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ICoMPAC 2020 - Preface for conference Proceedings

引用

Journal of Physics: conference Series 2021年第1期1821卷

作者： Soleha, S. Si Institut Teknologi Sepuluh Nopember Indonesia

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6th international conference on Business Intelligence, CBI 2021

6th International Conference on Business Intelligence, CBI 2...

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6th international conference on Business Intelligence, CBI 2021

ISBN: (纸本)9783030765071

the proceedings contain 33 papers. the special focus in this conference is on Business Intelligence. the topics include: Brain Cancer Ontology Construction;semantic Web for Sharing Medical Resources;construction of Glaucoma Disease Ontology;analyzing Moroccan Tweets to Extract Sentiments Related to the Coronavirus Pandemic: A New Classification Approach;creation of a Callbot Module for Automatic Processing of a Customer Service Calls;applied CNN for Automatic Diabetic Retinopathy Assessment Using Fundus Images;RFID Based Security and Automatic Parking Access Control System;towards a Support System for Brainstorming Based Content-Based Information Extraction and Machine Learning;classification of Documents Using Machine Learning and Genetic algorithms;toward Student Classification in Educational Video Courses Using Knowledge Tracing;Assessment of Lifestyle and Mental Health: Case Study of the FST Beni Mellal;the Search for Digital Information by Evaluating Four Models;overview of the Main Recommendation Approaches for the Scientific Articles;preface;Part-of-Speech Tagging Using Long Short Term Memory (LSTM): Amazigh Text Written in Tifinaghe Characters;online Students’ Classification Based on the Formal Concepts Analysis and Multiple Choice Questions;How BERT’s Dropout Fine-Tuning Affects Text Classification?;selection of Composite Web Services Based on QoS;A MapReduce Improved ID3 Decision Tree for Classifying Twitter Data;clustering Techniques for Big Data Mining;data Mining Approach for Intrusion Detection;markov Decision Processes with Discounted Rewards: New Action Elimination Procedure;learning Management System Comparison: New Approach Using Multi-Criteria Decision Making;finding Agreements: Study and Evaluation of Heuristic Approaches to Multilateral Negotiation;contribution to Arabic Text Classification Using Machine Learning Techniques.

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Emotion-Based Media Recommendation System

Emotion-Based Media Recommendation System

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Cybernetics, Cognition and Machine Learning Applications (ICCCMLA), IEEE international conference on

作者： Sayon Chakraborty Shubham Shreya Singh Mandeep Kaur Nitin Rakesh Monali Gulhane Department of Computer Science & Engineering SET Sharda University India Department of CSE Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune Nagpur India

ISBN: (数字)9798331505790

ISBN: (纸本)9798331505806

Emotion is a state of physical arousal that is subjective and private to the individual. Human emotions are divided into fear, anger, surprise, sadness, happiness, etc. this emotional umbrella encompasses a wide range of other emotions, including joy and contempt; they are subtle emotions. When it comes to recognizing emotions and present mental states, facial expressions are crucial (i.e., emotional and spiritual). Detecting these emotions can be difficult at times, as even minor variances might result in distinct displays. To detect emotions and produce good results, neural networks and machine learning were applied. Machine learning algorithms have proven to be very useful in pattern recognition and classification and thus can also be used for mood detection. With the development of digital music technology, it is also necessary to develop a personalized music recommendation system to recommend music to users. Emotions are an essential part of the human psyche. It has many different types, and the main purpose of our proposed system is to distinguish them. For this, our proposed system is based on the proposed structure of video content that is related to human emotions. Recommendation system based on user logs or history. the recommendation technique we use is not fully personalized nor is it considered a point of user content. therefore, the solution to this problem is to recommend personalized content based on emotional characteristics. According to letter of our proposed system, taking into account aspects such as age, gender and emotional characteristics, our main motivation is to control the problem of accuracy in applications running. Our proposed emotion-based media recommendation system is a novel and innovative approach that has the potential to revolutionize the way we interact with digital media.

关键词： Emotion recognition Portable computers Webcams Face recognition Personal voice assistants Nose Machine learning Media Feature extraction Recommender systems

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4th international conference on algorithms and discrete applied mathematics, CALDAM 2018

4th International Conference on Algorithms and Discrete Appl...

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4th international conference on algorithms and discrete applied mathematics, CALDAM 2018

ISBN: (纸本)9783319741796

the proceedings contain 24 papers. the special focus in this conference is on algorithms and discrete applied mathematics. the topics include: Consistent subset problem with two labels;the edge geodetic number of product graphs;burning spiders;drawing graphs on few circles and few spheres;on a lower bound for the eccentric connectivity index of graphs;on the tractability of (k,i)-coloring;window queries for problems on intersecting objects and maximal points;bounded stub resolution for some maximal 1-planar graphs;on structural parameterizations of firefighting;mixed unit interval bigraphs;on the simultaneous minimum spanning trees problem;variations of cops and robbers game on grids;alternation, sparsity and sensitivity: Combinatorial bounds and exponential gaps;on oriented l(p,1)-labeling;radius, diameter, incenter, circumcenter, width and minimum enclosing cylinder for some polyhedral distance functions;hamiltonian path in K1,t-free Split Graphs- A dichotomy;a fully polynomial time approximation scheme for refutations in weighted difference constraint systems;probabilistic properties of highly connected random geometric graphs;on indicated coloring of some classes of graphs;line segment disk cover;fixed-parameter tractable algorithms for tracking set problems;Exact computation of the number of accepting paths of an NTM.

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An outperforming hybrid discrete particle swarm optimization for solving the timetabling problem 12

An outperforming hybrid discrete particle swarm optimization...

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12th international conference on Knowledge and Smart Technology, KST 2020

作者： Unprasertporn, thanawat Lohpetch, Dome Faculty of Applied Science King Mongkut's University of Technology North Bangkok Department of Mathematics Bangkok Thailand

ISBN: (纸本)9781728144665

there are various categories of the timetabling problem, and one of them that is quite interesting is the post enrolment based course timetabling problem (PECTP). the PETCP is classified as an NP-complete and a combinatorial optimization problem, which is well known that no algorithm to solve it by spending time in the degree of the polynomial due to its complexity. Furthermore, the solution of the problem is an optimal timetable that has to satisfy all hard constraints and soft constraints as much as possible reflecting its quality. In this paper, we have developed a Hybrid Genetic-based discrete Particle Swarm Optimization algorithm hybridizing with two different local search algorithms including Local Search and Tabu Search (HGDPSOLTS) to improve the performance of searching solution by using the advantage of their exploitation abilities. In addition, we also have improved the representation of a solution to reduce complexity in computation, resulting in improving performance for solving the discrete function the proposed hybrid approach was tested on a standard benchmark problem in comparison with other approaches from the literature and the experimental results indicated that the proposed hybrid approach was able to find effective solutions for solving the PECTP, and it can outperform all algorithms from the literature. © 2020 IEEE.

关键词： Tabu search

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the forecast of household power load based on genetic algorithm optimizing BP neural network 6

The forecast of household power load based on genetic algori...

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2021 6th international Symposium on Advances in Electrical, Electronics and Computer Engineering, ISAEECE 2021

作者： Liu, Hengchao School of International Education North China Electric Power University Baoding Hebei071003 China

In view of the fact that power load forecasting is increasingly becoming an important part of power system planning and power dispatching, this paper proposed a forecasting method based on genetic algorithm optimizing BP neural network and applied it to household power load forecasting. First of all, the original data were pre-processed by factor analysis to eliminate the correlation between variables, and then the household load from January 1st to March 22nd was predicted by using BP and GA-BP models respectively. the author obtained the predicted results in the next 5 days summing to 120 hours and utilized MAPE and RMSE to compare their prediction errors quantitatively. the predicted results of the calculation example are in good agreement with actual values. therefore it is demonstrated that the BP neural network optimized by genetic algorithm has better forecasting effects, which can provide reference for residential and municipal short-term load forecasting. © Published under licence by IOP Publishing Ltd.

关键词： Genetic algorithms

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Machine Learning in Classification of the Wax Structure of Breathing Openings on Leaves Affected by Air Pollution 15th

Machine Learning in Classification of the Wax Structure of B...

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15th international conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020

作者： Procházka, Aleš Mudrová, Martina Cejnar, Pavel Mareš, Jan University of Chemistry and Technology Prague 6166 28 Czech Republic Czech Technical University Prague 6160 00 Czech Republic

ISBN: (纸本)9783030578015

Texture analysis and classification of image components belong to common problems of the interdisciplinary area of digital signal and image processing. the paper is devoted to the pattern matrix construction using features evaluated by the discrete Fourier transform (DFT) or the discrete wavelet transform (DWT) using the relative power in selected frequency bands or scale levels, respectively. Image features are then used to recognize groups of similar pattern vectors by self-organizing neural networks forming a mathematical tool for cluster analysis. Further classification methods including the decision tree, support vector machine, nearest neighbour method and neural networks are then applied for construction of specific models and evaluation of their accuracy and cross validation errors. the proposed algorithm is applied for analysis of given microscopic images representing wax structures covering breathing openings on leaves affected by environmental pollution in different locations. the classification accuracy depends upon the method used and it is higher than 92% for all experiments. © 2021, the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Support vector machines

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Murmur Detection in PCG signals using DWT Entropy and Feature Clustering 6

Murmur Detection in PCG signals using DWT Entropy and Featur...

引用

6th IEEE international conference on Electronics, Computing and Communication Technologies, CONECCT 2020

作者： Varshney, Shivam Singh, Satyendra Institute of Engineering and Technology Department of Electrical Engineering Lucknow U.P. India

ISBN: (纸本)9781728168289

Phonocardiogram (PCG) signals, their feature extraction and segmentation to diagnose several heart disorders and developing detection models is the primary area of research. Multiple challenges are associated with the recording and preprocessing of these data due to inherent environmental noise and subject wise variation in heart sound. In this work two different approaches based on Fast Fourier Transform (FFT) and discrete Wavelet Transform (DWT) is proposed and algorithms are developed to classify the normal subjects and the subjects having PCG signal with high level of murmur due to heart disorders. the results are finally processed through cluster-based analysis of the DWT components entropy value to discriminate the normal subjects and murmur inhibited PCG data. © 2020 IEEE.

关键词： discrete wavelet transforms

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Teaching of discrete mathematics using the dynamic learning environment 4

Teaching of discrete mathematics using the dynamic learning ...

引用

4th international conference on Informatization of Education and E-Learning Methodology: Digital Technologies in Education, IEELM-DTE 2020

作者： Mozhey, Natalya Belarusian State University of Informatics and Radioelectronics P. Brovki Street 6 Minsk220013 Belarus

In the paper describes the use of the distance learning system based on a modular object-oriented dynamic learning environment for teaching of discrete mathematics, discusses the advantages and disadvantages of this system. the methodological features of teaching technical specialties students to the main sections of discrete mathematics (elements of combinatorics, theory of sets and relations, elements of modern abstract algebra, graph theory, classical concepts of the theory of Boolean functions, as well as the foundations of the theory of formal languages) are considered. Examples of applications of discrete mathematics in the analysis of the computer algorithms effectiveness, working with expert systems, solving routing problems, classifying ordered data and searching in them, checking the correctness of algorithms, creating functional diagrams, etc. are given. the work can be useful to teachers, both reading a course in discrete mathematics and introducing modern technologies of distance learning into the educational process. Copyright © 2020 for this paper by its authors.

关键词： Formal languages

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Performance Analysis of Supervised Learning algorithms based on Classification Approach 6

Performance Analysis of Supervised Learning Algorithms based...

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6th IEEE international conference on Engineering, Technologies and applied Sciences, ICETAS 2019

作者： Khan, Fazeel Ahmed Ibrahim, Adamu Abubakar Rais, Mohammad Salman Rajpoot, Priyanka Khan, Ambareen Akhtar, Mohammad Nishat International Islamic University Malaysia Department of Computer Science Selangor Malaysia International Islamic University Malaysia Department of Mechatronics Engineering Selangor Malaysia School of Electrical and Electronics Engineering Universiti Sains Malaysia Penang Malaysia School of Aerospace Engineering Universiti Sains Malaysia Penang Malaysia

ISBN: (纸本)9781728140827

Machine learning algorithm integrates with various features and methods for learning. the performance metric has a major role in determining the capacity and ability of any machine learning algorithm. the supervised approach supports learning based on predefined parameters. the classification approach classifies the set of data with labels for training and evaluation purposes. this paper applies method of supervised learning algorithm based on classification approach to analyzed in terms of performance metrics. Some algorithms were applied in the experiment process to determine the clear outcome from them. the analysis gives an outcome based on certain parameters to obtain the results to understand the ability of these algorithm and their implementation in any potential use-cases. © 2019 IEEE.

关键词： Support vector machines

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