Search

Smart logistics (SL) reflects the digital transformation of the logistics industry, which is key for economic development. Most evaluations are based on the application of technology in SL, and few studies have evaluated SL from a comprehensive perspective. The paper builds the SL development index (SLDI) model from five dimensions based on the driving force, pressure, state, impact, and response (DPSIR) model and identifies the indicator weight by the entropy weight technique. The paper employs the ETDK method, a combined quantitative approach that incorporates entropy weight (E), the technique for order preference by similarity to an ideal solution (TOPSIS) (T), the Dagum Gini coefficient (D), and Kernel density estimation (K), to calculate the closeness degree, analyze spatial-temporal differentiation, and explain the distribution characteristics using data from China spanning 2013 to 2021. The findings show that (1) The SL evaluation is multidimensional and cannot be evaluated only based on technical indicators. A comprehensive evaluation indicator system is necessary. (2) A combined quantitative approach can measure SL development from multiple perspectives and get a clearer picture of the characteristics and regional differences of SL. (3) Influenced by economic development, infrastructure, regional clusters, location, talent, etc., the overall SL development is improving yearly, but SL development in different regions is unbalanced and has different distribution characteristics. The SLDI model developed in this paper will provide a more scientific and reasonable tool for comprehensively evaluating SL. The findings are helpful in proposing suggestions and optimization approaches for subsequent research on SL evaluation and development. [ABSTRACT FROM AUTHOR]

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The integration of high proportions of renewable energy into power systems has led to an increasing demand for flexible resources， highlighting the importance of flexible resources on demand side. Current research on demand-side response primarily focuses on peak load and lacks quantitative analysis on how demand-side response resources can enhance renewable energy consumption. To address this gap， this paper first develops a regulation model for various flexible single resources on demand side. Subsequently， it analyzes the regulation characteristics of single flexible resources and establishes an aggregation regulation model for a large number of these resources. The paper then constructs a quantitative analysis model of renewable energy consumption promoted by demand-side response based on time-series production simulation. Finally， it conducts a simulation study using a provincial power grid as a case study to analyze the impact of various types of demand-side response on improving renewable energy consumption. The results show that both shiftable load （SL） and transferable load （TL） can help enhance renewable energy consumption.

Background: Widening of the scapholunate (SL) interval greater than 2 mm is diagnostic of an injury in adults; however, this absolute number cannot be used for skeletally immature individuals due to the ossification of the carpal bones. The purpose of this study was to determine age-appropriate normative values for the radiographic SL interval in the skeletally immature population. Methods: Normal pediatric wrist radiographs were identified. The radiographic SL interval was measured as the distance between the scaphoid and the lunate at the mid-joint space between the scaphoid and the lunate, and the SL and capitolunate angles were measured on lateral views. An initial inter-rater reliability assessment was completed with strong inter-rater reliability. Results: In all, 529 radiographic series of children (276 male), aged 4 to 17 years, were reviewed. A negative linear correlation between chronological age and distance at the mid-joint space was observed. The average values for the radiographic SL interval ranged from 9.07 to 1.57 mm. The average SL and capitolunate angles were 52.0° and 10.6°, respectively. No linear relationship was found between chronological age and SL or capitolunate angle (R = 0.07 and 0.03, respectively). Conclusions: The visible radiographic distance between the scaphoid and the lunate decreases with increasing age as the carpal bones ossify. The normative values defined in this study can be used to determine whether a true widening of the SL interval is present in the pediatric population. No linear relationship exists between chronological age and SL or capitolunate angle. [ABSTRACT FROM AUTHOR]

Hand gesture-based Sign Language Recognition (SLR) serves as a crucial communication bridge between hard of hearing and non-deaf individuals. The absence of a universal sign language (SL) leads to diverse nationalities having various cultural SLs, such as Korean, American, and Japanese sign language. Existing SLR systems perform well for their cultural SL but may struggle with other or multi-cultural sign languages (McSL). To address these challenges, this paper introduces a novel end-to-end SLR system called GmTC, designed to translate McSL into equivalent text for enhanced understanding. Here, we employed a Graph and General deep-learning network as two stream modules to extract effective features. In the first stream, produce a graph-based feature by taking advantage of the superpixel values and the graph convolutional network (GCN), aiming to extract distance-based complex relationship features among the superpixel. In the second stream, we extracted long-range and short-range dependency features using attention-based contextual information that passes through multi-stage, multi-head self-attention (MHSA), and CNN modules. Combining these features generates final features that feed into the classification module. Extensive experiments with five culture SL datasets with high-performance accuracy compared to existing state-of-the-art models in individual domains affirming superiority and generalizability.

Smart logistics (SL) reflects the digital transformation of the logistics industry, which is key for economic development. Most evaluations are based on the application of technology in SL, and few studies have evaluated SL from a comprehensive perspective. The paper builds the SL development index (SLDI) model from five dimensions based on the driving force, pressure, state, impact, and response (DPSIR) model and identifies the indicator weight by the entropy weight technique. The paper employs the ETDK method, a combined quantitative approach that incorporates entropy weight (E), the technique for order preference by similarity to an ideal solution (TOPSIS) (T), the Dagum Gini coefficient (D), and Kernel density estimation (K), to calculate the closeness degree, analyze spatial-temporal differentiation, and explain the distribution characteristics using data from China spanning 2013 to 2021. The findings show that (1) The SL evaluation is multidimensional and cannot be evaluated only based on technical indicators. A comprehensive evaluation indicator system is necessary. (2) A combined quantitative approach can measure SL development from multiple perspectives and get a clearer picture of the characteristics and regional differences of SL. (3) Influenced by economic development, infrastructure, regional clusters, location, talent, etc., the overall SL development is improving yearly, but SL development in different regions is unbalanced and has different distribution characteristics. The SLDI model developed in this paper will provide a more scientific and reasonable tool for comprehensively evaluating SL. The findings are helpful in proposing suggestions and optimization approaches for subsequent research on SL evaluation and development.