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arXiv 2022年

作者： Froese, Vincent Kunz, Pascal Zschoche, Philipp Technische Universität Berlin Faculty IV Institute of Software Engineering and Theoretical Computer Science Algorithmics and Computational Complexity Germany

We study the network untangling problem introduced by Rozenshtein, Tatti, and Gionis [DMKD 2021], which is a variant of Vertex Cover on temporal graphs-graphs whose edge set changes over discrete time steps. They introduce two problem variants. The goal is to select at most k time intervals for each vertex such that all time-edges are covered and (depending on the problem variant) either the maximum interval length or the total sum of interval lengths is minimized. This problem has data mining applications in finding activity timelines that explain the interactions of entities in complex networks. Both variants of the problem are NP-hard. In this paper, we initiate a multivariate complexity analysis involving the following parameters: number of vertices, lifetime of the temporal graph, number of intervals per vertex, and the interval length bound. For both problem versions, we (almost) completely settle the parameterized complexity for all combinations of those four parameters, thereby delineating the border of fixed-parameter tractability. Copyright © 2022, The Authors. All rights reserved.

关键词： Complex networks

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Study on collaborative filtering recommendation algorithm based on prediction for item rating

Study on collaborative filtering recommendation algorithm ba...

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2020 International Conference on engineering Management of Communication and Technology, EMCTECH 2020

作者： Xiao, Shaozhang Ling, Haonan Lu, Yi Tang, Zhaoxia Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huai'an Jiangsu China

ISBN: (数字)9781728196688

ISBN: (纸本)9781665404488

As the Internet is developing rapidly and people are becoming increasingly dependent on e-commerce, whether the users can be provided with accurate recommendation information has become the key to attracting users. Under this background, corresponding personalized recommendation systems have been proposed, and collaborative filtering algorithm is one of the algorithms commonly used in the recommendation systems. Collaborative filtering recommends the information in which the user is interested through analyzing the preferences of a group with similar interests and common experience. With the increasing number of users and items in the e-commerce system, the collaborative filtering algorithm is limited by data sparsity in operation, which will influence the quality of the recommendation results. This paper studied the collaborative filtering recommendation algorithm based on the prediction for item rating, and enhanced the accuracy of the recommendation algorithm by designing an improved similarity-based algorithm for predicting ratings based on the Pearson correlation coefficient. © 2020 IEEE.

关键词： Collaborative filtering

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EEiF: Efficient Isolated Forest with e Branches for Anomaly Detection

EEiF: Efficient Isolated Forest with e Branches for Anomaly ...

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IEEE International Conference on Data Mining (ICDM)

作者： Yifan Zhang Haolong Xiang Xuyun Zhang Xiaolong Xu Wei Fan Qin Zhang Lianyong Qi School of software Nanjing University of Information Science and Technology China Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services China School of Computing Macquarie University Australia Uffield Department of Women's & Reproductive Health University of Oxford England College of Computer Science and Software Engineering Shenzhen University China Faculty of Science and Engineering University of Petroleum (East China) China

ISBN: (数字)9798331506681

ISBN: (纸本)9798331506698

Anomaly detection is a popular research topic in Artificial Intelligence and has been widely applied in network security, financial fraud detection, and industrial equipment failure detection. Isolation forest based methods are the base algorithms to detect anomalies in these scenarios for their simplicity and efficiency, which has been further exploited with multi-folk trees and learning mechanisms to realize the optimal isolation forest for high detection accuracy. However, the optimal isolation forest is time-consuming with the learning mechanisms, resulting in the task failing of time-constrained applications. Moreover, the original optimal isolation forest fails to construct the optimal tree structure restricted by the time complexity. To address the above challenges, we propose an efficient anomaly detection method called EEIF, which realizes the real e-folk structure of the optimal isolation forest in our practical algorithm design. Specifically, we design a distribution that perfectly matches the e-branch theory to construct the optimal isolation forest. Then, we design an FR clustering scheme to achieve fast training of the isolation forest with learning to hash and provide related proofs of accuracy and efficiency. Besides, a parallel algorithm is integrated into our method to reduce prediction time. Finally, extensive experiments are conducted on a large amount of real-world datasets and the results demonstrate that our method significantly improves efficiency while ensuring effectiveness, compared with the state-of-the-art methods.

关键词： Learning systems Training Accuracy Clustering algorithms Forestry Network security Fraud Time complexity Parallel algorithms Anomaly detection

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Intelligent Gender Recognition System for Classification of Gender in Malaysian Demographic 5th

Intelligent Gender Recognition System for Classification of ...

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5th International Conference on Electrical, Control and computer engineering, InECCE 2019

作者： Chi, Yap Su Kamarulzaman, Syafiq Fauzi Faculty of Computer Systems & Software Engineering University of Malaysia Pahang Kuantan Malaysia

ISBN: (纸本)9789811523168

Identification of a person gender as a man or woman based on the past experiences through features of face such as eyes, mouth, cheek can be obtained through an intelligent gender recognition system. Detection of a person’s gender can be difficult but important for security purposes, especially where safety issues concerning woman in public amenities. The objectives of this research are to identify the techniques for classifying features from man and woman facial images, through which embed as a system and validify using photos within Malaysian demographic. This research is focused on utilizing facial features for gender classification in real time, emphasizing on deep learning-based gender recognition and HAAR Cascade classifier using pre-trained caffe model in OpenCV library. Results show that under Malaysian demographic, probability of 86% accuracy of gender recognition were obtained. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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Named numeric characteristics extraction from text data in Russian 11

Named numeric characteristics extraction from text data in R...

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11th Majorov International Conference on software engineering and computer Systems, MICSECS 2019

作者： Uskov, Ivan Yarkeev, Alexander Tsopa, Evgenij Faculty of Software Engineering and Computer Systems ITMO University Saint Petersburg Russia

The article is focused on the problem of named numeric characteristics extraction from the text data in Russian. This problem have a significant impact to the wide variety of natural language processing tasks such as marketing analysis, statistic tools and data aggregation solutions. There are a lot of existing approaches such as scrappers and parsers, various natural language processing tools (Stanford CoreNLP, spaCy, Natural language toolkit, Apache OpenNLP) and Tomita parser from Yandex that are considered in the article. The structure of the numerical data in Russian has its own specific that have an impact to the algorithms of converting numbers from text form to their value that is also covered in the article. As a result of the research, the new method for extracting numerical data from texts in a natural language was proposed and software module for the proposed method proof was developed. The proposed solution uses semantic networks and semantic frames to determine the boundaries and extract the numerical data from the text. The developed software module was tested on a variety of data sets extracted from the different sources such as Avito and ***. The results of the testing shows the effectiveness of the proposed method in comparision with existing solutions. Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： software testing

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Vertex Cover and Feedback Vertex Set Above and Below Structural Guarantees

arXiv

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arXiv 2022年

作者： Kellerhals, Leon Koana, Tomohiro Kunz, Pascal Technische Universität Berlin Faculty IV Institute of Software Engineering and Theoretical Computer Science Algorithmics and Computational Complexity Germany

Vertex Cover parameterized by the solution size k is the quintessential fixed-parameter tractable problem. FPT algorithms are most interesting when the parameter is small. Several lower bounds on k are well-known, such as the maximum size of a matching. This has led to a line of research on parameterizations of Vertex Cover by the difference of the solution size k and a lower bound. The most prominent cases for such lower bounds for which the problem is FPT are the matching number or the optimal fractional LP solution. We investigate parameterizations by the difference between k and other graph parameters including the feedback vertex number, the degeneracy, cluster deletion number, and treewidth with the goal of finding the border of fixed-parameter tractability for said difference parameterizations. We also consider similar parameterizations of the Feedback Vertex Set problem. Copyright © 2022, The Authors. All rights reserved.

关键词： Parameterization

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Design of Face Recognition Attendance 5

Design of Face Recognition Attendance

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5th IEEE International Conference on Image, Vision and Computing, ICIVC 2020

作者： Lee, Hai-Wu Gu, Wen-Tan Wang, Yuan-Yuan Huaiyin Institute of Technology Faculty of Computer and Software Engineering Huaian City China

ISBN: (纸本)9781728166612

In recent years, face recognition technology has developed rapidly, and its application range has become more and more extensive. It is one of the most important application fields in computer vision technology. However, there are still many technical factors that restrict the application and promotion of face recognition technology. For example: shadows, occlusions, light and dark areas, dark light, highlights and other factors will make the face recognition rate drop sharply. Therefore, face recognition has extremely high research and application value. We use the Local Binary Patterns (LBP) algorithms with histogram equalization to obtain high-resolution images and improve the recognition rate in different scenarios, and try to apply face recognition to attendance. © 2020 IEEE.

关键词： Face recognition

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Multi-Transfer Learning Techniques for Detecting Auditory Brainstem Response

SSRN

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SSRN 2023年

作者： Özyurt, Fatih Majidpour, Jafar Rashid, Tarik A. Majidpour, Amir Koç, Canan Department of Software Engineering Faculty of Engineering Firat University Elazig Turkey Department of Computer Science University of Raparin Rania Iraq Computer Science and Engineering Department University of Kurdistan Hewlêr Erbil Iraq Audiology Department School of Rehabilitation Shahid Beheshti University of Medical Sciences Tehran Iran

Evaluation of peripheral auditory nerve system health in patients with hearing loss by auditory brainstem response (ABR) testing. Audiologists record and evaluate ABRs by manually timing and evaluating the waveforms for quality. Inaccurate assessment of ABR tests may lead to incorrect judgments regarding the integrity of the auditory nerve system;therefore, proper diagnosis and analysis are essential. In order to identify and assess ABR automation while decreasing the possibility of human error, machine learning methods, notably deep learning, may be an appropriate option. To address these issues, this study proposed deep-learning models using the transfer-learning (TL) approach to extract features from ABR testing and diagnose using support vector machines (SVM). Pre-trained convolutional neural network (CNN) architectures like AlexNet, DenseNet, GoogleNet, InceptionResNetV2, InceptionV3, MobileNetV2, NASNetMobile, ResNet18, ResNet50, ResNet101, ShuffleNet, and SqueezeNet are used to extract features from the collected ABR reported images dataset in the proposed model. It has been decided to use six measures accuracy, precision, recall, geometric mean (GM), standard deviation (SD), and area under the ROC curve to measure the effectiveness of the proposed model. According to experimental findings, the ShuffleNet and ResNet50 models' TL is effective for ABR diagnosis using an SVM classifier, with a high accuracy rate of 95% when using the 5-fold cross-validation method. © 2023, The Authors. All rights reserved.

关键词： Audition

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Multi-Transfer Learning Techniques for Detecting Auditory Brainstem Response

arXiv

引用

arXiv 2023年

The assessment of the well-being of the peripheral auditory nerve system in individuals experiencing hearing impairment is conducted through auditory brainstem response (ABR) testing. Audiologists assess and document the results of the ABR test. They interpret the findings and assign labels to them using reference-based markers like peak latency, waveform morphology, amplitude, and other relevant factors. Inaccurate assessment of ABR tests may lead to incorrect judgments regarding the integrity of the auditory nerve system;therefore, proper Hearing Loss (HL) diagnosis and analysis are essential. To identify and assess ABR automation while decreasing the possibility of human error, machine learning methods, notably deep learning, may be an appropriate option. To address these issues, this study proposed deep-learning models using the transfer-learning (TL) approach to extract features from ABR testing and diagnose HL using support vector machines (SVM). Pre-trained convolutional neural network (CNN) architectures like AlexNet, DenseNet, GoogleNet, InceptionResNetV2, InceptionV3, MobileNetV2, NASNetMobile, ResNet18, ResNet50, ResNet101, ShuffleNet, and SqueezeNet are used to extract features from the collected ABR reported images dataset in the proposed model. It has been decided to use six measures accuracy, precision, recall, geometric mean (GM), standard deviation (SD), and area under the ROC curve to measure the effectiveness of the proposed model. According to experimental findings, the ShuffleNet and ResNet50 models' TL is effective for ABR to diagnose HL using an SVM classifier, with a high accuracy rate of 95% when using the 5-fold cross-validation method. © 2023, CC BY.

关键词： Support vector machines

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A Small-Signal Stability Criterion for a Power System Dynamic Model with Constant Power Loads

SSRN

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SSRN 2024年

作者： Levron, Yoash Belikov, Juri Weiss, George The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering Technion—Israel Institute of Technology Haifa3200003 Israel Department of Software Science Tallinn University of Technology Tallinn12618 Estonia School of Electrical Engineering Tel-Aviv University Tel-Aviv69978 Israel

This theoretical paper continues a long line of research works about the stability of power systems represented by reduced order models. We provide a small-signal stability criterion for a dynamic model that uses time-varying phasors, and is characterized by a lossless transmission network and constant power loads located anywhere in the network. A key concept in this study is the matrix H of the partial derivatives of the generator powers with respect to their relative angles. Our main result is that the local stability of any equilibrium point is completely determined by properties of this matrix H. More specifically, we show that an equilibrium point is asymptotically stable if H is positive definite, and is unstable if H is full-rank and not positive definite. In addition, we also prove several relations between the eigenvalues of H and the eigenvalues of the system's Jacobian matrix. These results are demonstrated on a number of case-studies, and compared with related earlier ones from the literature. © 2024, The Authors. All rights reserved.

关键词： Electric power transmission networks

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