Bytecode-based approach for Ethereum smart contract classification by Dan LIN, Kaixin LIN, Jiajing WU, Zibin ZHENG

“…In recent years, blockchain technology has been widely used and concerned in many fields, including finance, medical care and government affairs.However, due to the immutability of smart contracts and the particularity of the operating environment, various security issues occur frequently.On the one hand, the code security problems of contract developers when writing contracts, on the other hand, there are many high-risk smart contracts in Ethereum, and ordinary users are easily attracted by the high returns provided by high-risk contracts, but they have no way to know the risks of the contracts.However, the research on smart contract security mainly focuses on code security, and there is relatively little research on the identification of contract functions.If the smart contract function can be accurately classified, it will help people better understand the behavior of smart contracts, while ensuring the ecological security of smart contracts and reducing or recovering user losses.Existing smart contract classification methods often rely on the analysis of the source code of smart contracts, but contracts released on Ethereum only mandate the deployment of bytecode, and only a very small number of contracts publish their source code.Therefore, an Ethereum smart contract classification method based on bytecode was proposed.Collect the Ethereum smart contract bytecode and the corresponding category label, and then extract the opcode frequency characteristics and control flow graph characteristics.The characteristic importance is analyzed experimentally to obtain the appropriate graph vector dimension and optimal classification model, and finally the multi-classification task of smart contract in five categories of exchange, finance, gambling, game and high risk is experimentally verified, and the F1 score of the XGBoost classifier reaches 0.913 8.Experimental results show that the algorithm can better complete the classification task of Ethereum smart contracts, and can be applied to the prediction of smart contract categories in reality.…”
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Popularity Bias in Recommender Systems: The Search for Fairness in the Long Tail by Filippo Carnovalini, Antonio Rodà, Geraint A. Wiggins

“…This article proposes a narrative review of the relevant literature to characterize and understand this phenomenon, both in human and algorithmic terms. The analysis of the literature highlighted the main themes and underscored the need for a multi-disciplinary approach that examines the interplay between human cognition, algorithms, and socio-economic factors. …”
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Combined treatment of an infected paraurethral cyst by A. A. Kostin, L. V. Shaplygin, N. G. Kulchenkо, A. Mansur

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Waterbody Detection and Reservoir Water Level Prediction Using Bayesian Mixture Models with Sentinel-1 GRD Data by DongHyeon Yoon, Ha-Eun Yu, Euiho Hwang, Ki-mook Kang, Gibeom Nam, Jin-Gyeom Kim

“…These findings underscore the potential of Sentinel-1 SAR data for effective reservoir monitoring, especially where real-time water level data may be lacking. For future research, higher-resolution data or complementary algorithms may further enhance detection accuracy for smaller and more complex water features, contributing to more refined water resource management strategies.…”
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Hybrid Weighted Random Forests Method for Prediction & Classification of Online Buying Customers by Umesh Kumar Lilhore, Sarita Simaiya, Devendra Prasad, Deepak Kumar Verma

“…A Random Forest is an efficient filter in high-dimensional data to reliably classify consumer behaviour factors. This research article mainly proposed an extension of the Random Forest classifier named “Weighted Random Forests” (wRF), which incorporates tree-level weights to provide much more accurate trees throughout the calculation as well as an assessment of vector relevance. …”
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MAOOA‐Residual‐Attention‐BiConvLSTM: An Automated Deep Learning Framework for Global TEC Map Prediction by Haoran Wang, Haijun Liu, Jing Yuan, Huijun Le, Weifeng Shan, Liangchao Li

“…There are two problems with the current prediction of TEC: (a) The existing TEC prediction models mainly based on stacked structure, which has insufficient predictive ability when the network has fewer layers, and loss of fine‐grained features when there are more layers, resulting in a decrease in predictive performance; (b) The existing research on ionospheric TEC prediction mainly focuses on building deep learning prediction models, while there is little research on optimizing the hyper‐parameters of TEC prediction models. …”
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Multiple-Image Hiding by Using Single-Shot Ptychography in Transform Domain by Wenhui Xu, Yong Luo, Tuo Li, Huaying Wang, Yishi Shi

“…The proposed method may open up a novel research perspective for multiple-image hiding combined with various efficient transform domain algorithms.…”
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Design of Multi-Level Inverter Design for Charging Stations of Electric Vehicles by Aung Kyaw Htay, Hla Myo Tun Tun, Devasis Pradhan, Lei Lei Yin Win, Ei Ei Khin, Khaing Thandar Soe

“…The research challenges in this study are: the lack of technology for higher level design of multilevel inverter systems for electric vehicles (EVs) is facing to solve the high performance and robustness of the system in reality, the control algorithm for maximum power observing is a crucial challenge in the designing and implementing such kind of multilevel inverter design, the pure sine wave inverter approaches with higher number steps could be a candidate for electric vehicles (EVs) in real world applications. …”
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Monoclonal anti-CD20 antibodies in lymphomas therapy during the COVID-19 pandemic: pro and contra by K. A. Sychevskaya, S. K. Kravchenko

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The close-open mixed-fleet electric vehicle routing problem by Themistoklis Stamadianos, Nikolaos A. Kyriakakis, Magdalene Marinaki, Yannis Marinakis

“…To solve large instances, three discrete optimization swarm intelligence algorithms are employed, alongside a Variable Neighborhood Search algorithm. …”
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Feasibility of estimating the percentage of desert pavement using Tasseled Cap Transformation indices extracted from Landsat 8 images by farzaneh Fotouhi Firoozabad, Atefeh jebali

“…Remote sensing technology is an effective tool for identifying and classifying landforms because it produces satellite images with spectral and spatial resolution, and it can also be a valuable tool for classifying desert pavements. …”
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Mapping Temperate Savanna in Northeastern China Through Integrating UAV and Satellite Imagery by Xiaoya Li, Tao Duan, Kaijie Yang, Bin Yang, Chunmei Wang, Xin Tian, Qi Lu, Feng Wang

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A Novel Jamming Method Based on Sine Function Secondary Modulation and Phase Coded Modulation by Guikun Liu, Guangyuan Li, Zhenyang Xu, Haoming Xu, Feng Ming, Liang Li, Chen Song, Zhengshuai Li, Peng Wang

“…With the development of synthetic aperture radar (SAR) imaging technology, the research of SAR jamming method has become an important topic in the field of electronic countermeasures. …”
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To the 110 anniversary since the birth of professor E.A.Vasyukova by Alexandr Sergeevich Ametov, Elena Valerievna Doskina, Irina Ivanovna Kochergina, Olga Mikhailovna Smirnova, Ekaterina Evgenyevna Mishina

“…The main areas of her research were the methods of diagnostics and treatment of diabetes, Cushing's disease, thyroid diseases, abnormalities of reproductive growth. …”
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Exploring the opportunities and challenges of using large language models to represent institutional agency in land system modelling by Y. Zeng, C. Brown, C. Brown, J. Raymond, M. Byari, R. Hotz, M. Rounsevell, M. Rounsevell, M. Rounsevell

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Sexual dysfunction in anxiety disorders by M. I. Yagubov, I. Yu. Kan, N. V. Dobaeva, I. R. Ayriyants

“…Based on the conducted research, the authors recommended the following algorithm for the supervision of patients suffering from anxiety disorders and sexual disorders: at the stage of seeking psychiatric help, along with standard diagnostic methods to determine the severity of mental pathology, it is advisable to use questionnaires to assess sexual function. …”
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OCTAVA: An open-source toolbox for quantitative analysis of optical coherence tomography angiography images. by Gavrielle R Untracht, Rolando S Matos, Nikolaos Dikaios, Mariam Bapir, Abdullah K Durrani, Teemapron Butsabong, Paola Campagnolo, David D Sampson, Christian Heiss, Danuta M Sampson

“…Optical coherence tomography angiography (OCTA) performs non-invasive visualization and characterization of microvasculature in research and clinical applications mainly in ophthalmology and dermatology. …”
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Machine Learning Accurately Predicts Need for Critical Care Support in Patients Admitted to Hospital for Community-Acquired Pneumonia by George S. Chen, BSc, Terry Lee, PhD, Jennifer L.Y. Tsang, MD, Alexandra Binnie, MD, Anne McCarthy, MD, Juthaporn Cowan, MD, Patrick Archambault, MD, Francois Lellouche, MD, Alexis F. Turgeon, MD, MSc, Jennifer Yoon, MD, Francois Lamontagne, MD, Allison McGeer, MD, Josh Douglas, MD, Peter Daley, MD, Robert Fowler, MD, David M. Maslove, MD, Brent W. Winston, MD, Todd C. Lee, MD, Karen C. Tran, MD, Matthew P. Cheng, MD, Donald C. Vinh, MD, John H. Boyd, MD, Keith R. Walley, MD, Joel Singer, PhD, John C. Marshall, MD, James A. Russell, MD, for the Community-Acquired Pneumonia: Toward InnoVAtive Treatment (CAPTIVATE) Investigators

“…None. MEASUREMENTS AND MAIN RESULTS:. Performance was evaluated with area under the receiver operating characteristic curve (AUROC) and accuracy. …”
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A Dataset of Real and Synthetic Speech in Ukrainian by Khrystyna Lipianina-Honcharenko, Hennadii Bohuta, Adam Ivaniush, Mariana Soia

“…The main focus of the research is on identifying statistically significant differences between generated and real speech, which is of great importance for the further development of automatic speech recognition systems. …”
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Teaching Additional Programming Languages on the Basis of Mapping in the System of Professional Development of Computer Science Teachers by Elisey Nigodin, Natalia Dobrovolskaia

“…The quality of acquired IT knowledge and Uniform State Exam (USE) results in informatics can be higher if students learn additional languages with broader capabilities in addition to the main programming language. The research is aimed at finding didactic technologies that allow expanding the range of programming languages studied by schoolchildren, which complements the professional skills of computer science teachers. …”
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