Network traffic classification using decision tree based on minimum partition distance by Zhe YANG, Ling-zhi LI, Qi-jin JI, Yan-qin ZHU

“…Before data communications,every application protocol to handshake at application layer and transmit some parameters.This process is quite different according to the protocols,such as the packet direction,payload size and the information entropy of each packet payload.So according to these features,decision tree algorithm based on minimum partition distance was used to train the classifier.The results of the offline experiments on real network traces and the online classification experiments in campus network indicate that,analyzing the first four or six packets of each flow is enough to classify eight common used application protocols with high overall accuracy and low cost.Contrast to other machine learning algorithms,decision tree can achieve better ent traces and low classification time.So it is very suitable for real-time traffic classification.…”
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Investing in Private Equity in Brazil by Antônio Marcos Duarte Junior, Luiz Carlos Barbosa Medeiros

“…The proposed methodology is based on multi-criteria decision-making. Real data obtained from one of the largest pension funds in Brazil is used to illustrate a practical application of the methodology when selecting investments among eleven private equity funds available in the local financial market. …”
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BCP-based joint delegation learning model and protocol by Sheng GAO, Kang XIANG, Youliang TIAN, Weijie TAN, Tao FENG, Xiaoxue WU

“…In order to realize data security sharing and reduce the computing costs of clients in data mining process, a joint delegation learning model and protocol based on BCP homomorphic encryption algorithm was proposed.Firstly, a privacy preserving method based on false records was proposed for the security of decision tree model.Secondly, in view of the vertical and horizontal distribution of data, the corresponding delegation learning protocols based on privacy preserving delegation dot product algorithm and privacy preserving delegation entropy algorithm was proposed.Finally, the security proof and the performance analysis of delegation learning protocols and decision tree model structure were given.The results show that the privacy protection method based on false records does not affect the final model construction, and the final model obtained by each client is the same as that constructed by real data.…”
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A selection mechanism using multi-criteria evaluation and hierarhical classifying tree for resume data processing by O. V. German, J. O. German, S. Nasr

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Rethinking military command and control systems by George-Ion TOROI

“…In the context of new multi-domain operational paradigms and accelerated technological progress, C2 adaptation involves the integration of emerging technologies such as artificial intelligence, automation and real-time response capabilities to optimize decision-making. …”
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Multilevel Constrained Bandits: A Hierarchical Upper Confidence Bound Approach with Safety Guarantees by Ali Baheri

“…The multi-armed bandit (MAB) problem is a foundational model for sequential decision-making under uncertainty. While MAB has proven valuable in applications such as clinical trials and online advertising, traditional formulations have limitations; specifically, they struggle to handle three key real-world scenarios: (1) when decisions must follow a hierarchical structure (as in autonomous systems where high-level strategy guides low-level actions); (2) when there are constraints at multiple levels of decision-making (such as both system-wide and component-level resource limits); and (3) when available actions depend on previous choices or context. …”
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Optimization of multiple access in the energy harvesting wireless sensor network with delivery deadline constraint by Aoqin YANG, Aoyu GONG, Ting FANG, Lei DENG, Qiang LI, Yijin ZHANG

“…With the wide application of the energy harvesting wireless sensor network (WSN) in many real-time communication scenarios, such as environmental monitoring, industrial automation and battlefield surveillance, the multiple access of such WSN needs to take into account both the delivery deadline constraint of data packets and the energy harvesting dynamics of sensor nodes.Due to the inherent decoupling of interference, delivery urgency and remaining energy, the design and optimization of such multiple access are more challenging than that of traditional multiple access that only needs to take into account the packet traffic pattern.A centralized access scheme was designed with the access actions relying on the global knowledge of current delivery urgency and remaining energy.And then, to avoid the costly overhead in the centralized access, a decentralized access scheme was designed with the access probabilities merely relying on the local knowledge of delivery urgency and remaining energy.Under the objective of maximizing the network throughput, the centralized access schemes were formulated with complete and simplified knowledge as two Markov decision processes (MDPs), respectively, and the backward induction algorithm was used to obtain optimal centralized policies for these MDPs.Furthermore, the decentralized access was formulated with simplified knowledge as a decentralized MDP, and the Markov policy search was used to propose an ε-optimal decentralized policy.Simulations under a wide range of network configurations were provided to verify the effectiveness of the simplified modeling and demonstrate the performance advantage of the proposed polices.…”
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Offshoring Location Decision in Fuzzy Environment by Mehmet Şahin

“…Offshoring location selection is a crucial decision for firms in terms of competitiveness, flexibility, productivity, and profitability. …”
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RETRACTED ARTICLE: Confidence level based complex polytopic fuzzy Einstein aggregation operators and their application to decision-making process by Khaista Rahman, Mohammad Khishe

“…Abstract A complex Polytopic fuzzy set (CPoFS) extends a Polytopic fuzzy set (PoFS) by handling vagueness with degrees that range from real numbers to complex numbers within the unit disc. …”
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Assessment of Teaching Quality of Traditional Decorative Patterns in Colleges and Universities Using an MCDM Approach and Circular Intuitionistic Information by Zi Wang, Liping Pan

“…The superiority of this model lies in the fact that general structure, less time complexity, and prioritization of factors make it real. The suggested framework prioritizes decision criteria and manages ambiguity well, making it a reliable tool for assessing the quality of instruction. …”
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A convolutional autoencoder framework for ECG signal analysis by Ugo Lomoio, Patrizia Vizza, Raffaele Giancotti, Salvatore Petrolo, Sergio Flesca, Fabiola Boccuto, Pietro Hiram Guzzi, Pierangelo Veltri, Giuseppe Tradigo

“…The results show interesting results in automatic anomaly detection to support physicians in the decision process. The results show that the CAE-based framework is able to identify anomalies in ECG signals with a ROC AUC of 97.82% on simulated test set and a ROC AUC of 99.75% using a real test set. …”
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Implementation of Fuzzy Logic in the Monitoring and Controlling System for Temperature and pH of Fry Aquarium Water Betta Fish Based on the Internet of Things by Rico Wahyudi, Aulia Ullah, Hilman Zarory, Ahmad Faizal

“…To overcome this problem, a system based on the Internet of Things was developed(IoT) which can monitor in real time and control the temperature and pH of the water in the Betta fish fry pond. …”
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A Voting-Based Star Identification Algorithm Using a Partitioned Star Catalog by Xu He, Lei Zhang, Jiawei He, Zhiya Mu, Zhuang Lv, Jun Wang

“…During star identification, a method based on a voting decision is employed for feature matching in the basic unit. …”
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A Data Fusion System for Simulation of Critical Scenarios and Decision-Making by Jimmy Anderson Flórez Zuluaga, Esteban Patiño Carrasco, Jose David Ortega Pabón, Kelly Gallego León, O. Lucía Quintero Montoya

“… The decision-making (DM) process in critical environments is a complex process that can be simulated due to current telematic capabilities, which allow the real time interaction of large amounts of data. …”
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Research on the impact of enterprise digital transformation based on digital twin technology on renewable energy investment decisions by Mengying Cao, Wanxiao Song, Yanyan Xu

“…Digital twin technology, as an emerging tool, enables real-time monitoring, prediction, and optimization by creating dynamic virtual models of real-world processes. …”
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Enterprise information system automatic fault diagnosis and analysis method based on decision tree by Xin JIN, Longchuan YAN, Jun LIU, Shulin ZHANG

“…The algorithm was verified, and the decision tree model and training method was simulated and analyzed comparatively under R language environment, using alarm data extracted from real operation data of a typical large-scale enterprise system. …”
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Les activités de gestion d’alerte épidémiologique : les transformations induites par l’utilisation d’un système de surveillance en temps réel by Charlotte Gaudin, Natalie Bonnardel, Lilianne Pellegrin, Hervé Chaudet

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Assessing hazard prediction and risk calibration skills in experienced and novice e-scooter riders by Petya Ventsislavova, Lydia Harrison, Thom Baguley

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Impact of Environmental Conditions on Renewable Energy Prediction: An Investigation Through Tree-Based Community Learning by Ferdi Doğan, Saadin Oyucu, Derya Betul Unsal, Ahmet Aksöz, Majid Vafaeipour

“…The real-time prediction of energy production is essential for effective energy management and planning. …”
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OSFS‐Vague: Online streaming feature selection algorithm based on vague set by Jie Yang, Zhijun Wang, Guoyin Wang, Yanmin Liu, Yi He, Di Wu

“…Its main idea is to combine uncertainty and three‐way decision theories to improve feature selection from the traditional dichotomous method to the trichotomous method. …”
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