Self-regulation as a type of managerial activity. by A. Algazina

“…The comparison of self-regulation other types of regulation (such as state regulation and co-regulation) highlighted the essential features of this phenomenon and the place of self regulation in the system of public administration. …”
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System of polarization autofluorescence diagnostics of biological layers with fuzzy logic of decision support by N.I. Zabolotna, V.V. Sholota

“…The article considers a new approach to solving the problem of increasing the reliability of diagnostics of biological tissues based on a combination of azimuthally invariant polarization and fluorescence methods for diagnosing the structure of optically anisotropic tissue samples. …”
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UX-MAPPER: An automated approach to analyze app store reviews with a focus on UX by Walter T. Nakamura, Edson C. C. de Oliveira, Elaine H. T. de Oliveira, Tayana Conte

“…From the participants’ feedback, we defined a set of suggestions to extract more useful features, which can contribute to future studies involving user review analysis. …”
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Learning a prior on regulatory potential from eQTL data. by Su-In Lee, Aimée M Dudley, David Drubin, Pamela A Silver, Nevan J Krogan, Dana Pe'er, Daphne Koller

“…The extent to which the different features influence the regulatory potential is learned automatically, making Lirnet readily applicable to different datasets, organisms, and feature sets. …”
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Child-Sum (N2E2N)Tree-LSTMs: An interactive Child-Sum Tree-LSTMs to extract biomedical event by Lei Wang, Han Cao, Liu Yuan

“…However, the original Child-Sum Tree-LSTMs ignores edge features during aggregating the sub-nodes hidden states. …”
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Addressing cross-population domain shift in chest X-ray classification through supervised adversarial domain adaptation by Aminu Musa, Rajesh Prasad, Monica Hernandez

“…Adversarial training fine-tunes the feature extractor, making features from both domains indistinguishable, thereby creating domain-invariant features. …”
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Pediatric burns and the leading factors of burn injury by Abdulkadir Başaran, Özer Özlü

“…Objective: Burn trauma is an important health problem especially in children who are mostly the affected group as they are not fully capable of protecting themselves from injuries. …”
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On expansions for nonlinear systems Error estimates and convergence issues by Beauchard, Karine, Le Borgne, Jérémy, Marbach, Frédéric

“…In particular, intrinsic formulas allowing to decouple time-dependent features from geometry-dependent features of the solution have been extensively studied.First, we give a didactic review of classical expansions for formal linear differential equations, including the celebrated Magnus expansion (associated with coordinates of the first kind) and Sussmann’s infinite product expansion (associated with coordinates of the second kind). …”
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Histopathological Image Analysis Using Deep Learning Framework by Sudha Rani Vupulluri, Jogendra Kumar Munagala

“…Graph-segmented images retrieve relevant features. Using recursive feature removal, breast cancer photographs are categorized. …”
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An Elderly-Oriented Form Design of Low-Speed New Energy Vehicles Based on Rough Set Theory and Support Vector Regression by Zimo Chen

“…Second, the cars’ appearances are deconstructed by morphological analysis, and the key design features affecting elderly-oriented satisfaction are identified by a rough set attribute reduction algorithm. …”
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Advancing Nighttime Object Detection through Image Enhancement and Domain Adaptation by Chenyuan Zhang, Deokwoo Lee

“…Due to the lack of annotations for nighttime low-light images, object detection in low-light images has always been a challenging problem. Achieving high-precision results at night is also an issue. …”
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Responsiveness to the Context: Information–Task–Situation Decisional Strategies and Electrophysiological Correlates by Angelica Daffinà, Carlotta Acconito, Michela Balconi

“…A total of 51 individuals performed a decision-making task that required participants to face real-life decision-making situations, during which an unexpected event prompted them to appraise the situation and rely on different sources of contextual features to make the best decision and manage the problem. …”
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An attention-based loss function and synthetic minority oversampling technique for alleviating class imbalance in predicting diabetes by Santanu Roy, Reshma Rachel Cherish, Gifty Roy

“…(ii) A Swish activation function is deployed in the hidden layer of DB-Lite instead of Rectified Linear Unit (ReLU) to deal with the non-linear dependency of features with the final outcome. (iii) The synthetic minority oversampling technique (SMOTE) is used as a pre-processing technique to mitigate the class imbalance problem from the Pima dataset. …”
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A UAV-Based Multi-Scenario RGB-Thermal Dataset and Fusion Model for Enhanced Forest Fire Detection by Yalin Zhang, Xue Rui, Weiguo Song

“…A time-synchronized multi-scene, multi-angle aerial RGB-Thermal dataset (RGBT-3M) with “Smoke–Fire–Person” annotations and modal alignment via the M-RIFT method was constructed as a way to address the problem of data scarcity in wildfire scenarios. Finally, we propose a CP-YOLOv11-MF fusion detection model based on the advanced YOLOv11 framework, which can learn heterogeneous features complementary to each modality in a progressive manner. …”
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Modern trends in chronic pain treatment with opioid analgetics by E. S. Vvedenskaya

“…It gives the information on the possibility and features of narcotic analgesics minimal dosages use for moderate pain control. …”
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A Predictive Approach for Enhancing Accuracy in Remote Robotic Surgery Using Informer Model by Muhammad Hanif Lashari, Shakil Ahmed, Wafa Batayneh, Ashfaq Khokhar

“…The method integrates the optimization problem into the Informer model by embedding constraints such as energy efficiency, smoothness, and robustness into its training process using a differentiable optimization layer. …”
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Predicting correlation relationships of entities between attack patterns and techniques based on word embedding and graph convolutional network by Weicheng QIU, Xiuzhen CHEN, Yinghua MA, Jin MA, Zhihong ZHOU

“…Threat analysis relies on knowledge bases that contain a large number of security entities.The scope and impact of security threats and risks are evaluated by modeling threat sources, attack capabilities, attack motivations, and threat paths, taking into consideration the vulnerability of assets in the system and the security measures implemented.However, the lack of entity relations between these knowledge bases hinders the security event tracking and attack path generation.To complement entity relations between CAPEC and ATT＆amp;CK techniques and enrich threat paths, an entity correlation prediction method called WGS was proposed, in which entity descriptions were analyzed based on word embedding and a graph convolution network.A Word2Vec model was trained in the proposed method for security domain to extract domain-specific semantic features and a GCN model to capture the co-occurrence between words and sentences in entity descriptions.The relationship between entities was predicted by a Siamese network that combines these two features.The inclusion of external semantic information helped address the few-shot learning problem caused by limited entity relations in the existing knowledge base.Additionally, dynamic negative sampling and regularization was applied in model training.Experiments conducted on CAPEC and ATT＆amp;CK database provided by MITRE demonstrate that WGS effectively separates related entity pairs from irrelevant ones in the sample space and accurately predicts new entity relations.The proposed method achieves higher prediction accuracy in few-shot learning and requires shorter training time and less computing resources compared to the Bert-based text similarity prediction models.It proves that word embedding and graph convolutional network based entity relation prediction method can extract new entity correlation relationships between attack patterns and techniques.This helps to abstract attack techniques and tactics from low-level vulnerabilities and weaknesses in security threat analysis.…”
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RP-DETR: end-to-end rice pests detection using a transformer by Jinsheng Wang, Tao Wang, Qin Xu, Lu Gao, Guosong Gu, Liangquan Jia, Chong Yao

“…In this regard, the paper introduces an effective rice pest detection framework utilizing the Transformer architecture, designed to capture long-range features. The paper enhances the original model by adding the self-developed RepPConv-block to reduce the problem of information redundancy in feature extraction in the model backbone and to a certain extent reduce the model parameters. …”
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A dual-stream ordered topology-aware network for accurate fish counting in aquaculture environments by Jiaming Xin, Zhengmeng Wu, Tongtong Gu, Yiying Wang, Dashe Li, Bin Wang

“…These features are then aggregated via a dynamic restoration unit, effectively mitigating the long-tail problem caused by uneven fish distribution. …”
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GTrans: Generic Knowledge Graph Embedding via Multi-State Entities and Dynamic Relation Spaces by Zhen Tan, Xiang Zhao, Yang Fang, Weidong Xiao

“…Eigenstate represents the features that an entity intrinsically owns, and mimesis expresses the features that are affected by associated relations. …”
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