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检索条件"主题词=Software Algorithms"

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Implementation of Single Camera Markerless Facial Motion Capture using Blendshapes

Implementation of Single Camera Markerless Facial Motion Cap...

引用

International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Meghana Rao Somepalli M.D. Sai Charan S Shruthi Suja Palaniswamy Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9781665406116

Facial motion capture is the process of digitizing the facial motion of an actor by locating several facial landmarks of the actor’s face and using the relative coordinates of these landmarks to drive the facial structure of a 3D character in software like Blender. Recent advances have enabled markerless technology to track the desired facial features from frame to frame. In this work, the input from a single front-facing camera is used and the face is located using face detection algorithms. Its output is then used to find the relative coordinates of facial landmarks like lip corners, upper eyelids, and eyebrows etc., using a facial landmark detector. To achieve comparable levels of accuracy without the depth or 3D information that would be captured from a multi-camera setup, morph targets have been used to add constraints to the animation to avoid unnatural positions of the virtual character. The distance between a referential landmark that has minimal movement and the driving landmark determines the influence of the corresponding morph target. To establish an orientation invariant landmark detection, geometric normalization and face size normalization have been deployed.

关键词： Three-dimensional displays Tracking Lips software algorithms Eyelids Cameras software

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Dissecting Strongly Subsuming Second-Order Mutants

Dissecting Strongly Subsuming Second-Order Mutants

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International Conference on software Testing, Verification, and Validation, ICST

作者： João P. Diniz Chu-Pan Wong Christian Kästner Eduardo Figueiredo Federal University of Minas Gerais Brazil Carnegie Mellon University USA

Mutation testing is a fault-based technique commonly used to evaluate the quality of test suites in software systems. It consists of introducing syntactical changes, called mutations, into source code and checking whether the test cases distinguish them. Since there are dozens of distinct mutation types, one of the most challenging problems is the high computational effort required to test the whole test suite against each mutant. Since mutation testing is proposed, researchers have presented techniques aiming at effort reduction in the phases of its process. This study focuses on the potential reduction in the number of mutants provided by a special set of mutants generated by the introduction of two syntactical changes (strongly subsuming second-order mutants). In this work, we exhaustively searched for those second-order mutants Our results show that they (i) are frequently generated by the "expression removal" mutation, (ii) are likely to be killed by the same test cases that kill their constituent mutants, and (iii) have the potential to reduce the number of mutants to be executed by about 22.3%.

关键词： software testing Conferences software algorithms software systems

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Research on Personalized Learning Route Model Based on Improved Collaborative Filtering Algorithm

Research on Personalized Learning Route Model Based on Impro...

引用

Big Data & Artificial Intelligence & software Engineering (ICBASE), International Conference on

作者： Hongbin Wang Zhengang Wei Ocean University of China Qingdao

ISBN: (纸本)9781665427104

In order to solve the contradiction between the free course selection mode and blind course selection, this paper combines the knowledge-based recommendation algorithm model and the memory based collaborative filtering recommendation model, and proposes an improved collaborative filtering recommendation algorithm to mine the implicit learning order and association relationship between courses and provide recommendations for freshmen, This algorithm solves the cold start problem caused by the data sparsity problem of the traditional collaborative filtering recommendation algorithm, so that the algorithm can still give high-quality recommendation results when the initial data is extremely sparse. The experimental results show that compared with the traditional recommendation algorithm, the accuracy and recall of this method have been improved, good recommendation results are obtained on real data sets.

关键词： Collaborative filtering software algorithms Knowledge based systems Filtering algorithms Data models Data mining software engineering

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AutoRoot: A Novel Fault Localization Schema of Multi-dimensional Root Causes

AutoRoot: A Novel Fault Localization Schema of Multi-dimensi...

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IEEE Conference on Wireless Communications and Networking

作者： Pengkun Jing Yanni Han Jiyan Sun Tao Lin Yanjie Hu Chinese Academy of Sciences Institute of Information Engineering Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China

The key challenge for large scale software system maintenance is to minimize the troubleshooting time when severe system anomaly (e.g., server failure, link congestion, software bugs) happens. It often takes hours for operators to manually locate the fault and thus degrades the service performance in terms of user experience and economics. Previous root cause localization algorithms are usually time-consuming and error-prone. In this paper, we present AutoRoot, a fast and accurate multi-dimensional root cause localization algorithm. Specifically, AutoRoot uses an adaptive density clustering to improve the accuracy and an effective filtering mechanism to reduce the search time. Extensive experiments using multiple real data traces validate the performance of AutoRoot compared with existing algorithms.

关键词： Location awareness Filtering software algorithms Clustering algorithms Manuals Maintenance engineering Filtering algorithms

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Methods and algorithms of geometric modeling of fractal structured objects

Methods and algorithms of geometric modeling of fractal stru...

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International Conference on Information Science and Communications Technologies (ICISCT)

作者： Nuraliyev Faxriddin Murodillaevich Anarova Shahzoda Amanbayevna Narzulloyev Oybek Mirzayevich Nabiyev Ilhom Sharifovich Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9781665432597

This article presents methods and algorithms for geometric modeling of objects with fractal structures. Analytical equations of fractal structures were constructed using geometric shapes and their basic concepts. algorithms have been developed using methods of R-function, binomial theorem, and two-dimensional geometric transformation in the 2D plane of computer graphics. The fractal dimension of the fractal based on the Pascal triangle was determined. The expressions obtained on the basis of the developed algorithm are presented in the form of a formula. A software tool was developed based on the algorithms developed using the presented methods. This software tool allows you to automate the interior and exterior decoration, equipment and design of the room in home construction, decorating construction products with patterns, creating patterns of carpets, designing them and choosing the colors and patterns of their products. The results obtained using the software tool are presented graphically.

关键词： Visualization Information science Spirals Shape Image color analysis software algorithms Geometric modeling

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Coupled Dynamic Thermoelasticity Problem for Isotropic Bodies

Coupled Dynamic Thermoelasticity Problem for Isotropic Bodie...

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International Conference on Information Science and Communications Technologies (ICISCT)

作者： U.Z. Djumayozov I.M. Mukhammadiyev A.A. Kayumov R.Z. Makhmudov Samarkand branch of Tashkent University of Information Technologies Samarkand Uzbekistan

ISBN: (纸本)9781665432597

The paper considers a numerical method for solving the one-dimensional and two-dimensional coupled dynamic boundary value problem of thermoelasticity. Discrete equations are compiled by the finite-difference method in the form of explicit and implicit schemes. The solution of the explicit schemes is reduced to the recurrence relations with respect to the components of displacement and temperature. Implicit schemas are solved by iteration.

关键词： Temperature distribution software algorithms Kinematics Thermoelasticity Mathematical models software Numerical models

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Performance Metrices of Different Machine Learning algorithms

Performance Metrices of Different Machine Learning Algorithm...

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Advances in Computing, Communication Control and Networking (ICAC3N), International Conference on

作者： Riya Shatakshi Gupta Vishvashdeep Vinit Kumar CSE GCET Greater Noida India

ISBN: (纸本)9781665438124

E-mail is one of the most significant components or applications of the internet. Without e-mail, the internet would be useless. E-mail is a convenient and speedy method of communication. Email is a common way for people to exchange personal and professional information. Spam emails and non-spam emails are the two forms of emails. The purpose of spam email detection is to distinguish spam from valid e-mail. Spam is typically defined as uninvited or unwelcome email messages. The majority of spam emails contain viruses or other dangerous software that can cause computer and network malfunctions, use network bandwidth and storage space, and cause email servers to slow down. Because of the increase in the abundance of information, spam has become a big issue for internet users in recent years. Email phishing is detected and prevented using text mining techniques. Phishers trick people into providing personal information by sending fake emails and visiting fraudulent websites. Because of the increase in the volume of unwanted emails, there is an urgent need for the development of more dependable and robust email systems. Every day, email users receive hundreds of spam emails with unique content from anonymous addresses generated by robot software agents. This paperwork focusses to compare the accuracy, precision, recall, and F1 of the following algorithms: KNN, SVM. Nave bias and Random forest using emails as input.

关键词： Support vector machines Text mining Machine learning algorithms Unsolicited e-mail Text categorization software algorithms software agents

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Analysis of disconnected neural networks

Analysis of disconnected neural networks

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International Conference on Information Science and Communications Technologies (ICISCT)

作者： Abdimurod Eshmuradov Aybek Khaytbaev Tashkent University of information technologies named after Muhammad Al-Khwarizmi Tashkent city Uzbekistan

ISBN: (纸本)9781665432597

The article made an analysis of disconnected neural networks. The main concepts of neural networks, their characteristics, features, areas of application, the main directions of application of neural networks, the structure of neural networks, the main types of neural networks, existing problems in the field of neural networks are given. The concept of a neural network algorithm is given. The solution of the analysis of disconnected neural networks in the form of basic mathematical expressions is shown. algorithms for searching for the extremum of secondary optimization functionals are shown.

关键词： Training Heuristic algorithms Neural networks software algorithms Routing software Mobile applications

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The Comparison of Some Algorithm Based on Ceemdan

The Comparison of Some Algorithm Based on Ceemdan

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Big Data & Artificial Intelligence & software Engineering (ICBASE), International Conference on

作者： Sijin Wang Yiran Shao Jingwen Qian Shuhan Sun Siyuan Yu School of Computer Science University of Nottingham Ningbo China Ningbo Zhejiang China Affiliated High School of South China Normal University Guangzhou Guangdong China Ningbo Huamao International School Ningbo Zhejiang China Suzhou Foreign Language School Suzhou Jiangsu China Justin-Siena High School Napa Valley California the United States of America

ISBN: (纸本)9781665427104

Stock price prediction is an indispensable part of the investment market and lots of approaches have been proposed. This article implements Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) to decompose the dataset, because the time series data were usually nonlinear and nonstationary. Meanwhile, our algorithms do not have to decide the basic function. In addition, different algorithms are adopted to process different levels of Intrinsic Mode Function (IMF) in order to capture their different characteristics. In that case, a combined algorithm containing CEEMDAN, MLP-BP, LSTM/GRU and Linear Regression is used. The combined algorithm works well on Tesla’s price series from 2010 to 2020, and it can not only process the data with a high accuracy, but also has a short running time because some of the algorithms in the combination are very simple. Then the combined algorithm is adopted on a more representative dataset called S&P 500 index. It turns out it is still very accurate and fast.

关键词： Runtime software algorithms Linear regression Time series analysis Prediction algorithms Market research Indexes

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Tracking and detecting network traffic based on capacity data prediction

Tracking and detecting network traffic based on capacity dat...

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Big Data & Artificial Intelligence & software Engineering (ICBASE), International Conference on

作者： Linwei Huang Guangzhou Huali College Institute of Computer Control Technology Guangzhou China

ISBN: (纸本)9781665427104

In order to improve the traffic tracking and monitoring ability of heterogeneous multi-core data migration network, a network traffic tracking and detection method based on capacity data prediction is proposed to construct a parameter structure model of audio and video data information collection and dynamic caching of heterogeneous multi-core data migration network traffic. Linear regression analysis and heterogeneous reorganization are used to reconstruct the time series of heterogeneous multi-core data migration network traffic, and matched filtering and time series analysis are used. The capacity data clustering model of heterogeneous multi-core data migration network traffic is established, and the spatial spectrum frequency-division feature quantity of heterogeneous multi-core data migration network traffic is extracted. The real-time prediction of heterogeneous multi-core data migration network traffic is realized through the traffic transmission channel equilibrium control method, and the transmission prediction of communication traffic is realized through the traffic feature fusion analysis. The simulation results show that the traffic tracking and detection accuracy of heterogeneous multi-core data migration network is high and the transmission reliability of the system is good.

关键词： Simulation Time series analysis Linear regression software algorithms Telecommunication traffic Streaming media Feature extraction

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