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1st international conference on Latest Advances in Machine learning and Data Science, LAMDA 2017

1st International conference on Latest Advances in Machine l...

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1st international conference on Latest Advances in Machine learning and Data Science, LAMDA 2017

ISBN: (纸本)9789811085680

The proceedings contain 38 papers. The special focus in this conference is on Latest Advances in Machine learning and Data Science. The topics include: Review on RBFNN design approaches: A case study on diabetes data;keyphrase and relation extraction from scientific publications;mixing and entrainment characteristics of jet control with crosswire;GCV-Based Regularized Extreme Learning Machine for Facial Expression Recognition;prediction of social dimensions in a heterogeneous social network;game theory-based defense mechanisms of cyber warfare;challenges inherent in building an intelligent paradigm for tumor detection using machine learning algorithms;segmentation techniques for computer-aided diagnosis of glaucoma: A review;performance analysis of information retrieval models on word pair index structure;Accelerating airline delay prediction-based P-CUDA computing environment;fast fingerprint retrieval using minutiae neighbor structure;key leader analysis in scientific collaboration network using H-type hybrid measures;a graph-based method for clustering of gene expression data with detection of functionally inactive genes and noise;OTAWE-Optimized topic-adaptive word expansion for cross domain sentiment classification on tweets;DCaP—Data confidentiality and privacy in cloud computing: strategies and challenges;design and development of a knowledge-based system for diagnosing diseases in banana plants;a review on methods applied on P300-based lie detectors;Implementation of spectral subtraction using sub-band filtering in DSP C6748 processor for enhancing speech signal;In-silico analysis of LncRNA-mRNA target prediction;Energy aware GSA-based load balancing method in cloud computing environment;IDPC-XML: Integrated data provenance capture in XML;relative performance evaluation of ensemble classification with feature reduction in credit scoring datasets.

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An easily extensible toolset for tabular mathematical expressions 5th

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5th international conference on Tools and algorithms for the Construction and Analysis of systems, TACAS 1999 Held as Part of the Joint European conferences on theory and practice of Software, ETAPS 1999

作者： Parnas, David Lorge Peters, Dennis K. Electrical and Computer Engineering Memorial University of Newfoundland St. John'sNLA1B 3X5 Canada Department of Computing and Software McMaster University HamiltonONL8S 4K1 Canada

ISBN: (纸本)3540657037

We describe the design of an open ended set of tools for manipulating multi-dimensional tabular expressions. The heart of the toolset is a set of modules that makes it possible to add new tools to the toolset without having detailed knowledge of the other tools. This set of modules, the Tool Integration Framework, supports new and existing tools by providing abstract communication interfaces. The framework that we describe has proven to be a practical approach to building an extensible set of tools. © Springer-Verlag Berlin Heidelberg 1999.

关键词： Artificial intelligence

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Supervised learning: Classification using decision trees for better practice in epidemiology Case study: The prevalence of tuberculosis

Supervised learning: Classification using decision trees for...

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13th international conference on Ambient systems, Networks and Technologies, ANT 2022 / 5th international conference on Emerging Data and Industry 4.0, EDI40 2022

作者： Salamate, Fatima Ezzahra Zahi, Jamal FEG Settat University Hassan the 1st Settat30 000 Morocco

In the current digital era, Artificial Intelligence is a technology that is accessible and used in many fields. In order to take advantage of the benefits of AI, different techniques can be used. Among them, supervised learning will allow to focus on machine learning algorithms to obtain relevant information from analyzed data [1]. Today, this technology appears to be an essential element for organizations wishing to improve their customer knowledge and thus respond to customer needs. We use supervised learning to diagnose a patient's health status and anticipate the risks of tuberculosis. 1276 patients were included in the study, 69% of whom reside in urban areas (the city of Settat), and 31% of whom live in rural areas. This study reveals that the disease mainly affects young adults with male predominance. The prevalence of tuberculosis in all forms during the five years fluctuates between 18.5% in 2015 and 22% in 2019. Pulmonary tuberculosis predominates with 66.75% of cases and remains higher than extra pulmonary tuberculosis during the whole study period, the latter being preferentially localized in the lymph nodes and pleura. © 2022 Elsevier B.V.. All rights reserved.

关键词： classification decision tree Tuberculosis

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On the Replicability of Experimental Tool Evaluations in Model-Based Development: Lessons Learnt from a Systematic Literature Review Focusing on MATLAB/Simulink 1st

On the Replicability of Experimental Tool Evaluations in Mod...

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1st international conference on systems Modelling and Management, ICSMM 2020

作者： Boll, Alexander Kehrer, Timo Department of Computer Science Humboldt-Universität zu Berlin Berlin Germany

ISBN: (纸本)9783030581664

Research on novel tools for model-based development differs from a mere engineering task by providing some form of evidence that a tool is effective. This is typically achieved by experimental evaluations. Following principles of good scientific practice, both the tool and the models used in the experiments should be made available along with a paper. We investigate to which degree these basic prerequisites for the replicability of experimental results are met by recent research reporting on novel methods, techniques, or algorithms supporting model-based development using MATLAB/Simulink. Our results from a systematic literature review are rather unsatisfactory. In a nutshell, we found that only 31% of the tools and 22% of the models used as experimental subjects are accessible. Given that both artifacts are needed for a replication study, only 9% of the tool evaluations presented in the examined papers can be classified to be replicable in principle. Given that tools are still being listed among the major obstacles of a more widespread adoption of model-based principles in practice, we see this as an alarming signal. While we are convinced that this can only be achieved as a community effort, this paper is meant to serve as starting point for discussion, based on the lessons learnt from our study. © 2020, Springer Nature Switzerland AG.

关键词： computers

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From elliott-macmahon to an algorithm for general linear constraints on naturals 1st

From elliott-macmahon to an algorithm for general linear con...

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1st international conference on Principles and practice of Constraint Programming, CP 1995

作者： Domenjoud, Eric Tomàs, Ana Paula CRIN/CNRS and INRIA-Lorralne France LIACC/University of Porto Portugal

ISBN: (纸本)3540602992

We describe a new algorithm for solving a conjunction of linear diophantine equations, inequations and disequations in natural numbers. We derive our algorithm from one proposed by Elliott in 1903 for solving a single homogeneous equation. This algorithm was then extended to solve homogeneous systems of equations by MacMahon. We show how it further extends to an algorithm which solves general linear constraints in nonnegative integers and allows a parallel implementation. This algorithm provides a parametric representation of the solutions from which minimal solutions may be extracted immediately. Moreover, it may be easily implemented in parallel. It has however one drawback: it is redundant which means that the same minimal solution is usually generated many times. We show how this redundancy may be eliminated at the cost of an increase in the space complexity. © Springer-Verlag Berlin Heidelberg 1995.

关键词： Constraint theory

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Communicating dynamic behaviors: Are interactive multimedia presentations better than static mixed-mode presentations? 1

Communicating dynamic behaviors: Are interactive multimedia ...

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1st international conference on theory and Application of Diagrams, Diagrams 2000

作者： Hari Narayanan, N. Hegarty, Mary Intelligent and Interactive Systems Laboratory Department of Computer Science and Software Engineering Auburn University AuburnAL36849 United States Department of Psychology University of California Santa BarbaraCA93106 United States

ISBN: (纸本)3540679154

static mixed-mode presentations consisting of verbal explanations illustrated with diagrams have long been used to communicate information. With the advent of multimedia, such presentations have become dynamic, by migrating from paper to the computer and by adding interactivity and animation. The conventional wisdom is that computer-based multimedia presentations are better than printed presentations. However, does the communicative power of mixed-mode representations stem from their careful design to match cognitive processes involved in comprehension or from their interactive and animated nature? This is an important issue that has never been investigated. This paper first presents a cognitive model of comprehension of mixed-mode representations. We describe how this model generates design guidelines for mixed-mode representations that present expository material in two domains - the concrete domain of mechanical systems and the abstract domain of computer algorithms. We then report on a series of studies that compared computer-based interactive multimedia presentations and their paper-based counterparts. Both were designed in accordance with the comprehension model and were compared against each other and against competing representational forms such as books, CD-ROMs, and animations. These studies indicate that the effectiveness of mixed-mode presentations has more to do with their match with comprehension processes than the medium of presentation. In other words, benefits of interactivity and animation are likely being overstated in the current milieu of fascination with multimedia. © Springer-Verlag Berlin Heidelberg 2000.

关键词： Animation

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Information Technology and Artificial Intelligence in Improving of Center Pivot Irrigation Control 1

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1st international Scientific and Practical conference on Information Technologies and Intelligent Decision Making systems, ITIDMS 2021

作者： Kamyshova, G. Ignar, S. Terekhova, N. Financial University under the Government of the Russian Federation Leningradskiy pr-d 49/2 Moscow125167 Russia Warsaw University of Life Sciences Nowoursynowska street 159 Warsaw02-776 Poland Saratov State Agrarian University Theatralnaia pl.1 Saratov410012 Russia

ISBN: (数字)9783031213403

ISBN: (纸本)9783031213397

The present study is focused on developing a center pivot irrigation control model that combines information technology and neuro-prediction. Modern digital technologies allow data collection, their analysis and operational management of equipment and technological processes in real time, which allows, on the one hand, to apply new approaches to modeling technical systems and processes -the so-called "data-driven models". On the other hand, it requires the development of fundamentally new models, which will be based on artificial intelligence methods. Information technology allows real-time analysis of the tracks and actual speeds of the sprinkler, which shows their significant deviations. We have developed a sprinkler control model based on information technology, the theory of artificial neural networks and predictive control. The application of the model makes it possible to implement control algorithms with a prediction of the reaction of the sprinkler to the control signal. We propose a diagram of an algorithm for constructing a predictive control, the structure of a neuro-regulator and tools for its synthesis using modern software. It is possible to use the proposed model both to improve the efficiency of the management of existing equipment, and in the development of new sprinklers with integrated intelligent control systems. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Neural networks

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Arrhythmias classification using singular value decomposition and support vector machine 1

Arrhythmias classification using singular value decompositio...

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1st Euro-China conference on Intelligent Data Analysis and Applications, ECC 2014

作者： Peterek, Tomáš Zaorálek, Lukásš Dohnák, Pavel Gajdoš, Petr IT4innovations VSB - Technical Univesity of Ostrava Ostrava708 33 Czech Republic Department of Computer Science FEECS VSB - Technical Univesity of Ostrava Ostrava708 33 Czech Republic

ISBN: (纸本)9783319077727

The main aim of this work is to recognize arrhythmias in ECG records. Many algorithms for this task have been proposed in the past, but in our solution we try to reduce redundancy of information in the signals by Singular Value Decomposition. The reduced dataset is classified by Support Vector Machine. Our approach gives very satisfactory results which can be used in medical practice. This expert system should offer automated recognition between physiological beat and one of the three basic pathological beats: Premature ventricular contractions, Right bundle branch block and Left bundle branch block. © 2014 Springer international Publishing Switzerland. All rights reserved.

关键词： Singular value decomposition

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Evaluation of recent computational approaches in short-term traffic forecasting 4th

Evaluation of recent computational approaches in short-term ...

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4th IFIP TC 12 international conference on rtificial Intelligence in theory and practice, IFIP AITP 2015 Held as Part of international Federation for Information Processing, WCC 2015

作者： Yang, Haofan Dillon, Tharam S Chen, Yi-Ping Phoebe Department of Computer Science and Information Technology La Trobe University MelbourneVIC3086 Australia

ISBN: (纸本)9783319252605

Computational technologies under the domain of intelligent systems are expected to help the rapidly increasing traffic congestion problem in recent traffic management. Traffic management requires efficient and accurate forecasting models to assist real time traffic control systems. Researchers have proposed various computational approaches, especially in short-term traffic flow forecasting, in order to establish reliable traffic patterns models and generate timely prediction results. Forecasting models should have high accuracy and low computational time to be applied in intelligent traffic management. Therefore, this paper aims to evaluate recent computational modeling approaches utilized in short-term traffic flow forecasting. These approaches are evaluated by real-world data collected on the British freeway (M6) from 1st to 30th November in 2014. The results indicate that neural network model outperforms generalized additive model and autoregressive integrated moving average model on the accuracy of freeway traffic forecasting. © IFIP international Federation for Information Processing 2015.

关键词： Traffic congestion

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Removal of high density impulse noise from digital images and image quality assessment

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1st international conference on Frontiers in Intelligent Computing: theory and Applications, FICTA 2012

作者： Anji Reddy, V. Vasudeva Rao, J. Department of Computer Science and Engineering GMR Institute of Technology Rajam Srikakulam District Andhra Pradesh A.P India

ISBN: (纸本)9783642353130

The digital images are corrupted by noise due to errors generated in camera sensors, analog to digital conversion and communication channels. Many types of noises may occur. In this paper we are concentrating on the impulse noise. Therefore it is necessary to remove impulse noise in order to provide the quality image. Filtering a noise image is one of the important methods in image processing. This paper presents a new method for impulse noise removal from digital images using iterative scheme. The performance of the iterative scheme is compared with other filters like SMF, DBA and VMF using image quality assessment metrics called peak signal to noise ratio, structural similarity (SSIM) index and region of index SSIM. The experimental results show the proposed algorithm can perform significantly better in terms of noise reduction by using image quality assessment algorithms ***, ROI-SSIM. © 2013 Springer-Verlag.

关键词： Impulse noise

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