Sharpening and generalizations of Shafer's inequality for the arc tangent function

In this paper, we sharpen and generalize Shafer's inequality for the arc tangent function. From this, some known results are refined

A Spectral Dai-Yuan-Type Conjugate Gradient Method for Unconstrained Optimization

A new spectral conjugate gradient method (SDYCG) is presented for solving unconstrained optimization problems in this paper. Our method provides a new expression of spectral parameter. This formula ensures that the sufficient descent condition holds. The search direction in the SDYCG can be viewed as a combination of the spectral gradient and the Dai-Yuan conjugate gradient. The global convergence of the SDYCG is also obtained. Numerical results show that the SDYCG may be capable of solving large-scale nonlinear unconstrained optimization problems

Energy Efficient Uplink Transmissions in LoRa Networks

LoRa has been recognized as one of the most promising low-power wide-area (LPWA) techniques. Since LoRa devices are usually powered by batteries, energy efficiency (EE) is an essential consideration. In this paper, we investigate the energy efficient resource allocation in LoRa networks to maximize the system EE (SEE) and the minimal EE (MEE) of LoRa users, respectively. Specifically, our objective is to maximize the corresponding EE by jointly exploiting user scheduling, spreading factor (SF) assignment, and transmit power allocations. To solve them efficiently, we first propose a suboptimal algorithm, including the low-complexity user scheduling scheme based on matching theory and the heuristic SF assignment approach for LoRa users scheduled on the same channel. Then, to deal with the power allocation, an optimal algorithm is proposed to maximize the SEE. To maximize the MEE of LoRa users assigned to the same channel, an iterative power allocation algorithm based on the generalized fractional programming and sequential convex programming is proposed. Numerical results show that the proposed user scheduling algorithm achieves near-optimal EE performance, and the proposed power allocation algorithms outperform the benchmarks. © 2020 IEEE

The Influencing Factors on Consumers’ Purchase Intention under the Cross-border E-commerce Platforms

The purpose of this paper is to explore the influencing factors of consumers\u27 willingness to purchase in the cross-border e-commerce websites and apps. We believe that the most significant factor affecting consumers’ cross-border online shopping is online trust. Therefore, this study divided online trust of cross-border e-commerce platforms into four dimensions, and extracted four independent variables which are perceived usefulness, perceived easy to use, perceived security and consumers’ trust propensity according to the TAM theory. Moreover, we used consumers’ online trust as a mediator variable, constructed a expanded TAM research model to explore the mechanism and determinants of consumers’ cross-border online shopping. Finally, the conclusions and implications were given according to the empirical analysis

Does COO Matter in Value Co-creation of Cross-border E-commerce?

The purpose of this paper is to explore the cross-border e-commerce value co-creation mechanism. We believe that the most significant factor affecting consumers’ cross-border online shopping is online service quality. And the country of origin effect also plays an important role in the cross-border purchase intention. Therefore, this study built a proposed model of cross-border online purchase intention based on co-create theory and two-side market theory. For the case of online cross-border shopping, perceived value is very important which can directly determine the purchase intention of customers. Based on the related theory, three significant latent variables that can indirectly determine the purchase intention of customers as follows: consumer resource, platform service quality (or ESQ), and country of origin. According to our positive study, platform service quality is the most important factor, COO is the second one, and consumer expertise is the last one. All of the antecedent variables are significant according to statistical results. Then we made the conclusions and implications

Does COO really Matter in Value Co-Creation of Cross-Border E-Commerce?

The purpose of this paper is to explore the cross-border e-commerce value co-creation mechanism. We believe that the most significant factor affecting consumers’ cross-border online shopping is online service quality. And the country of origin(COO) effect also plays an important role in the cross-border purchase intention. Therefore, this study built a proposed model of crossborder online purchase intention based on co-create theory and two-side market theory. For the case of online cross-border shopping, perceived value is very important which can directly determine the purchase intention of customers. Based on the related theory, three significant latent variables that can indirectly determine the purchase intention of customers as follows: consumer resource, platform service quality (or ESQ), and country of origin. According to our positive study, platform service quality is the most important factor, COO is the second one, and consumer expertise is the last one. All of the antecedent variables are significant according to statistical results. Then we made the conclusions and implications

Mixed Transportation Network Design under a Sustainable Development Perspective

A mixed transportation network design problem considering sustainable development was studied in this paper. Based on the discretization of continuous link-grade decision variables, a bilevel programming model was proposed to describe the problem, in which sustainability factors, including vehicle exhaust emissions, land-use scale, link load, and financial budget, are considered. The objective of the model is to minimize the total amount of resources exploited under the premise of meeting all the construction goals. A heuristic algorithm, which combined the simulated annealing and path-based gradient projection algorithm, was developed to solve the model. The numerical example shows that the transportation network optimized with the method above not only significantly alleviates the congestion on the link, but also reduces vehicle exhaust emissions within the network by up to 41.56%

Algorithms, Protocols & Systems for Remote Observation Using Networked Robotic Cameras

Emerging advances in robotic cameras, long-range wireless networking, and distributed sensors make feasible a new class of hybrid teleoperated/autonomous robotic remote "observatories" that can allow groups of peoples, via the Internet, to observe, record, and index detailed activity occurred in remote site. Equipped with robotic pan-tilt actuation mechanisms and a high-zoom lens, the camera can cover a large region with very high spatial resolution and allows for observation at a distance. High resolution motion panorama is the most nature data representation. We develop algorithms and protocols for high resolution motion panorama. We discover and prove the projection invariance and achieve real time image alignment. We propose a minimum variance based incremental frame alignment algorithm to minimize the accumulation of alignment error in incremental image alignment and ensure the quality of the panorama video over the long run. We propose a Frame Graph based panorama documentation algorithm to manage the large scale data involved in the online panorama video documentation. We propose a on-demand high resolution panorama video-streaming system that allows on-demand sharing of a high-resolution motion panorama and efficiently deals with multiple concurrent spatial-temporal user requests. In conclusion, our research work on high resolution motion panorama have significantly improve the efficiency and accuracy of image alignment, panorama video quality, data organization, and data storage and retrieving in remote observation using networked robotic cameras