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arXiv 2020年

作者： Andrikopoulos, Athanasios Dept. of Computer Engineering and Informatics University of Patras Patras26504 Greece

MSC Codes 54F45, 05C10, 05C85, 06A05, 06A06 06A06The notion of interval order was introduced by Norbert Wiener [28] in order to clarify the relation between the notion of an instant of time and that of a period of time. This was a problem on which Bertrand Russell [18] worked at the time. Interval orders play an important role in many areas of pure and applied mathematics, graph theory, computer science and engineering. Special cases of interval order are the semiorder and linear order. All of these notions are especially important in the study of linear-interval and linear-semiorder dimension of a binary relation. This kind of dimension, which we call hybrid order dimension, gives a common generalization of linear order and interval order (semiorder) dimension and is arguably the most important measure of ordered set complexity. In this paper, we present three main results of the theory of hybrid order dimension. More specifically, we obtain necessary and sufficient conditions for a binary relation to have an interval order (resp. linear-interval order, linear-simiorder) extension, as well as an interval order realizer of interval orders (resp. linear-interval orders, linear-simiorders). We also obtain a characterization of the interval order (resp. linear-interval order, linear-simiorder) dimension. Because a binary relation’s hybrid order dimension is less than its (linear) order dimension, these results will be able to improve known results in graph theory and computer science by identifying more efficient algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Graph theory

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Detecting Multi-Pose Masked Face Using Adaptive Boosting and Cascade Classifier

Detecting Multi-Pose Masked Face Using Adaptive Boosting and...

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International Electronics Symposium (IES)

作者： Bima Sena Bayu Dewantara Dhiska Twinda Rhamadhaningrum Dept of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

ISBN: (数字)9781728195308

ISBN: (纸本)9781728195643

This paper presents the use of the Adaptive Boosting and Cascade Classifier based method to detect someone wearing a mask or not on various facial poses. In general, masks are used to protect the nose and mouth to prevent dirt or bacteria or virus from entering the respiratory tract Simply stated, a person is said to use a mask well if the nose and mouth areas are not visually visible on the face. OpenCV has already provided a model for human face detection for both frontal and profile faces. These models are good for detecting human frontal faces and profile faces, but not to detect people with masks. To deals with multi-pose people's faces using masks, we have to train new nose and mouth-based Adaptive Boosting and Cascade Classifies based model on various face poses independently to achieve our expectation. The Caspeal face database and AISL face database are used to train the Haar-like feature, LBP feature, and HOG feature based Adaptive Boostings and Cascade Classifiers. Based on the results of experiments, Haar-like feature outperforms LBP feature and HOG feature by achieving the best detection accuracy of 86.9%. On the other hand, LBP features outperforms Haar- like feature and HOG feature in computation time by achieving less than 30 msec from image loading until showing the detection result.

关键词： Faces Nose Mouth Feature extraction Histograms Training Boosting

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Efficient Coupled Dictionary Learning And Sparse Coding For Noisy Piecewise-Smooth Signals: Application To Hyperspectral Imaging

Efficient Coupled Dictionary Learning And Sparse Coding For ...

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IEEE International Conference on Image Processing

作者： Alexandros Gkillas Dimitris Ampeliotis Kostas Berberidis Dept. of Computer Engineering & Informatics University of Patras 26500 Patras Greece

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Given two datasets that belong to different feature spaces and both correspond to the same underlying phenomenon, the scope of coupled dictionary learning is to compute two dictionaries, one for each dataset, so that each dataset is approximated using the respective dictionary but the same sparse coding matrix. In this work, the focus is on a particular, yet widespread, form of this problem in which the datasets correspond to slowly varying (piece-wise smooth) signals, and the measurements contain severe noise. A novel coupled dictionary learning technique is developed by including a suitable total-variation-based regularization term in the cost function. Furthermore, exploiting the smoothness of the datasets, new fast sparse coding algorithms are derived. The new techniques achieve effective modeling of the smooth signal and significantly alleviate the effects of noise. Finally, extensive simulation results for the problem of spectral super-resolution of hyperspectral images are provided, demonstrating the performance improvements offered by the derived techniques.

关键词： Dictionaries Encoding Machine learning Hyperspectral imaging Noise measurement Sparse matrices Cost function

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ReFuzzTiD: A Recurrent Neurofuzzy Model for Anomaly Detection in Time Series

ReFuzzTiD: A Recurrent Neurofuzzy Model for Anomaly Detectio...

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International Joint Conference on Neural Networks (IJCNN)

作者： George Kandilogiannakis Paris Mastorocostas Dept. of Informatics & Computer Engineering University of West Attica Egaleo Greece

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

In this paper a recurrent neurofuzzy model is proposed, for time series anomaly detection. ReFuzzTiD comprises fuzzy rules whose consequent parts are simple three-layer neural networks with internal feedback at the neurons of the hidden layer. ReFuzzTid is trained by the Simulated Annealing Dynamic Resilient Propagation algorithm. The model learns the dynamics of the time series such that it can classify them by detecting the anomaly points. A comparative analysis with a series of time series anomaly detection models is given, highlighting the characteristics of the proposed detector.

关键词： Time series analysis Anomaly detection Computational modeling Neurons Recurrent neural networks Simulated annealing Detectors

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Non-Linear Age of Information: An Energy Efficient Receiver-Centric Approach

arXiv

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arXiv 2021年

作者： Miridakis, Nikolaos I. Tsiftsis, Theodoros A. Yang, Guanghua The Institute of Physical Internet School of Intelligent Systems Science & Engineering Jinan University Zhuhai Campus Zhuhai519070 China The Dept. of Informatics and Computer Engineering University of West Attica Aegaleo 12243 Greece

The age of information (AoI) performance metric for point-to-point wireless communication systems is analytically studied under Rician-faded channels and when the receiver is equipped with multiple antennas. The general scenario of a non-linear AoI function is considered, which includes the conventional linear AoI as a special case. The stop-and-wait transmission policy is adopted, where the source node samples and then transmits new data only upon the successful reception of previous data. This approach can serve as a performance benchmark for any queuing system used in practice. New analytical and closed-form expressions are derived with respect to the average AoI and average peak AoI for the considered system configuration. We particularly focus on the energy efficiency of the said mode of operation, whereas some useful engineering insights are provided. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy efficiency

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CHARACTERIZATION OF THE EXISTENCE OF SEMICONTINUOUS RICHTER-PELEG MULTI-UTILITY REPRESENTATIONS

arXiv

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arXiv 2020年

作者： Andrikopoulos, Athanasios Dept. of Computer Engineering and Informatics University of Patras Patras26504 Greece

The utility representations of preference relations in symmetric topological spaces have the advantage of fully characterizing these relations. But this is not true in the case of representations of preference relations that are mostly incomplete and use asymmetric topologies. To avoid this unfortunate circumstance, due to lack of symmetry, the notion of semicontinuous Richter-Peleg multiutility representation was first introduced and studied by Minguzzi [29]. Generally, the study of semicontinuous functions reveals that topology and order are two aspects of the same mathematical object and therefore should be studied jointly. The mathematical object that can be used to model and analyze the concepts of asymmetry and duality that arise from the coexistence of topology and order is that of bitopological preordered space. In this paper, we characterize the existence of semicontinuous Richter-Peleg multi-utility representations in bitopological spaces. Based on this characterization, we prove that a preorder ≾ has the set of all Scott and ω-continuous functions as a Richter-Peleg multi-utility representation if and only if ≾ is precontinuous in the sense of Erné [18].MSC Codes 91B16 Copyright © 2020, The Authors. All rights reserved.

关键词： Topology

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Spatial photonic reservoir computing based on non-linear phase-to-amplitude conversion in micro-ring resonators

arXiv

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arXiv 2021年

作者： Mesaritakis, Charis Sozos, Kostas Dermanis, Dimitris Bogris, Adonis University of the Aegean Dept. of Information and Communication Systems Engineering Palama 2 Karlovassi Samos83200 Greece University of West Attica Dept. of Informatics and Computer Engineering. Aghiou Spiridonos Egaleo Athens12243 Greece

We present a photonic reservoir computing, relying on a non-linear phase-to-amplitude mapping process, able to classify in real-time multi-Gbaud time traces subject to transmission effects. This approach delivers an a... 详细信息

关键词： Optical resonators

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Intra-Datacenter Load Balancing in a Federated Cloud with Throttled Algorithm

Intra-Datacenter Load Balancing in a Federated Cloud with Th...

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Science, engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Damola Gideon Akinola Emmanuel Adetiba Abdultaofeek Abayomi Uche Nnaji Surendra Thakur Sibusiso Moyo Department of Electrical and Information Engineering Covenant Applied Informatics and Communications African Center of Excellence Covenant University Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Department of Information and Communication Technology Mangosuthu University of Technology Durban South Africa Dept. of Computer and Information Science Covenant Applied Informatics and Communications African Center of Excellence Covenant University Ota Nigeria KZN e-Skills CoLab Durban University of Technology Durban South Africa School for Data Science and Computational Thinking and Department of Mathematical Sciences Stellenbosch University Stellenbosch South Africa

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

The emergence of cloud computing technology has motivated a very high number of users in different organizations to access its services in running and delivering their various operations and services. However, this surge of cloud users has led to the problem of uneven load sharing among the cloud computing infrastructures. As a result, federated cloud infrastructure was initiated to provide more cloud computing resources to accommodate more cloud users’ requests and also to provide equal requests mapping with the available cloud resources. Nevertheless, the issue of unequal allocation of requests within the datacenter(s) that makes up the federated cloud environment still persists. This research work presents an intra-datacenter load balancing algorithm in a federated cloud environment named; the intra-balancer adapted throttled algorithm to evenly distribute requests in each datacenter that formulate the federated cloud infrastructures. The simulation of the intra-balancer was carried out in CloudAnalyst, the results of the implementation showed that the intra-balancer outperformed the Round-Robin and ESCE with 98.93ms and 2.26ms for the response and processing time respectively. The results assert that the intra-balancer algorithm provides a better load balancing solution in a federated cloud environment.

关键词： computers Cloud computing Organizations Load management Resource management Time factors Task analysis

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Analysis of temperature-sensitive on short-term electricity load forecasting 4

Analysis of temperature-sensitive on short-term electricity ...

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2020 IEEE-HYDCON International Conference on engineering in the 4th Industrial Revolution, HYDCON 2020

作者： Tung, Nguyen Xuan Dat, Nguyen Quang Thang, Tran Ngoc Solanki, Vijender Kumar Anh, Nguyen Thi Ngoc Cmc Corporation Hanoi Viet Nam Hanoi University of Science Technology School of Applied Mathematics and Informatics Hanoi Viet Nam Cmr Institute of Technology Dept of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9781728149943

Short-termelectricityloadforecastingisessentialfor the operating energy of a nation. Accuracy of forecasting is important for power operation however it is dependent on weather. This paper focuses on model sensitive analysis temperature on short-term electricity load forecasting. The new models have proposed to analyze the effect of temperature on the electricity load forecasting. In detail, three methods (linear regression, local method and Monte Carlo) are analysis for temperature-sensitive on short-term electricity load forecasting. Then, the proposed models are applied to Vietnam electricity load forecasting. Index Terms-Sensitive Analysis, Electricity load forecasting, Short-term forecasting, Temperature effect, Regression © 2020 IEEE.

关键词： Monte Carlo methods

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Mamba-Based Super-Resolution and Segmentation Network for UAV-Captured Blueberry Farmland Imagery

Mamba-Based Super-Resolution and Segmentation Network for UA...

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Data-driven Optimization of Complex Systems (DOCS), International Conference on

作者： Fan Zhao Jian Song Jiaqi Wang Yijia Chen Dianhan Xi Xinlei Shao Y ongying Liu Bangzhang Ma Yinyin He Guochen Zhang Qingyang Wu Zhengyue Tu Mengya Wu Yulun Chen Jiaolin Guo Chenyu Zhang Graduate School of Frontier Science The University of Tokyo Kashiwa Japan Dept. Land Surveying and Geo-Informatics The Hong Kong Polytechnic University Hong Kong Dept. of Computer and Information Sciences Hosei University Tokyo Japan Dept. Environmental Health Sciences University of California Los Angeles LA CA US Dept. Mechanical Engineering The University of Tokyo Bunkyo Japan Dept. Environmental Science Southwest Forestry University Kunming China Yunnan Yijiu Agricultural Development Co. Ltd. Yuxi City China Dept. Geographic Information Science Fujian Normal University Fuzhou China

ISBN: (数字)9798350377842

ISBN: (纸本)9798350377859

Traditional methods of inspecting blueberry maturity primarily rely on manual observation, which is inefficient and prone to visual errors. The high similarity in shape and color between immature blueberries and blueberry flowers poses significant challenges for accurate visual assessment. This study proposes a novel method for evaluating the overall maturity of a blueberry plantation using super-resolution reconstruction (SRR) and semantic segmentation. We designed and evaluated various SRR models, including SRCNN, EDSR, RCAN, Real-ESRGAN, SwinIR, HAT, and MambaIR, to enhance the detailed representation of blueberries at different maturity stages in low-resolution images. These enhanced images are then processed by the proposed semantic segmentation network to accurately segment blueberry flowers, leaves, and blueberries at different maturity stages. Experimental results demonstrate that MambaIR achieves 82.26% SSIM in the SRR task, while the image segmentation model developed based on the Mamba algorithm attains an average intersection over union (mIoU) of 80.48. In summary, the proposed method shows significant accuracy and efficiency advantages in assessing blueberry maturity.

关键词： Visualization Accuracy Shape Semantic segmentation Superresolution Plantations Manuals Flowering plants Image reconstruction Optimization

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