Carrier-independent screen-shooting resistant watermarking based on information overlay superimposition by Xiaomeng LI, Daidou GUO, Xunfang ZHUO, Heng YAO, Chuan QIN

“…Financial security, an important part of national security, is critical for the stable and healthy development of the economy.Digital image watermarking technology plays a crucial role in the field of financial information security, and the anti-screen watermarking algorithm has become a new research focus of digital image watermarking technology.The common way to achieve an invisible watermark in existing watermarking schemes is to modify the carrier image, which is not suitable for all types of images.To solve this problem, an end-to-end robust watermarking scheme based on deep learning was proposed.The algorithm achieved both visual quality and robustness of the watermark image.A random binary string served as the input of the encoder network in the proposed end-to-end network architecture.The encoder can generate the watermark information overlay, which can be attached to any carrier image after training.The ability to resist screen shooting noise was learned by the model through mathematical methods incorporated in the network to simulate the distortion generated during screen shooting.The visual quality of the watermark image was further improved by adding the image JND loss based on just perceptible difference.Moreover, an embedding hyperparameter was introduced in the training phase to balance the visual quality and robustness of the watermarked image adaptively.A watermark model suitable for different scenarios can be obtained by changing the size of the embedding hyperparameter.The visual quality and robustness performance of the proposed scheme and the current state-of-the-art algorithms were evaluated to verify the effectiveness of the proposed scheme.The results show that the watermark image generated by the proposed scheme has better visual quality and can accurately restore the embedded watermark information in robustness experiments under different distances, angles, lighting conditions, display devices, and shooting devices.…”
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Multichannel bioelectronic sensing using engineered Escherichia coli by Xu Zhang, Marimikel Charrier, Caroline M. Ajo-Franklin

“…We exploit the differing redox potentials of the two extracellular electron transfer pathways6 to develop a redox-potential-dependent algorithm that efficiently converts biological signals into 2-bit binary outputs. …”
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Pistachio Classification Based on Acoustic Systems and Machine Learning by Yavuz Türkay, Zekiye Seyma Tamay

“…These features are given as input to a support vector machine algorithm called FITCSVM for classification. FITCSVM is an algorithm that can perform one-class and two-class (binary) classification on low or medium-sized prediction datasets. …”
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Blockchain-Enabled Robust-Game Electricity Transaction Model for a Multi-Microgrid System Considering Wind Power Uncertainty by Jiayu Wu, Yang Liu, Qiming Yang, Wenfeng Li

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Identification of Arbitrary Length Shellcode for the Intel x64 Architecture as a NOP Sled by Austin Norby, Bhaskar P. Rimal, Bramwell Brizendine

“…The results from this paper are successful for the different types of constructed samples, polymorphic NOP sleds, and real-world data used to validate the artifact. We create an algorithm to calculate the differences between execution contexts, create an artifact to automatically process byte sequences to search for NOP sleds that satisfy our zero-difference policy, identify third-party NOP generators that did not produce NOP byte sequences that met this research’s standard and published the source code to an open-source repository.…”
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Design of public space guide system based on augmented reality technology by Pu Jiao, Limin Ran

“…For image quality and its influencing factors, binary robust invariant scalable keypoints and scale-invariant feature transformation algorithms in viewpoint changes had the highest recall of 92%. …”
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Digit recognition using decimal coding and artificial neural network by Toufik Datsi, Khalid Aznag, Ahmed El Oirrak

“…The method presented in this research consists to extract the characteristics of digit image by coding each row of the image by a decimal value, i.e. passage of the binary representation into a decimal value, this method called decimal coding of rows. …”
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Vote-Based: Ensemble Approach by Abdul Ahad Abro

“…In designing a method, training, validation and test sets are applied in terms of an ensemble approach to developing an efficient and robust binary classification model. Similarly, ensemble learning is the most prominent and broad research area of Machine Learning (ML) and image recognition, which assists in enhancing the capability of performance. …”
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Unsupervised feature selection in binarization of real attributes for conceptual clustering by Shkaberina Guzel, Masich Igor, Markushin Egor, Kraeva Ekaterina

“…The main idea of our research is to use the concepts derived through FCA as new features for clustering. …”
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Optimization of Identification and Zoning Method for Landscape Characters of Urban Historic Districts by Hong YUN, Zixuan HU, Zehao HU

“…By this way, recessive genes, which do not have spatial attribution, can be mapped into space. Then the research utilizes K-means clustering algorithm to optimize the zoning method for historic landscape characters. …”
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FArSide Trained Active Region Recognition (FASTARR): A Machine Learning Approach by Amr Hamada, Mitchell Creelman, Kiran Jain, Charles Lindsey

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A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction by Suleiman Daoud, Ahmad Nasayreh, Khalid M.O. Nahar, Wlla k. Abedalaziz, Salem M. Alayasreh, Hasan Gharaibeh, Ayah Bashkami, Amer Jaradat, Sultan Jarrar, Hammam Al-Hawamdeh, Absalom E. Ezugwu, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Laith Abualigah

“…We first convert the algorithm from continuous to binary, combine it with the K-Nearest Neighbor (KNN) algorithm for classification, and evaluate it on a dataset of brain MRI images collected from King Abdullah Hospital. …”
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Enhancing No Reference Laparoscopic Video Quality Assessment with Evolutionary ANFIS by Biswas Sria, Palanisamy Rohini

“…This study presents a real-time laparoscopic video quality assessment algorithm independent of reference content availability. …”
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Threat analysis model to control IoT network routing attacks through deep learning approach by K. Janani, S. Ramamoorthy

“…Most of the recent research has focused on the Internet of Things (IoT) and its applications. …”
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A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem by Gaochao Xu, Yan Ding, Jia Zhao, Liang Hu, Xiaodong Fu

“…We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration’s ability and local exploitation’s ability. …”
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Extracting Optimal Number of Features for Machine Learning Models in Multilayer IoT Attacks by Badeea Al Sukhni, Soumya K. Manna, Jugal M. Dave, Leishi Zhang

“…The proposed framework managed to extract an optimal set of 13 significant features out of 64 in the Edge-IIoT dataset, which is crucial for the efficient detection and classification of multilayer attacks, and also outperforms the performance of the KNN model compared to other classifiers in binary classification. The KNN algorithm demonstrated an average accuracy exceeding 94% in detecting several multilayer attacks such as UDP, ICMP, HTTP flood, MITM, TCP SYN, XSS, SQL injection, etc.…”
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A Diagnostic Model of Breast Cancer Based on Digital Mammogram Images Using Machine Learning Techniques by Farouk A. K. Al-Fahaidy, Belal Al-Fuhaidi, Ishaq AL-Darouby, Faheem AL-Abady, Mohammed AL-Qadry, Abdurhman AL-Gamal

“…The followed step-by-step procedure of the proposed method is performed by passing the Mammographic Image Analysis Society (MIAS) through five steps of image preprocessing, image segmentation using seeded region growing (SRG) algorithm, feature extraction using different feature’s extraction classes, and important and effectiveness feature selection using the Sequential Forward Selection (SFS) technique, and finally, the Support Vector Machine (SVM) algorithm is used as a binary classifier in two classification levels. …”
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Integrated pixel-level crack detection and quantification using an ensemble of advanced U-Net architectures by Rakshitha R, Srinath S, N Vinay Kumar, Rashmi S, Poornima B V

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Optimizing Remote Sensing Image Retrieval Through a Hybrid Methodology by Sujata Alegavi, Raghvendra Sedamkar

“…Low-level features are extracted using the modified Multiscale Multiangle Completed Local Binary Pattern (MSMA-CLBP) algorithm to capture local contexture features, while high-level features are obtained through a hybrid CNN structure combining pretrained networks (Alexnet, Caffenet, VGG-S, VGG-M, VGG-F, VGG-VDD-16, VGG-VDD-19) and a fully connected dense network. …”
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Online clustering with interpretable drift adaptation to mixed features by Flavio Corradini, Vincenzo Nucci, Marco Piangerelli, Barbara Re

“…In our research, we introduce FURAKI, an innovative online clustering algorithm that incorporates drift detection. …”
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