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The present study measured the relative efficiency of five major commercial ports in West Africa, using three different Data Envelopment Analysis (DEA) methods, the CCR, BCC, and Windows I-C methods over the years 2005-2016. Seven input variables and one output variable were used in the model analysis. The CCR and BCC methods were used to evaluate the technical and scale efficiency while the Windows I-C method provided a comprehensive ranking of the studied ports. The results showed that the scale efficiency score of 89.53% indicated that on average the production scale of the ports had deviated from the most productive scale size (MPSS) by 10.47%. These results revealed that the source of the overall inefficiency is due to scale rather than pure technical inefficiency. Hence, in order to improve the overall efficiency, the two scaled inefficient ports of Abidjan and Cotonou should adjust their scale of operations. Then, further investigations were conducted to detect correlations between various variables used in this study. The research found that the absence of any correlation for non-significant variables and negative correlation for the significant variables throughout time resulted from the fact that these variables were not fully utilized. Meaning that they were not efficiently used to boost the container throughput on a scale basis, the research also found that a pandemic or insecurity could easily impact seaports activities with the case of the Ebola outbreak which strucked the West African region from the year 2013 to 2016, or the terrorism threats which prevailed in the region around the year 2012. Thus, for ports to stand out in the present fiercely competitive environment, ports authorities ought to analyze their operational scale to identify whether or not the production size is fitting before further port capacity expansion.

The present study measured the relative efficiency of five major commercial ports in West Africa, using three different Data Envelopment Analysis (DEA) methods, the CCR, BCC, and Windows I-C methods over the years 2005-2016. Seven input variables and one output variable were used in the model analysis. The CCR and BCC methods were used to evaluate the technical and scale efficiency while the Windows I-C method provided a comprehensive ranking of the studied ports. The results showed that the scale efficiency score of 89.53% indicated that on average the production scale of the ports had deviated from the most productive scale size (MPSS) by 10.47%. These results revealed that the source of the overall inefficiency is due to scale rather than pure technical inefficiency. Hence, in order to improve the overall efficiency, the two scaled inefficient ports of Abidjan and Cotonou should adjust their scale of operations. Then, further investigations were conducted to detect correlations between various variables used in this study. The research found that the absence of any correlation for non-significant variables and negative correlation for the significant variables throughout time resulted from the fact that these variables were not fully utilized. Meaning that they were not efficiently used to boost the container throughput on a scale basis, the research also found that a pandemic or insecurity could easily impact seaports activities with the case of the Ebola outbreak which strucked the West African region from the year 2013 to 2016, or the terrorism threats which prevailed in the region around the year 2012. Thus, for ports to stand out in the present fiercely competitive environment, ports authorities ought to analyze their operational scale to identify whether or not the production size is fitting before further port capacity expansion.

Advanced airborne equipment liquid cooling system presents the development trend of multiple pumps in parallel, centralised heat dissipation and high efficiency circulation, but this type of system has the characteristics of many variable parameters and strong non-linearity, which makes the system operation and control become extraordinarily complex, posing a serious challenge to the system performance. Although some progress has been made in the current optimization of liquid cooling system performance, there are still gaps such as insufficient consideration of the multi-objective optimization problem and limited optimization effect. To fill this research gap, this study takes minimum specific energy consumption, minimum flow deviation and minimum impeller load as the optimization objectives, establishment of multi-objective optimization model for liquid-cooled power unit, the optimal solution set of the Pareto model is solved using the multi-objective grey wolf optimization algorithm (MOGWO), and the optimal solution set is substituted for the optimal solution, and the evaluation indexes are designed in combination with the actual working conditions to obtain the optimal schedule. By example analysis, the optimized system under variable operating conditions, the impeller load and specific energy consumption decreased by 16.88% and 3.64% respectively, while the rise in flow deviation was controlled within 0.76%. The newly established optimisation model effectively mitigates potential safety hazards during system operation. Finally, by combining all the indicators, three scheduling options are provided under variable operating conditions, focusing on reliability and economy, overall balance and high-precision flow, respectively, in order to adapt to the diversified requirements of different operating environments.

Advanced airborne equipment liquid cooling system presents the development trend of multiple pumps in parallel, centralised heat dissipation and high efficiency circulation, but this type of system has the characteristics of many variable parameters and strong non-linearity, which makes the system operation and control become extraordinarily complex, posing a serious challenge to the system performance. Although some progress has been made in the current optimization of liquid cooling system performance, there are still gaps such as insufficient consideration of the multi-objective optimization problem and limited optimization effect. To fill this research gap, this study takes minimum specific energy consumption, minimum flow deviation and minimum impeller load as the optimization objectives, establishment of multi-objective optimization model for liquid-cooled power unit, the optimal solution set of the Pareto model is solved using the multi-objective grey wolf optimization algorithm (MOGWO), and the optimal solution set is substituted for the optimal solution, and the evaluation indexes are designed in combination with the actual working conditions to obtain the optimal schedule. By example analysis, the optimized system under variable operating conditions, the impeller load and specific energy consumption decreased by 16.88% and 3.64% respectively, while the rise in flow deviation was controlled within 0.76%. The newly established optimisation model effectively mitigates potential safety hazards during system operation. Finally, by combining all the indicators, three scheduling options are provided under variable operating conditions, focusing on reliability and economy, overall balance and high-precision flow, respectively, in order to adapt to the diversified requirements of different operating environments.

The vehicle will generate an amount of current while the electric vehicle just starting to regeneratively brake. In order to avoid the impact of high current on the traction battery, a novel electrohydraulic hybrid electric vehicle has been proposed. The main power source is supplied by the electric drive system, and the hydraulic system performs the auxiliary drive system that fully exerts the advantages of the electric drive system and the hydraulic drive system. A proper regenerative braking control strategy is presented, and the control parameters are determined by the fuzzy optimization algorithm. The simulation analysis built the model through the united simulation of AMESim and MATLAB/Simulink. The results illustrated that the optimized control strategy can reduce battery consumption by 1.22% under NEDC-operating conditions.

The vehicle will generate an amount of current while the electric vehicle just starting to regeneratively brake. In order to avoid the impact of high current on the traction battery, a novel electrohydraulic hybrid electric vehicle has been proposed. The main power source is supplied by the electric drive system, and the hydraulic system performs the auxiliary drive system that fully exerts the advantages of the electric drive system and the hydraulic drive system. A proper regenerative braking control strategy is presented, and the control parameters are determined by the fuzzy optimization algorithm. The simulation analysis built the model through the united simulation of AMESim and MATLAB/Simulink. The results illustrated that the optimized control strategy can reduce battery consumption by 1.22% under NEDC-operating conditions.

The purpose of this study was to assess the extent to which agricultural farms meet the requirements for sustainable agritourism in Zimbabwe. This study was motivated by the realisation that despite that the country is agro-based and has great potential to become an agritourism destination, the country is still lagging in agritourism development. The conceptual framework for understanding agritourism and the Triple Bottom Line (TBL) approach was applied. In-depth interviews were conducted with thirty-four (34) farmers who were purposively selected from the Manicaland and Mashonaland provinces of Zimbabwe. Data collection was conducted from October 2020 to June 2021. Thematic content analysis aided by Nvivo 12 software was used to analyse the data. The results revealed that the sampled farms meet at least one of the requirements for sustainable agritourism. However, there is a lack of diversity in both core and peripheral agritourism activities on the farms. The farmers are recommended to increase agritourism activities through sustainable utilization of the existing farm resources. The study provides the relevant stakeholders with information on areas of improvement for agritourism growth in the country and a baseline for future investigations into the prospects of agritourism in Zimbabwe. The main limitation of this study was the use of a framework for understanding agritourism that was developed in a developed world context. Development of a framework for understanding agritourism in a developing world context is recommended for future research.

The purpose of this study was to assess the extent to which agricultural farms meet the requirements for sustainable agritourism in Zimbabwe. This study was motivated by the realisation that despite that the country is agro-based and has great potential to become an agritourism destination, the country is still lagging in agritourism development. The conceptual framework for understanding agritourism and the Triple Bottom Line (TBL) approach was applied. In-depth interviews were conducted with thirty-four (34) farmers who were purposively selected from the Manicaland and Mashonaland provinces of Zimbabwe. Data collection was conducted from October 2020 to June 2021. Thematic content analysis aided by Nvivo 12 software was used to analyse the data. The results revealed that the sampled farms meet at least one of the requirements for sustainable agritourism. However, there is a lack of diversity in both core and peripheral agritourism activities on the farms. The farmers are recommended to increase agritourism activities through sustainable utilization of the existing farm resources. The study provides the relevant stakeholders with information on areas of improvement for agritourism growth in the country and a baseline for future investigations into the prospects of agritourism in Zimbabwe. The main limitation of this study was the use of a framework for understanding agritourism that was developed in a developed world context. Development of a framework for understanding agritourism in a developing world context is recommended for future research.