Showing papers by "Shandong Institute of Business and Technology published in 2022"

Renewable quantile regression for streaming datasets

Abstract: Streaming data analysis has drawn much attention, where large amounts of data arrive in streams. Because limited memory can only store a small batch of data, fast analysis without access to the historical data is necessary. Quantile regression has been widely used in many fields because of its robustness and comprehensiveness. However, in the streaming data environment, it is challenging to implement quantile regression by the conventional methods, because they are all based on the assumption that the memory can fit all the data. To fix this issue, this paper proposes a novel online renewable quantile regression strategy, in which the resulting estimator is renewed with current data and summary statistics of historical data. Thus, it is computationally efficient, and not storage-intensive. What is more, the theoretical results also confirm that the proposed estimator is asymptotically equivalent with the oracle estimator calculated using the entire data together. Numerical experiments on both synthetic and real data verify the theoretical results and illustrate the good performance of the new method.

Comparison Between Subparaneural Upper Trunk and Conventional Interscalene Blocks for Arthroscopic Shoulder Surgery: A Randomized Noninferiority Trial

Abstract: Although interscalene nerve block is the standard for shoulder analgesia, the risk of hemidiaphragmatic paralysis restricts its use in patients with compromised pulmonary function. We hypothesized that a novel subparaneural upper trunk block would provide noninferior postoperative analgesia but superior diaphragmatic sparing effect compared to interscalene block.This randomized controlled trial comprised 96 patients who underwent arthroscopic shoulder surgery under either subparaneural upper trunk block (5 mL of 0.5% ropivacaine) or interscalene block (15 mL of 0.5% ropivacaine), followed by supraclavicular nerve block (5 mL of 0.5% ropivacaine). General anesthesia was standardized. The coprimary outcomes were (1) recovery room resting pain score at 30 minutes, measured on an 11-point numerical rating scale, with a prespecified noninferiority margin of 1 point and (2) the incidence of hemidiaphragmatic paralysis, diagnosed using ultrasound. Among secondary outcomes, resting pain scores were assessed with numerical rating scale at 4, 8, and 24 hours postoperatively.Recovery room resting pain scores at 30 minutes were 0 (0-1) in the subparaneural upper trunk group versus 0 (0-0) in the interscalene group, with a median difference of 0 (95% CI, 0-0); the upper 95% CI limit was lower than the prespecified noninferiority margin (noninferiority P < .001). Hemidiaphragmatic paralysis was observed in 16.7% of patients in the subparaneural upper trunk group versus 100% of those in the interscalene group (RR, 0.17; 95% CI, 0.09-0.31; P < .001), with complete paralysis occurring in 6.3% and 93.7% of patients, respectively. In this study, any reported differences in pain scores at 4, 8, and 24 hours postoperatively were not clinically important.The subparaneural upper trunk block compared to interscalene block provided noninferior analgesia at 30 minutes in the recovery room after arthroscopic shoulder surgery but resulted in less hemidiaphragmatic paralysis.

A Comparative Experimental Study of Link Prediction Methods with Structural Information

Abstract: Link prediction is an important task to predict missing or future links in complex networks, social networks, knowledge graphs, etc. Since networks naturally have topological structures, a key issue is how to use structural information. Existing methods for link prediction can be categorized into two types: heuristic-based and learning-based. This paper compares these two types of methods and explores the factors affecting the performance. Experiments on five real-world datasets showed that the learning-based methods outperform the heuristic-based method, and their link prediction performance is affected by the size of node coverage. For learning-based methods, training time can be reduced by using smaller training set with enough node coverage.

Application and development of robot sports news writing by artificial intelligence

Abstract: Robot sports news writing has been widely recognized and popularized both at home and abroad, which improves the quality and efficiency of sports news production and frees journalists from routine work. Combining the characteristics and disadvantages of robot sports news writing, this paper puts forward the development direction and countermeasures of robot sports news writing.

Development of PSA Tube Bundle Nitrogen Generating Modules with High-pressure and High-purity on Offshore Platforms

Abstract: Nitrogen is already widely used in pipeline replacement and other related processes in the operations of LNG/LPG and offshore platforms. Now, it is being applied to processes in deep-water operations as well. In the paper, skid-mounted PSA nitrogen generation modules using high-pressure, high-purity tube bundles were designed and developed for application on offshore platforms. Firstly, the special requirements of offshore platforms for nitrogen production modules, such as high pressure and high purity and certification, are analyzed, and key technical difficulties are identified. Integrated tube bundle modules were used to design the PSA nitrogen reaction tower and pressure vessel, which effectively avoided certification difficulties and reduced costs. The proposed equipment was combined with a high-pressure molecular sieve for experimental research. A carbon molecular sieve (CMS) with pressure up to 1.7 MPa was selected, which exceeded that of mainstream CMSs (0.6-0.8 MPa). For the control scheme, an overlapping start-up mode was adopted for compiling the control program, which is realized through PLC + touch screen implementation + pneumatic control. The entire machine was integrated into 3 skid-mounted modules, and the relevant performance tests were carried out after manufacturing was completed. The output pressure was at least 1.4 MPa and the overall indicators met the design requirements. This project had introduced a new design concept and method for the development of skid-mounted high-pressure, high-purity nitrogen generation modules to be used on LNG/LPG and offshore platforms, and especially those modules required for deep-water operations.

Book Review of Keyuan Zou and Yen-Chiang Chang (eds.), <i>Preserving Community Interests in Ocean Governance towards Sustainability</i>

Abstract: 1. The book under review, Keyuan Zou and Yen-Chiang Chang (eds.), Preserving Community Interests in Ocean Governance towards Sustainability, MDPI, 2022, vii+284 pp., index; ISBN 978-3-0365-2831-1(Hbk), addresses an important topic. 2. Protecting the marine environment and sustainably developing marine resources become critical for global ocean governance and international community interest. However, individual States are acquiring marine space and resources unsustainably, without serious consideration of the collective interests of the international community and future generations. Such self-centred behaviour has severely damaged the marine environment and the sustainability of marine resources, especially regarding the oceans beyond national jurisdiction, including the high seas, Antarctica and the international seabed, often referred to as the global commons. Therefore, it is increasingly urgent for the world to protect the marine environment and the sustainability of marine resources while safeguarding the common interests in ocean governance. 3. This book focuses on the community’s interests in achieving sustainability in ocean governance and how to safeguard these interests by effectively implementing the international law of the sea and the sustainable development goals. It stresses the concept of community interests in sustainable ocean governance, which will be fully reflected in several papers. This book draws on currently acknowledged academic papers in four respects. First, it reviews issues related to ocean governance law in the context of the sustainable development goals in the long-term interests of the international community. Second, new legal obligations are identified based on the marine environment to maintain navigation and maritime security. Third, a practical legal framework for sustainably using marine resources (biological and abiotic) is assessed. Fourth, new developments in marine scientific research regulations and environmental protection technologies are discussed.

A Decision Tree Classification Algorithm in University Archives Management

Abstract: Using computer technology to realize the digitization of archives management is a key point of archives management at present. Through the research on the decision tree classification algorithm of data mining technology, combined with the example of archives management in Colleges and universities, this paper shows that using D3 algorithm to realize the scientific classification of digital archives management in Colleges and universities.

Dual-Discriminator Based Multi-modal Medical Fusion

Abstract: The common medical image fusion algorithms often have the problems of information redundancy and spatial information loss. Therefore, an adversarial network generation method based on double discrimination is proposed in this paper. Firstly, the dual discriminant network designed by us is used for the initial fusion, and then the fusion strategy is used to enhance the detailed features to complete the final fusion. The experimental results show that the fusion results obtained by our method have clearer spatial structure and more accurate spectral information compared with the common representative methods.

The Research on Fishery Metadata in Bohai Sea Based on Semantic Web

Abstract: Abstract In this paper, a data sharing and management mechanism suitable for the characteristics of fishery industry was established to clarify the phenomenon of heterogeneous Web data and Information Island based on Semantic Web technology, and unified interface specification information platform was established. Form the specification of metadata from the physical and chemical database, developing and publishing the corresponding metadata management tool, assisting, assisting and guiding a specialized database centre, completing the construction of metadata from the professional database.

A Process Mechanism Study of the Impact of Service Robot Anthropomorphic Features on Users&amp;apos; Continuous Usage Intention

Abstract: Robots replacing the work of human employees is no longer a novelty. In the manufacturing industry, a large number of front-line employees have already been replaced by machines. With the maturity and development of robotics, the replacement of humans with machines is gradually shifting from the manufacturing industry to the service industry. The process by which robotic features affect users' willingness to use under intelligent services has been a hot topic in business management and academic research in recent years. However, anthropomorphism as an intuitive external feature, few studies have explored the process mechanisms of such features on customers' continuous usage intention. Based on Social information processing theory, the article investigates the mechanism by which anthropomorphic appearance features of service robots affect users' continuous usage intention. The results show that users' tendency to anthropomorphize the appearance of service robots positively influences continuous usage intention through the partial mediation of perceived usefulness and perceived enjoyment. In addition, the level of empathy of the service robot moderates the effect of anthropomorphism on perceived usefulness and perceived hedonicity. The findings of this study enrich the research on the processes that influence users' continuous usage intention in service encounters and also provide a useful reference for the management practices of service companies.