Investigating the Impact of Cloud Computing Vendor on the Adoption of Cloud Computing

Cloud computing offers significant impacts on organization by changing how information systems are developed, deployed, operated, maintained, and paid for. Therefore, the adoption of cloud computing becomes the focus of relevant research; however, previous studies have mostly studied the factors affecting cloud computing adoption from the perspective of adopters, ignoring the influence of the vendors. This study defines cloud service capability and develops scale to measure it from the perspective of cloud computing vendors to empirically examine the impact of the supply-side of cloud computing. The initial scale of cloud service capability is constructed using qualitative research, and the formal scale is obtained after two rounds of pretest. The statistical results of matched data collected from 132 cloud computing vendors and their users show that cloud service capability significantly affects cloud computing adoption. This study shifts the research perspective on cloud adoption to make theoretical contributions and management insights from the perspective of cloud computing vendors.

Ultra-Stable and Durable Piezoelectric Nanogenerator with All-Weather Service Capability Based on N Doped 4H-SiC Nanohole Arrays

Ultra-stable piezoelectric nanogenerator (PENG) driven by environmental actuation sources with all-weather service capability is highly desirable. Here, the PENG based on N doped 4H-SiC nanohole arrays (NHAs) is proposed to harvest ambient energy under low/high temperature and relative humidity (RH) conditions. Finite element method simulation of N doped 4H-SiC NHAs in compression mode is developed to evaluate the relationship between nanohole diameter and piezoelectric performance. The density of short circuit current of the assembled PENG reaches 313 nA cm−2, which is 1.57 times the output of PENG based on N doped 4H-SiC nanowire arrays. The enhancement can be attributed to the existence of nanohole sidewalls in NHAs. All-weather service capability of the PENG is verified after being treated at -80/80 ℃ and 0%/100% RH for 50 days. The PENG is promising to be widely used in practice worldwide to harvest biomechanical energy and mechanical energy.

Research on Comprehensive Evaluation of Service Capability of the Third-Party Logistics Suppliers with AHP and Gray Entropy Theory

To solve the problem of third-party logistics (3PL) evaluation and selection, a hybrid method with AHP and gray theory is proposed. First, the literature review about the 3PL evaluation method and technology is introduced. Furthermore, TPL comprehensive service capability evaluation system is established from aspects of service, time, cost and enterprise qualification. Besides, a comprehensive evaluation model process with gray entropy and AHP is introduced. Finally, a detailed evaluation process of 3PL supplier service capability in F company is introduced by an example, and the results show that the evaluation method in the paper is helpful to choose the TPL for logistics outsourcing.

Wireless Caching: Making Radio Access Networks More than Bit-Pipelines

Caching has attracted much attention recently because it holds the promise of scaling the service capability of radio access networks (RANs). We envision that caching will ultimately make next-generation RANs more than bit-pipelines and emerge as a multi-disciplinary area via the union with communications, pricing, recommendation, compression, and computation units. By summarizing cutting-edge caching policies, we trace a common root of their gains to the prolonged transmission time, which is then traded for higher spectral or energy efficiency. To realize caching, the physical layer and higher layers have to function together, with the aid of prediction and memory units, which substantially broadens the concept of cross-layer design to a multi-unit collaboration methodology. We revisit caching from a generalized cross-layer perspective, with a focus on its emerging opportunities, challenges, and theoretical performance limits. To motivate the application and evolution of caching, we conceive a hierarchical pricing infrastructure that provides incentives to network operators and users. To make RANs even more proactive, we design caching and recommendation jointly, showing a user what it might be interested in and what has been done for it. Furthermore, the user-specific demand prediction motivates edge compression and proactive MEC as new applications. The beyond-bit-pipeline RAN is a paradigm shift that brings with it many cross-disciplinary research opportunities.

Research on the Incentive Mechanism of the Pension Service Supply Chain under Asymmetric Information

The information asymmetry between the pension service integrator and the pension service providers will affect the efficiency of the whole supply chain, and information sharing can solve this problem to a certain extent. To achieve information sharing, mutual trust is the first condition and mutual trust is also one of the important means of endogenous incentives. In this paper, the trust incentive coefficient is embedded in the principal-agent model. Considering the service capability coefficient, the communication degree coefficient, and the information sharing degree coefficient of the pension service providers, the trust incentive model of the supply chain of the pension service is constructed, the model is solved, and the conclusion is drawn. Finally, the correctness of the conclusion is verified by the numerical simulation using SAS software. The final results show that, under the condition of information asymmetry, the trust incentive coefficient of the pension service integrator to the pension service providers is positively correlated with the effort coefficient, the service capability coefficient, the communication coefficient, and the information sharing degree coefficient of the pension service providers, while it is positively correlated with the effort cost coefficient, the output sharing coefficient, and the risk aversion coefficient of the pension service providers. The variance of number and external environmental variables is negatively correlated. This research has shown that the trust is a means of incentive for pension service providers to share information. This research has a certain practical significance for improving the service efficiency of the pension services supply chain and optimizing the level of pension services.

Effective perioperative scoring in orthopedic surgery to prevent Covid-19 infection

BackgroundThe pandemic has placed health-care workers (HCW) under an unprecedented strain where surgeries are being delayed and health care workers’ deaths because of COVID-19 are prominent and causing staff shortages. An effective, fast, and concise approach to preoperative screening is very much needed. Hospitals are suggested to develop their own algorithm to minimize delays and complications. The objective of this study was to optimize HCW safety by developing a working system based on the hospital’s service capability in treating orthopedic surgeries. Methods A retrospective study was conducted involving 305 HCW. Data were collected on the application of a novel elective and emergency orthopedic surgery clinical pathway and scoring method based on questionnaires, and laboratory and radiographic chest examinations for several months to ensure the safety of HCW. HCW COVID-19 status was routinely checked as the indicator of HCW’s safety. Results Mean age of all patients was 47.0 ± 22.41 years. The screening process was done in a series of questionnaires and laboratory examinations, with the majority of patients (82 or 35.9%) having a score of 0. Patients with a score of 3 or more and testing positive for COVID-19 were immediately referred to a hospital having adequate facilities to prevent delays. There were 51 patients (16.7%) with positive rapid test results, and 21 patients (6.8%) with positive PCR tests. There were 4 (1.3%) COVID-19 positive HCW. Conclusions Despite COVID-19 being a new threat, we have shown that developing an effective perioperative clinical pathway could eventually optimize healthcare worker safety.

A CLSTM and transfer learning based CFDAMA strategy in satellite communication networks

With the development of the economy and technology, people’s requirement for communication is also increasing. Satellite communication networks have been paid more and more attention because of their broadband service capability and wide coverage. In this paper, we investigate the scheme of convolutional long short term memory (CLSTM) network and transfer learning (TL) based combined free/demand assignment multiple access (CFDAMA) scheme (CFDAMA-CLSTMTL), which is a new multiple access scheme in the satellite communication networks. Generally, there is a delay time T between sending a request from the user to the satellite and receiving a reply from the satellite. So far, the traditional multiple access schemes have not processed the data generated in this period. So, in order to transmit the data in time, we propose a new prediction method CLSTMTL, which can be used to predict the data generated in this period. We introduce the prediction method into the CFDAMA scheme so that it can reduce data accumulation by the way of sending the slots request which is the sum of slots requested by the user and the predicted slots generated in the delay time. A comparison with CFDAMA-PA and CFDAMA-PB is provided through simulation results, which gives the effect of the CFDAMA-CLSTMTL in a satellite communication network.