In this paper, we base our research by dealing with a real-world problem in an enterprise. A RFM (recency, frequency, and monetary) model K-means clustering algorithm are utilized to conduct customer segmentation value analysis using online sales data. Customers classified into four groups based on their purchase behaviors. On basis, different CRM (customer relationship management) strategies brought forward gain high level of satisfaction. The effectiveness method proposed paper is...

In multi-objective evolutionary algorithms (MOEAs), the diversity of Pareto front (PF) is significant. For good can provide more reasonable choices to decision-makers. The PF includes span and uniformity. this paper, we proposed a dynamic crowding distance (DCD) based maintenance strategy (DMS) (DCD-DMS), in which individualpsilas DCD are computed on difference degree between distances different objectives. computes individualspsila dynamically during process population maintenance. Through...

Abstract Rationally designing on sundry multiphase compounds has come into the spotlight for sodium‐ion batteries (SIBs) due to enhanced structural stability and improved electrochemical performances. Nevertheless, there is still a lack of thorough understanding reaction mechanism high‐active phase boundaries existing between compounds. Here, VS 4 /Bi 2 S 3 @C composite anode SIBs with rich in heterostructure successfully synthesized. In situ X‐ray diffraction analyses demonstrate multistep...

Demanding for warehousing automation and intelligence is critical with the rapid development of information big data teleology.In most storehouses, cargos are mainly carried by Automatic Guided Vehicles (AGVs) or even manpower.Most AGVs follow predefined paths that normally paved some marks detected AGVs.It largely limits application AGVs.Some relies on highly accurate Light Laser Detection Ranging (LiDAR) devices navigation.The paper presents a low-cost localization approach indoor accuracy...

The rapid development of wireless communication technology has led to an increasing number internet thing (IoT) devices, and the demand for spectrum these devices their related applications is also increasing. However, scarcity become increasingly serious problem. Therefore, we introduce a collaborative sensing (CSS) framework in this paper identify available resources so that IoT can access them and, meanwhile, avoid causing harmful interference normal primary user (PU). process PUs signal...

Panoramic map construction of polar sea ice can provide significant assistance for intelligent navigation and routing planning in regions. Traditional methods panoramic observation generation suffer from issues such as limited parallax tolerance, poor stitching robustness, low mapping accuracy. In this paper, these problems are addressed by a proposed online method based on multi-perspective image projection camera pose rectification. The incorporates modified inverse module that dynamically...

Purpose The spectrum resources are becoming increasingly scarce and underutilized, cooperative sensing (CSS) in cognitive wireless sensor networks (CWSNs) offers many solutions with good results, but this paper aims to address the significant issue of CSS context low signal-to-noise ratio (SNR). Design/methodology/approach This study proposes Pearson Correlation Coefficient (PCC) obtain value feature values under Rayleigh channel model, which then used for Memorial K-means Clustering (MKC)...

Cognitive radio (CR) is a revolutionary paradigm to solve the spectrum scarcity problem in wireless networks. In cognitive networks, cooperative sensing regarded as promising approach method significantly improve performance of sensing, but it can be threatened by Byzantine attack. The existing defense references have focused on how mitigate negative effect attack, with some strong assumptions, such attackers are minority and/or trusted node exists for data fusion. This observation motivates...

Cooperative spectrum sensing (CSS) is regarded as a promising approach to identify the available spectrum. However, it not only requires large communication resource-consuming, but also exposes high vulnerability Byzantine attack. In this letter, starting with sequential voting rule, we propose low-complexity 0/1 (S0/1) for CSS in presence of strategic attack, which neither strong assumptions and any prior knowledge nor depends on careful threshold selection. Compared existing approaches,...

Cooperative spectrum sensing (CSS) is the key function of cognitive radio (CR) system to identify available spectrum. However, nature aggregating data makes CSS offer opportunities for Byzantine attackers undermine CR. In this letter, on basis a generalized soft attack model, we theoretically analyze strategies in absence any defense, terms strength and probability. Further, introduce classical trust-value based algorithm conduct evaluate security attackers, with aim providing guideline...

In the face of explosive growth wireless data and electronic devices, cognitive radio (CR) technology is an effective solution to identify spectrum resources underutilized by primary user (PU). Moreover, cooperative sensing (CSS) key function CR enhance detection performance exploiting spatial diversity via observations spatially located sensor nodes (SNs). However, in a classical paradigm, each SN always required report individual local decision about PU status fusion center (FC) for global...

We report high precision calculations of nonrelativistic energies the hydrogen molecular ion $\mathrm{H}_{2}{}^{+}$ in some low-lying states, using a variational method multiple Hylleraas basis sets. For ground state, for example, energy is established to an accuracy 8 parts ${10}^{30}$, which represents orders magnitude improvement over best previous value Cassar and Drake [J. Phys. B 37, 2485 (2004)]. Our lay firm foundation studying higher-order relativistic QED effects.

Cooperative spectrum sensing (CSS) is envisaged as a powerful approach to improve the utilization of scarce radio resources, but it threatened by Byzantine attack. attack has been becoming popular research topic in both academia and industry due demanding requirements security. Extensive mainly aims at mitigating negative effect on CSS, with some strong assumptions, such attackers are minority or trusted node(s) exist for data fusion, while paying little attention mobile scenario. This paper...

In an interweave cognitive radio system, cooperative spectrum sensing has been recognised as a key technology to enable secondary users opportunistically access licensed band without harmful interference primary users. At the same time, unmanned aerial vehicle equipped with and data transmission facilities is gaining more popularity in different applications. An vehicle-based investigated which used user, but unlike participation of multiple traditional sensing, virtual model introduced into...

In recent years, with the development of machine learning and big data technology, user has become an important element in production process enterprises. For today’s e‐commerce platforms, deep mining user’s purchase behavior is helpful to understand preferences accurately recommend products that meet expectations, which can not only improve satisfaction but also reduce platform marketing cost. To identify value online purchasing on platform, this paper uses improved RFM model extract...

The issue of students’ career choice is the common concern students themselves, parents, and educators. However, behavioral data have not been thoroughly studied for understanding their choice. In this study, we used eXtreme Gradient Boosting (XGBoost), a machine learning (ML) technique, to predict college using real-world dataset collected in specific college. Specifically, include information on education 18,000 graduates during years. addition, SHAP (Shapley Additive exPlanation) was...

Abstract Background Human vision has inspired significant advancements in computer vision, yet the human eye is prone to various silent diseases. With advent of deep learning, for detecting diseases gained prominence, but most studies have focused only on a limited number Results Our model demonstrated reduction inherent bias and enhanced robustness. The fused network achieved an Accuracy 0.9237, Kappa 0.878, F1 Score 0.914 (95% CI [0.875–0.954]), Precision 0.945 [0.928–0.963]), Recall 0.89...