Overall Efficiency of Four-Stage Structure with Undesirable Outputs: A New SBM Network DEA Model by Nasim Roudabr, Seyyed Esmaeil Najafi, Zohreh Moghaddas, Farzad Movahedi Sobhani

“…The proposed model differs from those proposed by other studies in the fact that all DEA models of benchmarking consider input and output values to be linear. However, in real-world problems, many DMU inputs and outputs have nonlinear values (values are the coefficients of inputs or outputs in modeling and can be the price of desirable outputs or the cost of inputs and undesirable outputs), something which was taken into account in the modeling process in this study. …”
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A Parametric Method for Ranking Intuitionistic Fuzzy Numbers and Its Application to Solve Intuitionistic Fuzzy Network Data Envelopment Analysis Models by B. Shakouri, R. Abbasi Shureshjani, B. Daneshian, F. Hosseinzadeh Lotfi

“…Also, in three appropriate examples, the validity of the suggested method and its capacity to solve real-world problems are illustrated.…”
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Hybrid clustering strategies for effective oversampling and undersampling in multiclass classification by Amirreza Salehi, Majid Khedmati

“…Abstract Multiclass imbalance is a challenging problem in real-world datasets, where certain classes may have a low number of samples because they correspond to rare occurrences. …”
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Multiscale network alignment model based on convolution of homogeneous multilayer graphs by CUI Jiahao, JIANG Tao, XU Mengyao

“…Experimental results on two real-world social networks of different scales show that the proposed method can effectively improve the performance of social network alignment tasks.…”
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Impulsive Control and Synchronization of Complex Lorenz Systems by Shaban Aly, Ali Al-Qahtani, Houari B. Khenous, Gamal M. Mahmoud

“…Nonlinear systems involving impulse effects, appear as a natural description of observed evolution phenomena of several real world problems; For example, many biological phenomena involving thresholds, bursting rhythm models in medicine and biology, optimal control models in economics, population dynamics and so forth do exhibit impulsive effects. …”
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Operational Risk Aggregation Based on Business Line Dependence: A Mutual Information Approach by Wenzhou Wang, Limeng Shi, Xiaoqian Zhu

“…The experiment on a real-world Chinese bank operational risk data set shows that using mutual information to model the dependencies between business lines is more reasonable than linear correlation.…”
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Optimizing Transit Network Departure Frequency considering Congestion Effects by Wei Tan, Xiaodong Peng, Jun Huang, Yuwen Wang, Jiandong Qiu, Xiaobo Liu

“…The effectiveness of the proposed model and algorithm is demonstrated through two test examples, one of which involves a real-world scenario comprising over 130 transit lines. …”
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On the Asymptotic Behavior of the Maximum and Record Values of Multivariate Data Using the R-ordering principle by Mahmoud H. Harpy, Haroon M. Barakat

“…Finally, we demonstrate in a real-world scenario how to model multivariate extreme data sets utilizing the R-ordering principle and different norms.…”
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Research Progress of Causal Inference in Bias Elimination by Chen Limanxi

“…The natural language processing (NLP) models have recently gained widespread attention and are increasingly being applied to real-world tasks. However, due to the presence of bias, the application of NLP models in specialized fields has led to various issues. …”
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Resilient Multi-Agent Systems Against Denial of Service Attacks via Adaptive and Activatable Network Layers by Deepalakshmi Babu Venkateswaran, Zhihua Qu

“…The simulation section, divided into two parts, demonstrates the effectiveness of the algorithm: one part showcases its scalability in a large-scale system, and the other applies it to a real-world power system using the IEEE 123-node system. …”
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Exploiting Blockchain Technology for Enhancing Digital Twins’ Security and Transparency by Alessio Ferone, Stefano Verrilli

“…In particular, we demonstrate how blockchain can improve critical aspects of the security and transparency of digital twins by analyzing a real-world scenario and evaluating produced experimental data. …”
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Efficient privacy-preserving image retrieval scheme over outsourced data with multi-user by Xiangyu WANG, Jianfeng MA, Yinbin MIAO

“…The traditional privacy-preserving image retrieval schemes not only bring large computational and communication overhead,but also cannot protect the image and query privacy in multi-user scenarios.To solve above problems,an efficient privacy-preserving content-based image retrieval scheme was proposed in multi-user scenarios.The scheme used Euclidean distance comparison technique to rank the pictures according to similarity of picture feature vectors and return top-k returned.Meanwhile,the efficient key conversion protocol designed in proposed image retrieval scheme allowed each search user to generate queries based on his own private key so that he can retrieval encrypted images generated by different data owners.Strict security analysis shows that the user privacy and cloud data security can be well protected during the image retrieval process,and the performance analysis using real-world dataset shows that the proposed image retrieval scheme is efficient and feasible in practical applications.…”
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Comparison of Ignition Control Techniques in HCCI Engines from Theoretical and Practical Perspectives by Yang Jiaqi

“…This paper aims to delve into the theoretical and practical aspects of ignition control methods in HCCI engines, highlighting the differences and challenges between theoretical models and real-world applications.…”
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SDN TCP-SYN Dataset: A dataset for TCP-SYN flood DDoS attack detection in software-defined networksMendeley Data by Sudesh Kumar, Sunanda Gupta

“…Generated in a controlled testbed using advanced simulation tools Mininet(v2.3.0) and real internet traffic captured from real-world internet browsing sessions via Google Chrome and recorded using Wireshark(v3.0.2), this dataset is essential for researchers and practitioners working on TCP-SYN flood DDoS attack detection and machine learning-based traffic classification. …”
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Development and trend of IoT identifier technology by Ye TIAN, Jia LIU, Jie SHEN

“…The Internet of things has broken through the traditional human-to-human communication model and introduced the perception of the real world,thereby establishing the communication between things,human being and things,as well as achieving the dynamic acquisition of information,intelligent processing,and seamless interaction and collaborative sharing.The IoT identifier that identifies and distinguishes different target objects is the basis and prerequisite for achieving the above mentioned information communications and various IoT applications.The IoT identifier is used to uniquely identify the physical and logical entities within a certain range,so that the network and application can manage the target objects based on it,and the acquisition,processing,transmission,and exchange of related information is the most important and fundamental resource in IoT Internet of things.Moreover,it is the “identity card” of IoT object.In order to uniquely identify various heterogeneous resources within a certain range,and to obtain and transmit related information based on the control and management of target objects,it is necessary to provide a identification resolution service based on the IoT identifier,and realize different levels of mapping between identifiers.…”
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Semi-supervised Gaussian process classification algorithm addressing the class imbalance by Zhan-guo XIA, Shi-xiong XIA, Shi-yu CAI, Ling WAN

“…The traditional supervised learning is difficult to deal with real-world datasets with less labeled information when the training sets class is imbalanced.Therefore,a new semi-supervised Gaussian process classification of address-ing was proposed.The semi-supervised Gaussian process was realized by calculating the posterior probability to obtain more accurate and credible labeled data,and embarking from self-training semi-supervised methods to add class label into the unlabeled data.The algorithm makes the distribution of training samples relatively balance,so the classifier can adaptively optimized to obtain better effect of classification.According to the experimental results,when the circum-stances of training set are class imbalance and much lack of label information,The algorithm improves the accuracy by obtaining effective labeled in comparison with other related works and provides a new idea for addressing the class im-balance is demonstrated.…”
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The history, current state and future possibilities of the non-invasive brain computer interfaces by Frederico Caiado, Arkadiy Ukolov

“…BCIs have evolved from early studies in neurophysiology to real-world applications that convert brain impulses into executable commands. …”
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A Similarity Classifier with Bonferroni Mean Operators by Onesfole Kurama, Pasi Luukka, Mikael Collan

“…The new proposed similarity classifier variants are tested on four real world medical research related data sets. The results are compared with results from two previously presented similarity classifiers, one based on the generalized mean and another based on an arithmetic mean operator. …”
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Feature Extraction and Classification of Music Content Based on Deep Learning by Qianqiu Shi, Young Chun Ko

“…To study the use of in-depth training in extracting and classifying the content of music samples, the work offers an algorithm for identifying and classifying musical genres based on a deep network of beliefs, enabling it to be used to extract and classify traditional Chinese musical instruments, and using real-world experiments to test its performance after training. …”
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An Extreme Learning Machine-Based Community Detection Algorithm in Complex Networks by Feifan Wang, Baihai Zhang, Senchun Chai, Yuanqing Xia

“…Furthermore, results of extensive experiments undertaken on computer-generated networks and real-world datasets illustrate acceptable performances of the introduced algorithm in comparison with other typical community detection algorithms.…”
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