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Many experts suggest that the human being explore marine resources and marine new energy sources to alleviate the shortage of land resources and the ecological degradation. However, island coastal zones are considered to be fragile ecosystems; their geographical location and natural characteristics, their biodiversity and associated ecosystems, and their exposure to diverse land and sea conditions all make them highly vulnerable to environmental changes and human activities. Therefore, it is necessary to achieve the goals of environmental protection and sustainable development on the basis of a comprehensive evaluation and understanding of islands.

Due to the importance of island groups, this paper conducts evaluation studies on them. Using the Delphi, AHP and TOPSIS methods, this study evaluated quantitatively the comprehensive development level and comprehensive development potential of island groups in terms of resources, natural environment, economy and society. Innovatively using them as two subsystems, the present study combined the coupling coordination model and the obstacle factor calculation method.

The prospective index of comprehensive development was applied to the Changdao Island Group in Yantai, Shandong Province as an example, and the final evaluation revealed that the comprehensive development prospect of this island group had an upward trend from 2010 to 2017. Future efforts should be made to improve its economic and social conditions and economic development status, apart from promoting its comprehensive development by improving human resources management, increasing the GDP growth rate, and improving fresh water and electricity supply.

This study takes the integrated development level of the island and the integrated development potential of the island as two subsystems, and the innovative application of the coupling coordination degree model is used to calculate the integrated development index of the island to understand the development status of the island area. On the basis of this model, the obstacle factor identification method is designed to identify the main obstacle factors, and on the basis of evaluation and identification, specific measures to ensure the sustainable development of the island area are effectively proposed.

The island areas, in particular, are characterized by a more fragile ecological carrying capacity and higher value of resources and environment, which requires us to take Xi Jinping's green ecological development view as the theoretical basis and adhere to the high-quality development path of gradual development and ecological environment priority. Taking Shengsi and Daishan counties as examples, on the basis of their high-quality development evaluation and identification of the main influencing factors, this study explores the specific path of Xi Jinping's ecological development view in the high-quality development of typical island counties in China.

This paper applies the interpretative structural model to construct an evaluation index system for the high-quality development of the island. In determining the factor weights of the index layer, the AHP hierarchical analysis method was combined with the Delphi method to increase the objectivity of the assignment process as much as possible. This study used the technique for order of preference by similarity to ideal solution to calculate island high quality development index. To measure the main obstacle factors, the index factor contribution rate, the index factor deviation, and the index factor obstacle degree were applied in this research.

As China intensifies its maritime strategy, the sustainability of coastal and island regions is critical, particularly given their fragile ecosystems and high resource value. Our study reveals a declining trend in the high-quality development index for Shengsi, peaking at 0.4262 in 2010 and dropping to 0.3261 in 2012. To reverse this, it's essential to align with President Xi Jinping's green ecological development framework and commit to a high-quality development pathway.

The connotation and extension of Xi Jinping's view of ecological development should be continuously studied in depth and enriched, with green development as the core idea to guide the correct direction of the high-quality development of the island. In this paper, it is suggested that researchers are supposed to focus on these problems, such as the changes of sea water quality, the reduction of urban greening, the continuous negative growth of population in island areas, the decline of forestry added value and air quality protection, so as to ensure the sustainable high-quality development of example islands.

This paper aims to analyze the application of remotely piloted aircraft (RPA) for remote oil spill sensing.

This paper is an analysis of RPA strong points.

To increase the accuracy and eliminate potentially false contamination detection, which can be caused by external factors, an oil thickness measurement algorithm is used with the help of the multispectral imaging that provides high accuracy and is versatile for any areas of water and various meteorological and atmospheric conditions.

SWOT analysis of implementation of RPA for remote sensing of oil spills.

The use of RPA will improve the remote sensing of oil spills.

The concept of oil spills monitoring needs to be developed for quality data collection, oil pollution control and emergency response.

The research covers the development of a method and design of a device intended for taking samples and determining the presence of oil contamination in an aquatorium area; the procedure includes taking a sample from the water surface, preparing it for transportation and delivering the sample to a designated location by using the RPA. The objective is to carry out the analysis of remote oil spill sensing using RPA. The RPA provides a reliable sensing of oil pollution with significant advantages over other existing methods. The objective is to analyze the use of RPA employing all of their strong points. In this paper, technical aspects of sensors are analyzed, as well as their advantages and limitations.

This article is based on a systematic and comprehensive review of the literature on two-sided platforms, the business structure based on the concept of matchmaking groups of customers (e.g. Uber or Airbnb). The research aims to identify gaps in the existing literature while providing a structured summary of the existing knowledge in the field. Finally, we propose a conceptual framework enabling platform thinking, the ability to see hybrid multi-sided platforms as a useful resource-orchestration structure to unveil innovation opportunities.

This study adopts a bibliometric approach, combing co-citation and text mining analyses of 196 papers, also implementing a longitudinal analysis that highlights the evolution of the field since its inception till today.

The novel aspect of the paper consists in taking a purely managerial stance of a very peculiar kind of platform, merging existing knowledge in comprehensive frameworks while providing potential avenues for research.

From an academic perspective, this research highlights the double nature of two-sided platforms: as an operational choice or as a way to exploit (digital) assets and reach the economic sustainability. A research agenda is proposed, based on three pillars: a side-based standpoint, a business model perspective and an evolutionary stance to see how these businesses may evolve.

The research identifies different literature streams that may help practitioners in identifying how two-sided platforms may help them in fostering innovation.

The identification of two-sided platforms as a different way to create value (transaction platforms) or to capture value (non-transaction platform), enhancing the debate on this innovative business model. A research agenda to bring the field forward is proposed.

This study aims to propose an enhanced eco-driving strategy based on reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the connected environment.

In this paper, an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed for connected EVs. The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving. Moreover, this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.

To illustrate the performance for the EEDC-HRL, the controlled EV was trained and tested in various traffic flow states. The experimental results demonstrate that the proposed technique can effectively improve energy efficiency, without sacrificing travel efficiency, comfort, safety and lane-changing performance in different traffic flow states.

In light of the aforementioned discussion, the contributions of this paper are two-fold. An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs. A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.

The purpose of this paper is to explore the actual walking distance to public transport (PuT) stations and to report passenger perceptions on route choice.

A systematic case study has been conducted after administrating a tailor-made paper-based intercept survey in a German city (Munich). It can determine the interrelation between the accessibility of the transit service and evaluation on walking distance acceptance. Statistical analysis and geo-spatial approach were completed for obtaining major findings.

Statistical and geo-spatial analysis shows that respondents living in low-density areas walk longer than residents living in nearby inner city areas. In terms of PuT modes, residents walk longer for suburban train and subway/metro (U-Bahn) than for bus/tram services. Transit users accept a longer walking distance to reach a train station than other PuT modes and they choose the most direct and quickest route to reach PuT stations.

Findings of this study would help to formulate future strategies and standards for the sustainable planning of public transportation systems in the context of Munich and many other cities around the globe with similar conditions. However, future research should be conducted using a large-scale survey for evaluating the comprehensive picture of walking patterns to PuT stations. Accessibility to PuT stations can also be modeled and evaluated by adopting open data and voluntary social media information. Unfortunately, this study only presents a partial evaluation of walking focused on accessibility at selected PuT stations in different settings of the urban fabric.

This empirical study can be considered as an initial finding in the favor of the city transport authority to provide a design scale for improved accessibility of transit users; however, further investigation should be conducted using a large-scale survey for evaluating the comprehensive walking patterns.

A systematic case study has been conducted after administrating a tailor-made paper-based intercept survey in a German city (Munich). Findings of this study would help to formulate future strategies and standard for the sustainable planning of the public transportation system in the context of Munich and many other cities in the globe with similar conditions.

Urban digital transformation has become a key strategy in global countries. This study aims to provide a comprehensive and dynamic exploration of the intrinsic traits associated with urban digital transformation, in order to yield detailed insights that can contribute to the formulation of well-informed decisions and strategies in the field of urban development initiatives.

Through analysis of parallels between urban digital transformation and gyroscope motion in physics, the study developed the urban digital transformation gyroscope model (UDTGM), which comprises of seven core elements. With the balanced panel dataset from 268 cities at and above the prefecture level in China, we validate the dynamic mechanism of this model.

The findings of this study underscore that the collaboration among infrastructure development, knowledge-driven forces and economic operations markedly bolsters the urban digital transformation gyroscope’s efficacy.

This research introduces a groundbreaking framework for comprehending urban digital transformation, potentially facilitating its balanced and systemic practical implementation.

This study pioneers the UDTGM theoretically and verifies the dynamic mechanism of this model with real data.

This study aims to improve the passenger accessibility of passenger demands in the end-of-operation period.

A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway, the minimum headway and the latest end-of-operation time. The objective of the model is to maximize the number of reachable passengers in the end-of-operation period. A solution method based on a preset train service is proposed, which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.

The results of the case study of Wuhan Metro show that the solution method can obtain high-quality solutions in a shorter time; and the shorter the time interval of passenger flow data, the more obvious the advantage of solution speed; after optimization, the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.

Existing research results only consider the passengers who take the last train. Compared with previous research, considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination. Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network, but due to the decrease in passenger demand, postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.

A growing number of studies have investigated the effect of ethical leadership on behavioral outcome of employees. However, considering the important role of ethics in IS security, the security literature lacks a theoretical and empirical investigation of the relationship between ethical leadership and employees' security behavior, such as information security policy (ISP) violation. Drawing on social learning and social exchange theories, this paper empirically tests the impact of ethical leadership on employees' ISP violation intention through both information security climate (i.e. from a moral manager's perspective) and affective commitment (i.e. from a moral person's perspective).

The research was developed based on social learning theory and social exchange theory. To measure the variables in the model, the authors used and adapted measurement items from previous studies. The authors conducted a scenario-based survey with 339 valid responses to test and validate the research model.

Results indicated that information security climate fully mediates the relationship between ethical leadership and ISP violation intention. The authors also found that information security climate enhances the negative effect of affective commitment on ISP violation intention.

This research contributes to the literature of information security by introducing the role of ethical leadership and integrating two theories into our research model. This study also calls attention to how information security climate and affective commitment mediate the relationship between ethical leadership and employees' ISP violation intention. The theory-driven study provides important pragmatic guidance for enhancing the understanding of the importance of ethical leadership in information systems security research.

Since many global path planning algorithms cannot achieve the planned path with both safety and economy, this study aims to propose a path planning method for unmanned vehicles with a controllable distance from obstacles.

First, combining satellite image and the Voronoi field algorithm (VFA) generates rasterized environmental information and establishes navigation area boundary. Second, establishing a hazard function associated with navigation area boundary improves the evaluation function of the A^* algorithm and uses the improved A^* algorithm for global path planning. Finally, to reduce the number of redundant nodes in the planned path and smooth the path, node optimization and gradient descent method (GDM) are used. Then, a continuous smooth path that meets the actual navigation requirements of unmanned vehicle is obtained.

The simulation experiment proved that the proposed global path planning method can realize the control of the distance between the planned path and the obstacle by setting different navigation area boundaries. The node reduction rate is between 33.52% and 73.15%, and the smoothness meets the navigation requirements. This method is reasonable and effective in the global path planning process of unmanned vehicle and can provide reference to unmanned vehicles’ autonomous obstacle avoidance decision-making.

This study establishes navigation area boundary for the environment based on the VFA and uses the improved A* algorithm to generate a navigation path that takes into account both safety and economy. This study also proposes a method to solve the redundancy of grid environment path nodes and large-angle steering and to smooth the path to improve the applicability of the proposed global path planning method. The proposed global path planning method solves the requirements of path safety and smoothness.