarly journals Coinductive Algorithms for Büchi Automata

2021 ◽  
Vol 180 (4) ◽  
pp. 351-373
Author(s):  
Denis Kuperberg ◽  
Laureline Pinault ◽  
Damien Pous
Keyword(s):  
State Space ◽  
State Of The Art ◽  
The State ◽  
Specific Structure ◽  
Büchi Automata ◽  
Deterministic Automata ◽  
Buchi Automata ◽  
Language Equivalence ◽  
Art Techniques

We propose a new algorithm for checking language equivalence of non-deterministic Büchi automata. We start from a construction proposed by Calbrix, Nivat and Podelski, which makes it possible to reduce the problem to that of checking equivalence of automata on finite words. Although this construction generates large and highly non-deterministic automata, we show how to exploit their specific structure and apply state-of-the art techniques based on coinduction to reduce the state-space that has to be explored. Doing so, we obtain algorithms which do not require full determinisation or complementation.

scholarly journals Certifying Inexpressibility

2021 ◽  
pp. 385-405
Author(s):  
Orna Kupferman ◽  
Salomon Sickert
Keyword(s):  
Winning Strategy ◽  
Expressive Power ◽  
The State ◽  
Infinite Words ◽  
Current State ◽  
Büchi Automata ◽  
Deterministic Automata ◽  
Buchi Automata

AbstractDifferent classes of automata on infinite words have different expressive power. Deciding whether a given language$$L \subseteq \varSigma ^\omega $$L⊆Σωcan be expressed by an automaton of a desired class can be reduced to deciding a game between Prover and Refuter: in each turn of the game, Refuter provides a letter in$$\varSigma $$Σ, and Prover responds with an annotation of the current state of the run (for example, in the case of Büchi automata, whether the state is accepting or rejecting, and in the case of parity automata, what the color of the state is). Prover wins if the sequence of annotations she generates is correct: it is an accepting run iff the word generated by Refuter is inL. We show how a winning strategy for Refuter can serve as a simple and easy-to-understand certificate to inexpressibility, and how it induces additional forms of certificates. Our framework handles all classes of deterministic automata, including ones with structural restrictions like weak automata. In addition, it can be used for refutingseparationof two languages by an automaton of the desired class, and for finding automata thatapproximateLand belong to the desired class.

scholarly journals A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration

2021 ◽  
Vol 2 ◽  
Author(s):  
Sidrah Liaqat ◽  
Kia Dashtipour ◽  
Adnan Zahid ◽  
Kamran Arshad ◽  
Sana Ullah Jan ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
State Of The Art ◽  
The State ◽  
Skin Hydration ◽  
Hydration Level ◽  
Independent Review ◽  
Intelligent Models ◽  
Electrocardiogram Ecg ◽  
Fast Heart Rate ◽  
Art Techniques

Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmia, with a prevalence of 1–2% in the community, increasing the risk of stroke and myocardial infarction. Early detection of AF, typically causing an irregular and abnormally fast heart rate, can help reduce the risk of strokes that are more common among older people. Intelligent models capable of automatic detection of AF in its earliest possible stages can improve the early diagnosis and treatment. Luckily, this can be made possible with the information about the heart's rhythm and electrical activity provided through electrocardiogram (ECG) and the decision-making machine learning-based autonomous models. In addition, AF has a direct impact on the skin hydration level and, hence, can be used as a measure for detection. In this paper, we present an independent review along with a comparative analysis of the state-of-the-art techniques proposed for AF detection using ECG and skin hydration levels. This paper also highlights the effects of AF on skin hydration level that is missing in most of the previous studies.

scholarly journals Lossless Image Compression Techniques: A State-of-the-Art Survey

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1274 ◽  
Author(s):  
Md. Atiqur Rahman ◽  
Mohamed Hamada
Keyword(s):  
Image Compression ◽  
High Speed ◽  
Communication Theory ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Daily Basis ◽  
The State ◽  
Huge Amount ◽  
Lossless Image Compression ◽  
Art Techniques

Modern daily life activities result in a huge amount of data, which creates a big challenge for storing and communicating them. As an example, hospitals produce a huge amount of data on a daily basis, which makes a big challenge to store it in a limited storage or to communicate them through the restricted bandwidth over the Internet. Therefore, there is an increasing demand for more research in data compression and communication theory to deal with such challenges. Such research responds to the requirements of data transmission at high speed over networks. In this paper, we focus on deep analysis of the most common techniques in image compression. We present a detailed analysis of run-length, entropy and dictionary based lossless image compression algorithms with a common numeric example for a clear comparison. Following that, the state-of-the-art techniques are discussed based on some bench-marked images. Finally, we use standard metrics such as average code length (ACL), compression ratio (CR), pick signal-to-noise ratio (PSNR), efficiency, encoding time (ET) and decoding time (DT) in order to measure the performance of the state-of-the-art techniques.

Performance and trends in recent opinion retrieval techniques

2013 ◽  
Vol 30 (1) ◽  
pp. 76-105 ◽  
Author(s):  
Sylvester O. Orimaye ◽  
Saadat M. Alhashmi ◽  
Eu-Gene Siew
Keyword(s):  
State Of The Art ◽  
Performance Comparison ◽  
The State ◽  
Future Research ◽  
Research Directions ◽  
Opinion Retrieval ◽  
Future Research Directions ◽  
And Performance ◽  
Comparison Table ◽  
Art Techniques

AbstractThis paper presents trends and performance of opinion retrieval techniques proposed within the last 8 years. We identify major techniques in opinion retrieval and group them into four popular categories. We describe the state-of-the-art techniques for each category and emphasize on their performance and limitations. We then summarize with a performance comparison table for the techniques on different datasets. Finally, we highlight possible future research directions that can help solve existing challenges in opinion retrieval.

scholarly journals Analyzing Tie-Breaking Strategies for the A* Algorithm

2018 ◽  
Author(s):  
Augusto B. Corrêa ◽  
André G. Pereira ◽  
Marcus Ritt
Keyword(s):  
State Space ◽  
Standard Method ◽  
State Of The Art ◽  
The State ◽  
Heuristic Function ◽  
A Algorithm ◽  
Minimum Number ◽  
Previous State

For a given state space and admissible heuristic function h there is always a tie-breaking strategy for which A* expands the minimum number of states [Dechter and Pearl, 1985]. We say that these strategies have optimal expansion. Although such a strategy always exists it may depend on the instance, and we currently do not know a tie-breaker that always guarantees optimal expansion. In this paper, we study tie-breaking strategies for A*. We analyze common strategies from the literature and prove that they do not have optimal expansion. We propose a novel tie-breaking strategy using cost adaptation that has always optimal expansion. We experimentally analyze the performance of A* using several tie-breaking strategies on domains from the IPC and zero-cost domains. Our best strategy solves significantly more instances than the standard method in the literature and more than the previous state-of-the-art strategy. Our analysis improves the understanding of how to develop effective tie-breaking strategies and our results also improve the state-of-the-art of tie-breaking strategies for A*.

scholarly journals Efficient Temporal Planning Using Metastates

2019 ◽  
Vol 33 ◽  
pp. 7554-7561 ◽  
Author(s):  
Amanda Coles ◽  
Andrew Coles ◽  
J. Christopher Beck
Keyword(s):  
State Space ◽  
State Of The Art ◽  
The State ◽  
The Other ◽  
Temporal Constraints ◽  
State Space Explosion ◽  
Temporal Planning ◽  
State Space Search ◽  
Temporal Inconsistency

When performing temporal planning as forward state-space search, effective state memoisation is challenging. Whereas in classical planning, two states are equal if they have the same facts and variable values, in temporal planning this is not the case: as the plans that led to the two states are subject to temporal constraints, one might be extendable into at temporally valid plan, while the other might not. In this paper, we present an approach for reducing the state space explosion that arises due to having to keep many copies of the same ‘classically’ equal state – states that are classically equal are aggregated into metastates, and these are separated lazily only in the case of temporal inconsistency. Our evaluation shows that this approach, implemented in OPTIC and compared to existing state-of-the-art memoisation techniques, improves performance across a range of temporal domains.

scholarly journals A FRAMEWORK FOR COMMUNITY DETECTION IN HETEROGENEOUS MULTI-RELATIONAL NETWORKS

2014 ◽  
Vol 17 (06) ◽  
pp. 1450018 ◽  
Author(s):  
XIN LIU ◽  
WEICHU LIU ◽  
TSUYOSHI MURATA ◽  
KEN WAKITA
Keyword(s):  
Community Detection ◽  
Real World ◽  
State Of The Art ◽  
General Structure ◽  
The State ◽  
New Method ◽  
World Systems ◽  
Relational Networks ◽  
Relational Network ◽  
Art Techniques

There has been a surge of interest in community detection in homogeneous single-relational networks which contain only one type of nodes and edges. However, many real-world systems are naturally described as heterogeneous multi-relational networks which contain multiple types of nodes and edges. In this paper, we propose a new method for detecting communities in such networks. Our method is based on optimizing the composite modularity, which is a new modularity proposed for evaluating partitions of a heterogeneous multi-relational network into communities. Our method is parameter-free, scalable, and suitable for various networks with general structure. We demonstrate that it outperforms the state-of-the-art techniques in detecting pre-planted communities in synthetic networks. Applied to a real-world Digg network, it successfully detects meaningful communities.

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