Supply chain management has become such a popular topic in modern business and researches. It brings the revolutionary philosophy approach to manage with sustained competitiveness. However, existing performance measurement theory fails provide its necessary support strategy development, decision making, improvement. This paper attempts propose an innovative method contribute development of supply management. A process‐based systematic perspective is employed build effective model measure...

Nowadays more than ever, supply chain management has gained a tremendous amount of attention from both the academic and practitioner communities. It provides revolutionary philosophy to cope with increasing business competition economy globalization. However, there exist many puzzles, especially in structure mapping analysis, performance measurement. The objective this paper is propose process‐based approach analyzing practically complex network. Via approach, measurement system proposed,...

Supply chain management (SCM) has gained a tremendous amount of attention from both industries and researchers since the last decade. Until now, there are numerous papers, articles, reports that address SCM, but is still lack integration between existing performance measurement methods practical requirements for SCM. An innovative method proposed to provide necessary assistance improvement in The will this purpose these four aspects: simplified supply model; tangible intangible measures...

Aiming at the photo fraud that often occurs in identity verification and accuracy robustness of real-time video face recognition, this paper proposes a detection method based on blink detection. This first extracts image texture features through LBP algorithm, which eliminates problem illumination changes to certain extent. Then extracted are input into ResNet network, facial feature extraction is enhanced by adding an attention mechanism added enhance extraction. Meanwhile, BiLSTM used...

Face recognition technology is a powerful means to capture biological facial features and match data in existing databases. With the advantages of noncontact long-distance implementation, it being used more scenarios. Affected by factors such as light, posture, background environment, face images captured device are still insufficient rate models. We propose an AB-FR model, convolutional neural network method based on BiLSTM attention mechanism. By adding mechanism CNN model structure,...

Expressions serve as intuitive reflections of a person's psychological state, making the extraction effective features for accurate facial expression recognition crucial research problem. However, when information is incomplete, existing convolutional neural networks face some challenges in extracting features. To address this issue, paper introduces pyramidal attention residual network(PCARNet) based on ResNet18. PCARNet combines convolution module and an improved mechanism to effectively...

The feature selection for interval-valued data(IVD) aims to identify representative features from a large set of features, which can reduce the model complexity, minimize training time, and enhance generalization ability model. Addressing inter-feature correlations in IVD, we propose method called maximum information coefficient data(IVD_MIC). First, balances relationship between midpoint radius IVD with an adjustment factor, constructing data unified representation frame (URF). Based on...

Nowadays supply chain management has gained a tremendous amount of attention from both academics and practitioners. It provides an innovative technology in order to assist enterprises survive the ever-increasing business competition sustain competitive advantages. Although there is literature addressing theories practices management, existing performance measurement methods fail provide significant assistance development effective method lacking. The objective this paper propose...

Diabetes is a chronic disease, which characterized by abnormally high blood sugar levels. It may affect various organs and tissues, even lead to life-threatening complications. Accurate prediction of diabetes can significantly reduce its incidence. However, the current methods struggle accurately capture essential characteristics nonlinear data, black-box nature these hampers clinical application. To address challenges, we propose KCCAM_DNN, method that integrates Kendall’s correlation...

The choice of energy conservation behavior (ECB) is a complicated process. In order to examine the feedback effect results under situational factors --- energy-conservation policy; this paper builds theory model and makes surveys on urban residents eastern region China. show that intention not coincident with behavior, because regulating factors. Perception has behavior. Finally, proposes suggestion optimize policy.

In the community of Granular Computing, knowledge is interpreted as one classification ability realistic or abstract objects. Generally, concept granularity used for characterizing such an ability, which has been widely explored in literatures. To calculate parameterized granularity, a naive approach to find terms parameter by one. Nevertheless, can only generate single based and difference granularities among different parameters may be slight. It follows that derived from lack...

. Laparoscopic renal unit-preserving resection is a routine and effective means of treating tumors. Image segmentation an essential part before tumor resection. The current method mainly relies on doctors manual delineation, which time-consuming, labor-intensive, influenced by their personal experience ability. And the image quality low, with problems such as blurred edges, unclear size shape, are not conducive to clinical diagnosis.

Accurate face recognition technology is of great significance for anti-counterfeiting. Due to illumination, posture, angle, and other reasons, the existing liveness detection difficult adapt environmental changes, resulting in low accuracy. To address this issue, paper presents a novel high-performance anti-spoofing method named RGCS_ConvNeXt. The data-enhanced images are fed into ConvNext network, which group convolution added extract correlation between different features, coordinate...

As a crucial extension of Pawlak′s rough set, fuzzy set has been successfully applied in real‐valued attribute reduction. Nevertheless, the traditional is not provided with adjustable ability due to maximal and minimal operators. It follows that associated measure for evaluation always appropriate. To alleviate such problems, novel model presented further introduced into parameterized Additionally, inner relationship between appointed parameter reduct result discovered, thereby nested...

After analyzing many typical association rule mining algorithms, a new algorithm, named as BOFP-V, is proposed for frequent item set mining. FP-V vectors are introduced in order to convert that of the course operating. The existing Apriori algorithm produces lot candidacy sets and needs scanning database times, BOM entails operation k vertors with ( <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sub> <sup...

In multilabel classification, the problems of a large number classification calculations and easy destruction label relations are very common. To solve these problems, hierarchical method based on clustering is proposed by mining possible dependencies between labels. First, algorithm adopts local strategy to cluster labels multiple times. Then, clusters with relation formed, implicit relationships hidden in analyzed. On this basis, clustered tree constructed train model. Finally, as random...