Hasil untuk "Balance of trade"

Yusuff Ridwan, Shunde Yin

The accelerating development of offshore wind energy in the Great Lakes region necessitates cost-effective solutions for auxiliary infrastructure, such as meteorological masts. While monopile foundations are well-established for turbine generators, their high flexural rigidity and capital cost are often disproportionate for non-generating platforms. This study presents a parametric optimization of a guyed tower foundation situated in the nearshore limestone shelf of Lake Huron (Point Clark), specifically designed to balance strict signal serviceability with foundation economy. Using a non-linear static solver with Ernst equivalent cable moduli, a full factorial sweep of 48 design configurations was conducted under site-specific hydrodynamic loads (1300 kN Average/3500 kN Storm). The results demonstrate that while all configurations satisfied the 0.004 rad rotation limit mandated by TIA-222-H, significant non-linear trade-offs exist between structural stiffness and foundation demand. Specifically, a “cost of rigidity” was identified, where increasing cable pretension to 800 kN resulted in foundation overturning moments exceeding 9.6 × 10⁴ kN·m—a threefold increase compared to lower-pretension alternatives. To resolve this trade-off, a formal multi-objective scoring function was applied to rank designs based on rotation, moment, and displacement. The analysis identifies a “balanced” configuration comprising three guys with high-stiffness anchors (5 × 10⁷ N/m) and moderate pretension (300–500 kN) as the optimal design. This configuration leverages the competent bedrock to minimize cable tension requirements, offering a resilient and economically efficient solution for Great Lakes offshore monitoring.

Florentin D. Hildebrandt

On-demand restaurant meal delivery platforms, such as DoorDash and Meituan, have recently introduced a multi-order delivery service: Customers may combine delivery requests from different restaurants in a single multi-order with the service promise of a synchronized delivery. However, the platform must not only ensure the synchronization of multi-orders but also improve punctuality and freshness for all customers. This is challenging because, as we show, synchronization, delay, and freshness are conflicting objectives. Uncertainty in the delivery process and unknown future orders further complicate the decision making. This raises several research questions: How does the introduction of a multi-order service affect the overall delivery operations with regard to service quality and operational expenses? How should a multi-order service be strategically rolled out? How can we balance the competing objectives of synchronizing deliveries while minimizing delay and maximizing freshness? To answer the research questions, we propose an effective policy that allows for a careful and controlled balance between the competing objectives and employ it in an extensive computational study. We evaluate the effect of different trade-offs between delay, freshness, and synchronization on delivery operations over varying demand for multi-orders. We observe that enforcing strict synchronization of multi-orders by assigning each multi-order to a single delivery driver is hardly operational feasible. Occasionally using split-deliveries provides the flexibility to better balance all objectives. Our detailed experiments further generate insights on how platforms may roll-out multi-orders as a new service offering without negatively affecting their existing delivery operation while benefiting from reduced operational expenses.

Joanna Wyszkowska-Kuna

The aim of this article is to assess the competitiveness and specialisation of Polish knowledge-intensive business services (KIBS) export during the years 2004–2022. The product mapping method is used, which is based on the values of two indicators, i.e.: the normalised revealed comparative advantage index (NRCA) and the trade balance index (TBI). The study contributes to the academic literature by: (1) identifying the leading exported KIBS as well as KIBS with the potential to gain comparative advantage in Polish exports; (2) examining export competitiveness and specialisation in very narrow KIBS categories for the entire period of Poland's participation in European Single Market; (3) comparing the competitiveness and export specialisation of the KIBS sector in Poland in the EU and non-EU markets. The empirical results demonstrate that some of the KIBS industries in Poland have improved their competitiveness during the period of EU membership, but rather in exports outside the EU than to the EU. This may be due to strong competition in EU market and the fact that distance does not play a significant role in trade in services, especially in case of KIBS delivered online (e.g. computer services). Poland has developed a regional specialisation in the export of accountancy services, which is proved by the highest values of both indicators for this category, compared to other KIBS categories in Poland and compared to other EU countries. On the other hand, computer services appeared to be the leading exported product from the KIBS sector, but only outside the EU. Unfortunately, despite the upward trends, the importance of the leading exported KIBS in Polish exports is still small, especially in EU market. Therefore, it is necessary to take further actions aimed at strengthening the competitiveness of the KIBS sector in Poland, and the support for investments in human capital, digital transformation and R&D is crucial.

T. V. Soumya, M. K. Sabu

Abstract The sequential three-way decision accepts additional information at each level and makes more accurate definite decisions with less uncertainty. This process can also be extended to two-way classification with the finer-grained information level. However, both the decision process cost and decision result cost of the model must be considered for optimal performance. The proposed model adapts the game-theoretic approach to deal with the trade-off between the decision process cost and the decision result cost, and thereby balance the number of levels of the model. The time complexity, information level, and feature importance contribute to the process cost while evaluation metrics stand for the result cost. The model starts with reliable initial results by using the most significant features at the first level itself and follows an objective function-based method to determine threshold pairs at each level, which avoids relying on domain experts. Furthermore, if the process cost outweighs the result cost, the number of levels is adjusted accordingly. Using the experimental datasets, instances are classified at each level at the optimal threshold pairs; therefore the trisection is obtained with the highest precision/recall value. The obtained results prove that the proposed model outperforms existing models in terms of precision, recall, and time complexity with balanced decision costs. In summary, the proposed model is cost-efficient, interpretable, termination-aware, and result-oriented, ensuring effective and practical decision-making.

Xiaoping Zhang, Chengliang Huang, Weixia Gui

Abstract The standard crow search algorithm suffers from low convergence accuracy, insufficient stability, and susceptibility to getting stuck in local optima. To tackle these formidable challenges, this paper proposes a novel multi-strategy improved crow search algorithm (MSICSA) specifically designed for multi-level image segmentation. The proposed approach incorporates three key enhancements: firstly, opposition-based learning (OBL) is utilized to improve the quality of initial solutions within MSICSA; secondly, an adaptive awareness probability mechanism is introduced to better balance the trade-off between exploration and exploitation; lastly, two differential mutation operators are developed to enhance global search capabilities, increase population diversity, and reduce the risk of converging on local optima. To validate the performance of the proposed algorithm, two sets of experiments are conducted. In the first set of experiments, CEC 2020 benchmark test functions are selected to compare the performance of MSICSA with other group intelligent optimization algorithms. In the second set of experiments, Otsu’s method and fuzzy entropy are employed as objective functions for performing multilevel threshold segmentation on twelve grayscale images. The experimental results demonstrate that MSICSA outperforms seven comparison algorithms in terms of both convergence speed and segmentation quality.

Vidya Venkatesan, Aomawa L. Shields, Russell Deitrick et al.

Eccentric planets may spend a significant portion of their orbits at large distances from their host stars, where low temperatures can cause atmospheric CO2 to condense out onto the surface, similar to the polar ice caps on Mars. The radiative effects on the climates of these planets throughout their orbits would depend on the wavelength-dependent albedo of surface CO2 ice that may accumulate at or near apoastron and vary according to the spectral energy distribution of the host star. To explore these possible effects, we incorporated a CO2 ice-albedo parameterization into a one-dimensional energy balance climate model. With the inclusion of this parameterization, our simulations demonstrated that F-dwarf planets require 29% more orbit-averaged flux to thaw out of global water ice cover compared with simulations that solely use a traditional pure water ice-albedo parameterization. When no eccentricity is assumed, and host stars are varied, F-dwarf planets with higher bond albedos relative to their M-dwarf planet counterparts require 30% more orbit-averaged flux to exit a water snowball state. Additionally, the intense heat experienced at periastron aids eccentric planets in exiting a snowball state with a smaller increase in instellation compared with planets on circular orbits; this enables eccentric planets to exhibit warmer conditions along a broad range of instellation. This study emphasizes the significance of incorporating an albedo parameterization for the formation of CO2 ice into climate models to accurately assess the habitability of eccentric planets, as we show that, even at moderate eccentricities, planets with Earth-like atmospheres can reach surface temperatures cold enough for the condensation of CO2 onto their surfaces, as can planets receiving low amounts of instellation on circular orbits.

Vo Phuc Tinh, Hoang Hai Son, Nguyen Hoang Nam et al.

In the large-scale deployment of federated learning (FL) systems, the heterogeneity of clients, such as mobile phones and Internet of Things (IoT) devices with different configurations, constitutes a significant problem regarding fairness, training performance, and accuracy. Such system heterogeneity leads to an inevitable trade-off between model complexity and data accessibility as a bottleneck. To avoid this situation and to achieve resource-adaptive FL, we introduce CrossHeteroFL to deal with heterogeneous clients equipped with different computational and communication capabilities. Our solution enables the training of heterogeneous local models with additional computational complexity and still generates a single global inference model. We demonstrate several CrossHeteroFL training scenarios and conduct extensive empirical evaluation, covering four levels of the computational complexity of three-model architectures on two datasets. The proposed mechanism provides the system with non-elementary access to a scattered fit among clients. However, the proposed method generalizes soft handover-based solutions by adjusting the model width according to clients’ capabilities and a tiered balance of data-source overviews to assess clients’ interests accurately. The evaluation results indicate our method solves the challenges in previous studies and produces greater top-1 accuracy and consistent performance under heterogeneous client conditions.

Shekhar Sharan Goyal, Raviraj Dave, Rohini Kumar et al.

Abstract Intensive agricultural practices have powered green revolutions, helping nations attain self-sufficiency. However, these fertilizer-intensive methods and exploitative trade systems have created unsustainable agricultural systems. To probe the environmental consequences on production hubs, we map the fate of Nitrogen and Phosphorus in India’s interstate staple crop trade over the recent decade. The nation’s food bowls, while meeting national food demand, are becoming pollution-rich, sustaining around 50% of the total surplus from trade transfer, accounting for 710 gigagrams of nitrogen per year and 200 gigagrams of phosphorus per year. In combination with water balance analysis, surplus nutrient conversion to a graywater footprint further highlights an aggravated situation in major producer regions facing long-term water deficits. Given India’s role in global food security, identifying the nation’s environmental vulnerability can help in designing appropriate policy interventions for sustainable development.

Célestin Coquidé, José Lages, Dima L. Shepelyansky

We extend the opinion formation approach to probe the world influence of economical organizations. Our opinion formation model mimics a battle between currencies within the international trade network. Based on the United Nations Comtrade database, we construct the world trade network for the years of the last decade from 2010 to 2020. We consider different core groups constituted by countries preferring to trade in a specific currency. We will consider principally two core groups, namely, 5 Anglo-Saxon countries which prefer to trade in US dollar and the 11 BRICS+ which prefer to trade in a hypothetical currency, hereafter called BRI, pegged to their economies. We determine the trade currency preference of the other countries via a Monte Carlo process depending on the direct transactions between the countries. The results obtained in the frame of this mathematical model show that starting from year 2014 the majority of the world countries would have preferred to trade in BRI than USD. The Monte Carlo process reaches a steady state with 3 distinct groups: two groups of countries preferring, whatever is the initial distribution of the trade currency preferences, to trade, one in BRI and the other in USD, and a third group of countries swinging as a whole between USD and BRI depending on the initial distribution of the trade currency preferences. We also analyze the battle between USD, EUR and BRI, and present the reduced Google matrix description of the trade relations between the Anglo-Saxon countries and the BRICS+.

Jin Sima, Chao Pan, Olgica Milenkovic

A combinatorial trade is a pair of sets of blocks of elements that can be exchanged while preserving relevant subset intersection constraints. The class of balanced and swap-robust minimal trades was proposed in [1] for exchanging blocks of data chunks stored on distributed storage systems in an access- and load-balanced manner. More precisely, data chunks in the trades of interest are labeled by popularity ranks and the blocks are required to have both balanced overall popularity and stability properties with respect to swaps in chunk popularities. The original construction of such trades relied on computer search and paired balanced sets obtained through iterative combining of smaller sets that have provable stability guarantees. To reduce the substantial gap between the results of prior approaches and the known theoretical lower bound, we present new analytical upper and lower bounds on the minimal disbalance of blocks introduced by limited-magnitude popularity ranking swaps. Our constructive and near-optimal approach relies on pairs of graphs whose vertices are two balanced sets with edges/arcs that capture the balance and potential balance changes induced by limited-magnitude popularity swaps. In particular, we show that if we start with carefully selected balanced trades and limit the magnitude of rank swaps to one, the new upper and lower bound on the maximum block disbalance caused by a swap only differ by a factor of $1.07$. We also extend these results for larger popularity swap magnitudes.

Munir Ahmad, Gul Jabeen, S. Shah et al.

Nilay Tulukcu Yildizbas, Hülya Kılıç Hernandez, Hülya Yıldırım et al.

The current study emphasizes the inherent shortcomings of laws and policy approaches that are based on the premise that by increasing wood production, much more emission credits can be achieved by using wood in alternative uses. The article aims to exploit the financing of emission reductions, discuss how carbon sinks held in forest resources can be activated, traded, and financed, and explain how Turkiye's forest carbon potential can be exploited. To make a comparative analysis of the situation of Turkiye at global level, Russian’s potential for carbon sequestration and its trade have been dealt with as a comparison by following quantitative research methodology.  In this research, the calculation method has been used to determine the number of houses that are likely to be built in rural areas using wood materials, e.g., the construction of 100,000 houses with a construction area of 100 m2 per year. Consequently, the forest carbon generated by alternative scenarios contributes positively to the emission balance sheet, as well as climate change mitigation through carbon emission trade despite all legal and technical constraints. Although both countries have similar shortcomings of obtaining carbon credits and its trade, of course Russia has a promising situation in comparison with Turkiye with respect to the amount of carbon sequestered and the likelihood of its trade potential at global level.

V.V. , T.O. , I.H.

The article reveals the problems that arose in the field of foreign trade policy formation and implementation as a result of the Russian invasion of the territory of Ukraine. Foreign trade is one of the components of the formation of the national economy, and its state affects the gross national product, the country's balance of payments and other socio-economic indicators of the country's development. Using the methods of analysis and synthesis, comparison and generalization, an analysis of the commodity and geographical structure of foreign trade in goods was carried out before and after the full-scale invasion of Russia into the territory of Ukraine. The consequences of the changes that occurred in the structure of export-import operations were analyzed. Reduction of export and import volumes for almost all groups of goods and reduction of shares of all regions of the world in favor of EU countries. The leading place in the product structure of exports is occupied by goods of agricultural industry, and in imports – mineral products. The directions for the formation of state policy in the field of regulation of foreign trade operations in the short-term, medium-term and strategic dimensions, which are determined by the National Council for the Recovery of Ukraine from the Consequences of the War, are substantiated. Foreign trade policy, which is formed under the influence of risks and threats of war, is aimed at developing and increasing the volume of foreign trade with EU countries and the USA, Japan and Canada. The priority areas of foreign trade development are: defense-industrial complex; metallurgy and metalworking; agro-industrial complex; engineering; mining industry; furniture and woodworking industries. An important place is also defined for the development of innovative enterprises and knowledge-intensive production, which will ensure the transition to a developing economy.

Célestin Coquidé, José Lages, Dima L. Shepelyansky

During his state visit to China in April 2023, Brazilian President Lula proposed the creation of a trade currency supported by the BRICS countries. Using the United Nations Comtrade database, providing the frame of the world trade network associated to 194 UN countries during the decade 2010 - 2020, we study a mathematical model of influence battle of three currencies, namely, the US dollar, the euro, and such a hypothetical BRICS currency. In this model, a country trade preference for one of the three currencies is determined by a multiplicative factor based on trade flows between countries and their relative weights in the global international trade. The three currency seed groups are formed by 9 eurozone countries for the euro, 5 Anglo-Saxon countries for the US dollar and the 5 BRICS countries for the new proposed currency. The countries belonging to these 3 currency seed groups trade only with their own associated currency whereas the other countries choose their preferred trade currency as a function of the trade relations with their commercial partners. The trade currency preferences of countries are determined on the basis of a Monte Carlo modeling of Ising type interactions in magnetic spin systems commonly used to model opinion formation in social networks. We adapt here these models to the world trade network analysis. The results obtained from our mathematical modeling of the structure of the global trade network show that as early as 2012 about 58 percent of countries would have preferred to trade with the BRICS currency, 23 percent with the euro and 19 percent with the US dollar. Our results announce favorable prospects for a dominance of the BRICS currency in international trade, if only trade relations are taken into account, whereas political and other aspects are neglected.

Andrii Voshchepynets, Oleksiy Agapitov, Lynn Wilson et al.

We present the results of processing the effects of the powerful Gamma Ray Burst GRB221009A captured by the charged particle detectors (electrostatic analyzers and solid-state detectors) onboard spacecraft at different points in the heliosphere on October 9, 2022. To follow the GRB221009A propagation through the heliosphere we used the electron and proton flux measurements from solar missions Solar Orbiter and STEREO-A; Earth magnetosphere and the solar wind missions THEMIS and Wind; meteorological satellites POES15, POES19, MetOp3; and MAVEN - a NASA mission orbiting Mars. GRB221009A had a structure of four bursts: less intense Pulse 1 - the triggering impulse - was detected by gamma-ray observatories at 131659 UT (near the Earth); the most intense Pulses 2 and 3 were detected on board all the spacecraft from the list, and Pulse 4 detected in more than 500 s after Pulse 1. Due to their different scientific objectives, the spacecraft, which data was used in this study, were separated by more than 1 AU (Solar Orbiter and MAVEN). This enabled tracking GRB221009A as it was propagating across the heliosphere. STEREO-A was the first to register Pulse 2 and 3 of the GRB, almost 100 seconds before their detection by spacecraft in the vicinity of Earth. MAVEN detected GRB221009A Pulses 2, 3, and 4 at the orbit of Mars about 237 seconds after their detection near Earth. By processing the time delays observed we show that the source location of the GRB221009A was at RA 288.5 degrees, Dec 18.5 degrees (J2000) with an error cone of 2 degrees

T. Dogru, C. Işık, E. Sirakaya-Turk

Abstract The purpose of this study is to investigate the effects of exchange rate depreciations and appreciations on the tourism trade balance. Specifically, we employed linear and nonlinear autoregressive distributed lag (ARDL) cointegration techniques to analyze the extent to which currency depreciations and appreciations affect the United States (U.S.) bilateral tourism trade with Canada, Mexico, and the United Kingdom (U.K.). The results showed that the depreciation of the U.S. dollar subsequently improves the U.S. trade balance with all three trading partners. However, while the appreciation of the U.S. dollar deteriorates the U.S. bilateral tourism trade balance with Canada and the U.K., it does not ultimately affect the U.S. bilateral tourism trade with Mexico in the long term. These results provide evidence contradicting the J-curve theory, supporting the postulations of the ML condition. Theoretical and policy implications are discussed within the realms of J-curve theory, Marshall-Lerner (ML) condition, international trade, and tourism.

Muhammad Omer, Junaid Kamal, J. de Haan

Suna Şahin

Not many analyses have been conducted on net errors and omissions in publications on Economics which is relevant to the origins of net errors and omissions and their effects on the balance of payments. There is no clarified answer to indicate the degree to which errors and omissions are acceptable. Each country has its characteristics, and it is tough to generalize the reasons behind the balance of payment mismatches. This research intends to study the relationship between selected countries’ (India, Singapore, Malaysia, United States, Uruguay, Philippines) balance of payment accounts ‘net errors and Omissions’ account of macroeconomic variables (GDP, trade volume considered as import and export figures) in the years of 1980-2018. The data for this study were collected from the World Bank and IMF international financial statistics and the selected countries’ annual data. In the study, panel data analysis was preferred after stasis analysis of the data. According to the results obtained, while trade volüme harms net errors and omissions, the increases in GDP are being affected positively in that direction. The inconsistencies are often unknown, although in some cases, explanations that require a review of statistics emerge later. Timing gaps, insufficient coverage, or methodological issues can cause imbalances. By finding the reason for the existence of the net error and omissions account, that is, its source, the quality of the balance of payments statistics can be further improved. Data sources should be chosen well, and laws and penal policies should be clearly stated to avoid problems.

S. Bhat, Javed Ahmad Bhat

Applying an asymmetric model, the study reported no evidence of J-curve phenomenon in case of India. In the short-run currency appreciation deteriorates the trade balance and currency depreciation improves it. In the long-run, again the similar response is observed, however, only the impact of currency depreciation is statistically significant. Increase in domestic demand deteriorates the trade balance by a greater magnitude than improvement is observed due to the decline in domestic demand conditions. Finally, foreign demand hike improves the trade balance relatively by a higher magnitude; however, the impact of a foreign demand decline is statistically insignificant. JEL Codes: F4, F41, F42

J. Horák

Economic sanctions are among the most powerful instruments of international policy. However, this study, using the example of the so-called anti-Russian sanctions, shows that in the global economy, countries are rapidly using other alternatives, and sanctions in the case analyzed act as a catalyst for balance of trade between the Russian Federation and the People’s Republic of China. The study is based on a highly topical sophisticated model of neural networks, which provides clear results confirming the unintended positive effect. The time series and aggregated data became inputs into multilayer perceptron networks, while the methodology used enabled eliminating of both too large averaging and extreme fluctuations of the equalized time series. Out of 10,000 networks created for each variable and each time lag, five showing the best characteristics given by correlation coefficients and absolute residual sums were retained. Thus, the created equalized time series were able to describe the basic trend of the actual development of export and import, while also capturing their local extremes. The interpolation of the two time series shows that the sanctions imposed on the Russian Federation in 2014 have clearly strengthened its balance of trade with the People’s Republic of China. The results of the study also predict further growth in the balance of trade between the Russian Federation and the People’s Republic of China, although this development may be delayed by current events.