Transport Routes Research Articles

Ship detection and water level measurement system based on 3D point cloud

ABSTRACT With the continuous development of the water transportation and shipping industries, the number of ships in rivers has steadily multiplied, followed by the increasing complexity of the ship routes. These changes have highlighted the growing importance of ship detection and water level measurement systems. Such systems not only enhance the management efficiency of waterborne traffic, ensure navigation safety, and reduce congestion and collision accidents, but also effectively safeguard the integrity of riverside and bridge structures. Ship detection and river elevation measurement based on 3D point clouds can directly acquire depth information without being affected by lighting conditions. So it has a good research prospect. Therefore, this paper proposes a novel ship detection algorithm based on improved PointRCNN and a novel method for riverbank line extraction and water level measurement based on 3D point clouds, respectively. For ship detection, the improved PointRCNN algorithm can increase the performance of data processing and keypoint extraction techniques, and make the network to keep more foreground point clouds and learn more effective features. This improves the recognition capability of distant ships. Compared to the original PointRCNN algorithm, the improved PointRCNN algorithm has achieved a 3.84% increase in detection precision in practical scenarios. Regarding riverbank extraction and water level measurement, the proposed method based on 3D point clouds can directly extract riverbank lines with depth information, obtaining water level height without direct contact with the river surface. Within a distance range between 15 and 45 m from the LiDAR, the average absolute error using this measurement method is less than 5 cm, demonstrating the good detection accuracy of this method.

Development of HTC-DBSCAN: A Hierarchical Trajectory Clustering Algorithm with Automated Parameter Tuning

Existing route-clustering methods often fail to identify abnormal sections or similarities between routes, mainly when working with large or long datasets. While sub-route clustering can detect regional patterns, it struggles to accurately capture the overall route structure. The present study proposes a new ship route-clustering method that enhances computational efficiency and noise recognition while addressing these limitations. We refined Automatic Identification System data via four data-cleaning processes and applied a statistical distance measurement to assess ship trajectory similarity. Dimensionality reduction was then used to facilitate clustering. The clustering of ship route similarities is non-parametric and can be applied to datasets not separated based on density to find clusters of various densities. Density-Based Spatial Clustering of Applications (DBSCA) applies to many research fields; using the DBSCA with Noise (DBSCAN) algorithm, we propose an improved DBSCAN algorithm that automatically determines the parameters Epsilon and MinPts. In this study, as a core ship route-clustering process, we propose a sub-route clustering process by setting the distance and density of data points to clear standards for re-analysis and completion. The proposed approach demonstrates markedly enhanced clustering performance, offering a more sophisticated and efficient basis for ship route decision-making.

Evaluating Strategies for Cost Reduction in Supply Chain Management Relating to Exports and Imports

This study explores different approaches to supply chain management cost reduction, with an emphasis on imports and exports. As the economy becomes more globalized, controlling supply chain expenses is essential to preserving profitability and competitive advantage. According to the study, procurement, transportation, inventory control, and technology integration are important areas where cost reductions can be made. Highlighting the main cost drivers in international trade, the paper starts with a review of the body of research on supply chain cost management. After that, it looks at particular tactics like utilizing economies of scale, transport route optimization, and shipment consolidation. The potential of technology to simplify processes and cut expenses is examined, including the use of automation, supply chain management software, and block chain technology for transparency. For an organization to keep a competitive edge in a globalized economy, effective supply chain management is essential. Exports and imports are the main focus of the current research paper, which provides a thorough assessment of various cost-cutting strategies in supply chain management. Transportation optimization, inventory management, supplier collaboration, technology integration, process improvement, regulatory compliance, sustainability, risk management, and continuous improvement are all topics covered in this study in an effort to give a comprehensive overview of effective cost-reduction strategies.

The Impact of Recent Crises on Kazakhstan‘s Mining Industry

The mining and quarrying industry is one of the main pillars of Kazakhstan’s economy. According to the National Bank of Kazakhstan (2023), the industry accounts for about 15% of the country's GDP. Kazakhstan is source of 1.8% of the world’s oil reserves. From FDI-perspective the EU is the largest investment partner. As a member of the Eurasian Economic Union dominated by the Russian Federation, Russia is also the major trading partner. On the other hand, the country has close ties with China as many transportation routes of the extractive East towards the consuming West pass-through Kazakhstan. In times of the COVID-19 crisis, the Russian-Ukrainian conflict and the intense focus on the dependence on natural resources and diversification of the supply portfolio, Kazakhstan has recently attracted increased international attention. The mining industry also faces the risk of additional sanctions from the EU and the USA. This article focuses on the impact of the recent crises on the mining industry of Kazakhstan. The source for the research on the mining industry is the country’s foreign trade and foreign direct investment data. It also provides a forecast based on the country’s strategy for the development of the mining industry in the coming years.

Assessment of Safety Probability of Fastening Operations in Loading-unloading Work Process

One of the important strategic objectives in the target programs for economic and social development adopted by the Government of Georgia is to improve the coordination of all types of transport – sea, rail, road, air, and pipeline. The methods of organizing and managing the transport system at different levels greatly impact solving the problems faced by water transport. Therefore, research in the field of improving the organization and management of the transport hub (port), as an integral part of this system, plays an important role in increasing the traffic volume and service quality of all types of transport on the transport corridors of Georgia. Foreign and domestic experience shows that a large percentage of waiting times for cargo operations by ships and berths is mainly due to the lack of coordinated actions between the adjacent modes of transport and ports and the imperfection of the organization and management of loading and unloading processes in ports. In this regard, it is necessary to focus on identifying and eliminating "vegetables". First of all, this link of the transport system connects water and land transport routes. Transport communications have long been called the arteries of life. Without them, the economy's rise and the country's prosperity, even if it has huge natural resources, is impossible. Whoever controls the transportation system holds the levers of economic management, which means that he can decide the fate of the entire state. The development of transport communications of the global transport system puts new demands on the quality of functioning of the existing intermodal corridor through Georgia. In particular, the transport corridor created by the EU countries under the name ITC TRACECA creates new challenges for the existing transport system of Georgia to maintain the transit cargo flows between Europe and Asia in competition with the seaports of Georgia, Azerbaijan, and partly Ukraine and Russia. In this regard, all the main directions of improving the organization and management of the technological processes of seaports become relevant: (i) increasing the capacity of berths and transport complexes in the Black Sea ports of Georgia to the maximum limit by reducing costs; (ii) creating new methods for identifying capacity reserves, which will ensure the competitiveness of Georgian seaports in competition with these ports; (iii) speeding up the process of transit cargo transportation through seaports, as well as reducing the processing time of cargo going to export and import in Georgian ports. Keywords: Transport hub, organization of technological processes, ship unloading work.

Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste

The cold chain logistics industry faces significant challenges in terms of transportation costs and carbon emissions. It is imperative to plan multimodal transportation routes efficiently to address these issues, minimize food waste, and reduce carbon emissions. This paper focuses on four key optimization objectives for multimodal cold chain transport: minimizing total transportation time, costs, carbon emissions, and food waste. To tackle these objectives, we propose a high-dimensional multiobjective route optimization model for multimodal cold chain networks. Our approach involves the development of a multiobjective evolutionary algorithm, utilizing Monte Carlo simulation and a one-by-one selection strategy. We evaluate the proposed algorithm’s performance by analyzing various convergence and distribution indicators. The average values for the minimum total transportation time, transportation cost, carbon emission cost, and cargo loss rate derived from the proposed algorithm ultimately converge to 6721.7, 5184.4, 301.5, and 0.21, respectively, demonstrating the effectiveness of the algorithmic solution. Additionally, we benchmark our algorithm against the existing literature to showcase its efficiency in solving high-dimensional multi-objective route optimization problems. Furthermore, we investigate the impact of different parameters, such as carbon tax rates, temperature, and cargo activation energy, on carbon emissions, and food waste. Moreover, we conduct a real-world case study to apply our approach to solving a practical business problem related to multimodal cold chain transportation. The insights gained from this research offer valuable decision-making support for multimodal carriers in developing low-carbon and environmentally friendly transportation strategies to efficiently transport perishable goods.

Implementation of AI Transportation Routing in Reverse Logistics to Reduce CO2 Footprint

Purpose: This study explores the implementation of artificial intelligence (AI) in transportation routing within reverse logistics to reduce CO2 emissions. By optimizing routing processes, we aim to enhance the efficiency of logistics operations while minimizing environmental impact. Methodology: we analyze the implications of improved transportation strategies. Furthermore, we discuss the intersection of technological innovation and environmental economics in shaping sustainable practices. Findings: The findings underscore the importance of AI-driven decision-making frameworks (D81) and their role in advancing IT management in logistics. The study on AI-driven transportation routing in reverse logistics highlights significant implications for both businesses and the environment. By optimizing routes, AI reduces fuel consumption and CO₂ emissions, helping companies meet sustainability goals. This leads to cost savings, as AI improves route efficiency and fleet utilization, while also enhancing operational efficiency. AI’s ability to predict and adjust to real-time conditions ensures scalability and adaptability, making it easier to handle increasing returns volumes in e-commerce. Moreover, AI enables better inventory management and resource planning, reducing the need for urgent shipments. It also paves the way for innovations like autonomous vehicles, further transforming reverse logistics. Unique Contribution to Theory, Practice and Policy: The study shows how AI can help businesses comply with environmental regulations, providing a competitive edge. Ultimately, AI integration in reverse logistics contributes to both operational improvements and environmental sustainability, reinforcing corporate social responsibility.

The Potential Effects of Climate Change on Arctic Ocean Navigation and Its Implications for Taiwan's Socio-Economic Society: An International Law Perspective

This study explores the potential effects of climate change on Arctic navigation and its implications for Taiwan's socio-economic fabric, through an international legal lens that considers geographical, socio-economic, and global political factors. The research review followed the methodological framework established by the Joanna Briggs Institute (2015) and drew upon Arksey and O'Malley's (2005) approach for summarizing and disseminating research findings, while adhering to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The ongoing effects of climate change and global warming have accelerated glacial melting, easing access to Arctic waters and opening new shipping routes, such as the Northeast Passage and Northwest Passage, which have notably impacted Taiwan's socio-economic dynamics. Climate change significantly affects ocean-based economies, as it shapes oceanic processes, which in turn directly influence social and economic activities.

Enhancing monitoring to promote early detection and eradication of invasive species

Ecological niche models are often used to predict the distribution of invasive species before or after they have been detected in new regions. Such models should also be used to guide surveys to promote the early detection and eradication of invasive species. Here we propose a practical framework that seamlessly uses ecological niche models to develop sampling routes that promote detection of invasive species. Our framework uses habitat suitability predictions and occurrence data on incursion populations to generate potential survey sites, which are then prioritized for sampling based on their size and suitability. The generated survey route is then displayed on an open street map platform. Our framework was developed into the ‘enmRoute' R package and a user‐friendly website to facilitate its application, and we validated our framework with a case study. We show that integrating ecological niche models with human transport routes promotes identification of survey sites that are predicted to collect more individuals and have a greater potential for species detection than traditional sampling approaches. Our framework may help industries, invasion biologists, and regulators develop economical and efficient survey programs for invasive pest monitoring that make eradication programs more attainable.

Analysis of the Performance of the City Transport Route Network System (AKDP) in Gorontalo Province, Indonesia

This study evaluates the performance of the intercity public transportation route network system (AKDP) in Gorontalo Province, Indonesia, with a focus on aspects of service coverage, overlap, density, and route network deviations. Data were obtained through field surveys. The research method includes spatial analysis using Geographic Information Systems (GIS) to evaluate the coverage and distribution of routes, as well as statistical analysis to measure the density and ratio of routes based on operational data and field surveys. The research results show that the coverage of route services is not yet even, with some areas being underserved. Route overlaps were identified on several main corridors, resulting in operational inefficiencies. The density of the routes shows significant variation, with some routes experiencing overcrowding while others are underutilized. The route ratio also shows an imbalance between the number of vehicles and passenger needs. Deviations from the established route plan were also found, which could potentially reduce service reliability. Based on these findings, it is recommended to restructure the route network and improve operational management to enhance the efficiency and quality of transportation services in Gorontalo Province.

Investigation Methods of Combating Smuggling and Suspicious Trade Through Transport Routes: Ukrainian Case

Smuggling poses a threat both to individuals and to national security. The problem of smuggling is complicated by the constant transformation of criminal schemes, thereby urging the search for appropriate investigation methods of this offense. The aim of the research is to improve the methods of investigation of smuggling through the integration of legislative, international, human, and technical resources. The research employed a doctrinal approach, a statistical method, and a descriptive method. As a result of the research, the Ukrainian legislation on combating smuggling was analysed in the context of European integration. It is noted that the criminalization of smuggling of goods is a welcome innovation, but the legislative framework needs further improvement. The legal basis of Ukraine's international cooperation in the investigation and countering of smuggling has been disclosed. The priority forms of cooperation were determined and directions for further improvement were revealed using the experience of several international initiatives. The value of human capital in combination with the latest technologies in the process of investigating crimes related to smuggling is noted. The obtained conclusions can be useful for regulatory bodies in the context of developing anti-smuggling policies based on identified priority areas.

A study of short-term passenger flow forecasting for public transportation based on the time series method

Abstract. In order to solve the conflicts between the supply and demand of urban transport, improve the living standard of urban residents, raise the level of urbanization, and promote the sustainable socio-economic development of the whole city, it is necessary to increase the pace of urban transport construction, planning and management in China. And at the same time, its necessary to take various measures to regulate the structure of urban transport and guide urban transport to develop in the direction of taking public transport as the mainstay. The experience of the development of urban transportation in China and abroad also proves that prioritizing the development of public transportation is the fundamental way to solve the problem of urban transportation. Public transport passenger flow data is the basis for optimizing public transport operations and scheduling. Accurate passenger flow forecasts on public transport routes can effectively guide public transport operation decisions, formulate operation scheduling plans and effectively improve the operational efficiency of the public transport system. The following are some of the key factors that can be taken into consideration when making passenger flow forecasts. The main contribution of this article is to propose the use of data mining technology, use bus IC card data and bus GPS data to integrate and organize them, conduct correlation analysis on the data, and on this basis, obtain the main distribution characteristics of bus passenger flow, and provide short-term Passenger flow forecast provides relevant ideas.

Barging and Transshipment Market Research in the Coal Logistics Industry in Indonesia

This market research aims to analyze opportunities for coal barging and transshipment companies in Indonesia, analyze the market prices for transport barging & transhipment in 2023 and 2024, identify factors that affect the performance of coal logistics companies in Indonesian as well as prospects and strategies implemented by the coal Logistics industry. This type of research is qualitative research. The method of qualitative research is done using a survey method that describes, explains and interprets a phenomenon that occurs in an object and data is qualitatively characterized. The research was conducted qualitatively through interviews with companies operating in the field of coal logistics and coal users’ logistics. The results of the research conclude that the coal logistics industry in the future still has a fairly high prospect of business. As the largest island country with the longest coastline in the world, Indonesia has the potential and advantages to be optimized as a strategic maritime transport route. With coal reserves awakened, then coal production in Indonesia is also expected to increase with the national production target of 2024 to 922.14 million tons. This growth of production will improve the performance of the coal transportation sector, thus creating a positive business prospect for the coal logistics industry

Analysis of Building Distribution and Accessibility of Kanigoro Urban Roads

The Kanigoro Settlement Area's land is mostly utilized for residential and agricultural purposes. Modifications to the city's construction and development are necessary to turn Kanigoro into a sustainable urban region, particularly in the field of urban morphological pattern development. City or area morphology may be analyzed using three primary components: building density, land use patterns, and road network patterns. This research aims to investigate the urban morphology pattern in Kanigoro Urban Area, focusing on road accessibility and building dispersion. In order to accomplish this goal, land use and building distribution were identified using satellite image data from 2011, 2015, 2019 and 2023, along with questionnaire data on residential location selection. The findings demonstrate that elongated patterns dominate settlement patterns in Kanigoro, with group patterns and the main road network following closely behind. Kinship and historical factors also play a role in this pattern. During the study, there was a notable increase in settlement growth, particularly on main transportation routes. The population density analysis shows that there is a concentration of population in the city center and some rapidly developing residential areas as a result of this rapid settlement growth. According to the road accessibility analysis, most areas are served by arterial roads, but there are still some areas with limited accessibility, especially with regard to collector roads. Based on the research results, there is a need for sustainable integrated spatial planning, adequate infrastructure, improving the quality of the collector road network and developing integrated public transportation.

Dynamic Testing and Finite Element Model Adjustment of the Ancient Wooden Structure Under Traffic Excitation

In situ dynamic testing is conducted to study the dynamic characteristics of the wooden structure of the North House main hall. The velocity response signals on the measurement points are obtained and analyzed using the self-interaction spectral method and stochastic subspace method, yielding natural frequencies, mode shapes, and damping ratios. This study reveals that the natural frequencies and damping ratios are highly consistent between the two methods. Therefore, to eliminate errors, the average of the results from both modal identification methods is taken as the final measured modal parameters of the structure. The natural frequencies of the first and second order in the X direction were 2.097 Hz and 3.845 Hz and in the Y direction were 3.955 Hz and 5.701 Hz. The modal frequency in the Y direction of the structure exceeds that in the X direction. Concurrently, a three-dimensional finite element model was established using ANSYS 2021R1, considering the semi-rigid properties of mortise–tenon connections, and validated based on in situ dynamic testing. The sensitivity analysis indicates adjustments to parameters such as beam–column elastic modulus, tenon–mortise joint stiffness, and roof mass for finite element model refinement. Modal parameter calculations from the corrected finite element model closely approximate the measured modal results, with maximum errors of 9.41% for the first two frequencies, both within 10% of the measured resonant frequencies. The adjusted finite element model closely matches the experimental results, serving as a benchmark model for the wooden structure of North House main hall. The validation confirms the rationality of the benchmark finite element model, providing valuable insights into ancient timber structures along transportation routes.

Waste collection route optimisation for the second waste-to-energy plant in Budapest

The city of Budapest produces approximately 680–700 000 tonnes of municipal solid waste every year, of which <2/3 is being recycled or used for energetic purposes, the rest ends up in a landfill. To combat this environmental and logistical problem the installation of a second waste incineration plant has been proposed in the south of the city. The only cost associated with fuel consumption in the case of waste to energy powerplants (WtE plants) is the transport cost, as the city council provides economic support for waste disposal. Since the transportation has a huge influence on the cost of opertation, logistical optimisation of the transport routes promises a direct impact on cost savings. In this study the logistical optimisation of the Southern Budapest area was carried out using image processing and logic based algorithm programming. As a result the optimal transport of 230 000 tonnes of municipal solid waste (MSW) was solved resulting in a 4 835.2 km monthly travel distance reduction.This value can be translated to 7 823 €/month cost, 9 459.6 kg/month CO2 and 45.3 kg/month NOx emissions reduction in the urban areas.

Computational analysis of the Logistics Supply Chain from a global trade perspective

Global trade is based on coordinated factors, that means labor and products are moved from their point of origin to the point of use. Strategies have a significant impact on global trade because they enable the effective development of goods across international borders. The decision making is an important task for the development of Logistics Supply Chain (LSC) infrastructure and process. Decisions on supplier selection, production schedule, transportation routes, inventory levels, pricing strategies, and other issues need to be made. These decisions may have a big influence on customer service, profitability, operational efficiency, and overall competitiveness. The Artificial Intelligence (AI) approach of Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-Promethee-2) is used to assess the priority selection of the factors associated with the LSC and evaluate the importance in global trade. The role of AI is very useful compare to statistical analysis in terms of decision making. The computational analysis placed promotion of exports as the most important priority out of five selected attributes in LSC, with infrastructure development. The result suggests that LSC depends heavily on export promotion as the most significant attribute. Infrastructural development also appeared another factor influencing LSC. The foreign investment was ranked the lowest. The evaluated results are useful for the policy makers, supply chain managers and the logistics professionals associated with the supply chain management.

Supply security beyond mines and scrap recycling: valorization potential of metallurgical residues.

In the context of the European Critical Raw Materials Act, this work attempts to demonstrate the potential of residual material flows from non-ferrous metallurgy and their possible contribution to the supply security of metals by locally available new secondary resources, assuming technically and economically viable processing. Based on the aluminium, zinc, copper and lead industries, the resulting waste streams are discussed and, in particular, the complex process consisting of physical, chemical and metallurgical steps is described. Their diversity, be it slags, dusts or even sludges, has a wide variety of morphologies and compositions due to the process of generation. In the past, many concepts for reprocessing were investigated, but the goal was usually only the recovery of one target element or to avoid landfilling by using it, for example, as a building material, whereby the metals contained are completely lost. If the target is the extraction of valuables, the required interdisciplinary process development must be based on an in-depth characterization to understand the behaviour of metals and trace elements in possible extraction steps and also to develop suitable strategies for influencing the behaviour of target elements with the aim of extraction. This starts with an in-depth comprehension of the formation process, which is the subject of this article and has a direct influence on the composition and morphology of the materials, thus forming the basis for understanding the behaviour in potential recycling processes. Furthermore, typical compositions of the residual material streams, sources and, if available, quantities are shown and, in summary, an attempt is made to evaluate the materials in a SWOT analysis and to address the challenges in developing extraction steps for processing. While mine tailings are mostly found outside of Europe, the potential of the residual materials from metallurgy is local due to the processing of the concentrates in Europe. This leads to several potential advantages in a possible reprocessing, such as no or shorter transport routes, which is linked to lower quantity of emissions, defined volume and known composition, no geopolitical risk, conservation of primary resources, and increasing Europe's sustainability through a more comprehensive use of the raw materials.This article is part of the discussion meeting issue 'Sustainable metals: science and systems'.

Role of membrane H+ transport and plasmalemma excitability in pattern formation, long-distance transport and photosynthesis of Characean algae

Illuminated giant cells of Characeae comprise alternating areas with H+ pump activity and zones with high conductivity for H+/OH–, which create counter-directed H+ flows between the medium and the cytoplasm. In areas where H+ enters the cell, the pH on the surface (pHo) increases to pH 10, while the cytoplasmic pH (pHc) decreases. The lack of the permeant substrate of photosynthesis (CO2) and the acidic pHc shift in the region of external alkaline zones redirect electron transport in chloroplasts from CO2-dependent (assimilatory) pathway to O2 reduction. This electron transport route is associated with an increase in thylakoid membrane ΔpH and an enhanced nonphotochemical quenching (NPQ) of chlorophyll excitations, which underlies strict coordination between nonuniform distributions of pHo and photosynthetic activity in resting cells. When the action potential (AP) is generated, the longitudinal pH profile is temporarily smoothed out, while the heterogeneity of the distribution of NPQ and PSII photochemical activity (YII) sharply increases. The damping of the pHo profile is due to the suppression of the H+ pump and passive H+ conductance under the influence of an almost 100-fold increase in the cytoplasmic of Ca2+ level ([Ca2+]c) during AP. The increase in [Ca2+]c stimulates photoreduction of O2 in chloroplasts under external alkaline zones and, at the same time, arrests the cytoplasmic streaming, which causes the accumulation of excess amounts of H2O2 in the cytoplasm in areas of intense production of this metabolite, with a weak effect on areas of CO2 assimilation. These changes enhance the nonuniform distribution of cell photosynthesis and account for the long-term oscillations of chlorophyll fluorescence Fm' and the quantum efficiency of linear electron flow in microscopic cell areas after the AP generation.

Prioritizing Criteria for Establishing a Green Shipping Corridor Between the Ports of Sines and Luanda Using Fuzzy AHP

As port authorities and cargo operators seek strategies to reduce carbon emissions while ensuring operational efficiency, some are turning to the concept of green corridors. These solutions aim to establish formalized partnerships among ports, carriers, shippers, and countries. During the process, the stakeholders must consider four priority areas (alternative fuels, bunkering infrastructure, vessel decarbonization pathways, and cargo demand dynamics) from seven angles (environmental, economic, infrastructure, regulatory, operational, technological, and social). This study explores the prioritization of these criteria for establishing a green maritime corridor between two major ports in Portugal and Angola, which would be a significant step toward promoting sustainable global trade. Utilizing the fuzzy AHP, this research analyzes all these factors and their associated sub-criteria derived from a comprehensive literature review and consultations with stakeholders from the Ports of Sines and Luanda. The findings show the dominance of environmental compatibility and economic viability, while social acceptance shows the lowest score. This framework guides the decision-making process for developing a sustainable shipping corridor. The results offer valuable insights for policymakers which can guide them in fostering resilient maritime transport routes, accelerating the adoption of decarbonization strategies and playing a critical role in achieving the IMO’s zero-emission targets by 2050.