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This paper aims to find a new method that could be applied to the high and mid-grade prosthesis knee joint.

Based on analysis, calculation, modeling, simulation and experimental study of the motion law of knee joint, this paper not only determines the structure and parameters of the knee joint and calculates the instantaneous center but also analyzes the stance stability and completes the optimization. With the help of experimental tests (fatigue test and gait curve test), the quality and performance of the designed knee joint is verified.

The experimental results show that the gait curve of the designed knee joint is much closer to health people. The designed prosthesis knee joint, with adjustable swing speed and gait curve which are close to health limb, has a better performance when compared to the ordinary knee joint with four-bar linkage structure.

This paper developed a prosthesis knee joint based on a novel design method that could be applied to the “high and mid” grade prosthesis knee joint and verified its function on an amputee performed the lower amputation, which could provide theoretical support for researches and designs related to prosthesis knee joint in future.

The purpose of this paper is to introduce an innovative theoretical, numerical and experimental investigations on the HP NGD function. The identified HP NGD topology under study is constituted by first order passive RC-network. The simulations and measurements confirm in very good agreement the HP NGD behaviors of the tested circuits. NGD responses with optimal values of about -1 ns and cut-off frequencies of about 20 MHz are obtained.

The identified HP NGD topology understudy is constituted by a first-order passive Resistor-capacitor RC network. An innovative approach to HP NGD analysis is developed. The analytical investigation from the voltage transfer function showing the meaning of HP properties is established.

This paper introduces innovative theoretical, numerical and experimental investigations on the HP NGD function.

The NGD characterization as a function of the resistance and capacitance parameters is investigated. The feasibility of the HP NGD function is verified with proofs of concept constituted of lumped surface mounted components on printed circuit boards. The simulations and measurements confirm in very good agreement the HP NGD behaviors of the tested circuits. NGD responses with optimal values of about −1 ns and cut-off frequencies of about 20 MHz are obtained.

This paper aims to develop a signal acquisition system of surface electromyography (sEMG) and use the characteristics of (sEMG) signal to interference action pattern.

This paper proposes a fusion method based on combining the coefficient of AR model and wavelet coefficient. It improves the recognition rate of the target action. To overcome the slow convergence speed and local optimum in standard BP network, the study presents a BP algorithm which combine with LM algorithm and PSO algorithm, and it improves the convergence speed and the recognition rate of the target action.

Experiments verify the effectiveness of the system from two aspects the target motion recognition rate and the corresponding reaction speed of the robotic system.

The study developed a signal acquisition system of sEMG and used the characteristics of (sEMG) signal to interference action pattern. The myoelectricity integral values are presented to determine the starting point and end point of target movement, which is more effective than using single sample point amplitude method.

This study aims to examine the effect of the Securities and Exchange Commission's regulation fair disclosure (Reg. FD) on analyst forecast performance for pre‐Reg. FD closed‐call (CLC) and open‐call (OPC) firms compared with the non‐conference‐call (NCC) firms in the post‐Reg. FD period.

Specifically, it examines whether Reg. FD influenced the earnings forecast accuracy and forecast dispersion of financial analysts for the previous‐CLC firms in the post‐Reg. FD period compared with the previous‐OPC firms, and both sets of conference call firms relative to the NCC firms in the same period.

The main findings indicate that forecast accuracy improved for both OPC and CLC firms compared with the NCC firms in the post‐Reg. FD period. More importantly, the differences in earnings forecast performance between the pre‐Reg. FD OPC and CLC firms had disappeared in the post‐Reg. FD period.

These results offer further confirmation of previous findings that Reg. FD has contributed to leveling the playing field for financial analysts and investors.

Relative performance evaluation (RPE) involves board comparisons of firm performance to that of a peer group when evaluating CEO performance. To date, research on RPE in the USA has typically relied on models where RPE is implicitly assumed. In contrast, Bannister and Newman provide some direct evidence on the explicit RPE usage by US firms showing that it is limited and there is significant inter-industry variation in its use. The authors aim to focus on why boards in some industries employ RPE to a greater extent than those in other industries do using measures of industry discretion, industry homogeneity, industry competition.

The authors utilize the sample use in the Bannister and Newman study of RPE usage in industries (160 firms from the 1992 Fortune 250 with proxy statements for 1992 and 1993). The authors compile measures of industry membership (using SIC codes), industry discretion, industry homogeneity, and industry competition from Compustat a well. Multiple regression is used to test the hypotheses.

The authors find that the use of RPE at the industry level is significantly related to industry discretion (i.e. the degree of latitude that managers have over strategic and operational choices in the particular industry environment) and industry homogeneity, but not to industry competition.

The study is limited in terms of a dated sample (necessary to be consistent with the Bannister and Newman paper). It would bear updating. In addition, multi-year panel data could be used to generate more robust results. It would also be useful to replicate the study in other national (and hence governance) contexts.

The findings should help boards when deciding how to reward or punish CEOs and top managers for their firm performance by filtering out relative performance in a more rational manner (e.g. by taking relevant industry context into account).

In terms of originality, this is the first study, to the authors' knowledge, that investigates RPE at the industry level. It is valuable because industry discretion is an important contextual variable that a board of directors will find useful in evaluating managers since this type of discretion is beyond managerial control.

Need: The previous suggestion assists with administrative methodology. The contribution explores customer understandings in different industry and transaction texts. They include online education, video marketing, and entertainment analytics. The communication needs to be detailed to improve the system.

Purpose: The suggestion aims to improve the previous contribution by enhancing the user experience. The study increases the usage of video content. The recommendation brings better business to the video host.

Methodology: The work includes the machine learning algorithm to understand the user and improve the client’s experience. The recommendation uses the Apriori algorithm to map various attributes of the trainer and learners. The suggested work has three features. It focusses on video possessions, educator feelings, physical characteristics, and visible aesthetic characteristics. The study considers 1,200 different samples.

Findings: The work simulates using python. It improves efficiency by 29.5% compared to previous work.

Practical Implications: Machine learning has pitched in to understand diverse customers’ behaviour. Various features affecting the behaviour are collected and analysed by the system. The study intends to find an appropriate mapping between the attributes of the user and educator.

This research provides accounting-ethics authors and administrators with a benchmark for accounting-ethics research. While Bernardi and Bean (2010) considered publications in business-ethics and accounting’s top-40 journals this study considers research in eight accounting-ethics and public-interest journals, as well as, 34 business-ethics journals. We analyzed the contents of our 42 journals for the 25-year period between 1991 through 2015. This research documents the continued growth (Bernardi & Bean, 2007) of accounting-ethics research in both accounting-ethics and business-ethics journals. We provide data on the top-10 ethics authors in each doctoral year group, the top-50 ethics authors over the most recent 10, 20, and 25 years, and a distribution among ethics scholars for these periods. For the 25-year timeframe, our data indicate that only 665 (274) of the 5,125 accounting PhDs/DBAs (13.0% and 5.4% respectively) in Canada and the United States had authored or co-authored one (more than one) ethics article.

Lenders in online peer-to-peer (P2P) lending platforms are always non-experts and face severe information asymmetry. This paper aims to achieve the goals of gaining high returns with risk limitations or lowering risks with expected returns for P2P lenders.

This paper used data from a leading online P2P lending platform in America. First, the authors constructed a logistic regression-based credit scoring model and a linear regression-based profit scoring model to predict the default probabilities and profitability of loans. Second, based on the predictions of loan risk and loan return, the authors constructed linear programming model to form the optimal loan portfolio for lenders.

The research results show that compared to a logistic regression-based credit scoring method, the proposed new framework could make more returns for lenders with risks unchanged. Furthermore, compared to a linear regression-based profit scoring method, the proposed new framework could lower risks for lenders without lowering returns. In addition, comparisons with advanced machine learning techniques further validate its superiority.

Unlike previous studies that focus solely on predicting the default probability or profitability of loans, this study considers loan allocation in online P2P lending as an optimization research problem using a new framework based upon modern portfolio theory (MPT). This study may contribute theoretically to the extension of MPT in the specific context of online P2P lending and benefit lenders and platforms to develop more efficient investment tools.

Driving cycle is an essential requirement to evaluate the exhaust emissions of various types of vehicles on the chassis dynamometer test. This study presents a real world comparison of the driving cycles of Edinburgh motorcycles in two world cities; Edinburgh in Scotland and Delhi in India. The two driving cycles (EMDC & DMDC) driving cycle (EMDC) that were was developed through the analysis of experimental data. This data was collected from trips on a number of routes in each city. In Edinburgh, five different routes between the home addresses in the surrounding areas and place of work at Edinburgh Napier University in Edinburgh were selected. In Delhi data were collected in East Delhi (Geeta Calony) to Central Delhi (Raisena Road). The data collected data was divided into two categories of urban and rural roads in the case of Edinburgh while it was only the urban route in Delhi.. Forty four trips were made on the five designated routes in both urban and rural areas and 12 trips were made in Delhi. The aims of the study were to assess the various parameters (i.e. motorcycle speed, cruise, accelerations and decelerations and percentage time spent in idling) and their statistical validity over total trip lengths for producing a real world EMDC in each of the two cities. The results show that EMDC in Edinburgh, the EMDC has a cycle length of 770 and 656 seconds for urban and rural trips, respectively, which was found more than ECE cycle length. Time spent in acceleration and deceleration modes were found to be significantly higher than any other driving cycle reported to date for motorcycles, reflecting a typical characteristic of the driving cycle in Edinburgh; this was presumably due to diverse driving conditions of motorcycles in the city. In Delhi on the other hand, the DMDC has a cycle length of 847.5 seconds for the urban trips, which higher than that of the EMDC length. The overall percentage time spent in acceleration in Delhi was higher than that of Edinburgh while the time spent in deceleration was lower in Delhi. The overall average speed in the case of Delhi was slightly higher than that of Edinburgh.

The purpose of this paper is to review and explore the evolution, advances and future trends of cloud manufacturing, placing the focus on the quality of services. Moreover, moving toward the new trend of cyber-physical systems (CPS), a cloud-based cyber-physical system (CBCPS) is proposed combining the key enabling techniques of this decade, namely Internet of Things (IoT), cloud computing, Big Data analytics and CPS.

First, an extensive review is made on cloud computing and its applications in manufacturing sectors, namely product development, manufacturing processes and manufacturing systems management. Second, a conceptual CBCPS which combines key enabling techniques including cloud computing, CPS and IoT is proposed. Finally, a review on the quality of the services (QoS) presented in the second step, along with the main security issues of cloud manufacturing, is conducted.

The findings of this review indicate that the combination of the key enabling techniques presented in the CBCPS will lead to a new manufacturing paradigm capable of facing the new challenges and trends. The opportunities, as well as the challenges and barriers of the proposed framework are presented, concluding that the transition into this whole new era of networked computing and manufacturing has a valuable impact, but also generates several security and quality issues.

The paper is the first to specifically study the QoS as a factor in the proposed manufacturing paradigm.