Embedding Ethics Into Artificial Intelligence: Understanding What Can Be Done, What Can't, and What Is Done by Clayton Peterson

“…Given the impact of autonomous technologies on individuals and society, it is worth taking the time to assess and manage the ethical aspects and possible consequences of our technological endeavors. While the growing rapidity of autonomous decision processes makes it hard to keep individuals in the decision loops, people are turning their attention to the ways in which ethics could be integrated to machines and algorithms, as well as to the possibility of defining autonomous ethical machines that would be able to solve ethical dilemmas and act ethically (e.g. autonomous vehicles). …”
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Interpretable Machine Learning for the German residential rental market – shedding light into model mechanics by Severin Bachmann

“…DT models capture intricate interactions among variables with fewer features, while XGB accommodates more variables, emphasizing its higher complexity and thus superior performance. …”
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Real-Time Football Match Prediction Platform by An Zhongqi

“…The platform’s real-time data updating mechanism ensures prediction accuracy, while the integration of multiple models through a Stacking method further enhances reliability. …”
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New Metaphorical Models in Modern Sports Discourse by A. N. Gritsenko, P. V. Moroslin

“…The novelty of the study lies in revealing the fact that more and more new conceptual areas are involved in presenting sporting events and building communication with reader: various terms of IT technologies, the world of TV series and computer games, while new stable systems of comparison begin to form: “sport” — “virtual computer world”, “sport” — “series”. …”
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Modeling and proving dynamic behaviors of a routing protocol: A tutorial by Agnieszka Paszkowska, Konrad Iwanicki

“…By building a dedicated model of the protocol, we illustrate common problems, such as keeping complexity in control, modeling processing and communication, abstracting algorithms comprising the protocol, and dealing with open issues and external dependencies. …”
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Rise of the microsong: the platformification of music on TikTok as an artform by Peter Stones

“…The findings suggest that while established artists and music production teams are better placed to overcome the challenges of platformification, the creation of microsongs remains a significant challenge for all musicians and their authenticity.…”
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Investigating the dynamics and uncertainties in portfolio optimization using the Fourier-Millen transform. by Muhammad Hilal Alkhudaydi, Aiedh Mrisi Alharthi

“…Investors will always look for a portfolio that can handle the required amount of risk while still producing the desired level of expected returns. …”
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Unlocking the power of antimicrobial peptides: advances in production, optimization, and therapeutics by Mohd Sadeeq, Yu Li, Chaozhi Wang, Feifei Hou, Jia Zuo, Peng Xiong

“…Their broad-spectrum efficacy and inherent low resistance development are countered by production challenges, including limited yields and proteolytic degradation, which restrict their clinical translation. While chemical synthesis offers precise structural control, it is often prohibitively expensive and complex for large-scale production. …”
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Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN by Yousuf Babiker M. Osman, Wei Li

“…Moreover, stochastic gradient descent (SGD) is used to train each layer of SAE to optimize weight parameters, while a strategy of genetic algorithms to identify the number of neurons in each hidden layer is developed. …”
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Efficient knowledge updating method for inconsistent decision tables by Changchun Li

“…Following the proposed principles, incremental algorithms for acquiring approximations in IDTs are presented while the objects change with time. …”
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Prediction of customer engagement behaviour response to marketing posts based on machine learning by Yonghui Dai, Tao Wang

“…It is proved that the post features designed by humans can be used to get good predictions, while the best results are achieved by combining the human-designed features with the high-dimensional features automatically extracted from post texts by the BERT model. …”
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Precision neuropsychology in the area of AI by Astri J. Lundervold

“…By providing practical implementation guidelines while preserving holistic patient care, precision neuropsychology shows promise for enhancing both diagnostic accuracy and treatment efficacy in neuropsychological practice.…”
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Retracted: A Novel Radio Frequency Identification Collision Resolution Method Based on Statistical Learning by Zhong Dongbo

“…Unlike traditional algorithms, the proposed method does not require prior knowledge of the number of clusters and does not need to constantly iterate. …”
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Essay Answer Detection System Uses Cosine Similarity and Similarity Scoring in Sentences by Siti Yuliyanti, Diah Hidayatul Ula

“…To improve accuracy and usability, future developments could use sophisticated text scoring algorithms and provide more features. This study highlights the importance of automated grading systems for optimizing essay scoring in educational settings while maintaining scalability and reliability. …”
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Mapping Data to Concepts: Enhancing Quantum Neural Network Transparency with Concept-Driven Quantum Neural Networks by Jinkai Tian, Wenjing Yang

“…Experimental results demonstrate that CD-QNN maintains high predictive accuracy while offering clear and meaningful explanations of its decision-making process. …”
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Aspirational Politics of Talent Acquisition: Entrepreneurial Limits and Indian Short Video Platforms by Rahul Mukherjee

“…The article contends that while theorizing aspirational politics, it is not enough to study (in isolation) how creators aspire to be more successful and gain more followers and influence. …”
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Multi-step partitioning combined with SOM neural network-based clustering technique effectively improves SAT solver performance by Siyu Yun, Xinsheng Wang

“…The primary issue of SAT solver now is the divergence between SAT used in industry and research on pure solution algorithms. We propose a strategy for partitioning the SAT problem based on the structural information then solving it. …”
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PCA-based membership inference attack for machine learning models by Changgen PENG, Ting GAO, Huilan LIU, Hongfa DING

“…Aiming at the problem of restricted access failure in current black box membership inference attacks, a PCA-based membership inference attack was proposed.Firstly, in order to solve the restricted access problem of black box membership inference attacks, a fast decision membership inference attack named fast-attack was proposed.Based on the perturbation samples obtained by the distance symbol gradient, the perturbation difficulty was mapped to the distance category for membership inference.Secondly, in view of the low mobility problem of fast-attack, a PCA-based membership inference attack was proposed.Combining the algorithmic ideas based on the perturbation category in the fast-attack and the PCA technology to suppress the low-migration behavior caused by excessive reliance on the model.Finally, experiments show that fast-attack reduces the access cost while ensuring the accuracy of the attack.PCA-based attack is superior to the baseline attack under the unsupervised setting, and the migration rate of model is increased by 10% compared to fast-attack.…”
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Fast quantitative time lapse displacement imaging of endothelial cell invasion. by Christian Steuwe, Marie-Mo Vaeyens, Alvaro Jorge-Peñas, Célie Cokelaere, Johan Hofkens, Maarten B J Roeffaers, Hans Van Oosterwyck

“…SPIM successfully tackles the problem of imaging large volumes while upholding the spatial resolution required for the analysis of matrix displacements at a subcellular level. …”
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A Rational Cluster Strategy: Manoeuvring between Market and Government Failures by Evgeniy Kutsenko

“…It is argued that an efficient policy should be aimed at dealing with market failures, while the procedures and implementing algorithms — at overcoming government failures.      …”
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