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We propose in this paper a novel reliable detection method to recognize forged inpainting images. Detecting potential forgeries and authenticating the content of digital images is extremely challenging and important for many applications. The proposed approach involves developing new probabilistic support vector machines (SVMs) kernels from a flexible generative statistical model named “bounded generalized Gaussian mixture model”. The developed learning framework has the advantage to combine properly the benefits of both discriminative and generative models and to include prior knowledge about the nature of data. It can effectively recognize if an image is a tampered one and also to identify both forged and authentic images. The obtained results confirmed that the developed framework has good performance under numerous inpainted images.

This paper analyzes the impact of macroeconomic variables such as real exchange rate, exchange-rate volatility, and economic growth of the UK and Norway on Norway’s bilateral trade flow to the UK via maritime and other transport modes. The first two models considered trade volume (import and export) via only maritime transport, while the third and fourth models considered trade volume via modes other than maritime transport. The empirical validity of the Marshall-Lerner condition is tested to see whether a devaluation of the real exchange rate improves the trade balance in the long term. In addition to the long-term relationship among variables, short-term effects are also evaluated. The results show that the real income of Norway and its trading partner (the UK) is the main determinant of bilateral trade flow via maritime and other transport modes. Moreover, the results indicate that in the long run, the Marshall-Lerner condition is satisfied only for bilateral trade via modes other than maritime transport.

The purpose of this study is to empirically weigh the evidence for financial depth, liquidity and efficiency role to economic growth, and test for the existence of cointegration between financial development variables and economic growth in Tanzania.

The study used the autoregressive distributed lag model with bound testing procedures. The sample covered yearly time-series data from 1980 to 2017, i.e. 38 years.

The results suggest that financial system depth is positively related to economic growth in the short run and that financial system liquidity and efficiency is strongly negatively associated with economic growth both in the short and long run. Further, it is found that financial development is cointegrated with economic growth. Thus, financial reforms and liberalisation have not fully brought the desired positive effects on economic growth yet.

The study uses principal component analysis to capture specific dimensions within the financial system as an intuitive way to aggregate financial development effects. Unlike studies that included several countries with heterogeneous characteristics, which are sometimes difficulty to homogenise, in recognition of countries’ unique experiences, this study uses data from Tanzania as a specific case. It documents pertinent pieces of evidence for a developing economy necessary for financial policy adjustments post the financial and economic liberalisation and reforms period. It nevertheless sheds light on financial policies for other comparable developing economies during and after both financial and economic liberalisation settings.

The purpose of this study is to investigate long-run and short-run relationships between trade diversification, financial system development, capital formation and economic growth.

ARDL estimation approach is applied to analyze long-run and short-run relationships between the financial system development, capital formation, economic growth and trade diversification in case of the Sultanate of Oman over the period 39 years starting from 1979 till 2017.

The results show that financial system development and economic growth has a positive impact on trade diversification in the short-run and long-run. However, capital formation has a negative impact on trade diversification in the short run and long run. The negative relationship between trade diversification and capital formation implies that over the period of study, the investment in capital goods was made to enhance the production capacity of the oil sector to maximize revenue.

This research is limited to analyze long-run and short-run relationship between the financial system development, capital formation and economic growth and trade diversification in case of Sultanate of Oman.

To achieve the diversification goal, the policymakers need to formulate policies to strengthen the financial system and invest in infrastructure development to promote the non-oil sector. The research findings of this study will provide insights to the policymakers to formulate an effective diversification policy.

This research contributes to the existing literature by providing empirical evidence of the short-run and long-run analysis of the selected variables in the context of an oil-dependent country.

The purpose of this paper is to address the issue of knowledge visualization and its connection with performance measurement from an epistemological point of view, considering quantification and measurement not just as technical questions but showing their relevant implications on the management decision-making of knowledge-based organizations.

This study proposes a theoretical contribution that combines two lines of research for identifying the three main meta-choices problems that arise in the multidimensional benchmarking of knowledge-based organizations. The first is the meta-choice problem related to the choice of the algorithm used (Iazzolino et al., 2012; Laise et al., 2015; Daraio, 2017a). The second refers to the choice of the variables to be included in the model (Daraio, 2017a). The third concerns the choice of the data on which the analyses are carried out (Daraio, 2017a).

The authors show the interplay existing among the three meta-choices in multidimensional benchmarking, considering as key performance indicators intellectual capital, including Human Capital, Structural Capital and Relational Capital, and performances, evaluated in financial and non-financial terms. This study provides an empirical analysis on Italian Universities, comparing the ranking distributions obtained by several efficiency and multi-criteria methods.

This study demonstrates the difficulties of the “implementation problem” in performance measurement, related to the subjectivity of results of the evaluation process when there are many evaluation criteria, and proposes the adoption of the technologies of humility related to the awareness that we can only achieve “satisficing” results.

The main objective of this study is to examine how political institutions affect economic performance in Ethiopia over the 1980–2019 time periods.

Mainly, the impact of political institution indicators including, level of democracy, political violence, democratic accountability and regime durability have been examined using auto regressive distributed lag (ARDL) bound test approach to co-integration and the error correction model.

This study confirms that level of democracy and democratic accountability has an adverse long effect on the economic performance of Ethiopia. On the other hand, political violence has a negative short-run causal effect on economic performance in Ethiopia. The study concluded that the deterioration of political institutions harmfully affected economic performance in Ethiopia.

Government policymakers should primarily pay attention to promoting and changing those political institutions that harm economic performance. Additionally, better management of political violence has important implications for fostering the economic performance of Ethiopia.

This study provides some valuable evidence on the nexuses between political institutions and economic performance in Ethiopia. Likely, this is the first investigation on the subject under the consideration to use time analysis and will vigorously contribute to the literature as well by employing the ADRL bound test. Previous studies have examined the impact of the institution on economic growth on a cross-country basis. Further analysis is required to understand the effects of institutions such as level of democracy, political violence and democratic accountability on economic development.

The purpose of this paper is to investigate US noncombatant evacuation operations (NEO) in South Korea and devise planning and management procedures that improve the efficiency of those missions.

It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. This solution considers the capacity and resource constraints of multiple transportation modes and effectively allocates the limited assets across a time-staged network to create a feasible evacuation plan. That solution is post-processed and a vehicle routing procedure then produces a high resolution schedule for each individual asset throughout the entire duration of the NEO.

This work makes a clear improvement in the decision-making and resource allocation methodology currently used in a NEO on the Korea peninsula. It immediately provides previously unidentifiable information regarding the scope and requirements of a particular evacuation scenario and then produces an executable schedule for assets to facilitate mission accomplishment.

The significance of this work is not relegated only to evacuation operations on the Korean peninsula; there are numerous other NEO and natural disaster related scenarios that can benefit from this approach.