The Patient-Reported Outcomes Thermometer–5-Item Scale (5T-PROs): Validation of a New Tool for the Quick Assessment of Overall Health Status in Painful Rheumatic Diseases by Fausto Salaffi, Marco Di Carlo, Marina Carotti, Sonia Farah

“…We used the intraclass correlation coefficient (ICC) as an estimate of test-retest reliability. Additionally, discriminant validity was tested using analysis of variance (ANOVA) with Bonferroni post hoc multiple comparisons, in different disease conditions. …”
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Predicting Treatment Outcomes in Patients with Low Back Pain Using Gene Signature-Based Machine Learning Models by Youzhi Lian, Yinyu Shi, Haibin Shang, Hongsheng Zhan

“…The Elastic Net with Logistic Regression achieved the highest accuracy of 88.7% ± 8.0% (mean ± standard deviation), followed closely by Elastic Net with Linear Discriminant Analysis (88.7% ± 7.5%) and Lasso with Multilayer Perceptron (87.7% ± 6.7%). …”
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GenVFNet: Generating Visual Field From Optical Coherence Tomography Angiography by Conditional Generative Adversarial Networks by Anita Manassakorn, Supatana Auethavekiat, Vera Sa-Ing, Sunee Chansangpetch, Kitiya Ratanawongphaibul, Nopphawan Uramphorn, Visanee Tantisevi

“…This study aimed to generate a visual field pattern deviation map (GenVF) from optical coherence tomography angiography (OCTA) using conditional generative adversarial networks (cGAN), namely GenVFNet. cGAN consisted of two components: generator and discriminator. The generator consisted of encoder and decoder blocks and the discriminator was the classification learner. …”
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Psychometric properties of the Iranian version of the polycystic ovary syndrome quality of life questionnaire for married and unmarried women with PCOS: PCOSQoL-47 and PCOSQoL-42 by Fatemeh Bazarganipour, Seyed Abdolvahab Taghavi, Ali Montazeri, Fazlollah Ahmadi, Zahra Derakhshideh, Zahra Asadikalameh

“…Subsequently, a semi-structured interview was carried out to evaluate face validity. Consequently, discriminant validity was assessed using the known groups comparison. …”
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Multi-scale aware dual path network for face detection in resource-constrained edge computing environment by Qi QI, Yingxin MA, Jingyu WANG, Haifeng SUN, Jianxin LIAO

“…Aiming at the problem that face detectors with complex deep neural structures are difficult to deploy in the resource-constrained edge computing environment,to reduce the resource consumption while maintain the accuracy in complex scenes such as multi-scale face changes,occlusion,blur,and illumination,SDPN(multi-scale aware dual path network) for face detection was proposed.The Face-ResNet (face residual neural network) was improved,and a dual path shallow feature extractor was used to understand the multi-scale information of the image through parallel branches.Then the deep and shallow feature fusion module,a combination of the underlying image information and the high-level semantic feature,was used in conjunction with the multi-scale awareness training strategy to supervise the multi-branch learning discriminating features.The experimental results show that SDPN can extract more diversified features,which effectively improve the accuracy and robustness of face detection while maintaining the efficiency of the model and low inference delay.…”
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Single-Object-Based Region Growth: Key Area Localization Model for Remote Sensing Image Scene Classification by Feiyang Li, Jiangtao Wang, Mingyang Wang, Ziyang Wang

“…To tackle this problem, this paper proposes a single-object-based region growth algorithm to effectively localize the most key area in the whole image, so as to generate more discriminative local fine-grained features for the image scene. …”
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Tracking algorithm of Siamese network based on online target classification and adaptive template update by Zhiwang CHEN, Zhongxin ZHANG, Juan SONG, Haipeng LEI, Yong PENG

“…Aiming at the problem that tracking algorithm of Siamese network learned the embedded features of the tracked target and the object in the offline training stage, and these embedded features often lacked the target-specific context information, which made these tracking algorithms less robust, a tracking algorithm of the Siamese network based on online target classification and adaptive template update was proposed, which used SiamRPN++ as the baseline algorithm.Firstly, a cross-correlation feature map supervision module for classification was designed in the offline training phase to learn more discriminative embedded features.Secondly, an online target classification module that included an attention mechanism in the online tracking phase was designed, and the online update filter strategy in the module was used to filter out the background noise.Finally, an adaptive template update module was designed to update the target template information using the UpdateNet.The results of experiments on VOT2018 and VOT2019 datasets verify the effectiveness of the proposed algorithm, which brings 13.5% and 18.2% (EAO) improvement respectively compared with the baseline algorithm SiamRPN++.…”
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Differentially private sequence generative adversarial networks for data privacy masking by Yu ZHANG, Xixiang LYU, Yucong ZOU, Yige LI

“…Based on generative adversary networks and the differential privacy mechanism,a differentially private sequence generative adversarial net (DP-SeqGAN) was proposed,with which the privacy of text sequence data sets can be filtered out.DP-SeqGAN can be used to automatically extract important features of a data set and then generate a new data set which was close to the original one in terms of data distributions.Based on differential privacy,randomness is introduced to the model,which improves the privacy of the generated data set and further reduces the over fitting of the discriminator.The proposed DP-SeqGAN was universal,so there is no need to adjust the model adaptively for datasets or design complex masking rules against dataset characters.The experiments show that the privacy and usability of a sequence data set are both improved significantly after it is processed by the DP-SeqGAN model,and DP-SeqGAN can greatly reduce the success rate of member inference attacks against the generated data set.…”
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Action recognition method based on fusion of skeleton and apparent features by Hongyan WANG, Hai YUAN

“…Focusing on the issue that traditional skeletal feature-based action recognition algorithms were not easy to distinguish similar actions, an action recognition method based on the fusion of deep joints and manual apparent features was considered.The joint spatial position and constraints was firstly input into the long short-term memory (LSTM) model equipped with spatio-temporal attention mechanism to acquire spatio-temporal weighted and highly separable deep joint features.After that, heat maps were introduced to locate the key frames and joints, and manually extract the apparent features around the key joints that could be considered as an effective complement to the deep joint features.Finally, the apparent features and the deep skeleton features could be fused frame by frame to achieve effectively discriminating similar actions.Simulation results show that, compared with the state-of-the-art action recognition methods, the proposed method can distinguish similar actions effectively and then the accuracy of action recognition is promoted rather obviously.…”
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Scrambler blind recognition method based on soft information by Ze-liang CHEN, Hua PENG, Ke-xian GONG, Pei-dong YU

“…Two scrambler blind recognition methods based on soft information were proposed for received signal in non-cooperative ways.The first method established a cost function of the scrambler coefficients by using the soft information,and adopted the optimization theory of real number field for positive solution.So it didn’t need to traverse the closed set of test polynomial any more.The second method built conformity degree concept with the soft information,and used the size of conformity of each test scrambler polynomial as the discriminant criteria.So it made more full use of the received information compared to the hard sentence recognition algorithm.Simulation results show that the first method can shorten the recognition time of a synchronous scrambler polynomial from 5 min 18 s to 8 s compared with the traversal method put forward by Cluzeau,and the second method has 2 dB SNR gain when to achieve the relatively high accuracy compared with the hard sentence recognition algorithm.…”
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STUDY ON FAULT DIAGNOSIS METHOD BASED ON MORLET WAVELET-SVD AND VPMCD by QI Peng, FAN YuGang, WU JianDe

“…A novel method based on Morlet wavelet-Singular Value Decomposition（ SVD） and Variable Predictive Model based Class Discriminate（ VPMCD） was proposed in this paper aiming to solve this problem. …”
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Underwater Incomplete Target Recognition Network via Generating Feature Module by Qi Shen, Jishen Jia, Lei Cai

“…Specifically, for targets that lack features, features are generated by dual discriminators and generators to improve target detection accuracy. …”
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The Online Jealousy Scale: an adaptation, extension, and psychometric analysis of the Facebook Jealousy Scale by Kieran T. Sullivan, Kathryn Bruchmann

“…ObjectiveTo test the reliability and validity of the Online Jealousy Scale.BackgroundRomantic jealousy is often examined in online and social media settings and a validated measure of online jealousy is needed.MethodAcross two studies, the present research tests the psychometric properties of the Online Jealousy Scale (adapted from the Facebook Jealousy Scale) on an undergraduate (Study 1, N = 111) and two broader community (Study 2, N = 200; Study 3, N = 143) samples.ResultsData across all studies provide evidence of strong inter-item and test–retest reliability; and construct, convergent and discriminant validity. Consistent with other jealousy measures, evidence of three factors emerged: emotional, cognitive, and behavioral jealousy.DiscussionThese studies indicate that the OJS is a reliable and valid instrument.ImplicationsThis measure fills the need for a valid, reliable assessment of online jealousy and can be used in research about online jealousy across age and relationship type. …”
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Replicating the comparison between item-based tests and language samples in Portuguese kindergarteners’ language assessment by Alves Paula C., Vale Ana Paula

“…Additionally, two relatively innovative trends emerged: errors produced in the narrative seem to be a good discriminative metric for this age range, and testing language by units (words and sentences) might be appropriate to assess language development.…”
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Feature Selection Using Particle Swarm Optimization in Intrusion Detection by Iftikhar Ahmad

“…Evolutionary optimization approach like genetic algorithm (GA) has been used to search the most discriminative subset of transformed features. The particle swarm optimization (PSO) is another optimization approach based on the behavioral study of animals/birds. …”
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Cancer Classification Using Pattern Recognition and Computer Vision Techniques by Haddou Bouazza Sara, Haddou Bouazza Jihad

“…A comparative analysis of classifiers, including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), and Linear Discriminant Analysis (LDA), demonstrated that the HFWGS method consistently improved classification performance, achieving 100% accuracy with a reduced subset of genes. …”
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Class imbalance learning–driven Alzheimer’s detection using hybrid features by Ran Baik

“…Statistical and histogram of gradients is used from shape-based features. Fisher linear discriminant analysis is used for dimensionality reduction and the resampling method is used to handle the class imbalance problem. …”
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Advanced imaging techniques in crystal arthritis by Victor Laurent, Georgios Filippou, Silvia Sirotti, Tristan Pascart

“…In CPPD disease, the definition of elementary lesions and their scoring has been well established for ultrasound, while the proof of concept that DECT can help discriminate calcium pyrophosphate crystal deposits among other calcium-containing structures has been shown. …”
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Criterion for Unbounded Synchronous Region in Complex Networks by Jin Zhou

“…Synchronization of complex networks has been extensively studied in many fields, where intensive efforts have been devoted to the understanding of its mechanisms. As for discriminating network synchronizability by Master Stability Function method, a dilemma usually encountered is that we have no prior knowledge of the network type that the synchronous region belongs to. …”
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Anti-Oppressive Practice and Reflexive Lifeworld-Led Approaches to Care: A Framework for Teaching Nurses about Social Justice by Jacqueline Sarah Hutchison

“…This paper seeks to identify concepts and approaches to understanding oppression, power, and justice which enable nurses to challenge the structures in health care environments which discriminate or disempower clients. Anti-oppressive practice theory and reflexive lifeworld-led approaches to care enable nurses to be critical of their practice. …”
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