Current Issue : January-March Volume : 2026 Issue Number : 1 Articles : 5 Articles
The increasing complexity of maritime traffic, driven by the expansion of international trade and growing shipping demand, has resulted in frequent ship collisions with significant consequences. This paper evaluates the credibility of the risk, calculated using the automatic identification system (AIS), in busy waterways and integrates AIS data with video surveillance data to comprehensively analyze the risk of ship collision. Specifically, this study utilizes the IALAWaterways Risk Assessment Program (IWRAP) tool to simulate maritime traffic flow and assess collision risk probabilities across various study areas and time periods. In addition, we analyze data from 2019 to 2022 to explore the impact of the COVID-19 pandemic on maritime traffic and find that the number of ship arrivals during the epidemic has decreased, resulting in a decrease in accident risk. We identify four traffic conflict areas in the real-world study area and point out that there are multi-directional ship interactions in these areas, but compliance with traffic rules can effectively reduce the risk of accidents. Additionally, simulations suggest that even a 13.5% increase in ocean-going vessel (OGV) traffic would raise collision risk by only 0.0247 incidents/year. To more accurately analyze the risk of waterways, we investigate the capture of dynamic information for ships in waterways by using the learning-driven detection model for real-time ship detection. These findings highlight the effectiveness of combining AIS and visual data for waterway risk assessment, offering critical insights for improving safety measures and informing policy development....
The research investigated how exchange rate fluctuations influence the bilateral trade balance between Kenya and the European Union (EU). It relied on secondary data sourced from institutions such as the World Bank, the Central Bank of Kenya, and surveys conducted by the Kenya National Bureau of Statistics. Descriptive analysis was applied to reliable import and export data from selected EU countries, and the findings were presented narratively. The study focused on the period between 2001 and 2016. The results revealed that several key factors, including trade openness, inflation, and foreign aid shape Kenya’s economic growth. Specifically, trade openness, net foreign assets, and oil prices emerged as significant determinants of growth. While greater trade openness was found to promote economic expansion, rising oil prices had the opposite effect, constraining Kenya’s economic performance....
Stock markets are notoriously complex and volatile, which makes accurate price prediction a necessity for investor decision-making, risk mitigation, and profitability. This study develops and evaluates an AI-driven trading bot using historical stock data to forecast short-term price movements. The core research question examines whether machine learning can reliably predict prices to generate profitable automated trades. The hypothesis posits that effectively trained ML models can identify patterns to enable superior trading strategies compared to traditional methods. Four models—Linear Regression, Random Forest, Decision Tree, and MLP Regressor—were trained and assessed using Mean Squared Error and a custom Mean Absolute Percentage Error metric. The Random Forest model’s predictions directed a simulated trading bot executing buy/sell decisions over 1200 time points, starting with a user-specified amount of capital and incorporating technical indicators and risk management rules. The simulation showcased a tangible potential for profit by consistently achieving considerable returns with reduced risk. These findings strongly support the use of ML for automated trading and offer investors a powerful tool to optimize portfolio performance....
This paper investigates the impact of trade openness on domestic investment in selected Sub-Saharan African countries. The study uses panel data of 19 African countries covering the study period 1980-2020. This research uses as a baseline model the pooled Ordinary Least Square (OLS) and fixed effects (FE) with robust standards errors and assuming an AR(1) disturbances. Further, we estimated the fixed effects with country specific effects assuming AR(1) disturbances and adjusted for autocorrelation, and finally, we used the random effects with instrumental variables and the Generalized Method of Moments (GMM) to deal with endogeneity issues in our data. The empirical findings give evidence of a positive impact of trade openness on domestic investment in Africa. Regarding our control variables, the research concludes on the one hand, that the weak development of the credit sector in Africa does not encourage domestic investment and on the other hand, it is argued that the size of population does not improve the domestic investment in Africa....
This paper focuses on the interactive relationship between China's agricultural products international trade and rural development, aiming to clarify the impact of agricultural trade on rural areas and explore feasible rural development paths under the background of globalization. By adopting research methods such as literature review, case analysis and data statistical analysis, the study first sorts out the relevant theories of agricultural products international trade, including the application of comparative advantage theory and factor endowment theory in China's agricultural trade. Then, it analyzes the current situation of China's agricultural products international trade from the aspects of trade scale, trade structure and main trading partners. On this basis, the paper deeply discusses the economic, social and environmental impacts of agricultural products international trade on rural development. For example, it promotes farmers' income growth and industrial structure adjustment economically, increases employment opportunities and improves farmers' quality socially, while promoting green agriculture development and bringing potential environmental challenges environmentally....
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