Re-mapping Zagreb‘s Urban Space by Martina Jakovčić, Karlo Mak

“…Based on the analysis of various spatial datasets, we assumed the existence of a queer men’s residential core in Zagreb, described its position within the city’s spatial structure, and examined the spatial dynamics of its development. …”
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Application on text classification of telecom user complaints based on GRW and FastText model by Jin ZHAO, Xiaojun YANG

“…With the widespread application of neural network, the application of neural network to natural language processing text classification problems has become an effective solution.The customer service center of telecom operator collected user complaint information from multiple channels.In order to automatically classify the complaint text information and assign it to the specific responsible department for processing and reply, enhancing customer perception further, a textclassification method based on GRW and FastTextmodel was proposed.Firstly, the GRW model was used to select the features of the complaint text, extract effective feature words, and then a user complaint text classification method based on FastText model was constructed.Experiments on public datasets and a complaint text data by one of telecom company show that the text classification method based on GRW and FastText model is better than naive Bayes, bidirectional LSTM and Bert pre-trained model in accuracy, Kappa coefficient and Hamming loss.…”
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Experimental assessment of аdversarial attacks to the deep neural networks in medical image recognition by D. M. Voynov, V. A. Kovalev

“…The white-box Projected Gradient Descent attacks were examined based on 8 classification tasks and 13 image datasets containing more than 900 000 chest X-ray and histology images of malignant tumors. …”
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Analyzing the Application of Machine Learning in Anemia Prediction by Li Yuxi

“…Machine learning techniques provide innovative solutions by analyzing complex datasets that incorporate questionnaire, clinical features, demographic information, and laboratory results, thereby enhancing the accuracy of anemia predictions. …”
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An Improved Recursive ARIMA Method with Recurrent Process for Remaining Useful Life Estimation of Bearings by Zeyu Luo, Xian-Bo Wang, Zhi-Xin Yang

“…The experiment on FEMTO datasets reveals that the proposed ARIMA-R method outperforms the ARNN method in terms of predictive performance evaluation indicators.…”
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Quelle base factuelle pour une stratégie européenne de développement durable dans les régions de montagne ? by Erik Gløersen, Clemens Mader, Engelbert Ruoss

“…Mountain territories have highly diverse social, economic and physical characteristics; their shared traits in terms of ecological fragility, economic development challenges and exposure to natural hazards are not reflected in mainstream datasets. Two complementary instruments are proposed to produce and present evidence for sustainable resource management and processes: the Nexus Model and the Sustainability Profile Matrix. …”
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Efficient privacy-preserving decision tree classification protocol by Lichuan MA, Jiayi PENG, Qingqi PEI, Haojin ZHU

“…To provide privacy-preserving decision tree classification services in the Internet of things (IoT) big data scenario, an efficient privacy-preserving decision tree classification protocol was proposed by adopting the secure multiparty computation framework into the classification model.The entire protocol consisted of three parts: the original decision tree model mixing, the Boolean share-based privacy-preserving comparing, and the 1-out-of-n oblivious transfer-based classification result obtaining.Via the proposed protocol, the service providers could protect the parameters of their decision tree models and the users were able to derive the classification result without exposing their privately hold data.Through a concrete security analysis, the proposed protocol was proved to be secure against semi-honest adversaries.By implementing the proposed protocol on various practical decision tree models from open datasets, the classification accuracy and the average time cost for completing one privacy-preserving classification service were evaluated.After compared with existing related works, the performance superiority of the proposed protocol is demonstrated.…”
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Recurrences Reveal Shared Causal Drivers of Complex Time Series by William Gilpin

“…Through extensive benchmarks against classical signal processing and machine learning techniques, we demonstrate our method’s ability to extract causal drivers from diverse experimental datasets spanning ecology, genomics, fluid dynamics, and physiology.…”
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Incremental Gene Expression Programming Classifier with Metagenes and Data Reduction by Joanna Jedrzejowicz, Piotr Jedrzejowicz

“…The approach enables us to deal with big datasets through controlling computation time using data reduction mechanisms. …”
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Spatiotemporal squeeze-and-excitation residual multiplier network for video action recognition by Huilan LUO, Kang TONG

“…Aiming at the shortcomings of shallow networks and general deep models in two-stream network structure,which could not effectively learn spatial and temporal information,a squeeze-and-excitation residual network was proposed for action recognition with a spatial stream and a temporal stream.Meanwhile,the long-term temporal dependence was captured by injecting the identity mapping kernel into the network as a temporal filter.Spatiotemporal feature multiplication fusion was used to further enhance the interaction between spatial information and temporal information of squeeze-and-excitation residual networks.Simultaneously,the influence of spatial-temporal stream multiplication fusion methods,times and locations on the performance of action recognition was studied.Given the limitations of performance achieved by a single model,three different strategies were proposed to generate multiple models,and the final recognition result was obtained by integrating these models through averaging and weighted averaging.The experimental results on the HMDB51 and UCF101 datasets show that the proposed spatiotemporal squeeze-and-excitation residual multiplier networks can effectively improve the performance of action recognition.…”
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Particle-flow reconstruction with Transformer by Wahlen Paul, Suehara Taikan

“…We are studying this architecture applied to the particle-flow method, which reconstructs particles by clustering hits at highly-segmented calorimeters. Using datasets consisting of one or two initial photons, the network is asked to predict clusters one by one using hits from the calorimeters as input. …”
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CFA-Based Splicing Forgery Localization Method via Statistical Analysis by Lei Liu, Peng Sun, Yubo Lang, Jingjiao Li

“…Experimental results on the Columbia and Korus datasets indicate that the proposed method outperforms the state-of-the-art methods and is also more robust to various attacks, such as noise addition, Gaussian filtering, and JPEG compression with a quality factor of 90.…”
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An Expert Diagnosis System for Parkinson Disease Based on Genetic Algorithm-Wavelet Kernel-Extreme Learning Machine by Derya Avci, Akif Dogantekin

“…The Parkinson disease datasets are obtained from the UCI machine learning database. …”
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A hybrid unsupervised machine learning model with spectral clustering and semi-supervised support vector machine for credit risk assessment. by Tao Yu, Wei Huang, Xin Tang, Duosi Zheng

“…Despite the efficacy of unsupervised learning methods in handling unlabeled datasets, their performance remains limited owing to challenges such as imbalanced data, local optima, and parameter adjustment complexities. …”
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Fusion reconstruction mechanism and contrast learning method for WSN abnormal node detection by YE Miao, CHENG Jin, HUANG Yuan, JIANG Qiuxiang, WANG Yong

“…Through a series of comparative experiments on actual public datasets and their experimental results, it is shown that the method designed has better accuracy and recall compared to traditional anomaly detection methods and recent graph neural network methods.…”
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Multilayer Perceptron for Robust Nonlinear Interval Regression Analysis Using Genetic Algorithms by Yi-Chung Hu

“…Simulation results demonstrate that the proposed method performs well for contaminated datasets.…”
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Semi-supervised emotion-driven music generation model based on category-dispersed Gaussian Mixture Variational Autoencoders. by Zihao Ning, Xiao Han, Jie Pan

“…Experimental results on real-world datasets demonstrate that the proposed method effectively separates music with different emotions in the latent space, thereby strengthening the association between music and emotions. …”
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Continuous User Verification in Cloud Storage Services using Deep Learning by burhan albayati

“…To increase the accuracy of making a reliable decision, this paper proposes to combine two private datasets which are real-life user interactions with the desktop computer and Dropbox Cloud storage. …”
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Shortening of 3'UTRs correlates with poor prognosis in breast and lung cancer. by Antonio Lembo, Ferdinando Di Cunto, Paolo Provero

“…Using large-scale gene expression datasets, we show that a similar phenomenon takes place in breast and lung cancer: tumors expressing shorter 3' UTRs tend to be more aggressive and to result in shorter patient survival. …”
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Study of forecasting urban private car volumes based on multi-source heterogeneous data fusion by Chenxi LIU, Dong WANG, Huiling CHEN, Renfa LI

“…By effectively capturing the spatio-temporal characteristics of urban private car travel, a multi-source heterogeneous data fusion model for private car volume prediction was proposed.Firstly, private car trajectory and area-of-interest data were integrated.Secondly, the spatio-temporal correlations between private car travel and urban areas were modeled through multi-view spatio-temporal graphs, the multi-graph convolution-attention network (MGC-AN) was proposed to extract the spatio-temporal characteristics of private car travel.Finally, the spatio-temporal characteristics and external characteristics such as weather were integrated for joint prediction.Experiments were conducted on real datasets, which were collected in Changsha and Shenzhen.The experimental results show that, compared with the existing prediction model, the root mean square error of the MGC-AN is reduced 11.3%～20.3%, and the average absolute percentage error is reduced 10.8%～36.1%.…”
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