Knowledge triple extraction in cybersecurity with adversarial active learning by Tao LI, Yuanbo GUO, Ankang JU

“…Aiming at the problem that using pipeline methods for extracting cybersecurity knowledge triples may cause the errors propagation of entity recognition and did not consider the correlation between entity recognition and relation extraction,and training triple extraction model lacked labeled corpora,an end-to-end cybersecurity knowledge triple extraction method with adversarial active learning was proposed.For knowledge triple extraction,the conventional entity recognition and relation extraction were modelled as sequence labeling task through joint labeling strategy firstly.And then,a BiLSTM-LSTM-based model with dynamic attention mechanism was designed to jointly extract entities and relations,forming triples.Finally,with adversarial learning framework,a discriminator was trained to incrementally select high-quality samples for labeling,and the performance of the joint extraction model was continuously enhanced by iterative retraining.Experiments show that the proposed joint extraction model outperforms the existing cybersecurity knowledge triple extraction methods,and demonstrate the effectiveness of proposed adversarial active learning scheme.…”
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An activity of daily living primitive–based recognition framework for smart homes with discrete sensor data by Rong Chen, Danni Li, Yaqing Liu

“…The ordinal data can be likely less discriminative due to the great uncertainty in level of measurement. …”
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La recomposition des savoirs au Maghreb à l’époque de la coopération by Jean-Robert Henry

“…Indeed, a theoretical universalism intended as replacement for discriminating colonialist discourse, vested itself in a more or less modernized Marxist vulgate of the economy, sociology, linguistics, law, anthropology. …”
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Feature Extraction and Wear Damage Degree Identification of Planetary Gear based on PSO-FC Optimization KPCA by Yan He, Zongyan Wang

“…The optimization mathematical model of the kernel function scale parameter is constructed by means of Fisher criterion（FC） discriminate function in pattern recognition， and the improved particle swarm optimization method is applied to the optimization to fully improve the analysis performance of the kernel principal component analysis（KPCA） for nonlinear problem. …”
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Ear Recognition Based on Gabor Features and KFDA by Li Yuan, Zhichun Mu

“…For its eminent characteristics in spatial local feature extraction and orientation selection, Gabor filter based ear feature extraction is presented in this paper. Kernel Fisher Discriminant Analysis (KFDA) is then applied for dimension reduction of the high-dimensional Gabor features. …”
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Fractal Assessment of the Disturbances of Phosphate Series Using Lacunarity and Succolarity Analysis on Geoelectrical Images (Sidi Chennane, Morocco) by Abderrahim Ayad, Saad Bakkali

“…This has an important implication to discriminate between the phosphate deposit at high risk of disturbances and the deposit at low risk. …”
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A Group Feature Screening Procedure Based on Pearson Chi-Square Statistic for Biology Data with Categorical Response by Hanji He, Jianfeng He, Guangming Deng

“…In the application of lung cancer diagnosis, the proposed method for imbalanced data categorization is impressive, and the dimension reduction using linear discriminant is still good.…”
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Research on anomaly detection algorithm based on sparse variational autoencoder using spike and slab prior by Huahua CHEN, Zhe CHEN

“…Anomaly detection remains to be an essential and extensive research branch in data mining due to its widespread use in a wide range of applications.It helps researchers to obtain vital information and make better decisions about data by detecting abnormal data.Considering that sparse coding can get more powerful features and improve the performance of other tasks, an anomaly detection model based on sparse variational autoencoder was proposed.Firstly, the discrete mixed modelspike and slab distribution was used as the prior of variational autoencoder, simulated the sparsity of the space where the hidden variables were located, and obtained the sparse representation of data characteristics.Secondly, combined with the deep support vector network, the feature space was compressed, and the optimal hypersphere was found to discriminate normal data and abnormal data.And then, the abnormal fraction of the data was measured by the Euclidean distance from the data feature to the center of the hypersphere, and then the abnormal detection was carried out.Finally, the algorithm was evaluated on the benchmark datasets MNIST and Fashion-MNIST, and the experimental results show that the proposed algorithm achieves better effects than the state-of-the-art methods.…”
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Policy-focused Stance Detection in Parliamentary Debate Speeches by Gavin Abercrombie, Riza Batista-Navarro

“…We analyse the output of the best performing system, finding that discriminating features for the task are highly domain-specific, and that speeches that address policy preferences proposed by members of the same party can be among the most difficult to predict. …”
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Almost general analysis of CKM and MNS matrices for hierarchical Yukawa structure and interpretation of Dirac CP phase probed by DUNE and T2HK by Masaki J.S. Yang

“…In this letter, we perform an almost general analysis of flavor-mixing matrices VCKM and UMNS to investigate the discriminative power of CP phases by next-generation neutrino oscillation experiments. …”
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The Virtual Meets the Real in Sports World: Is There a Circular Effect Between Traditional Sports and eSports Fan Identification? by Andre Ferreira Gavinho Cardoso, Victor Manoel Cunha de Almeida

“…Data analysis was completed by applying descriptive analysis, exploratory factor analysis, and confirmatory factor analysis, to verify the reliability of the constructs, as well as the convergent and discriminant validity. The Structural Equation Modeling technique was used to test the substantive hypotheses. …”
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Deep image semantic communication model for 6G by Feibo JIANG, Yubo PENG, Li DONG

“…Current semantic communication models still have some parts that can be improved in processing image data, including effective image semantic codec, efficient semantic model training, and accurate image semantic evaluation.Hence, a deep image semantic communication (DeepISC) model was proposed.The vision transformer-based autoencoder (ViTA) network was used to achieve high-quality image semantic encoding and decoding.Then, an autoencoder realized channel codec to ensure the transmission of semantics on the channel.Furthermore, the discriminator network (DSN) and ViTA’s dual network architecture were used to jointly train, thus improving the semantic accuracy of the reconstructed image.Finally, for different downstream vision tasks, different evaluation indicators of image semantics were presented.Simulation results show that compared with other schemes, DeepISC can more effectively restore the semantic features of the transmitted image, so that the reconstructed image can show the same or similar semantic results as the original image in various downstream tasks.…”
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Migrants' rights: problems remain by N. A. Voronina

“…The study notes that in recent years, Western countries have been reviewing approaches to state regulation of the social sphere, which in some cases discriminates towards refugees and displaced persons from other countries. …”
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Structure-guided engineering of immunotherapies targeting TRBC1 and TRBC2 in T cell malignancies by Mathieu Ferrari, Matteo Righi, Vania Baldan, Patrycja Wawrzyniecka, Anna Bulek, Alexander Kinna, Biao Ma, Reyisa Bughda, Zulaikha Akbar, Saket Srivastava, Isaac Gannon, Mathew Robson, James Sillibourne, Ram Jha, Mohamed El-Kholy, Oliver Muhammad Amin, Evangelia Kokalaki, Mohammed Amin Banani, Rehan Hussain, William Day, Wen Chean Lim, Priyanka Ghongane, Jade R. Hopkins, Dennis Jungherz, Marco Herling, Martin Welin, Sachin Surade, Michael Dyson, John McCafferty, Derek Logan, Shaun Cordoba, Simon Thomas, Andrew Sewell, Paul Maciocia, Shimobi Onuoha, Martin Pule

“…Unlike other hematologic malignancies, the lack of target antigens to discriminate healthy from malignant cells limits the efficacy of immunotherapeutic approaches. …”
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Advancements in Vision–Language Models for Remote Sensing: Datasets, Capabilities, and Enhancement Techniques by Lijie Tao, Haokui Zhang, Haizhao Jing, Yu Liu, Dawei Yan, Guoting Wei, Xizhe Xue

“…Differing from previous AI approaches that generally formulated different tasks as discriminative models, VLMs frame tasks as generative models and align language with visual information, enabling the handling of more challenging problems. …”
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Alterations of amino acids in older adults with Alzheimer’s Disease and Vascular Dementia by Xin Ma, Xin-Meng Wang, Guo-Zhang Tang, Yi Wang, Xue‑Chun Liu, Shuai-Deng Wang, Peng Peng, Xiu-Hong Qi, Xin-Ya Qin, Yue‑Ju Wang, Chen-Wei Wang, Jiang-Ning Zhou

“…Notably, creatine, spermidine, cystine, and tyrosine demonstrated favorable results in decision curve analyses and good discriminative performances, suggesting their potential for clinical application. …”
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Inference of Wildfire Causes From Their Physical, Biological, Social and Management Attributes by Yavar Pourmohamad, John T. Abatzoglou, Erica Fleishman, Karen C. Short, Jacquelyn Shuman, Amir AghaKouchak, Matthew Williamson, Seyd Teymoor Seydi, Mojtaba Sadegh

“…Our model more accurately separated wildfires ignited by natural versus human causes (93% accuracy), and discriminated among the 11 classes of human‐ignited wildfires with 55% accuracy. …”
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The symbiotic origin of the eukaryotic cell by López-García, Purificación, Moreira, David

“…Here, we review the recent discoveries that led to this conceptual shift, briefly evoking current models of eukaryogenesis and the challenges ahead to discriminate between them and to establish a detailed, plausible scenario that accounts for the evolution of eukaryotic traits from those of their prokaryotic ancestors.…”
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Specific types of male infertility are correlated with T cell exhaustion or senescence signatures by Giada Amodio, Giorgia Giacomini, Luca Boeri, Massimiliano Raffo, Simone Cilio, Edoardo Pozzi, Federico Belladelli, Fausto Negri, Anna Maria Ferrara, Alessia d’Arma, Francesca Romana Santoni de Sio, Luca Pagliardini, Enrico Papaleo, Eugenio Ventimiglia, Massimo Alfano, Francesco Montorsi, Andrea Salonia, Silvia Gregori

“…Transcriptomic profiling confirms the upregulation of genes associated with the interferon-gamma and -alpha responses in peripheral blood T cells of infertile men with oligo-astheno-teratozoospermia or non-obstructive azoospermia, with distinct T cell signatures of exhaustion and senescence discriminating the two infertile conditions. These findings provide evidence that subtypes of male infertility are characterized by specific immune signatures and unravel the potential link between infertility and the risk of developing secondary diseases.…”
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Quantitative Analysis and Fingerprint Profiles for Quality Control of Fructus Schisandrae by Gas Chromatography: Mass Spectrometry by Yong-Gang Xia, Bing-You Yang, Jun Liang, Qi Yang, Di Wang, Hai-Xue Kuang

“…Meanwhile, relative peak areas may be a feasible approach to discriminate the S. chinensis and S. sphenanthera. Finally, these pharmacologically active constituents in the titled plant, schisandrins A–C and schizandrols A and B, were quantitatively determined using a validated GC-MS method.…”
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