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This study aims to propose a novel method based on model learning with sparsity inducing norms for estimating dynamic gravity terms of the serial manipulators. This method is realized by operating the robot, acquiring data and filtering the features in signal acquisition to adapt to the dynamic gravity parameters.

The core principle of the method is to analyze the dictionary composition of the basis function of the model based on the dynamic equation and the Jacobian matrix of an arm. According to the structure of the basis function and the sparsity of the features, combined with joint-angle and driving-torque data acquisition, the effective features of dynamic gravity parameters are screened out using L1-norm optimization and learning algorithms.

The theoretical analysis revealed that training data obtained based on joint angles and driving torques could rapidly update dynamic gravity parameters. The simulation experiment was carried out by using the publicly available robot model and compared with the previous disassembly method to evaluate the feasibility and performance. The real 7-degree of freedom (DOF) industrial manipulator was used to further discuss the effects of the feature selection. The results show that this estimation method can be fully operational and efficient in industrial applications.

This approach is applicable to most serial robots with multi-DOF and the dynamic gravity parameters of the robot are estimated through learning and optimization. The method does not require prior knowledge of the robot arm structure and only requires joint-angle and driving-torque data acquisition under low-speed motion. Furthermore, as it is a data-driven-based method, it can be applied to gravity parameters updating.

Different from previous general robot dynamic modelling methods, the sparsity of the analytical form of dynamic equations was exploited and model learning was formulated as a convex optimization problem to achieve effective gravity parameters screening. The novelty of this estimation approach is that the method does not only require any prior knowledge but also does not require a specifically designed trajectory. Thus, this method can avoid the laborious work of parameter calibration and the induced modelling errors. By using a data-driven learning approach, the new parameter updating process can be completed conveniently when the robot carries additional mass or the end-effector changes for different tasks.

This paper aims to use the approach based on the application of the law of gravity for the study of the flows of export and the effects of the RTAs.

In this paper, the authors evaluate the effects of RTAs on exports between members and non-members taking into account the Vinerian specification. The authors also try to estimate the impact of the recent economic crisis on the flows of export and the success of the RTAs. The authors use a model of static and dynamic gravity for 40 countries and six RTAs during the period 1980-2011.

Definitely the proliferation of RTAs will continue to be one of the driving forces that will constitute the political system and the global economy in the following years. It indicates a process that implies the merger of economies separated in bigger regions of free trade. Regional integration is seen as beneficial in many senses and is the major economic objectives in addition to presenting a stabilizing factor in international relations.

The gravity model is estimated using the last techniques of panel data which takes into account the endogeneity of the effects of integration and the existence of dynamic effect.

Economists have had problems interpreting the gravity model, particularly as applied to migration behaviour. Its physical analogy is unappealing and theories of economic behaviour do not generally give rise to gravity laws. Some years ago Niedercorn and Bechdolt (1969) published a paper in which they provide a derivation of the gravity model using utility theory. Their approach is, however, much more applicable to other flows of human interaction across space, such as travel or communication flows, than it is to migration flows. The major purpose of this paper is to indicate a set of assumptions which might underlie a gravity model of migration and to show that these assumptions are quite severe. One important implication is that we should fully expect any real world migration pattern to deviate from the predictions of a gravity model. Nevertheless, the gravity specification may be a useful starting point in the analysis of migration behaviour, as it imposes restrictions on the formulation of the estimating equations. Thus we may fruitfully study how and why the real world migration patterns diverge from gravity flows.

The purpose of this paper is to analyse the role of the enlargement process of the European Union as a factor fostering international competitiveness of EU Member States. The paper argues that the economic integration process has reduced the technological gap between old and new EU Member States, and this pattern of technological innovation can partially explain the strong impulse on the export dynamics of European countries.

The paper builds an augmented gravity model by including the role of technological innovation, proxied by the stock of knowledge at the sector level. The authors gather together information on patents applied to international offices and bilateral export flows available from COMTRADE dataset.

By using a dynamic panel data estimator the authors find three main empirical evidences. First, the enlargement process has produced an overall larger positive impact on export flows for new Members than for old ones, and more importantly that sectors with the higher technological content have received the strongest impulse. Second, the augmented gravity model allows shaping the crucial role of technological innovation in fostering export competitiveness. Third, this impact seems to be stronger for old EU Member States than for new ones.

The major limitation concerns time span adopted in this work. By expanding the dataset to further years it could be possible to better disentangle the effects also related to the new wave of the EU enlargement.

The policy implication derived is that the more the new EU Members catch up technologically as a result of the integration process, the more they will benefit in terms of economic development.

The major originality of this paper is the construction of an augmented gravity model by including the role of technological innovation, applied to distinguished manufacturing sectors in a dynamic panel setting.

Aerospace assembly demands high drilling position accuracy for fastener holes. Hole position error correction is a key issue to meet the required hole position accuracy. This paper aims to propose a combined hole position error correction method to achieve high positioning accuracy.

The bilinear interpolation surface function based on the shape of the aerospace structure is capable of dealing with position error of non-gravity deformation. A gravity deformation model is developed based on mechanics theory to efficiently correct deformation error caused by gravity. Moreover, three solution strategies of the average, least-squares and genetic optimization algorithms are used to solve the coefficients in the gravity deformation model to further improve position accuracy and efficiency.

Experimental validation shows that the combined position error correction method proposed in this paper significantly reduces the position errors of fastener holes from 1.106 to 0.123 mm. The total position error is reduced by 43.49% compared with the traditional mechanics theory method.

The position error correlation method could reach an accuracy of millimeter or submillimeter scale, which may not satisfy higher precision.

The proposed position error correction method has been integrated into the automatic drilling machine to ensure the drilling position accuracy.

The proposed position error method could promote the wide application of automatic drilling and riveting machining system in aerospace industry.

A combined position error correction method and the complete roadmap for error compensation are proposed. The position accuracy of fastener holes is reduced stably below 0.2 mm, which can fulfill the requirements of aero-structural assembly.

Political risk factors play a pivotal role in determining the bilateral trade flow of Asian countries in general and the Association for Southeast Asian Nations (ASEAN) countries in particular. The main purpose of this research paper is to examine the impact of disaggregated political risk in lowering the bilateral trade flow of Thailand, a prominent member of ASEAN, vis-à-vis her 132 trading partners.

Using panel data of Thailand with her partner countries for the period 1984–2015, this paper uses four different panel specifications named pooled ordinary least squares and random effects estimations (estimated generalized least squares estimation) of three types by controlling for cross-sectional heteroscedasticity, time-wise heteroscedasticity and contemporaneous correlation.

Holding other gravity-based determinants constant, for one unit increase in the ranking of indicator of military in politics at home and abroad, trade flow decreases by 5–9% of the total trade flow of Thailand per year. For other types of political risks like government instability at home and abroad, difficulties in investment profile at home and abroad and internal and external conflict at home and abroad, the decrease is also substantial and most statistically significant. The magnitude of loss due to the military channel at home and abroad can amount to US$9.38–US$16.88 bn per year for Thailand, after controlling for other gravity variables.

The reasons for risk originating from different political channels could be explored at the regional or global level to understand their global and local dimensions.

Policymakers should attempt to resolve the political risks at home and abroad in an amicable manner, through dialogue, so that bilateral trade flow is not inhibited.

By taking economic reforms only, the trading problem cannot be resolved until and unless Thailand involves her society, politics and administrative mechanisms in a conducive manner to facilitate her trade. A dialogue among bureaucracy, political authority and military is beneficial in mitigating political risks.

The paper is unique in the sense that it makes a solid attempt to identify the potential channels of disaggregated political risk in affecting trade flow negatively, in a gravity framework, by controlling for different kinds of error structure.

This study attempts to explore the determinants of tourism demand that impact tourist arrivals in Australia from Asia using an augmented panel gravity model.

The augmented panel gravity model was utilised to analyse the demand for Australian tourism from 15 major countries of Asia over the period 1991 to 2018. Tourist arrivals were the dependent variable while per capita gross domestic product (GDP) and weighted distance were important explanatory variables. Further other indicators like population, money supply, globalisation, price index, exchange rate, uncertainty and two dummy variables were added as control variables.

The results demonstrate based on the novel methodology of Pesaran (2006), namely CCE (common correlated effects) that tourist arrivals are impacted positively and significantly by per capita GDP of both the country of origin and destination country, globalisation also impacts tourist flows positively. However, tourist arrivals are adversely affected by distance and prices confirming the economic theory.

Gravity models have been intensively used in the recent literature on tourism; however, this study has attempted to explore tourism demand from Asia into Australia which is indeed an unexplored area further the study has used the CCE methodology which takes care of the problems of cross-sectional dependence unlike the earlier methods widely used in the literature like the DOLS and the FMOLS. Last by utilising a wide-ranging set of macro factors the study contributes a novel assessment to the recent literature on tourism demand model.

This paper aims to address a new iterative tuning method of PID control for robot manipulators.

This tuning method uses several properties of the robot control, such as any PD control can stabilize a robot in regulation case, the closed-loop system of PID control can be approximated by a linear system, the control torque to the robot manipulator is linearly independent of the robot dynamic.

Compared with the other PID tuning methods, this novel method is simple, systematic, and stable. The transient properties of this PID control are better than the other normal PID controllers.

In this paper, a new systematic tuning method for PID control is proposed. The paper applies this method on an upper limb exoskeleton, and real experiment results give validation of our PID tuning method.

The purpose of this paper is to examine the determinants of foreign direct investment (FDI) flows from some leading developed countries (the USA, Japan, Germany, the Netherlands, the UK and France) into major four Asian economies (China, Korea, India and Singapore).

Using one basic and four augmented versions of gravity model technique, the authors tried to examine the determinants of bilateral FDI flows in four major Asian economies. The study used World Development Indicators, CEPII, KOF and Heritage Foundation data for period 2001–2012.

The results revealed that besides the market size for host and source country, other criteria such as distance, common language and common border also influence foreign investors. Other macroeconomic factors such as inflation rate and real interest rate are among the key factors that attract more FDI. In addition to economic factors, institutional and infrastructural factors such as telecommunication, degree of openness, index of globalisation and index of economic freedom also stimulate the international investors from the developed world to the major Asian countries.

It is altogether possible that only a set of home country specific characteristics or host country specific characteristics does not matter when determining FDI. Most empirical studies using indices such as the index of globalisation and economic freedom are subject to certain methodological limitations such as model selection, parameter heterogeneity, outliers and moral hazard.

More distance between the host and source country would result in less FDI flows due to more managerial and raw material supply chain cost. Similarly, more gross domestic product (GDP) and per capita income (PCI) are leading to more FDI flows into Asian economics. Therefore, major Asian economies should frame their economic policies in such a manner where these counties can strengthen their GDP as well as PCI. Furthermore, above countries should open its economy more and more for better FDI flows as it seems that economic globalisation and economic freedom are major determinants of bilateral FDI flows. The negative impact of inflation and interest rate should be controlled.

From policy perspective, higher scores of economic, social and political globalisation also attract high FDI to the host country. On the same line higher scores in economic freedom mean that less restrictions in terms of economic policies and the policy environment are conducive for free trade and resource transfers. Higher scores in trade freedom, investment freedom and freedom from corruptions also show more developed and conducive policy environment. In the same reasoning higher scores in the composite index of economic freedom which takes information from trade freedom, investment freedom and freedom from corruption and others also encourage flow of FDI in to the host country.

This is the first paper which combines the globalisation index, economic freedom index and distance along with some major macroeconomic variables.

The aim of this paper is to implement direct teaching of industrial manipulators using current sensors. The traditional way to implement teaching is either to use a teaching pedant, which is time consuming, or use force sensors, which increases system cost. To overcome these disadvantages, a novel method is explored in the paper by using current sensors installed at joints as torque observers.

The method uses current sensors installed at each joint of a manipulator as torque observers and estimates external forces from differences between joint-driven torque computed based on the values of current sensors and commanded values of motor-driven torque. The joint-driven torque is computed by cancelling out both pre-calibrated gravity and friction resistance (compensation). Also, to make the method robust, the paper presents a strategy to detect unexpected slowly drifts and zero external forces and stop the robot in those situations.

Experimental results demonstrated that compensating the joint torques using both pre-calibrated gravity and friction resistance has performance comparable to a force sensor installed on the end effector of a manipulator. It is possible to implement satisfying direct teaching without using force sensors on 7 degree of freedom manipulators with large mass and friction resistance.

The main contribution of the paper is that the authors cancel out both pre-calibrated gravity and friction resistance to improve the direct teaching using only current sensors; they develop methods to avoid unsafe situations like slow drifts. The method will benefit industrial manipulators, especially those with large mass and friction resistance, to realize flexible and reliable direct teaching.