Superficially Plausible Outputs from a Black Box: Problematising GenAI Tools for Analysing Qualitative SoTL Data by Mirjam Sophia Glessmer, Rachel Forsyth

“…In some instances, interpretations and extrapolations of data happened when it was clearly stated in the prompt that the tool should only analyse a specified dataset based on explicit instructions. Since both algorithm and training data of the GenAI tools are undisclosed, it is impossible to know how the outputs had been arrived at. …”
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Data traceability mechanism based on consortium chain by Shoucai ZHAO, Lifeng CAO, Xuehui DU

“…With the unprecedented growth in the speed of data generation and circulation in the era of big data, the emergence of blockchain technology provides a new solution for data authenticity verification.However, with the increasing demand for data flow between different blockchains, new security issues arise.Cross-chain data transmission can lead to data leakage, and detecting data leakage caused by illegal access becomes challenging.To address these problems, a data traceability mechanism based on a consortium chain was proposed.A cross-blockchain data traceability model was designed, incorporating private data pipelines to ensure the security of cross-chain data transmission.User behaviors were recorded through authorization and access logs, ensuring the traceability of illegal unauthorized access.To improve the efficiency of data traceability and query, an on-chain and off-chain synchronous storage mechanism was adopted.The state of data flow before each transaction was encrypted and stored in the database, and its index was stored in the blockchain transaction.This enables a one-to-one correspondence between on-chain and off-chain data.Additionally, Merkle trees were introduced into the block body to store block summaries, enhancing the efficiency of block legitimacy verification.Based on the data storage form and cross-chain data interaction mechanism, a data traceability algorithm was designed.The traceability results were displayed in the form of an ordered tree.An experimental environment for consortium chain traceability was built using fabric, targeting the cross-domain data traceability scenario in the e-commerce industry.The GO language was used to simulate and test the data traceability performance with a large number of blocks and transactions.The results demonstrate that with the increasing number of blocks and transactions, the proposed data traceability mechanism maintains satisfactory performance.…”
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Control of Magnetic Manipulator Using Reinforcement Learning Based on Incrementally Adapted Local Linear Models by Martin Brablc, Jan Žegklitz, Robert Grepl, Robert Babuška

“…We have introduced modifications to the RFWR algorithm to better suit the low-dimensional continuous-time systems we are mostly dealing with. …”
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Reentry Capsule Reachable Tube Boundary Prediction via Evolutionary Multiobjective Optimization by Wen Zou, Zhanxin Cui, Genghui Li, Zhiwei Feng, Zhenkun Wang, Qingyu Gao, Qingbin Zhang, Tao Yang

“…Ultimately, the multiobjective evolutionary algorithm based on decomposition was employed to solve the multiobjective optimization model, and the geometric boundary of the tube corresponds to the Pareto front of the multiobjective optimization. …”
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Creating a model of threats to Ukraine’s national critical infrastructure as a basis for ensuring its security and resilience by D. S. Melnyk

“…The formation of a basic threat model for critical infrastructure facilities, which should include related models of the facility, situation and intruder, is currently an important element of the algorithm for solving this problem. The basic model of threats to critical infrastructure is the framework on which the state determines who and what it needs to protect itself from at the national level. …”
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Log-Based Analysis of Creativity in the Context of Computational Thinking by Rotem Israel-Fishelson, Arnon Hershkovitz

“…We developed a Python algorithm to automatically analyze the logged solutions across four creativity measures. …”
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Integration of flexible corporate demographic policy tools into the personnel management system by Natalya V. Tonkikh, Marina V. Chudinovskikh, Svetlana V. Begicheva

“…The paper presents a model and an algorithm for integrating flexible organizational and labour tools of corporate demographic policy into the personnel management system. …”
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Neural Network and Home Hydroponics by Dmitry M. Borodulin, Anton V. Shafrai, Alexander A. Maximenko

“…Further practical tests showed an increase in energy efficiency by 32.3%, compared to the classical control algorithm at close values of plant transpiration. …”
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Intelligence analysis of drug nanoparticles delivery efficiency to cancer tumor sites using machine learning models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…To further model performance and strength, the study also applied cutting-edge methods including the Firefly Algorithm for hyperparameter tuning and Recursive Feature Elimination (RFE) for feature selection. …”
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Multiple programmed cell death patterns predict the prognosis and drug sensitivity in gastric cancer by Qiying Song, Shihe Liu, Di Wu, Aizhen Cai

“…Immune cell infiltration, immune checkpoint expression, Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and drug sensitivity analysis were used to explore immunotherapy response. …”
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EPPTA: Efficient partially observable reinforcement learning agent for penetration testing applications by Zegang Li, Qian Zhang, Guangwen Yang

“…Furthermore, by integrating the algorithm with the high‐performance RL framework, sample factory, EPPTA significantly reduces convergence time compared to existing pen‐testing methods, resulting in an approximately 20‐fold acceleration. …”
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Lattice‐based hash‐and‐sign signatures using approximate trapdoor, revisited by Huiwen Jia, Yupu Hu, Chunming Tang

“…Due to the fact that the signature size and the concrete security are closely related to the Gaussian parameter of the sampling algorithm, this technique provides a tradeoff between them. …”
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Numerical characterization of hemodynamics conditions near aortic valve after implantation of left ventricular assist device by Annalisa Quaini, Sunčica Čanić, David Paniagua

“…The use of LVADs has been associated with thrombus formation next to the aortic valve and close to the anastomosis region,especially in patients in which the native cardiac function isnegligible and the aortic valve remains closed.Stagnation points and recirculation zones have been implicated as the main fluid dynamics factors contributing to thrombus formation.The purpose of the present study was to develop and use computer simulations based on afluid-structure interaction (FSI) solver to study flow conditions corresponding to different strategies inLVAD ascending aortic anastomosis providing a scenario with the lowest likelihood of thrombus formation.A novel FSI algorithm was developed to dealwith the presence of multiple structures corresponding to different elastic properties ofthe native aorta and of the LVAD cannula.A sensitivity analysis of different variables was performed to assess their impact of flow conditionspotentially leading to thrombus formation.It was found that the location of the anastomosis closest to the aortic valve(within 4 cm away from the valve)and at the angle of 30$^\circ$ minimizes the likelihood of thrombus formation.Furthermore, it was shownthat the rigidity of the dacron anastomosis cannula plays almost no role in generating pathologicalconditions downstream from the anastomosis.Additionally, the flow analysis presented in this manuscriptindicates that compliance of the cardiovascular tissue acts as a natural inhibitor of pathological flow conditions conducive to thrombus formationand should not be neglected in computer simulations.…”
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Enhancing Persian text summarization through a three-phase fine-tuning and reinforcement learning approach with the mT5 transformer model by Vahid Nejad Mahmood Abadi, Fahimeh Ghasemian

“…Subsequently, reinforcement learning via the PPO algorithm is integrated with the fine-tuned model. …”
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Expert Detection In Question Answer Communities by Hamed Salimian, Mohammad Amin Fazli, Jafar Habibi

“…We used some ideas such as profile making for users, categorize users’ expertise, A-Priori algorithm and showed that neural networks method results the best for the purpose of expert detection.…”
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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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Application of the Professional Psychological Quest in the Professional Training of Police Officers by N. E. Miloradova, N. Ye. Tverdokhliebova

“…It is noted that the basis of the police quest is the situational method, the content of which is aimed at mastering the algorithm of actions by the cadets associated with the implementation of the service tasks of the police. …”
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A new -means singular value decomposition method based on self-adaptive matching pursuit and its application in fault diagnosis of rolling bearing weak fault by Hongchao Wang, Wenliao Du

“…To overcome the above-mentioned shortcomings of K -means singular value decomposition, a new K -means singular value decomposition sparse representation method based on traditional K -means singular value decomposition method was proposed in this article, which uses the sparse adaptive matching pursuit algorithm and an iterative method based on the minimum similarity of atomic structure. …”
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Selection of sampling sites in Germany for the International Moss Survey 2020 using statistics and decision modelling by Stefan Nickel, Winfried Schröder

“…To ensure methodological transparency and objectivity, a procedure based on statistical methods and decision modelling was developed for this purpose. The decision algorithm enabled taking into account a large number of technical criteria. …”
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Empirical mode decomposition/Hilbert transform analysis of postural responses to small amplitude anterior-posterior sinusoidal translations of varying frequencies by Rakesh Pilkar, Erik M. Bollt, Charles Robinson

“…The Empirical Mode Decomposition (EMD) algorithm decomposes the Center of Pressure (CoP) data (5 young, 4 mature adults) into Intrinsic Mode Functions (IMFs). …”
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