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Finding the optimal tradeoff between area and delay in multiple constant multiplications

MICROPROCESSORS AND MICROSYSTEMS 2011年第8期35卷 729-741页

作者： Aksoy, Levent Costa, Eduardo Flores, Paulo Monteiro, Jose INESC ID Lisbon Portugal Univ Catolica Pelotas Pelotas Brazil Univ Tecn Lisboa INESC ID IST Lisbon Portugal

Over the years many efficient algorithms for the multiplierless design of multiple constant multiplications (MCMs) have been introduced. These algorithms primarily focus on finding the fewest number of addition/subtraction operations that generate the MCM. Although the complexity of an MCM design is decreased by reducing the number of operations, their solutions may not lead to an MCM design with optimal area at gate-level since they do not consider the implementation costs of the operations in hardware. This article introduces two approximate algorithms that aim to optimize the area of the MCM operation by taking into account the gate-level implementation of each addition and subtraction operation which realizes a constant multiplication. To find the optimal tradeoff between area and delay, the proposed algorithms are further extended to find an MCM design with optimal area under a delay constraint. Experimental results clearly indicate that the solutions of the proposed algorithms lead to significantly better MCM designs at gate-level when compared to those obtained by the solutions of algorithms designed for the optimization of the number of operations. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Multiple constant multiplications Addition and subtraction architectures Gate-level area optimization Delay aware area optimization 0-1 Integer linear programming graph-based algorithms

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Treatment Recommendations for COVID-19 Patients along with Robust Explanations 34

Treatment Recommendations for COVID-19 Patients along with R...

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34th IEEE International Symposium on Computer-based Medical Systems (IEEE CBMS)

作者： Symeonidis, Panagiotis Andras, Christos Zanker, Markus Univ Aegean Samos Greece Int Hellen Univ Thessaloniki Greece Free Univ Bozen Bolzano Bolzano Italy

ISBN: (纸本)9781665441216

The global response to the pandemic introduced by COVID-19 is unprecedented. Scientists develop methods, which analyze data to identify an effective treatment that uncovers possible responses to the SARS-COV-2 virus. However, our global response should be based on knowledge exchange and collaboration among countries. In this paper, we present a recommender system for treatment recommendations, which exploits similar patterns among patients of different clinical studies, and recommends them health interventions (such as to provide oxygen therapy) and drugs (e.g., Remdesivir) based on their symptoms' or diseases' similarity with patients of other similar clinical studies. Our approach can also provide explanations along with recommended treatments to assist doctors in understanding the reasons behind a suggested drug or health intervention. We also perform experiments to identify the effectiveness of our system in terms of recommendation accuracy. Our results demonstrate that our system is able to minimize the false positive and false negative prediction rates. Finally, we provide web links to download both (i) our program's setup file and (ii) our Neo4j database file.

关键词： recommender systems graph-based algorithms meta path

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Web Services for Guiding Persons with Locomotor Impairments in Public Spaces 26

Web Services for Guiding Persons with Locomotor Impairments ...

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26th International Conference on System Theory, Control and Computing (ICSTCC)

作者： Damian, Ioan Lacatusu, Marian Lacatusu, Florin Ionita, Anca Daniela Univ Politehn Bucuresti Automat & Ind Informat Dept Bucharest Romania

ISBN: (数字)9781665467469

ISBN: (纸本)9781665467469

The navigation of pedestrians to a certain destination poses a challenge for large or unknown public spaces, even for those with very good wayfinding designs. This is amplified when people having locomotory impairments try to orientate themselves while being limited by accessibility restrictions. The approach presented here is based on modeling public spaces as graphs and adding weights corresponding to the potential difficulty to cross their edges. The typical path generation algorithm is extended to deliver the right guidance to pedestrians with mobility problems. By selecting a policy specific to their needs in the routing application, the users can have details on how hard it is to access a certain location of the public space. The paper presents an implementation using RESTful web services and an example of routing directions inside a building from our faculty.

关键词： RESTful Web Services graph-based algorithms assistive software

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Vulnerability Assessment Methods - A Review

Vulnerability Assessment Methods - A Review

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4th International Conference on Network Security and Applications (CNSA 2011)

作者： Nath, Hiran V. Amrita Sch Engn Coimbatore TIFAC CORE Cyber Secur Ctr Coimbatore Tamil Nadu India

ISBN: (纸本)9783642225390

This paper reviews the major contributions in the field of Vulnerability Assessment from 1990 onwards. Even well administered networks are vulnerable to attack. Vulnerabilities are weaknesses in the requirements, design, and implementation, which attackers exploit to compromise the system. Researchers have proposed a variety of methods like graph-based algorithms to generate attack trees (or graphs), "black-box" and "whitebox" analysis, using Mobile Ambients, using Honepots, different Vulnerability tools and their Scoring System's, and so on. After surveying lot of research papers in the field, the amount of existing works for each method is identified and classified. Especially, the graph-based algorithms itself is a major area for researchers. The paper concludes with some inferences and results obtained in each method so can be used as a guideline for researchers.

关键词： Vulnerability Assessment graph-based algorithms attack trees Mobile Ambients Honepots

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Distributed-Memory algorithms for Maximal Cardinality Matching using Matrix Algebra

Distributed-Memory Algorithms for Maximal Cardinality Matchi...

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IEEE International Conference on Cluster Computing (CLUSTER)

作者： Azad, Ariful Buluc, Aydin Lawrence Berkeley Natl Lab Computat Res Div Berkeley CA 94720 USA

ISBN: (纸本)9781467365987

We design and implement distributed-memory parallel algorithms for computing maximal cardinality matching in a bipartite graph. Relying on matrix algebra building blocks, our algorithms expose a higher degree of parallelism on distributed memory platforms than existing graph-based algorithms. In contrast to existing parallel algorithms, empirical approximation ratios of the new algorithms are insensitive to concurrency and stay relatively constant with increasing processor counts. On real instances, our algorithms achieve up to 300 x speedup on 1024 cores of a Cray XC30 supercomputer. Even higher speedups are obtained on larger synthetically generated graphs where our algorithms show good scaling on up to 16,384 processors.

关键词： distributed memory systems graph theory matrix algebra parallel algorithms pattern matching Cray XC30 supercomputer bipartite graph distributed-memory parallel algorithms empirical approximation ratios graph-based algorithms maximal cardinality matching processor counts Algorithm design and analysis Approximation algorithms Bipartite graph Heuristic algorithms Matrices Partitioning algorithms Sparse matrices cardinality matching matching maximal matching

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21st International Conference on Web Engineering (ICWE)

作者： Symeonidis, Panagiotis Univ Aegean Samos Greece

ISBN: (纸本)9783030742966;9783030742959

In this tutorial, we provide a rich blend of theory and practice regarding graph algorithms, to deal with challenging issues such as scalability, data noise, and sparsity in recommender systems. We also demonstrate real-life systems that use the graph algorithms for Social Media (http://***/moviexplain/), News (http://***) and Health (https://***) industry along with user studies which were used to evaluate the acceptance of the users for these systems.

关键词： Recommender systems graph-based algorithms

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Recommending What Drug to Prescribe Next for Accurate and Explainable Medical Decisions 34

Recommending What Drug to Prescribe Next for Accurate and Ex...

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34th IEEE International Symposium on Computer-based Medical Systems (IEEE CBMS)

作者： Symeonidis, Panagiotis Chairistanidis, Stergios Zanker, Markus Univ Aegean Samos Greece Aristotle Univ Thessaloniki Thessaloniki Greece Free Univ Bozen Bolzano Bolzano Italy

ISBN: (纸本)9781665441216

Patients with complex diseases (i.e., cancer, diabetes, etc.) often follow a therapeutic that consists of multiple drugs, focusing at different human targets such as genes, proteins, etc. There is already related work in medical research for drug-target prediction and drug re-purposing. In this paper, we try to provide both accurate and explainable drug recommendations. In particular, we develop models to help doctors screen candidate drugs and their possible substitutes more comprehensively, by providing also robust explanations. To do this, we build a heterogeneous information network to capture the latent associations between patients, their therapeutics, the drugs used, and diseases nodes by using a meta path-based similarity measure. based on previous similar patients' historical drug treatments, we can provide personalized drug recommendations along with explanations to support critical medical decisions. Demo code for our hybrid meta-based explanations can be found here. We have performed experiments on three real life data sets, which show that we can increase drastically the explainability of our drug recommendations by using more historical data, whereas the recommendations' accuracy still remains at a high level.

关键词： medicine recommendations graph-based algorithms meta path-based explanations

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Analysis of label noise in graph-based semi-supervised learning 20

Analysis of label noise in graph-based semi-supervised learn...

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35th Annual ACM Symposium on Applied Computing (SAC)

作者： de Aquino Afonso, Bruno Klaus Berton, Lilian Univ Fed Sao Paulo Sao Jose Dos Campos Brazil

ISBN: (纸本)9781450368667

In machine learning, one must acquire labels to help supervise a model that will be able to generalize to unseen data. However, the labeling process can be tedious, long, costly, and error-prone. It is often the case that most of our data is unlabeled. Semi-supervised learning (SSL) alleviates that by making strong assumptions about the relation between the labels and the input data distribution. This paradigm has been successful in practice, but most SSL algorithms end up fully trusting the few available labels. In real life, both humans and automated systems are prone to mistakes;it is essential that our algorithms are able to work with labels that are both few and also unreliable. Our work aims to perform an extensive empirical evaluation of existing graph-based semi-supervised algorithms, like Gaussian Fields and Harmonic Functions, Local and Global Consistency, Laplacian Eigenmaps, graph Transduction Through Alternating Minimization. To do that, we compare the accuracy of classifiers while varying the amount of labeled data and label noise for many different samples. Our results show that, if the dataset is consistent with SSL assumptions, we are able to detect the noisiest instances, although this gets harder when the number of available labels decreases. Also, the Laplacian Eigenmaps algorithm performed better than label propagation when the data came from high-dimensional clusters.

关键词： Machine learning semi-supervised learning graph-based algorithms classification label noise

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Keyphrase Extraction Using Knowledge graphs

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DATA SCIENCE AND ENGINEERING 2017年第4期2卷 275-288页

作者： Shi, Wei Zheng, Weiguo Yu, Jeffrey Xu Cheng, Hong Zou, Lei Chinese Univ Hong Kong Shatin Hong Kong Peoples R China Peking Univ Beijing Peoples R China

Extracting keyphrases from documents automatically is an important and interesting task since keyphrases provide a quick summarization for documents. Although lots of efforts have been made on keyphrase extraction, most of the existing methods (the co-occurrence-based methods and the statistic-based methods) do not take semantics into full consideration. The co-occurrence-based methods heavily depend on the co-occurrence relations between two words in the input document, which may ignore many semantic relations. The statistic-based methods exploit the external text corpus to enrich the document, which introduce more unrelated relations inevitably. In this paper, we propose a novel approach to extract keyphrases using knowledge graphs, based on which we could detect the latent relations of two keyterms (i.e., noun words and named entities) without introducing many noises. Extensive experiments over real data show that our method outperforms the state-of-the-art methods including the graph-based co-occurrence methods and statistic-based clustering methods.

关键词： Keyphrase extraction Knowledge graph graph-based algorithms

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Search algorithms for the multiple constant multiplications problem: Exact and approximate

Search algorithms for the multiple constant multiplications ...

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26th Norchip Conference

作者： Aksoy, Levent Gunes, Ece Olcay Flores, Paulo Istanbul Tech Univ Dept Elect & Commun Engn TR-34469 Istanbul Turkey Univ Tecn Lisboa INESC ID IST P-1000029 Lisbon Portugal

This article addresses the multiplication of one data sample with multiple constants using addition/subtraction and shift operations, i.e., the multiple constant multiplications (MCM) operation. In the last two decades, many efficient algorithms have been proposed to implement the MCM operation using the fewest number of addition and subtraction operations. However, due to the NP-hardness of the problem, almost all the existing algorithms have been heuristics. The main contribution of this article is the proposal of an exact depth-first search algorithm that, using lower and upper bound values of the search space for the MCM problem instance, finds the minimum solution consuming less computational resources than the previously proposed exact breadth-first search algorithm. We start by describing the exact breadth-first search algorithm that can be applied on real mid-size instances. We also present our recently proposed approximate algorithm that finds solutions close to the minimum and is able to compute better bounds for the MCM problem. The experimental results clearly indicate that the exact depth-first search algorithm can be efficiently applied to large size hard instances that the exact breadth-first search algorithm cannot handle and the heuristics can only find suboptimal solutions. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Multiple constant multiplications problem Depth-first search Breadth-first search graph-based algorithms Finite Impulse Response filters

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