Mathematical Formalization and Algorithmization of the Main Modules of Organizational and Technical Systems by A. A. Solodov

“…As an example, a nontrivial problem of optimal detection of Poisson signal against a background of Poisson noise is considered; graphs of the potential noise immunity of this algorithm are calculated and presented. …”
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Benchmarking and improving algorithms for attributing satellite-observed contrails to flights by A. Sarna, V. Meijer, R. Chevallier, A. Duncan, K. McConnaughay, S. Geraedts, K. McCloskey

“…Recent work has introduced automated algorithms for solving the attribution problem, but it lacks an evaluation against ground-truth data. …”
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Differential Evolution Algorithm for Identification of Structural Damage in Steel Beams by Brunno Emidio Sobrinho, Gilberto Gomes, Welington Vital da Silva, Ramon Silva, Erwin U. L. Palechor, Luciano M. Bezerra

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Algorithms weighing lives and freedoms: The case of China’s health code by Ina Virtosu, Chen Li

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Sparse wavelet decomposition in problems of vibration-based diagnostics of rotary equipment by Y. P. Aslamov, A. P. Aslamov, I. G. Davydov, A. V. Borsuk

“…At the present an increase in the effectiveness of vibration-based diagnostics is achieved by automating the solution of this problem and also by the use of matched sets of informative features, which causes the urgency of the development of algorithms for their detection. …”
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Coverage problem in camera-based sensor networks using the CUDA platform by Jae-Hyun Seo, Yourim Yoon, Yong-Hyuk Kim

“…The closed-circuit television deployment in downtown is similar to solving coverage problem in wireless camera-based sensor networks. …”
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Examining the Efficiency of Learning-Based Algorithms in the Process of Declaring Customs by Mustafa Günerkan, Ender Şahinaslan, Önder Şahınaslan

“…Intelligent structures supported by current information technologies are needed to solve these problems. For this purpose, being able to use learning algorithms over big data is important in the field of customs declaration creation in the logistics industry. …”
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Improved Algorithm for Analysis of DNA Sequences Using Multiresolution Transformation by T. M. Inbamalar, R. Sivakumar

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SMOTEHashBoost: Ensemble Algorithm for Imbalanced Dataset Pattern Classification by Seema Yadav, Dhruvanshu Joshi, Soham Mulye, Sandeep S. Udmale, Girish P. Bhole

“…The majority class is often favored by conventional classifiers, which can lead to biases from improper oversampling or subpar performance when detecting instances of the minority class. Consequently, there is growing concern about algorithmic fairness. …”
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Parallel clustering algorithm for large-scale biological data sets. by Minchao Wang, Wu Zhang, Wang Ding, Dongbo Dai, Huiran Zhang, Hao Xie, Luonan Chen, Yike Guo, Jiang Xie

“…<h4>Backgrounds</h4>Recent explosion of biological data brings a great challenge for the traditional clustering algorithms. With increasing scale of data sets, much larger memory and longer runtime are required for the cluster identification problems. …”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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Blind multiuser detection based on instantaneous mixtures by ZHAO Chen, GOU Bin, WANG Ke

“…The basic thought is to apply the existing blind source separation （BSS） algorithm to the signal detection in MIMO-OFDM systems. …”
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MODERN METHODS OF AUTOMATIC RECTANGLE OBJECTS DETECTION by E. S. Matusevich, I. E. Kheidorov

“…The algorithms were tested on the base of 1000 passports for the problem of accurate photo edges detection.…”
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cpop: Detecting Changes in Piecewise-Linear Signals by Paul Fearnhead, Daniel Grose

“… Changepoint detection is an important problem with a wide range of applications. …”
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Lightweight Anomaly Detection for Wireless Sensor Networks by Pu Cheng, Minghua Zhu

“…In this paper two lightweight anomaly detection algorithms LADS and LADQA are proposed for WSNs. …”
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Explainable MRI-Based Ensemble Learnable Architecture for Alzheimer’s Disease Detection by Opeyemi Taiwo Adeniran, Blessing Ojeme, Temitope Ezekiel Ajibola, Ojonugwa Oluwafemi Ejiga Peter, Abiola Olayinka Ajala, Md Mahmudur Rahman, Fahmi Khalifa

“…With the advancements in deep learning methods, AI systems now perform at the same or higher level than human intelligence in many complex real-world problems. The data and algorithmic opacity of deep learning models, however, make the task of comprehending the input data information, the model, and model’s decisions quite challenging. …”
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Mobile Recommendation Based on Link Community Detection by Kun Deng, Jianpei Zhang, Jing Yang

“…In order to solve this problem, this paper proposes a novel mobile recommendation algorithm based on link community detection (MRLD). …”
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Lightweight blasthole image detection and positioning method by Shan PAN, Ting YU, Zhongwen YUE, Zijian TIAN, Qingyu JIN

“…In terms of blasthole detection accuracy, the algorithm addresses the issue of false detection caused by the influence of surrounding rock backgrounds and rock shadows, as well as the problem of missed detection due to limited contextual information and identifiable features of blastholes in images. …”
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Multipath Detection Using Boolean Satisfiability Techniques by Fadi A. Aloul, Mohamed El-Tarhuni

“…The paper presents a framework for modeling the multipath detection problem as a SAT application. It also provides simulation results that demonstrate the effectiveness of the proposed scheme in detecting the multipath components in frequency-selective Rayleigh fading channels.…”
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Using deep learning for detecting BotCloud by Guang KOU, Guang-ming TANG, Shuo WANG, Hai-tao SONG, Yuan BIAN

“…To solve this problem, a CNN(convolution neural network)-based method for detecting the BotCloud was pro-posed. …”
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