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Deep Learning Aided Emotion Recognition from Music 1

Deep Learning Aided Emotion Recognition from Music

引用

1st IEEE international conference on Automation, Computing and Renewable systems, ICACRS 2022

作者： Raja Subramanian, R. Ram, Kokkirala Aditya Sai, Dola Lokesh Venkatesh Reddy, K. Chowdary, Kondeti Akarsh Reddy, Kundu Dheeraj Datta Department of Computer Science and Engineering Kalasalingam Academy of Reasearch and Education Tamil Nadu Virudhunagar India

ISBN: (纸本)9781665460842

Emotion identification by audio signal is a contemporary study area in Human computer Interaction domain. The desire for improving the communication interface between people and digital media has increased. The emotion of the song is detected through music. Music is a great medium for conveying emotion. The practice of determining emotions from music snippets is known as music emotion recognition. Audio dataset is collected from the Kaggle. Researchers are now increasingly concerned towards increasing the precision of emotion recognition techniques. However, a complete system that can discern emotions from speech is not yet developed. This research work has suggested a novel emotion recognition technique, where the neural networks are trained to identify emotions based on the retrieved information. The performance of neural networks is then compared to the performance of baseline machine learning classification algorithms. The obtained results show that MFCC characteristics combined with deep RNN perform better for instrument emotion identification. The results also reveal that MFCC features paired with a deep neural network outperform other emotion recognition methods. It also shows that the class has a major influence on the mood evoked by music. To make human-computer interaction more natural, the computer should be able to perceive different emotional states. The voice of a person is very essential in assessing individuals. The emotion of the individual is detected through the person's speech. These audio types are further classified as joyful, sad, neutral, or fearful. © 2022 IEEE

关键词： Emotion Recognition

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Evolutionary neuro-fuzzy system for protein secondary structure prediction

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

作者： Krishnaji, Andey Appa Rao, Allam Dept. of Computer Applications Swarnandhra College of Engineering and Technology Narasapur Andhra Pradesh 534 280 India JNTUK CRRao Advanced Institute for Mathematics Statistics and Computer Science University of Hyderabad Campus Gachibowli Hyderabad 500 046 India

ISBN: (纸本)9783642353130

Protein secondary structure prediction is an essential step for the understanding of both the mechanisms of folding and the biological function of proteins. Experimental evidences show that the native conformation of a protein is coded within its primary structure. This work investigates the benefits of combining genetic algorithms, fuzzy logic, and neural networks into a hybrid Evolutionary Neuro-Fuzzy System, especially for predicting a protein's secondary structure directly from its primary structure. The proposed system will include more biological information such as protein structural class, solvent accessibility, hydrophobicity and physicochemical properties of amino acid residues to improve accuracy of protein secondary structure prediction. The proposed system will experiment on three-class secondary structure prediction of proteins, that is, alpha helix, beta sheet or coil. The experimental results indicate that the proposed method has the advantages of high precision, good generalization, and comprehensibility. The method also exhibits the property of rapid convergence in fuzzy rule generation. © 2013 Springer-Verlag.

关键词： Proteins

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Medical Data Engineering – theory and practice 10th

Medical Data Engineering – Theory and Practice

引用

10th international conference on New Trends in Model and Data Engineering, MEDI 2021 held with 4th international Workshop on Modeling, Verification and Testing of Dependable Critical systems, DETECT 2021, Symposium on Intelligent and Autonomous systems, SIAS 2021, 1st Workshop on Control Software: Methods, Models, and Languages, CSMML 2021, Workshop on Blockchain for Inter-Organizational Collaboration, BIOC 2021 and 1st international Health Data Workshop, HEDA 2021

作者： Kock-Schoppenhauer, Ann-Kristin Schreiweis, Björn Ulrich, Hannes Reimer, Niklas Wiedekopf, Joshua Kinast, Benjamin Busch, Hauke Bergh, Björn Ingenerf, Josef IT Center of Clinical Research Universität zu Lübeck Lübeck23562 Germany Institute for Medical Informatics and Statistics Kiel University and University Hospital Schleswig-Holstein Kiel24114 Germany Lübeck Institute of Experimental Dermatology Universität zu Lübeck and University Hospital Schleswig-Holstein Lübeck23562 Germany Institute of Medical Informatics Universität zu Lübeck Lübeck23562 Germany

ISBN: (纸本)9783030876562

Data integration and exchange are becoming more crucial with the increasing amount of distributed systems and ever-growing amounts of data. This need is also widely known in medical research and not yet comprehensively solved. Practical implementation steps will demonstrate the different challenges in the context of the National Medical Informatics Initiative in Germany. Top-down versus bottom-up approaches as general methods of standard-based data integration in healthcare will be discussed and illustrated in the process of building up Medical Data Integration Centers. As practical examples, the use cases Infection Control, Cardiology, and Molecular Tumor Board, will be presented. Finally, limitations that prevent the use of theoretically recommended data integration methods in the particular field of medical informatics are illustrated. © 2021, Springer Nature Switzerland AG.

关键词： Data integration

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Applications and Advancements of Firefly Algorithm in Classification: An Analytical Perspective 1st

Applications and Advancements of Firefly Algorithm in Classi...

引用

1st international conference on Computational Intelligence in Pattern Recognition, CIPR 2019

作者： Nayak, Janmenjoy Vakula, Kanithi Dinesh, Paidi Naik, Bighnaraj Department of Computer Science and Engineering Sri Sivani College of Engineering SrikakulamAndhra Pradesh532410 India Department of Computer Applications Veer Surendra Sai University of Technology Burla SambalpurOdisha768018 India

ISBN: (纸本)9789811390418

Nature-inspired algorithms, particularly those located on swarm intelligence and population-based, have dragged much attention in the last few years. Firefly algorithm is one of the leading swarm-based algorithms, which came into view about 10 years ago. It has become progressively an essential appliance of swarm intelligence that has been enforced in many vicinities of optimization along with the engineering practice. Abundant difficulties from distinctive regions have been solved effectively by using firefly algorithm and its development. In this paper, we conducted a brief study on the applications and advancements of firefly algorithm in the area of data classification. Various classification areas, such as image classification, text classification, neural network-based classification and some other classifications, are taken into consideration for this study. Special attention has been paid toward the usage level and implementation issues of firefly algorithm in different classification domains. The main aim of this survey is to inspire researchers toward further research of firefly algorithm in several other application areas other than the intended area. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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Service Provider Information System in Technopreneurship Learning for MSMEs 1

Service Provider Information System in Technopreneurship Lea...

引用

1st Paris Van Java international Seminar on computer, Science, Engineering, and Technology, PVJ ISComSET 2020

作者： Hasanudin, Muhaimin Yuliana, Khozin Roihan, Ahmad Arribathi, Abdul Hamid Haris Information System Department Raharja University Tangerang Indonesia Computer Systems Department Raharja University Tangerang Indonesia

This study aims to involve students in Technopreneurship courses by utilizing the emarketplace as a marketing, sales and service medium for Micro, Small and Medium Enterprises (MSMEs). Where previously the lecture material was given in class in theory, amended by giving field practice assignments in collaboration with material entrepreneurs and building service providers as MSMEs in the City of Tangerang. Based on the results of research that the application of information technology, especially e-marketplaces in learning Technopreneurship has a real impact on the ability and level of understanding of students about Technopreneurship courses, students gain experience and insight about Technopreneurship, can design and test prototypes of service provider information systems (SijasPro) eMarketplace, students directly involved in helping solve the problems of business people, especially in the field of promotion and sales to customers. siJaspro is able to produce promotional media that can be used directly by business people. students are expected to have insight to foster entrepreneurial spirit among students, this is one of the new breakthrough strategies to anticipate the problem of increasing intellectual unemployment. © Published under licence by IOP Publishing Ltd.

关键词： students

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MU-CSeq 0.3 Sequentialization by read-implicit and coarse-grained memory unwindings (competition contribution) 21

MU-CSeq 0.3 Sequentialization by read-implicit and coarse-gr...

引用

21st international conference on Tools and algorithms for the Construction and Analysis of systems, TACAS 2015 held as part of the European Joint conferences on theory and practice of Software, ETAPS 2015

作者： Tomasco, Ermenegildo Inverso, Omar Fischer, Bernd La Torre, Salvatore Parlato, Gennaro Electronics and Computer Science University of Southampton United Kingdom Division of Computer Science Stellenbosch University South Africa Dipartimento di Informatica Universita di Salerno Italy

ISBN: (纸本)9783662466803

We describe a new CSeq module that implements improved algorithms for the verification of multi-threaded C programs with dynamic thread creation. It is based on sequentializing the programs according to a guessed sequence of write operations in the shared memory (memory unwinding, MU). The original algorithm (implemented in MU-CSeq 0.1) stores the values of all shared variables for each write (read-explicit fine-grained MU), which requires multiple copies of the shared variables. Our new algorithms store only the writes (readimplicit MU) or only a subset of the writes (coarse-grained MU), which reduces the memory footprint of the unwinding and so allows larger unwinding bounds. © Springer-Verlag Berlin Heidelberg 201.

关键词： C (programming language)

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Automata for modeling the distributed probabilistic reversible processes 1

引用

1st international conference on Applied algorithms, ICAA 2014

作者： Arpit Shafie, Afza Wan Ahmad, Wan Fatimah Computer and Information Sciences Department Universiti Teknologi PETRONAS Bandar Seri Iskandar Tronoh Perak31750 Malaysia Fundamental and Applied Sciences Department Universiti Teknologi PETRONAS Bandar Seri Iskandar Tronoh Perak31750 Malaysia

ISBN: (纸本)9783319041254

This paper presents the construction of an automaton termed the Concurrent Probabilistic Reversible Automata (CPRA). It models the distributed systems which exhibit probabilistic behaviour and also relies on backtracking as the basis to make a system fault tolerant. Here, the basic concepts of non-probabilistic automata have been extended by introducing the discrete probabilities on the set of transitions for modelling the probabilistic nature of computing environment. In addition, concurrency has been implemented by defining parallel joint(ˆ) operator dealing with the odds of shared transitions. A memory structure has also been defined to keep track of past transitions in order to facilitate the backtracking without losing the initial computations, which may result in inconsistent states as well. The major contribution of this work can be seen in three aspects: first, defining an automaton to model full non-determinism along with probabilistic characterisation without making any distinctions between states and actions by which some of the previous formalism suffers;second, association of memory with the automata that preserves concurrency during backtracking;third, the implementation of the parallel joint operator to facilitate the concurrency. Although, the full probabilistic analysis of CPRA can be performed by applying the principles of measure theory on the traces of CPRA but it is reported as future work. © Springer international Publishing Switzerland 2014.

关键词： Automata theory

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Partial metrics and co-continuous valuations 1st

引用

1st international conference on Foundations of Software Science and Computation structures, FoSSaCS 1998 Held as Part of the Joint European conferences on theory and practice of Software, ETAPS 1998

作者： Bukatin, Michael A. Shorina, Svetlana Yu Department of Computer Science Brandeis University WalthamMA02254 United States Moscow State University Moscow Russia

ISBN: (纸本)3540643001

The existence of deep connections between partial metrics and valuations is well known in domain theory. However, the treatment of non-algebraic continuous Scott domains has been not quite satisfactory so far. In this paper we return to the continuous normalized valuations μ on the systems of open sets and introduce notions of co-continuity ({U i , i I} is a filtered system of open sets ⟹ μ(Int(∩ iI Ui)) = inf iI μ(Ui)) and strong non-degeneracy (U ⊂ V are open sets ⟹ μ(U) x ∩ Cy)) − μ(Ix ∩ Iy), where Cx = {y A ¦ y ⊑ x } and Ix = {y A ¦ {x, y } and lx = {y A ¦ (x, y)is unbounded }. This construction covers important cases based on the real line and allows to obtain an induced metric on Total(A) without the unpleasant restrictions known from earlier work. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Topology

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Alleviating sparsity and scalability issues in collaborative filtering based recommender systems

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

作者： Kumar, Akshi Sharma, Abhilasha Dept. of Computer Engineering Delhi Technological University Delhi India

ISBN: (纸本)9783642353130

Commercial recommender systems in general are used to evaluate very large product sets. In a user - item rating database, though users are very active, there are a few rating of the total number of items available. The user-item matrix is thus extremely sparse. Since a collaborative filtering algorithm is mainly based on similarity measures computed over the co-rated set of items, the large levels of sparsity can lead to less accuracy and can challenge the predictions or recommendations of the collaborative filtering (CF)systems. Further, a CF algorithm is assumed to be efficient if it is able to filter items that are interesting to users. But, they require computations that are very expensive and grow non-linearly with the number of users and items in a database. In general, the whole ratings database is searched in collaborative filtering and thus it suffers from poor scalability when more and more users and items are added into the database. Instigated by these challenges, we investigate two collaborative filtering algorithms, firstly an algorithm based on weighted slope one scheme and item clustering & secondly an algorithm based on item classification & item clustering, which deal with the sparsity and scalability issues simultaneously. Experiments were carried to determine which is better in terms of simplicity and accuracy among the two methods. © 2013 Springer-Verlag.

关键词： Collaborative filtering

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Mathematical Research for Blockchain Economy 1

引用

丛书名： Springer Proceedings in Business and Economics

1000年

作者： Panos Pardalos Ilias Kotsireas Yike Guo William Knottenbelt

ISBN: (数字)9783030371104

ISBN: (纸本)9783030371098;9783030371128

This book presents the best papers from the 1st international conference on Mathematical Research for Blockchain Economy (MARBLE) 2019, held in Santorini, Greece. While most blockchain conferences and forums are dedicated to business applications, product development or Initial Coin Offering (ICO) launches, this conference focused on the mathematics behind blockchain to bridge the gap between practice and theory.;Every year, thousands of blockchain projects are launched and circulated in the market, and there is a tremendous wealth of blockchain applications, from finance to healthcare, education, media, logistics and more. However, due to theoretical and technical barriers, most of these applications are impractical for use in a real-world business context. The papers in this book reveal the challenges and limitations, such as scalability, latency, privacy and security, and showcase solutions and developments to overcome them.

关键词： Financial Engineering Game theory, Economics, Social and Behav. Sciences Math Applications in computer Science Economic theory/Quantitative Economics/Mathematical Methods Business Finance

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