Current Issue : April-June Volume : 2025 Issue Number : 2 Articles : 5 Articles
Telecom fraud has emerged as one of the most pressing challenges in the criminal field. With advancements in artificial intelligence, telecom fraud texts have become increasingly covert and deceptive. Existing prevention methods, such as mobile number tracking, detection, and traditional machine-learning-based text recognition, struggle in terms of their real-time performance in identifying telecom fraud. Additionally, the scarcity of Chinese telecom fraud text data has limited research in this area. In this paper, we propose a telecom fraud text detection model, RoBERTa-MHARC, which combines RoBERTa with a multi-head attention mechanism and residual connections. First, the model selects data categories from the CCL2023 telecom fraud dataset as basic samples and merges them with collected telecom fraud text data, creating a five-category dataset covering impersonation of customer service, impersonation of leadership acquaintances, loans, public security fraud, and normal text. During training, the model integrates a multi-head attention mechanism and enhances its training efficiency through residual connections. Finally, the model improves its multi-class classification accuracy by incorporating an inconsistency loss function alongside the cross-entropy loss. The experimental results demonstrate that our model performs well on multiple benchmark datasets, achieving an F1 score of 97.65 on the FBS dataset, 98.10 on our own dataset, and 93.69 on the news dataset....
The dispatching telephone functionality acts as a pivotal interconnection between the power grid dispatch business and telecommunications business, playing a vital role in ensuring the efficient conduct of grid dispatch activities. Nonetheless, the current power grid dispatch system and communication program-controlled exchange system are disjointed, leading to a cumbersome process for the dispatching telephone functionality that severely impacts grid dispatch efficiency. To better tackle the above challenges, in this paper, we introduce an innovative intelligent call technology designed to facilitate data interchange and information integration between the power grid dispatch system and the communication program-controlled exchange system. By leveraging the K-Nearest Neighbors (KNN) algorithm, the technology enables automated querying of operational information with heightened efficiency and precision, thereby optimizing the operations of the dispatching telephone functionality. Subsequently, a prototype software application is developed to conduct experimental testing of intelligent call technology. The findings demonstrate that the method proposed in this paper successfully reduces the time expenditure associated with the dispatching telephone functionality, enhancing the productivity of dispatchers in routine operations and emergency response, thus ensuring the secure and stable operation of the power grid....
Quantum networks, relying on the distribution of quantum entanglement between remote locations, have the potential to transform quantum computation and secure long-distance quantum communication. However, a fundamental ingredient for fibre-based implementations of such networks, namely entanglement between a single spin and a photon directly emitted at telecom wavelengths, has been unattainable so far. Here, we use a negatively charged exciton in an InAs/InP quantum dot to implement an optically active spin qubit taking advantage of the lowest-loss transmission window, the telecom C-band. We investigate the coherent interactions of the spin-qubit system under resonant excitation, demonstrating high fidelity spin initialisation and coherent control using picosecond pulses.Wefurther use these tools to measure the coherence of a single, undisturbed electron spin in our system. Finally, we demonstrate spin-photon entanglement in a solid-state system with entanglement fidelity F = 80.07 ± 2.9%, more than 10 standard deviations above the classical limit....
We present a novel growth technique for fabricating low-density InAs/GaAs quantum dots that emit in the telecom O-band. This method combines local droplet etching on GaAs surfaces using gallium with Stranski–Krastanov growth initiated by InAs deposition. Quantum dots nucleate directly within nanoholes, avoiding the critical layer thickness typical of standard InAs Stranski–Krastanov growth, resulting in larger, low-density quantum dots. InGaAs strain reduction layers further redshift the emission into and beyond the telecom O-band. Photoluminescence spectra show a small energy difference between ground and excited states, while capacitance-voltage spectroscopy reveal small Coulomb blockade energy. Atomic force microscopy analysis indicates that quantum dots formed within nanoholes exhibit a larger volume compared to standard quantum dots. Additionally, these nanohole nucleated quantum dots require less indium to achieve O-band emission and demonstrate comparable or even better homogeneity, as indicated by the full-width at half-maximum. This improved homogeneity, low density, and increased size make these quantum dots particularly suitable for single-photon sources in quantum communication applications....
The telecommunications industry is one of the pillar industries of the country, and with the popularization of mobile Internet and the vigorous development of the digital economy, the importance of network infrastructure has become increasingly prominent. The purpose of this paper is to use machine learning methods to predict telecom subscriber churn and identify the key factors influencing subscriber churn. By analyzing the Telco Customer Churn dataset on the Kaggle platform, this study provides an in-depth analysis of the attributes and behaviors of more than 7,000 users. During the data processing phase, data cleansing, preprocessing, and feature engineering were performed to better understand user data and build predictive models. The random forest algorithm was used to evaluate the performance of the model by calculating precision, recall and F1-Score. Through model testing and iterative optimization, model parameters are continuously adjusted to improve prediction accuracy. This study finally identified the important factors influencing user churn and analyzed these important factors through a series of visualization methods. Then, based on the conclusions drawn from the analysis, it provides recommendations for marketing strategies and user retention measures for telcos. The successful implementation of this study in the real world can help telcos prevent subscriber churn more effectively and improve customer satisfaction....
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