| 1. |
- Du, Bisheng, et al.
(författare)
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Customer's Channel Selection Behavior on Purchasing Standardized and Customized Products : Optimized Prices and Channel Performances
- 2022
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Ingår i: Frontiers in Psychology. - : Frontiers Media SA. - 1664-1078. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Nowadays, the traditional production is unable to meet the new diverse needs of target customers. In the current customization era, more and more companies are required by customers to provide more desirable customized products. However, research on customization and standardization based on quantitative analysis has drawn little attention in the literature of dual channel supply chain. In this paper, we study the effect of adopting a dual channel supply chain on the performance of a two-level system (manufacturer-retailer) by using a novelty quantitative approach. We try to analyze the system to get optimal prices and maximize profits, where manufactures offer both standardized and customized products via their traditional and customized channels, respectively. We build a Stackelberg game mode to construct a centralized and a decentralized dual channel scenarios. Furthermore, we study the effects of the different channel structures on price, degree of customization, degree of standardization, and supply chain profitability. We also analyze the effects of both standardized and customized demand sensitivities on their prices and profits. Eventually, we introduce a cost-sharing coordinating contract to optimize the channel's performance. We find that the potential market demand for customization affects the price of customized products and the profits of customized channels. Compared with the decentralized dual channel case, the cost-sharing contract can achieve higher total channel profits. In the cost-coordination case, there is an optimal range for the proportion of standardized costs borne by manufacturers.
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| 2. |
- Lv, Zhihan, et al.
(författare)
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Advanced Human–Computer Interaction Technology in Digital Twins
- 2023
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Ingår i: Studies in Computational Intelligence. - 1860-949X .- 1860-9503. ; , s. 99-123
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Bokkapitel (refereegranskat)abstract
- To explore the application of Human–Computer Interaction (HCI) in industrial Digital Twins (DTs), the current application status of DTs in Intelligent Manufacturing (IM) and the HCI problem in human–computer assembly are explored; aiming at the Human Action Recognition (HAR) of machine perspective in human–computer assembly, it proposes the Human Pose Estimation (HPE) method based on improved HRNet and inroduces the attention mechanism to establish the SE_NewHRNet model for the optimization of HPE; in addition, it points out Adaptive Architecture of Deep Learning Based on Confrontation (ADLC), and performs case analysis for the performance verification of the model. The accuracy of SE_NewHRNet in $$\mathrm{A}{P}:{pose}$$ indicator is 75.1%. Compared with other models, its network performance is improved to different extents, the number of parameters and calculation amount are lower, the Loss value decreases rapidly, and the decrease rate becomes slower after 40 iterations. In ADLC, the recognition accuracy of the branch model with three domain discrimination is the highest, reaching 86.50%; in most cases, ADLC performance is better in contrast to other models. Compared with the Wasserstein Generative Adversarial Networks (WGAN) model with the second comprehensive performance, the average accuracy of ADLC is 69.72, 9.24% higher than that of WGAN, and 27.67% higher than that of Source-only. Therefore, the proposed human recognition method performs better.
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| 3. |
- Lv, Zhihan, et al.
(författare)
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Distributed computing to blockchain: Architecture, technology, and applications
- 2023
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Ingår i: Distributed Computing to Blockchain: Architecture, Technology, and Applications. - 9780323961462 ; , s. 39-54
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Bokkapitel (refereegranskat)abstract
- This chapter aims to explore the correlation between distributed computing and blockchain technology and deeply investigate the architecture and application of blockchain technology. Mobile devices are taken as the research object, and blockchain technology is used to provide a distributed computing model for mobile terminals in the wireless communication scenario. Besides, deep learning is employed to classify tasks and enhance the analysis efficiency of multisource data. Finally, a distributed deep learning network model based on blockchain technology is constructed. In addition, the performance of the model is verified by simulation experiments. The experimental results demonstrate that through the comparative analysis of system performance, the computational overhead of the model constructed here is the lowest, maintained at about 0.12s, and the comprehensive income and system operation efficiency are the highest. In terms of the security performance of data transmission, the average delay of the distributed framework reported here is stable at about 250ms, and the identification accuracy of transmitted data reaches 92.40%. Therefore, the distributed deep learning model proposed here realizes splendid recognition accuracy, comprehensive income, and system operation efficiency and shows excellent system performance, which can provide a reference for the improvement of blockchain technology application in future.
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| 4. |
- Zhai, Gang, et al.
(författare)
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Sex-specific differences in zebrafish brains
- 2022
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Ingår i: Biology of Sex Differences. - : BioMed Central (BMC). - 2042-6410. ; 13:1
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Forskningsöversikt (refereegranskat)abstract
- In this systematic review, we highlight the differences between the male and female zebrafish brains to understand their differentiation and their use in studying sex-specific neurological diseases. Male and female brains display subtle differences at the cellular level which may be important in driving sex-specific signaling. Sex differences in the brain have been observed in humans as well as in non-human species. However, the molecular mechanisms of brain sex differentiation remain unclear. The classical model of brain sex differentiation suggests that the steroid hormones derived from the gonads are the primary determinants in establishing male and female neural networks. Recent studies indicate that the developing brain shows sex-specific differences in gene expression prior to gonadal hormone action. Hence, genetic differences may also be responsible for differentiating the brain into male and female types. Understanding the signaling mechanisms involved in brain sex differentiation could help further elucidate the sex-specific incidences of certain neurological diseases. The zebrafish model could be appropriate for enhancing our understanding of brain sex differentiation and the signaling involved in neurological diseases. Zebrafish brains show sex-specific differences at the hormonal level, and recent advances in RNA sequencing have highlighted critical sex-specific differences at the transcript level. The differences are also evident at the cellular and metabolite levels, which could be important in organizing sex-specific neuronal signaling. Furthermore, in addition to having one ortholog for 70% of the human gene, zebrafish also shares brain structural similarities with other higher eukaryotes, including mammals. Hence, deciphering brain sex differentiation in zebrafish will help further enhance the diagnostic and pharmacological intervention of neurological diseases.
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