DDAC: a feature extraction method for model of image steganalysis based on convolutional neural network by Xiaodan WANG, Jingtai LI, Yafei SONG

“…To solve the problem that for image steganalysis based on convolution neural network, manual designed filter kernels were used to extract residual characteristics, but in practice, these kernels filter were not suitable for each steganography algorithm and have worse performance in application, a directional difference adaptive combination (DDAC) method was proposed.Firstly, the difference was calculated between center pixel and each directional pixel around, and 1 × 1 convolution was adopted to achieve linear combinations of directional difference.Since the combination parameters self-adaptively update according to loss function, filter kernels could be more effective in extracting diverse residual characteristics of embedding information.Secondly, truncated linear unit (TLU) was applied to raise the ratio of embedding information residual to image information residual.The model’s coveragence was accelerated and the ability of feature extraction was promoted.Experimental results indicate that substituting the proposed method could improve the accuracy of Ye-net and Yedroudj-net by 1.30%~8.21% in WOW and S-UNIWARD datasets.Compared with fix and adjustable SRM filter kernels methods, the accuracy of test model using DDAC increases 0.60%~20.72% in various datasets, and the training progress was more stable.DDAC-net was proved to be more effective in comparsion with other steganalysis model.…”
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Graphic Perception System for Visually Impaired Groups by Jingzi Wen

“…Finally, the proposed algorithm is compared with other algorithms on PASCAL VOC and MS-COCO data. …”
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Type 1 and Type 2 Diabetes Measurement Using Human Face Skin Region by L. Aneesh Euprazia, A. Rajeswari, K. K. Thyagharajan, N. R. Shanker

“…Viola Jones’ face-detecting algorithm extracts face skin regions from a diabetic person’s face image in video frames. …”
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Adaptive Integral-Based Robust Q-S Synchronization and Parameter Identification of Nonlinear Hyperchaotic Complex Systems by Sami Ud Din, Muhammad Rafiq Mufti, Humaira Afzal, Majid Ali, Muhammad Abdul Moiz Zia

“…The stability of the proposed algorithm is established in an impressive way, using Lyapunov criteria. …”
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Prediction of the Loss of Feed Water Fault Signatures Using Machine Learning Techniques by Anselim M. Mwaura, Yong-Kuo Liu

“…The performance indices of residual plots, mean absolute percentage error, root mean squared error, and coefficient of determination were used to determine the most suitable algorithms for accurately diagnosing the loss of feed water transient signatures. …”
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Low Orbit Satellite Internet of Things Transmission Technology Based on LoRa by Zehao LI, Jianpeng MA, Shun ZHANG, Xiao WEI, Jing ZHANG

“…As an emerging wide area network technology, LoRa has the characteristics of low power consumption and wide coverage.It has very broad prospects in the field of internet of things applications.In recent years, it has been deployed in countless objects around the world.The advantages of wide coverage of low-orbit satellite networks make it an inevitable technology to achieve global coverage of massive internet of things.Firstly, the basic principles of LoRa technology were expounded.Then the problems existed after the LoRa technology was directly introduced into the low-orbit satellite IoT were analyzed.Finally, a set of LoRa transmission technology suitable for low-orbit satellite IoT was proposed, focused on solved the problem of LoRa frame synchronization under the condition of low-orbit long-distance low-power transmission, and the problem of LoRa demodulation caused by the high-speed movement of satellites due to the Doppler frequency off set.The simulation results showed that the proposed joint synchronization and frequency off set estimation algorithm could obviously improved the synchronization probability and transmission reliability of LoRa technology under the conditions of extremely low SNR and large Doppler frequency shift.…”
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q-Rung Orthopair Fuzzy Matroids with Application to Human Trafficking by Muhammad Asif, Doha A. Kattan, Dragan Pamučar, Ghous Ali

“…Ultimately, to show the significance of our proposed work, we combine these ideas and offer an application. We provide an algorithm to solve the numerical problems related to human flow between particular regions to ensure the increased government response action against frequently used path (heavy path) for the countries involved via directed q-rung orthopair fuzzy graph (q-ROFG). …”
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Non-Invasive Techniques for Monitoring Cultural Heritage: Change Detection in Dense Point Clouds at the San Pietro Barisano Bell Tower in Matera, Italy by Carmen Fattore, Sara Porcari, Arcangelo Priore, Vito Domenico Porcari

“…The investigation uses a variety of change detection algorithms, including the Iterative Closest Point (ICP) algorithm, which is renowned for its robust registration capabilities in aligning point clouds with high accuracy. …”
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Crack detection based on attention mechanism with YOLOv5 by Min‐Li Lan, Dan Yang, Shuang‐Xi Zhou, Yang Ding

“…Aiming at the problems of poor real‐time performance and low precision of traditional pavement crack detection, a crack detection method based on improved YOLOv5 one‐step target detection algorithm of convolutional neural network is proposed by using the advantages of depth learning network in target detection. …”
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Research on gating alignment strategy for flow scheduling in satellite formation by XU Chuan, ZHANG Rufeng, HE Xiongwen, CUI Zhaojing, ZHAO Guofeng

“…Secondly, an online rolling gray scale prediction algorithm was designed to predict the delay of inter-node links, and based on the prediction results, the gated list deviation of neighboring nodes could be corrected dynamically to ensure the consistency of multi-node gated scheduling. …”
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Experimental economics for machine learning-a methodological contribution on lie detection. by Dmitri Bershadskyy, Laslo Dinges, Marc-André Fiedler, Ayoub Al-Hamadi, Nina Ostermaier, Joachim Weimann

“…To demonstrate this, we focus on algorithms trained to detect lies. Such algorithms are of high relevance for research in economics as they deal with the ability to retrieve otherwise private information. …”
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FPGA Implementation of Reconfigurable Finite State Machine with Input Multiplexing Architecture Using Hungarian Method by Nitish Das, P. Aruna Priya

“…As a solution, an iterative greedy heuristic based Hungarian algorithm is proposed. The experimental results from MCNC FSM benchmarks demonstrate a significant speed improvement by 30.43% as compared with variation-based reconfigurable multiplexer bank (VRMUX) and by 9.14% in comparison with combination-based reconfigurable multiplexer bank (CRMUX) during field programmable gate array (FPGA) implementation.…”
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Research on Optimization of Aircraft Climb Trajectory considering Environmental Impact by Fangzi Liu, Minghua Hu, Wenying Lv, Honghai Zhang

“…Finally, the multiobjective model is solved by genetic algorithm. The B737-800 civil aviation aircraft is selected for simulation experiment to analyze the impact of speed change on the optimization target. …”
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The Quality of Ranking during Simulated Pairwise Judgments for Examined Approximation Procedures by Paul Thaddeus Kazibudzki

“…In order to provide credible and high quality results, the problem is studied via a properly designed and coded seminal simulation algorithm, executed in Wolfram Mathematica 8.0.…”
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Design optimization of inner and outer‐rotor PMSGs for X‐ROTOR wind turbines by Reza Yazdanpanah, Seyed Abolfazl Mortazavizadeh, Mohammad Salehian, David Campos‐Gaona, Olimpo Anaya‐Lara

“…The GA optimization algorithm was used to find optimized designs in terms of efficiency, weight, cost, and temperature rise. …”
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Quantitative Detection of Financial Fraud Based on Deep Learning with Combination of E-Commerce Big Data by Jian Liu, Xin Gu, Chao Shang

“…Therefore, in the context of e-commerce big data, this paper proposes a quantitative detection algorithm for financial fraud based on deep learning. …”
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Optical Design and Simulation of Snapshot Hyperspectral Dental Imaging Spectrometer with One-Dimensional Random Coding by Jiajing Cao, Jun Chang, Yi Huang, Wenxi Wang, Xinran Guo, Shangnan Zhao

“…The target spectral information is reconstructed through the reconstruction algorithm. The simulation result shows that spectral imaging has the potential to improve the accuracy and precision of teeth whiteness measurements.…”
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Real-Time Pipeline Leak Detection: A Hybrid Deep Learning Approach Using Acoustic Emission Signals by Faisal Saleem, Zahoor Ahmad, Jong-Myon Kim

“…The core of the framework combines convolutional neural networks (CNNs) with long short-term memory (LSTM), ensuring a comprehensive examination of both spatial and temporal features of AE signals. A genetic algorithm (GA) optimizes the neural network by isolating the most important features for leak detection. …”
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Unit Disk Graph-Based Node Similarity Index for Complex Network Analysis by Natarajan Meghanathan

“…We run a binary search algorithm to determine the minimum value for the threshold distance that would yield a connected unit disk graph of the vertices. …”
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Research on integrated communication and positioning technology based on visible light by Wei WANG, Jianping WANG, Lifang FENG, Jianli JIN

“…Visible light wireless technology transmits information through visible light, utilizing light-emitting diode (LED) light sources to achieve communication and positioning while illuminating.Visible light communication positioning integration (VLCP) technology is one of the key supporting technologies for future large-scale Internet of things (IoT) applications.Orthogonal frequency division multiplexing (OFDM) technology can be used to allocate different spectral resources to visible light communication (VLC) and visible light positioning (VLP) systems, while achieving communication and positioning functions.Resource allocation is the key to improving the efficiency of VLCP systems and expanding their applicability.A new resource allocation method based on error vector magnitude(EVM) was proposed.EVM was utilized to allocate subcarriers for positioning and communication in VLCP systems, communication and positioning performance was dynamically adjusted based on channel parameters, system quality of service (QoS) was ensured, and system channel utilization was improved.The experimental results indicate that at 1.5 m×1.5 m×1.5 m indoor environment, the proposed resource allocation algorithm can improve channel utilization by at least 19.5% compared to fixed resource allocation algorithms.Under the premise of comparable performance to algorithms that use signal-to-noise ratio (SNR) for resource allocation, it greatly saves system resources and is easy to apply in practice.…”
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