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AAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference

作者： Manaris, Bill Roos, Patrick Machado, Penousal Krehbiel, Dwight Pellicoro, Luca Romero, Juan Computer Science Department College of Charleston 66 George Street Charleston SC 29424 United States CISUC Department of Informatics Engineering University of Coimbra 3030 Coimbra Portugal Psychology Department Bethel College North Newton KS 67117 United States RNASA Lab. Creative Computer Group University of Coruña Spain

ISBN: (纸本)1577353234

We present a corpus-based hybrid approach to music analysis and composition, which incorporates statistical, connectionist, and evolutionary components. Our framework employs artificial music critics, which may be trained on large music corpora, and then pass aesthetic judgment on music artifacts. Music artifacts are generated by an evolutionary music composer, which utilizes music critics as fitness functions. To evaluate this approach we conducted three experiments. First, using music features based on Zipf's law, we trained artificial neural networks to predict the popularity of 992 musical pieces with 87.85% accuracy. Then, assuming that popularity correlates with aesthetics, we incorporated such neural networks into a genetic-programming system, called NEvMuse. NEvMuse autonomously "composed" novel variations of J.S. Bach's Invention #13 in A minor (BWV 784), variations which many listeners found to be aesthetically pleasing. Finally, we compared aesthetic judgments from an artificial music critic with emotional responses from 23 human subjects. Significant correlations were found. We provide evaluation results and samples of generated music. These results have implications for music information retrieval and computer-aided music composition. Copyright © 2007, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： computer music

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Implementation of Naïve Bayes Classification Algorithm on Infant and Toddler Nutritional Status

Implementation of Naïve Bayes Classification Algorithm on I...

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International Conference of computer and informatics engineering (IC2IE)

作者： Euis Oktavianti Ade Rahma Yuly Fitria Nugrahani G.A Siwabessy Department of Computer and Informatics Engineering Politeknik Negeri Jakarta Kampus UI Depok Indonesia

Body weight and length are often used as a reference index in classifying the nutritional status of infants and toddlers. In Posyandu Anggrek in Limo, Depok, Indonesia, the anthropometric index calculation used is still manual, using the z-score list or WHO NCHS standard deviation found in KMS (Healthy Cards for Toddlers). Nutritional status is only seen based on the colors in the KMS without calculation or looking at the index in the anthropometric table. Naïve Bayes, one of the methods used in classifying by calculating probability data, will be used in this study to measure the nutritional status of infants and children. The variables used in evaluating the nutritional status of infants and toddlers are data about body weight and body length. Based on the results of research and discussions conducted, 46 data about infants and toddlers are divided into 90% testing data and 10% training data by type of sampling using stratified sampling at RapidMiner. Based on the data obtained, the accuracy of Naïve Bayes in classifying the nutritional status of infants and toddlers up to 75%.

关键词： Pediatrics Data mining Classification algorithms Indexes informatics Anthropometry Standards

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Statistical delay calculation with vector synthesis model

Statistical delay calculation with vector synthesis model

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： T. Fujita H. Onodera Department of Communications and Computer Engineering Graduate School of Informatics Kyoto University Kyoto Japan

A statistical delay model for CMOS digital circuits called the "vector synthesis model" is proposed. The model provides a relationship between process random variables and a digital circuit path delay. A first order coefficient vector (FOCV), which characterizes the drain current of a transistor, is introduced as a characteristic parameter of the cell delay. The circuit path delay is modeled by synthesizing a FOCV of the path using the FOCVs of the cells constituting the path. The simple structure of the vector synthesis model enables the reduction of simulation cost for a statistical analysis. The accuracy of the vector synthesis model has been verified experimentally. The deviation of the worst case delay from the result by SPICE Monte Carlo analysis is around 5%, whereas that of an usual corner (slow-slow and fast-fast) analysis is as high as 25%.

关键词： Delay Circuit synthesis Semiconductor device modeling Digital circuits CMOS digital integrated circuits Random variables Analytical models Circuit simulation Costs Statistical analysis

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Increasing accuracy of classification physical activity based on smartphone using ensemble logistic regression with boosting method 3

Increasing accuracy of classification physical activity base...

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3rd International Conference on Science, ICOS 2019

作者： Lawi, A. Aziz, F. Wungo, S.L. Department of Computer Science Universitas Hasanuddin Makassar90245 Indonesia Faculty of Mathematics and Natural Sciences Universitas Pancasakti Makassar90132 Indonesia Program Study Informatics Engineering STMIK Kreatindo Monokwari98300 Indonesia

At present, the smartphone is equipped with several sensors such as Accelerometer, Gravity sensor, and Gyroscope which can be used to recognize human physical activities such as walking upstair and walking downstairs etc. Machine learning is needed to group data and get information. Statistical methods have poor performance in classifying because procedures must be met. To overcome this, an ensemble technique was used. This study proposes the application of the gradientboost ensemble method to classify walking upstair and walking downstairs. The *** system is designed for data retrieval using a smartphone. Then, the dataset will be partitioned into 70% training data and 30% test data. The results show that the performance of the ensemble boosting method produces 81.82% accuracy, 86.11% sensitivity and 77.50% specificity. © Published under licence by IOP Publishing Ltd.

关键词： Smartphones

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Generating robotic elliptical excisions with human-like tool-tissue interactions

Generating robotic elliptical excisions with human-like tool...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Artūras Straižys Michael Burke Subramanian Ramamoorthy School of Informatics University of Edinburgh Department of Electrical and Computer Systems Engineering Monash University

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In surgery, the application of appropriate force levels is critical for the success and safety of a given procedure. While many studies are focused on measuring in situ forces, little attention has been devoted to relating these observed forces to surgical techniques. Answering questions like "Can certain changes to a surgical technique result in lower forces and increased safety margins?" could lead to improved surgical practice, and importantly, patient outcomes. However, such studies would require a large number of trials and professional surgeons, which is generally impractical to arrange. Instead, we show how robots can learn several variations of a surgical technique from a smaller number of surgical demonstrations and interpolate learnt behaviour via a parameterised skill model. This enables a large number of trials to be performed by a robotic system and the analysis of surgical techniques and their downstream effects on tissue. Here, we introduce a parameterised model of the elliptical excision skill and apply a Bayesian optimisation scheme to optimise the excision behaviour with respect to expert ratings, as well as individual characteristics of excision forces. Results show that the proposed framework can successfully align the generated robot behaviour with subjects across varying levels of proficiency in terms of excision forces.

关键词： Force measurement Force Surgery Safety Bayes methods Robots Optimization

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A Comprehensive Framework for Cold Start Problem in Hybrid Recommendation Systems Extending the Efficient Multi-Mode Approach

A Comprehensive Framework for Cold Start Problem in Hybrid R...

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International computer Science and engineering Conference (ICSEC)

作者： Tessy Badriyah Yunaz Gilang Ramadhan Iwan Syarif Informatics and Computer Engineering Department Politeknik Elektronika Negeri Surabaya (PENS) Surabaya INDONESIA

E-Commerce is a prominent application of information technology in business, offering convenience in transactions. However, as more products and users join the platform, the complexity of E-Commerce systems increases. This necessitates the implementation of a recommendation system to enhance the user experience and address individual preferences. E-Commerce platforms often face the challenge of the cold start problem, where new products are introduced to the platform or when there is limited information available about new users. In such cases, traditional recommendation systems struggle to provide accurate recommendations due to the lack of historical data or user preferences. In this research, a comprehensive framework for an efficient multi-mode Hybrid Recommendation System is proposed, focusing on addressing the cold start problem. The system leverages user behavior tracking, specifically search history and product visit history, to capture user preferences effectively. Through experimental evaluation, the system demonstrates its adaptability to different dataset conditions, achieving a high precision rate of 90%. This research addresses the challenges of data sparsity and the cold start problem in recommendation systems, particularly in the E-Commerce context. The flexibility of the recommendation system ensures optimal recommendations in various scenarios, with potential applications beyond E-Commerce.

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Verifying Shortest Paths in Linear Time

arXiv

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arXiv 2024年

作者： Shokry, Ahmed Elmasry, Amr Khalafallah, Ayman Aly, Amr Computer and Systems Engineering Department Alexandria University Egypt Egypt University of Informatics Egypt

In this paper we propose a linear-time certifying algorithm for the single-source shortest-path problem capable of verifying graphs with positive, negative, and zero arc weights. Previously proposed linear-time approa... 详细信息

关键词： Graph algorithms

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A Web-based ITS controlled by a hybrid expert system

A Web-based ITS controlled by a hybrid expert system

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International Conference on Advanced Learning Technologies (ICALT)

作者： J. Prentzas I. Hatzilygeroudis C. Koutsojannis School of Engineering Department of Computer Engin. & Informatics University of Patras Patras Greece

The authors present the architecture of a Web-based intelligent tutoring system (ITS) for teaching high school teachers how to use new technologies. It offers course units covering the needs of users with different knowledge levels and characteristics. It tailors the presentation of the educational material to the users' diverse needs by using AI techniques to specify each user's model as well as to make pedagogical decisions. This is achieved via an expert system that uses a hybrid knowledge representation formalism integrating symbolic rules with neurocomputing.

关键词： Control systems Expert systems Education Educational institutions Knowledge representation Internet User interfaces informatics computer architecture Intelligent systems

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Training Artificial Neural Networks by Coordinate Search Algorithm

Training Artificial Neural Networks by Coordinate Search Alg...

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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Rokhsatyazdi, Ehsan Rahnamayan, Shahryar Miyandoab, Sevil Zanjani Bidgoli, Azam Asilian Tizhoosh, H.R. Lab Ontario Tech University Department of Electrical Computer and Software Engineering OshawaON Canada Brock University Department of Engineering St. CatharinesON Canada Wilfrid Laurier University Faculty of Science WaterlooON Canada Rhazes Lab Mayo Clinic Department of Artificial Intelligence and Informatics RochesterMN United States

ISBN: (纸本)9781665430654

Training Artificial Neural Networks (ANNs) poses a challenging and critical problem in machine learning. Despite the effectiveness of gradient-based learning methods, such as Stochastic Gradient Descent (SGD), in training neural networks, they do have several limitations. For instance, they require differentiable activation functions, and cannot optimize a model based on several independent non-differentiable loss functions simultaneously;for example, the F1-score, which is used during testing, can be used during training when a gradient-free optimization algorithm is utilized. Furthermore, the training (i.e., optimization of weights) in any DNN can be possible with a small size of the training dataset. To address these concerns, we propose an efficient version of the gradient-free Coordinate Search (CS) algorithm, an instance of General Pattern Search (GPS) methods, for training (i.e., optimizing) neural networks. The proposed algorithm can be used with non-differentiable activation functions and tailored to multi-objective/multi-loss problems. Finding the optimal values for weights of ANNs is a large-scale optimization problem. Therefore instead of finding the optimal value for each variable, which is the common technique in classical CS, we accelerate optimization and convergence by bundling the variables (i.e., weights). In fact, this strategy is a form of dimension reduction for optimization problems. Based on the experimental results, the proposed method is comparable with the SGD algorithm, and in some cases, it outperforms the gradient-based approach. Particularly, in situations with insufficient labeled training data, the proposed CS method performs better. The performance plots demonstrate a high convergence rate, highlighting the capability of our suggested method to find a reasonable solution with fewer function calls. As of now, the only practical and efficient way of training ANNs with hundreds of thousands of weights is gradient-based algorithms such

关键词： Artificial Neural Network (ANN) Coordinate Search Expensive Optimization Gradient-free Large-Scale Optimization Stochastic Gradient Descent (SGD)

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Performance evaluation of the frequency-domain DORT imaging method with UWB radar for a finite-sized target

Performance evaluation of the frequency-domain DORT imaging ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Takuya Sakamoto Toru Sato Department of Communications and Computer Engineering Graduate School of Informatics Kyoto University Kyoto Japan

Ultra wide-band (UWB) radar imaging systems are a promising field of research as they cover a variety of applications. Among all UWB radar imaging methods, the time-reversal (TR) method enables high-resolution imaging in a multi path environment. Conventional TR methods have been applied to antenna array systems while our previous work proposed a type of TR method, namely the frequency-domain Decomposition de Operateur de Retournement Temporel (DORT) method, designed for a low-cost single antenna based system. Because the frequency-domain DORT method was developed assuming a point-like target, the performance of the method for a finite-sized target is unknown. In this study, we investigate numerically the performance of the frequency-domain DORT method by applying it to finite sized targets and evaluating the quality of the resultant images.

关键词： Frequency domain analysis Imaging Radar imaging Ultra wideband radar Scattering Antennas

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