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This paper aims to present a new approach for robot programming by demonstration, which generates robot programs by tracking 6 dimensional (6D) pose of the demonstrator’s hand using a single red green blue (RGB) camera without requiring any additional sensors.

The proposed method learns robot grasps and trajectories directly from a single human demonstration by tracking the movements of both human hands and objects. To recover the 6D pose of an object from a single RGB image, a deep learning–based method is used to detect the keypoints of the object first and then solve a perspective-n-point problem. This method is first extended to estimate the 6D pose of the nonrigid hand by separating fingers into multiple rigid bones linked with hand joints. The accurate robot grasp can be generated according to the relative positions between hands and objects in the 2 dimensional space. Robot end-effector trajectories are generated from hand movements and then refined by objects’ start and end positions.

Experiments are conducted on a FANUC LR Mate 200iD robot to verify the proposed approach. The results show the feasibility of generating robot programs by observing human demonstration once using a single RGB camera.

The proposed approach provides an efficient and low-cost robot programming method with a single RGB camera. A new 6D hand pose estimation approach, which is used to generate robot grasps and trajectories, is developed.

This study aims to propose an integrated model based on the DeLone and McLean Information System Success Model (DMISS) to examine whether quality factors (system, service and information) can affect user satisfaction and performance of cloud-based marketing systems.

Recently, technologies change quickly, innovation becomes a vital base of productivity and sustainable growth of businesses is widely accepted. Cyber-physical system technologies help industries change production and marketing cycles according to customers’ needs in real-time. In addition, processing information through cloud service helps companies meet customer needs. The advantages of cloud technology also make it easier for companies to quickly collect the latest data from various sources, making it more effective in decision-making. This research recommends cloud-based marketing to help companies maximize their revenue by providing useful information and better quality for business development. The data were gathered from China automotive companies’ customers. A total of 220 questionnaires were distributed, and 165 (82.5%) usable questionnaires were analyzed using structural equation modeling.

This study verified that costumers’ perceived information quality, system quality and service quality positively caused the user satisfaction in the cloud-based marketing system.

This paper presents beneficial advice for improving cloud-based marketing systems. Besides, the topic is relevant to cloud-based marketing systems’ success. A better understanding of the impact of intention to use and user satisfaction on cloud-based marketing systems could significantly enhance companies’ success. This paper’s theoretical and practical contributions are expressed to guide organizations and policymakers in increasing cloud-based marketing systems acceptance.

This study empirically tests the relationship of quality factors and performance outcome of cloud-based marketing system through a model based on DeLone and McLean theory. This study bridges the research gap by identifying the factors that drive the adoption of cloud-based services in marketing and the impact of user satisfaction and intention to use on the cloud-based marketing system performance in the case of china companies.

This paper aims to explore factors influencing apartment price volatility in the two biggest cities in Vietnam, Hanoi and Ho Chi Minh City.

The study uses the supply and demand approach and provides a literature review of previous studies to develop four main hypotheses using four determinants of apartment price volatility in Vietnam: gross domestic product (GDP), inflation rate, lending interest rate and construction cost. Subsequently, the Vector Error Correction Model (VECM) is used to analyze a monthly data sample of 117.

The research highlights the important role of construction costs in apartment price volatility in the two largest cities. Moreover, there are significant differences in how all four determinants affect apartment price volatility in the two cities. In addition, there is a long-run relationship between the determinants and apartment price volatility in both Hanoi and Ho Chi Minh City.

Limitations related to data transparency of the real estate industry in Vietnam lead to three main limitations of this paper, including: this paper only collects a sample of 117 valid monthly observations; apartment price volatility is calculated by changes in the apartment price index instead of apartment price standard deviation; and this paper is limited by only four determinants, those being GDP, inflation rate, lending interest rate and construction cost.

The study provides evidence of differences in how the above determinants affect apartment price volatility in Hanoi and Ho Chi Minh City, which helps investors and policymakers to make informed decisions relating to the real estate market in the two biggest cities in Vietnam.

This paper makes several recommendations to policymakers and investors in Vietnam to ensure a stable real estate market, contributing to the stability of the national economy.

This paper provides a new approach using VECM to analyze both long-run and short-run relationships between macroeconomic and sectoral independent variables and apartment price volatility in the two biggest cities in Vietnam.

This study focuses on analyzing the relation between money supply, inflation and output in Vietnam and China.

Using the error correction model and the vector autoregression model (ECM and VAR) and the canonical cointegration regression (CCR), the study shows similar patterns of these variable relations between the two economies.

The study points out the difference in the estimated coefficients between the two countries with different economic scales. While inflation in Vietnam is strongly influenced by expected inflation and output growth, inflation in China is strongly influenced by money supply growth and output growth.

To the best of the authors’ knowledge, this is the first empirical and comparative research on the relation between money supply, inflation and output for Vietnam and China. The study demonstrates that the relationship between money supply, inflation and output is still true in case of transition economies.

The paper is aimed to avoid the situation that historical relics are encroached, isolated and fragmented because of cities in the rapid urban process. Taking the environment around the Qinglong Temple in Xi'an city as an example and based on the characteristics of urban patterns in the history, this paper explores the spatial connection relationship between historical relics and surrounding villages as well as the connection between metro traffic and commercial bodies. At the end of the paper, the improvement strategy is put forward, namely the design concepts of “stepwise style” and “landscape style”, which can be achieved by the demand of ecological restoration and the relationship between urban axis. To be noted, the research shows, by restructuring new connection space, the city can promote the urban memory to be restored, the urban appearance to be reshaped, and the urban patterns in the history to be respected and displayed.

This paper investigates the impact of intellectual capital and its components on slack-based technical efficiency (SBM-TE) of banks.

Data envelopment analysis is used to compute SBM-TE scores and the Value-Added Intellectual Coefficient (VAIC™) model is used to measure intellectual capital. An unbalanced panel of 32 banks that operated from 2000 to 2017 has been used.

Overall, the efficiency scores are averaged at 79%, suggesting that an inefficient bank needs to enhance technical efficiency by 21% to be at par with the best performing banks. Beta-convergence and sigma-convergence exist among banks with faster speed evident among listed and local banks. Intellectual capital has a positive impact on SBM-TE and human capital is the main driver of technical efficiency among banks. This result is specifically evident among non-listed banks and foreign banks. Economies of scale property are also evident among the banks. Competition and asset tangibility inhibit technical efficiency among banks.

Banks are advised to invest in value-adding emerging technologies and their employees so as to enhance their efficiency. The study offers insights for policymakers, practitioners and researchers in emerging markets.

The study is premier in employing the SBM-TE to explain the intellectual capital and efficiency nexus, as well as, testing for both beta-convergence and sigma-convergence.

The finite element method has been increasingly applied in stress, thermal and dynamic analysis of gear transmissions. Preparing the models with different design and modification parameters for the finite element analysis is a time-consuming and highly skilled burden.

To simplify the preprocessing work of the analysis, a parametric finite element modeling method for spur and helical gears including profile and lead modification is developed. The information about the nodes and elements is obtained and exported into the finite element software to generate the finite element model of the gear automatically.

By using the three-dimensional finite element tooth contact analysis method, the effects of tooth modifications on the transmission error and contact stress of spur and helical gears are presented.

The results demonstrate that the proposed method is useful for verifying the modification parameters of spur and helical gears in the case of deformations and misalignments.

In 2001, the US moved to regulate internal control reporting by management and auditors. While some jurisdictions have followed the lead of the US, many others have not. An important question, therefore, is the relevance of internal control to stakeholders. The more specific issue of the benefits of US-style regulation of internal control reporting is also topical. We review studies on the determinants of internal control quality and its economic consequences for stakeholders including investors, creditors, managers, auditors and financial analysts. We extend previous reviews by focusing on US studies published since 2013 as well as all non-US studies investigating IC quality including countries regulating IC disclosure as well as unregulated settings and both developed and developing economies. In doing so, we identify research questions where evidence remains mixed and new directions in which there are research opportunities.

Three main insights arise from our analysis. First, evidence on the economic consequences of internal control quality suggests that the quality of internal control can have a significant effect on decision making by users of financial information. Second, the results of research on the empirical association between ownership structure, certain board characteristics and internal control quality is generally mixed. Empirical evidence concerning the association between audit committee characteristics and internal control quality generally supports a positive and significant association. Finally, while studies in non-US jurisdictions are increasing, opportunities remain to explore the determinants and consequences of internal control in other jurisdictions. Our review provides evidence for policy makers of whether there are benefits from requiring management and auditors to report on internal control over financial reporting.

This paper aims to undertake the efficiency analysis in the form of stochastic frontier to estimate a Cobb–Douglas production function by controlling for the heterogeneity across Russian firms by including firm size, ownership, age, innovation activity and market competition.

During the peak period of Covid-19, certain firms witnessed either a decrease or increase in sales. Using this segregation of firms from World Bank’s Covid-19 impact surveys follow-up to the Enterprise Survey for Russia, this study empirically investigates the determinants of technical efficiency of these firms focusing on the role of government assistance.

The findings suggest that by segregating firms in terms of sales, different internal factors can enable in steering through pandemic situation besides just depending on external assistance.

One of the few papers to analyse the impact of the pandemic on Russian firms by considering World Bank Covid Survey.

This study examined a mediating model of income and pay satisfaction with a direct path (income → pay satisfaction) and an indirect path with two mediators (income → the love of money → pay equity comparison → pay satisfaction). Results of the whole sample showed that the indirect path was significant and the direct path was insignificant. When the indirect path was eliminated, income contributed positively to pay satisfaction. We then tested the model across two moderators: culture (the United States versus Spain) and gender. This study provides the following theoretical and empirical contributions: the direct relationship between income and pay satisfaction depends on the indirect path and the extent to which (1) income enhances the love of money and (2) the love of money is applied to evaluate pay equity comparison satisfaction. If both conditions exist, income leads to pay dissatisfaction. If the second condition does not exist, income does not lead to pay dissatisfaction. Pay satisfaction depends on (1) one’s love of money and (2) how one compares. The role of the love of money in pay satisfaction is “not”universal across cultures and gender.