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The Spanish passenger railway market saw the entrance of two competitors in 2022–2023: the full-service operator Iryo and the low-cost operator Ouigo. Using a unique dataset of Spanish ticket price collected throughout an entire year and the Diff-In-Diff method, this paper investigates the impact on incumbent's prices of newcomers' entrance on the less congested corridors Madrid - Alicante and Madrid - Malaga/Sevilla. The Spanish government's strategy seems to be successful: the decision to lead the liberalisation process and the choice of having up to three asymmetric competitors induced a significant decrease in price even on the less attractive corridors, stimulating the demand and addressing the problem of under-utilization of some high-speed infrastructure. The results show that prices decreased by 28%–30% after nine months of competition. The impact has been the same on both the analysed corridors, despite the competition environment has been different in terms of number of competitors, pricing strategy and market share of those. • Spain is the first country with three competitors in the high-speed railway market. • Competition in high-speed rail in Spain reduced prices by 28%–30% in nine months. • The impact on incumbent's first-class and second-class prices was the same. • Both low-cost and full-service competitors similarly affected incumbent pricing. [ABSTRACT FROM AUTHOR]

When a wheel passes over a rail surface irregularity, the resulting vehicle excitations lead to the application of additional system forces to both the track and the vehicle. These forces contribute to an accelerated track geometry deterioration, which in turn results in increased costs. In a recent paper, a clear correlation between the presence of rail irregularities and poor track geometry quality was demonstrated. Rail surface irregularities thereby were quantified by raw data of a chord-based optical measurement system mounted on the regular track recording vehicle in Austria. This paper deals with deconvolution of the recorded data in order to guarantee irregularity quantification without any distortion. Two different deconvolution approaches are developed and validated by additional measurements. Using the deconvoluted data, previously published evaluations were repeated, and the impact of using deconvoluted data instead of chord values was analysed. The correlation between short-wave effects and track geometry quality can not only be confirmed; it is even stronger than predicted by the chord data. The results of the analysis demonstrate that irregularities with amplitudes exceeding 0.08 mm contribute to an accelerated deterioration in track geometry. Amplitudes of a greater severity result in track geometry levels that are up to 120% inferior to the average. [ABSTRACT FROM AUTHOR]

The article proposes a methodological approach to quantifying direct economic damage from unfavorable and hazardous natural processes and phenomena for railways—an element of the critical infrastructure of the Russian Federation. The methodology is based on a normative approach to assessing the replacement cost of railway lines, which varies depending on the cost of construction in the orographic and climatic conditions of a particular region. The results are presented in the context of municipalities, which makes it possible to better take into account intraregional differences and facilitates their comparison with parameters characterizing natural hazards (floods, hazardous slope-related and geocryological processes, etc.). The calculations showed that the maximum cost of replacing railway lines in the event of natural threats for the country as a whole is about RUB 11 trln in 2021 prices, or approximately 8.4% of Russia's GDP for this year. The first ten regions in terms of the maximum amount of probable damage—Irkutsk, Amur, and Sverdlovsk oblasts; Khabarovsk, Zabaykalsky, Krasnoyarsk, Altai, Krasnodar, and Primorsky krais; and the Republic of Buryatia—account for over 40% of the total replacement cost. It is in these regions that measures to protect the fixed assets of railway transport are particularly important. The obtained data can be used in studies of natural and man-made risk: by comparing them with parameters characterizing the impact of hazardous natural processes and phenomena, it is possible to predict the risk and probable damage to railway infrastructure facilities in certain territories. Using the example of snow avalanches and permafrost degradation due to climate change in the Russian Arctic, the possibilities of this type of assessment are demonstrated. [ABSTRACT FROM AUTHOR]

Estimating line impedance is relevant in transmission and distribution networks, in particular for planning and control. The large number of deployed PMUs has fostered the use of passive indirect methods based on network model identification. Electrified railways are a particular example of a distribution network, with moving highly dynamic loads, that would benefit from line impedance information for energy efficiency and optimization purposes, but for which many of the methods used in industrial applications cannot be directly applied. The estimate is carried out onboard using a passive method in a single-point perspective, suitable for implementation with energy metering onboard equipment. A comparison of two methods is carried out based on the non-linear least mean squares (LMS) optimization of an over-determined system of equations and on the auto- and cross-spectra of the pantograph voltage and current. The methods are checked preliminarily with a simulated synthetic network, showing good accuracy, within 5%. They are then applied to measured data over a 20 min run over the Swiss  16.7  Hz railway network. Both methods are suitable to track network impedance in real time during the train journey; but with suitable checks on the significance of the pantograph current and on the values of the coefficient of determination, the LMS method seems more reliable with predictable behavior. [ABSTRACT FROM AUTHOR]

Historian Raul Hilberg once observed of death trains: "It's just very regular traffic. Death traffic". Though subtle, his insinuation that this death traffic represented a "new normal" is, in fact, an astute observation of a largely unresearched process whereby Polish railway workers, and locals living near railway tracks, became witnesses to the Holocaust through observing the distinctive new "traffic" flowing by their spaces of home and work. In this case study, therefore, I examine these "death traffic witnesses" to reveal how their experiences highlight a critical reality about genocide in our modern world – its ability to transform relatively banal spaces (in peacetime) into horrific ones when employed for sinister purposes. In this case, those banal spaces are the railways that cut through our modern landscapes as symbols of connection, commerce and transport; their steel rails cutting through backyards and city centres linking even remote villages with major metropolises. [ABSTRACT FROM AUTHOR]

We use a DEA analysis to compare the efficiency of the railways of Western and Eastern Europe and find while most railways of Western Europe are on the efficiency frontier, those of Eastern Europe are typically a long way from it. One explanation may be that the reform process only started much later in Eastern Europe than in the West, although it appears that Eastern Europe has largely caught up. Secondly, Eastern Europe suffered a significant loss of traffic after the end of the communist regime, and this may still be resulting in an excess of labour and assets. There is some evidence that this remains the case for labour and freight vehicles. Although the excess of freight vehicles may be largely vehicles out of service, they still contribute to the poor efficiency scores for Eastern Europe. It is also the case that the countries of Eastern Europe suffer some disadvantages in terms of population density. However, we believe that two aspects of policy play an important role in the poorer performance of Eastern European countries compared with Western. Firstly, is the poorer infrastructure quality associated with lower levels of investment. This shows up as less use of electric traction and slower train speeds, resulting in lower productivity of staff and assets. Despite the efforts of the European Commission to overcome this problem, there is still a long way to go. Secondly, is the strong use of public service obligations to maintain high levels of service with relatively low load factors. If it is desired to raise the efficiency of Eastern European railways, governments in Eastern Europe will need to consider whether they are specifying excessively high levels of service.

Infrastructure investments are being undertaken to improve efficiency, economic activity, and growth. Therefore, policy makers are increasingly looking for modelling tools that can evaluate the impact of transport infrastructure on the economy, firms and households from the lens of economic activity and equity. We have developed a large scale national CGE model for India that is calibrated to economic data as well as validated to data observed from the Indian Railways. The novelty of this work lies in three main areas (1) The CGE model incorporates multi-modal transport with road and rail (2) It is the largest model developed so far with 33 regions, 29 industries, 312,530 kms of highways and 126,366 km of Railways (3) Validation of the CGE model. The CGE model was able to predict the tonnage freighted on the Western Dedicated Freight Corridor to within 3.9 % accuracy. The Dedicated Freight Corridor Network (DFC) contributes a 2.94 % increase in the revenue for the railways as well as a 0.08 % increase in GDP. This implies that DFC can directly contribute INR 160 billion to the 2019 GDP. The CGE model distributed the benefits of faster and cheaper alternatives to the entire economy. This was observed during the evaluation of the road projects that were found to improve GDP, household welfare and rail revenue for rail, as well as improved equity.

Railways were an important driver of global economic growth in the nineteenth and early twentieth centuries. Whilst their role is well documented in industrial economies, we know less about their macro‐economic impact in developing countries. In this paper, we first estimate the aggregate growth impact of Indian railways, one of the largest networks in the world in the early twentieth century. Then, we compare their impact in India to four emerging Latin American economies (Argentina, Brazil, Mexico, and Uruguay) and the Cape colony. Using growth accounting techniques common to the cross‐country estimates, we argue that the aggregate growth impact of Indian railways was significant, increasing Indian gross domestic product (GDP) per capita by 13.5 per cent by 1912. We also find that the growth impact of Indian railways was similar to Brazil and Mexico, but smaller than Argentina and the Cape. Compared with the latter, India had a smaller size of railway freight revenues in the economy and lower wages to fares leading to lower passenger time savings. Railways were the most important infrastructure driver of economic growth in India during the first era of globalization from 1860 to 1912, but they contributed less than in richer and more dynamic developing economies. [ABSTRACT FROM AUTHOR]

The Sokoto Caliphate of northern Nigeria was the workshop of West Africa in the pre‐colonial nineteenth century, producing famous blue‐black cloth that reached many markets south of the Sahara as well as across it. Under British colonial rule this large handicraft textile industry was faced with the winds of foreign competition. We rely on a newly digitized set of colonial district reports to measure the impact of trade on northern Nigerian textile manufacturing and find that (contrary to British expectations) areas closer to railway stations were less likely to experience industrial decline. We argue that the resilience of local textiles relied on the low opportunity cost of dry‐season labour. Analysing a piece of tax microdata, we show that a low opportunity cost of labour outside of the rainy season was associated with a higher likelihood of engaging in textile by‐employment. Seasonal changes in relative factor prices were a trap as well as a refuge. Part‐time employment limited specialization and technological innovation, and can help to explain why northern Nigerian textiles eventually declined. Thus, beyond our particular case study, these results contribute to our understanding of the role of seasonality in determining the structure and pace of development of tropical economies. [ABSTRACT FROM AUTHOR]

Abstract A novel method is proposed for rail fastener detection based on millimetre‐wave (mmWave) radar, mmWave radar fastener counter (MMW‐FC), which can accurately detect and record the fasteners in real‐time as the train traverses its route. Under circumstances where GNSS signals remain unavailable for prolonged durations, precise train localisation can be accomplished by correlating the number of fasteners derived from this method with the corresponding track map. Initially, MMW‐FC utilises fast Fourier transform and adaptive beamforming to focus the energy reflected from fasteners. Subsequently, it applies an adaptive template‐matching algorithm to detect each fastener. Furthermore, by leveraging known fastener spacing and the average time for trains to pass adjacent fasteners, the Kalman filter can execute precise speed tracking, used as a speed reference when adjusting the matching template adaptively. The experimental results indicate that the proposed method can precisely count the fasteners the train encounters in diverse road and speed conditions. The fastener counter maintains the Counting Error less than 0.067%, the speed error stays below 1.8 km/h, and the maximum values of the mean absolute error and root mean square error for speed are 0.7337 and 0.9584 km/h, respectively.

Purpose – It aims to emphasize the importance of effective performance management practices in today's competitive business landscape, highlighting how they contribute to organizational success through enhanced employee motivation, engagement, and productivity. Aims(s) –The aim of this paper is to investigate various aspects of performance management, focusing on goal setting, feedback mechanisms, performance appraisals, recognition, and coaching. By examining the relationship between performance management and employee motivation, the paper aims to provide insights for organizations to design strategies that foster a motivated workforce and drive performance. Design/methodology/approach – it examines real-world examples and best practices to illustrate how organizations can implement these strategies to enhance employee motivation and ultimately achieve organizational success. Findings – The findings underscore the significance of goal setting within performance management, highlighting that specific and challenging goals increase employee motivation and performance levels. Moreover, performance management systems that emphasize goal alignment and regular feedback are found to further enhance motivation. Limitations of the study – Despite the comprehensive review of literature and empirical evidence, this paper acknowledges several limitations. Firstly, the findings are primarily based on existing research and may not encompass all possible perspectives or developments in the field of performance management and employee motivation. Originality/value – This paper contributes to the existing body of knowledge by synthesizing various theories and empirical evidence on performance management and employee motivation. It provides a comprehensive overview of key components of effective performance management practices and their impact on employee motivation and organizational success.

Abstract This paper provides an overview of the applications of Convolutional Neural Networks (CNN) in the railway maintenance industry. Our research covers specifically the subdomain of railway track maintenance. In this study, we have analyzed the state-of-the-art of CNNs applied to railway track maintenance by conducting an extensive literature review, summarizing different tasks and problems related to the topic and presenting solutions based on CNNs with a special emphasis on the data used to create these models. The results of our research show different applications of CNNs within the scope, including the detection of defects in the surface of railway rails and railway track components, such as fasteners, joints, sleepers, switches and crossings, as well as the recognition of track components, and the continuous monitoring of railway tracks. The architecture of CNNs is fitting to learning spatial hierarchies of features directly from the input data, making them of great use for Computer Vision and other applications related to the topic at hand. The implementation of IoT devices and smart sensors aid the collection of real-time data which can be used to feed powerful CNN models to recognize patterns and identify complex events related to the maintenance of railway tracks. This and more insights are discussed in detail within the contents of this paper.

Abstract This paper presents the development and validation of two artificial neural networks (ANN) models, utilising time and power‐based architectures, to accurately predict key parameters of a hydrogen hybrid train profile and its optimal trajectory. The research employs a hybrid train simulator (HTS) to authenticate the ANN models, which were trained using simulated trajectories from five unique hybrid trains on a designated route. The models’ performance was evaluated by computing the mean square normalisation error and mean absolute performance error, while the output's reliability was confirmed through the HTS. The results indicate that both ANN models proficiently predict a hybrid train's critical parameters and trajectory, with mean errors ranging from 0.19% to 0.21%. However, the cascade‐forward neural network (CFNN) topology in the time‐based architecture surpasses the feed‐forward neural network (FFNN) topology concerning mean squared error (MSE) and maximum error in the power‐based architecture. Specifically, the CFNN topology within the time‐based structure exhibits a slightly lower MSE and maximum error than its power‐based counterpart. Additionally, the study reveals the average percentage difference between the benchmark and FFNN/CNFN trajectories, highlighting that the time‐based architecture exhibits lower differences (0.18% and 0.85%) compared to the power‐based architecture (0.46% and 0.92%).

Abstract With the increasing concerns about railway energy efficiency, two typical driving strategies have been used in actual train operation. One includes a sequence of full power traction, cruising, coasting, and full braking (CC). The other uses coasting–remotoring (CR) to replace cruising in CC. However, energy‐saving performance by CC and CR, which can be affected by route parameters of gradients and speed limits, has not been fully compared and studied. This paper analyses the energy distribution of CC and CR considering various route parameters and proposes an improved strategy for different gradients and speed limits. The detailed energy flow of CC and CR is analysed by Cauchy–Bunyakovsky–Schwarz inequality and the generalised Hölder's inequality, and then, a novel driving strategy CC_CR is designed. To verify the theoretical results and the effectiveness of the proposed strategy, three simulators with CC, CR, and CC_CR driving modes have been developed and implemented into case studies of four scenarios as well as a real‐world metro line. Simulation results demonstrate that CR can only outperform CC on routes with steep downhill and CC_CR is always the best strategy. The energy savings of CC_CR can be as much as 15% more than CR and 42% greater than CC.

The demonstration of compliance of rolling stock against disturbance limits for railway signaling, and in particular track circuits, is subject to a large deal of variability, caused by the diverse values of the electrical parameters of the railway line and resulting transfer functions, as well as the operating conditions of the rolling stock during tests. Instrumental uncertainty is evaluated with a type B approach and shown to be much less than the experimental variability. Repeated test runs in acceleration, coasting, cruising, and braking conditions are considered, deriving both max-hold (spread) and sample (or experimental) standard deviation curves compared to the respective mean values (type A approach to the evaluation of uncertainty, as defined in of the Guide to the Uncertainty in Measurement. The major source of variability affecting a significant portion of the spectrum is caused by the superposed oscillations of the onboard LC filter, for which different choices of the transformation window duration are discussed. The test runs and the acquired data covered, overall, 1 day of tests along about 300 km of the Italian 3 kV DC railway network. [ABSTRACT FROM AUTHOR]

A novel method is proposed for rail fastener detection based on millimetre‐wave (mmWave) radar, mmWave radar fastener counter (MMW‐FC), which can accurately detect and record the fasteners in real‐time as the train traverses its route. Under circumstances where GNSS signals remain unavailable for prolonged durations, precise train localisation can be accomplished by correlating the number of fasteners derived from this method with the corresponding track map. Initially, MMW‐FC utilises fast Fourier transform and adaptive beamforming to focus the energy reflected from fasteners. Subsequently, it applies an adaptive template‐matching algorithm to detect each fastener. Furthermore, by leveraging known fastener spacing and the average time for trains to pass adjacent fasteners, the Kalman filter can execute precise speed tracking, used as a speed reference when adjusting the matching template adaptively. The experimental results indicate that the proposed method can precisely count the fasteners the train encounters in diverse road and speed conditions. The fastener counter maintains the Counting Error less than 0.067%, the speed error stays below 1.8 km/h, and the maximum values of the mean absolute error and root mean square error for speed are 0.7337 and 0.9584 km/h, respectively. [ABSTRACT FROM AUTHOR]

Prior studies indicate that expanding the length of roadways and railways has a beneficial effect on economic performance. Nevertheless, the requirement for land transport infrastructure, which offers different degrees of accessibility and mobility, to facilitate economic expansion differs based on a country's stage of development. The present study has two objectives. Firstly, it is essential to ascertain the required investment for different types of land transport infrastructure to facilitate different stages of economic performance. Secondly, the objective is to examine the impact of different forms of land transportation infrastructure on economic performance by means of urbanization and exports. To highlight these concerns, a fixed-effects panel linear regression analysis was conducted on a panel consisting of 50 countries spanning the years 1980–2018. In countries with lower levels of urbanization and exports, improvements to road infrastructure, especially roads with high accessibility, are of greater importance for economic performance compared to the improvement of railways. Nevertheless, as urbanization and exports rise, the comparative impact of improvements in road infrastructure on economic performance in relation to improvements in railway infrastructure diminishes. Railway improvements have a more significant effect on economic performance compared to road improvements, owing to increased urbanization and export rates. During these stages of development, high-mobility roads are more crucial for economic performance compared to high-accessibility roads. The conclusion of the research examined a variety of policy recommendations derived from our findings, which are applicable to different levels of urbanization and exports. • Evaluate the economic benefits of various land transportation infrastructure. • Assess the capital needed for various transport infrastructure to help the economy. • Low urbanization and export require high-access roads to boost economy. • High urbanization and export require railways to boost economy. [ABSTRACT FROM AUTHOR]

In this article, we analyse India's transport sector policy. The study examines the two important modes of transport, viz., road and rail, and analyses the efficiency of transport infrastructure from 2011 to 2019. Through Data Envelopment Analysis (DEA), we evaluate modes in terms of the capacity of registered road goods vehicles and railway goods wagons, truck km/train km and energy consumption and corresponding freight traffic. The analysis gives valuable insight into the fact that rail infrastructure is more efficient than road infrastructure. Still, current transport sector policies promote energy-intensive carbon-fuel road vehicles rather than energy-efficient alternative transport modes. The study suggests the changes that may be incorporated in inputs to improve the efficiency of the road infrastructure. The Data Envelopment Analysis (DEA)-Malmquist Index analysis reports the need for total factor productivity improvement in rail transport and the introduction of technological innovations in road and rail transport sector management. The study employs a well-to-wheel (WTW) based index to ascertain the energy consumed and pollutants emitted by freight-carrying road and rail modes between two leading business hubs of India, i.e., Ludhiana and Mumbai. The paper identifies policy gaps and suggests a holistic approach for need-based roadway investment and a time-bound development of railway infrastructure in India. Our study generates valuable implications for India's policy planners and government authorities and provides new insights to other countries. • The study examines road and rail transport, and analyses the efficiency and energy consumption of these modes. • The study suggests the changes to improve the efficiency of the road infrastructure. • The Data Envelopment Analysis (DEA)-Malmquist Index analysis and well-to-wheel (WTW) based index have been employed for the analysis. • The paper suggests a need-based roadway investment approach and a time-bound development of railway infrastructure. [ABSTRACT FROM AUTHOR]

The article presents the contents of a recently discovered list detailing steam and diesel locomotives used in Poland from 1956 to 1970 on narrow-gauge railways of the State Forests. The document includes information such as the markings of individual locomotives, their manufacturers, production years, technical specifi cations, and operational history on specifi c forest railways. This information is presented in tabular format and supplemented with commentary on locomotive marking practices specifi c to forest railways, as well as a comprehensive literature review. [ABSTRACT FROM AUTHOR]

This paper explores the multifaceted cultural history of ghost trains in Victorian fiction by situating three little-known ghost stories in the publishing and social history of the second half of the nineteenth century. The figure of the ghost train offers a route into the entangled history of publishing and railways by contextualising the anxieties presented in railway ghost stories with the real-world experiences of passengers. Taking ideas of mobility as a focal point, this paper brings together discussions of virtual travel and the supernatural to demonstrate some of the impact railways had on reading and writing about train travel. More so than tales of other haunted transport technologies, it is the ghost train's unnatural capacity for movement that disturbs both passengers and readers. By both enhancing and warping reality, railways are ripe source material for Victorian ghost stories to entertain and demand questions of spatio-temporal experience from their reading passengers. [ABSTRACT FROM AUTHOR]

The article reappraises nature of technology transfer in a colonial context by underlining how the colonised mediated and shaped what was ostensibly an imposition by the imperial administration. This wider point is illustrated by demonstrating the ways in which in the late nineteenth and early twentieth centuries, different groups of Indians used newly introduced railways to reconceptualise meanings of travel by adding new categories of travel while significantly modifying the extant ones. Crucially deviating from both ‘technology as imperialism’ and ‘technology as subversion’ historiographical paradigms, this article argues for a more nuanced appraisal of technology transfer, especially emphasising the role of users in shaping the impact of technology. Examining a diverse range of sources, viz., railway records (Annual Railway Reports and railway passenger statistics), newspaper reports and travelogues and pamphlets written by Indian railway travellers, the article claims Indians not only mediated the impact of trains on travel in late colonial India; but they shaped the outcome of this technology transfer in ways that reveals agency and remarkable involvement with a new mode of transit. In short, the article demonstrates dynamic interaction between imperial policies and responses of the colonised through the lens of technology transfer. [ABSTRACT FROM AUTHOR]

The Belt and Road Initiative (BRI) is important to China's development vision. Under the BRI, Chinese policymakers have focused on exporting railway systems to developing countries, yet progress on some projects remains limited. This article focuses on delays associated with a planned railway project in Pakistan: the ML-1. It answers the following question: What explains delays in the ML-1 railway project despite strong Chinese interest in it? The article uses a two-step conceptual framework to answer this question. In the first step, it highlights the role of railway bureaucrats involved in project-level negotiations. It shows that local bureaucrats contribute to delays by actively negotiating technical parameters. Chinese firms have limited policy levers to ensure their acquiescence. In the second step, the article places delays in the context of Pakistan's political economy by analysing the role of the political and military elite. It also explores the impact of political change and economic factors on the project. Projects not in sync with the local political elites' development vision face delays. Domestic political changes also contribute to delays. Furthermore, a failure to gain major veto actors' support, coupled with economic problems and differences over financing terms, constrains China's ability to pursue large-scale projects. [ABSTRACT FROM AUTHOR]

With the increasing concerns about railway energy efficiency, two typical driving strategies have been used in actual train operation. One includes a sequence of full power traction, cruising, coasting, and full braking (CC). The other uses coasting–remotoring (CR) to replace cruising in CC. However, energy‐saving performance by CC and CR, which can be affected by route parameters of gradients and speed limits, has not been fully compared and studied. This paper analyses the energy distribution of CC and CR considering various route parameters and proposes an improved strategy for different gradients and speed limits. The detailed energy flow of CC and CR is analysed by Cauchy–Bunyakovsky–Schwarz inequality and the generalised Hölder's inequality, and then, a novel driving strategy CC_CR is designed. To verify the theoretical results and the effectiveness of the proposed strategy, three simulators with CC, CR, and CC_CR driving modes have been developed and implemented into case studies of four scenarios as well as a real‐world metro line. Simulation results demonstrate that CR can only outperform CC on routes with steep downhill and CC_CR is always the best strategy. The energy savings of CC_CR can be as much as 15% more than CR and 42% greater than CC. [ABSTRACT FROM AUTHOR]

This paper presents the development and validation of two artificial neural networks (ANN) models, utilising time and power‐based architectures, to accurately predict key parameters of a hydrogen hybrid train profile and its optimal trajectory. The research employs a hybrid train simulator (HTS) to authenticate the ANN models, which were trained using simulated trajectories from five unique hybrid trains on a designated route. The models' performance was evaluated by computing the mean square normalisation error and mean absolute performance error, while the output's reliability was confirmed through the HTS. The results indicate that both ANN models proficiently predict a hybrid train's critical parameters and trajectory, with mean errors ranging from 0.19% to 0.21%. However, the cascade‐forward neural network (CFNN) topology in the time‐based architecture surpasses the feed‐forward neural network (FFNN) topology concerning mean squared error (MSE) and maximum error in the power‐based architecture. Specifically, the CFNN topology within the time‐based structure exhibits a slightly lower MSE and maximum error than its power‐based counterpart. Additionally, the study reveals the average percentage difference between the benchmark and FFNN/CNFN trajectories, highlighting that the time‐based architecture exhibits lower differences (0.18% and 0.85%) compared to the power‐based architecture (0.46% and 0.92%). [ABSTRACT FROM AUTHOR]

This paper provides an overview of the applications of Convolutional Neural Networks (CNN) in the railway maintenance industry. Our research covers specifically the subdomain of railway track maintenance. In this study, we have analyzed the state-of-the-art of CNNs applied to railway track maintenance by conducting an extensive literature review, summarizing different tasks and problems related to the topic and presenting solutions based on CNNs with a special emphasis on the data used to create these models. The results of our research show different applications of CNNs within the scope, including the detection of defects in the surface of railway rails and railway track components, such as fasteners, joints, sleepers, switches and crossings, as well as the recognition of track components, and the continuous monitoring of railway tracks. The architecture of CNNs is fitting to learning spatial hierarchies of features directly from the input data, making them of great use for Computer Vision and other applications related to the topic at hand. The implementation of IoT devices and smart sensors aid the collection of real-time data which can be used to feed powerful CNN models to recognize patterns and identify complex events related to the maintenance of railway tracks. This and more insights are discussed in detail within the contents of this paper. [ABSTRACT FROM AUTHOR]

Abstract Huge regenerative braking (RB) energy is generated in the AC traction power supply system (TPSS) which is related to safe operation and comprehensive energy utilisation. For the RB energy utilisation, the authors propose a railway regenerative braking power conditioner (RBPC) with no energy storage system (ESS) integrated which is located at the end of the power sections between adjacent traction substations (TSSs). First, the RB characteristics are studied based on a large amount of measured data, and the load power states are classified according to the load powers of adjacent power sections. Then, the RB energy utilisation scheme, transferring the RB power to the adjacent power section where traction power exists, has been studied. Moreover, a dual closed‐loop control strategy for a back‐to‐back converter is adopted to achieve RB energy utilisation. Finally, a case study and an engineering application are carried out. The results have verified the feasibility of this method, which can illustrate that more than half of the RB energy can be mutually utilised in adjacent power sections.

Abstract In urban railway systems, the timetable guides the section operation of the single train and the arrangement of the train group to meet the dual needs of cost and passengers. This paper proposes a two‐objective train operation optimization based on eco‐driving and timetabling to restore a more realistic scene, including a method level and an objective level. For the method level, the speed curve optimization of the single train and the timetable optimization of the train group are adopted jointly. For the objective level, both the total energy consumption of the train group and the consuming time of passengers are considered. A hybrid solution strategy based on quadratic programming and improved artificial bee colony algorithm is proposed. A hardware‐in‐the‐loop platform is built to carry out validation experiments. Both the cases in general hours and special hours are verified based on the actual data from Beijing Metro Line 15. The results show that both the energy consumption and the passenger consuming time are reduced simultaneously. Correspondingly, the speed curve and the time distribution of the timetable are individually optimized based on the fluctuating passenger flow.

Ballast behaviour has a profound impact on global track performance and durability, particularly for turnouts where dynamic forces are substantial. As ballast is a discontinuous material, this paper proposes the application of a Discrete Element Method (DEM) to model its behaviour under a conventional track turnout, a new approach that has not yet been tried for turnouts, only for main tracks. The model was validated with real vertical stiffness data measured in an actual turnout and used to analyse ballast behaviour under dynamic traffic loads. The results show remarkable differences in ballast behaviour for train speeds close to 180 km/h, as particle interactions and stress levels extend to the entire ballast layer. At lower speeds, the stress under the sleeper forms a trapezoidal shape for a given cross-section, while the rest of the layer remains barely affected. Overall, the DEM model is a reliable tool for simulating ballast behaviour and provides new insights into ballast-turnout interactions, which may help improve maintenance in these essential track elements.

The measurement of the longitudinal rail profile is relevant to the condition monitoring of the rail infrastructure. The running surface is recognizable as a shiny metallic area on top of the rail head. The detection of the running surface is crucial for vehicle-based rail profile measurements, as well as for defect detection. This paper presents a methodology for the automatic detection of the running surface based on a laser profilometer. The detection of the running surface is performed based on the light reflected from the rail surface. Three rail surfaces with different surface conditions are considered. Supervised machine learning is applied to classify individual surface elements as part of the running surface. Detection by a linear support vector machine is performed with accuracy of > 90 % . The lateral position of the running surface and its width are calculated. The average deviation from the labeled widths varies between − 1.2 m m and 5.6 m m. The proposed measurement approach could be installed on a train for the future onboard monitoring of the rail network. [ABSTRACT FROM AUTHOR]

Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations of existing algorithms. To address this challenge, we present Rail3D, the first comprehensive dataset for semantic segmentation in railway environments with a comparative analysis. Rail3D encompasses three distinct railway contexts from Hungary, France, and Belgium, capturing a wide range of railway assets and conditions. With over 288 million annotated points, Rail3D surpasses existing datasets in size and diversity, enabling the training of generalizable machine learning models. We conducted a generic classification with nine universal classes (Ground, Vegetation, Rail, Poles, Wires, Signals, Fence, Installation, and Building) and evaluated the performance of three state-of-the-art models: KPConv (Kernel Point Convolution), LightGBM, and Random Forest. The best performing model, a fine-tuned KPConv, achieved a mean Intersection over Union (mIoU) of 86%. While the LightGBM-based method achieved a mIoU of 71%, outperforming Random Forest. This study will benefit infrastructure experts and railway researchers by providing a comprehensive dataset and benchmarks for 3D semantic segmentation. The data and code are publicly available for France and Hungary, with continuous updates based on user feedback. [ABSTRACT FROM AUTHOR]

In the near future, there will be a greater emphasis on sharing network resources between roads and railways to improve transportation efficiency and reduce infrastructure costs. This could enable the development of global Cooperative Intelligent Transport Systems (C-ITSs). In this paper, a software-defined networking (SDN)-based common emergency service is developed and validated for a railway and road telecommunication shared infrastructure. Along with this, the developed application is capable of reducing the chances of distributed denial-of-service (DDoS) situations. A level-crossing scenario is considered to demonstrate the developed solution where railway tracks are perpendicular to the roads. Two cases are considered to validate and analyze the developed SDN application for common emergency scenarios. In case 1, no cross-communication is available between the road and railway domains. In this case, emergency message distribution is carried out by the assigned emergency servers with the help of the SDN controller. In case 2, nodes (cars and trains) are defined with two wireless interfaces, and one interface is reserved for emergency data communication. To add the DDoS resiliency to the developed system the messaging behavior of each node is observed and if an abnormality is detected, packets are dropped to avoid malicious activity. [ABSTRACT FROM AUTHOR]

Copyright of Brazilian Journal of Production Engineering / Revista Brasileira de Engenharia de Produção is the property of Brazilian Journal of Production Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper investigates the impact of globalization on transportation corridors in Azerbaijan, which are strategically located to serve as hubs for crossroads between north-south and east-west trade. The main hypothesis is that globalization has had a significant impact on transportation corridors in Azerbaijan, resulting in greater connectivity and trade flows within the region. The recent triumph over Armenia has resulted in significant changes in the region, enhancing Azerbaijan's reputation. Alongside the ongoing conflict in Ukraine and the imposition of sanctions on Russia and Iran, Azerbaijan has emerged as a secure passage between these influential powers. Furthermore, the rising demands for major international trade routes have created a pressing need for Azerbaijan to enhance its capabilities to effectively meet these growing requirements. According to the World Systems Theory, semi-periphery countries play the role of bridges between core and periphery states. Globalization has led to Azerbaijan's integration into the global economic system as a semi-peripheral country. This has resulted in increased trade and investment, which in turn has led to the development of transportation infrastructure and the expansion of transportation networks. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economic Research & Business Administration is the property of Al-Farabi Kazakh National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The cloudification and virtualisation of railway functions have the potential to improve railway operation efficiency, reliability, safety, and security, as well as to enhance passenger experience by offering innovative services. This paper considers issues related to the management and orchestration of railway clouds that host cloudified railway functions. A microservices-based approach to the design of railway cloud management and orchestration functionality is proposed. The basic railway cloud concepts were defined, and functionality related to the basic orchestration of the railway cloud and deployments is analysed in order to derive the requirements of platform resources and workload management. This functionality is further designed in the form of microservices, meaning that they could possibly be used in orchestration applications to enable improvements in scalability, fault isolation, and data security. The design of microservices follows the principles of the Representational State of Transfer (REST) application programming interface (API) as a set of interlinked resources. Resources related to railway cloud orchestration are identified with their associated data, relationships to other resources, and applicable methods. The resources' methods are used in railway applications to implement the required orchestration functionality and to maintain the state of railway cloud orchestration processes. To verify the synthesised microservices, the common orchestration application logic and microservices' logic were modelled, and it was proved that the orchestration processes, which run concurrently, expose equivalent behaviour. The proposed approach was validated using a simulation, aiming to evaluate injected latency as a key performance indicator for the reliability and safety of railway operations. Additionally, some safety and security issues related to railway cloud management and orchestration are considered. [ABSTRACT FROM AUTHOR]

Increased demand on rail, due to climate initiatives and passenger numbers, places significant pressure on existing railway operations; specifically on capacity, operational flexibility, and network robustness. These pressures are exacerbated by constraints, which prevent the construction of new track and infrastructure. This results in the need to use existing infrastructure and operating processes. One proposed solution is digitalization, which results in autonomous rail, where automated and connected intelligent transport systems facilitate smart traffic management. However, this generates the challenge of integrating autonomous trains and their associated technologies with existing infrastructure and operations. To understand this issue from an enterprise level, this paper has applied Brian Wilson's Soft Systems Methodology (a variation of Checkland's methodology) to the problem situation. This methodology explores and investigates the existing rail system in Great Britain (UK less Northern Ireland) and its stakeholders. The paper aims to propose a solution into how to transform the legacy system into one which incorporates autonomous operations and ultimately becomes fully autonomous. It culminates in a series of models that are relevant to those with a legitimate interest in the system. The models identify the activities required to analyze whether autonomy is worthwhile and if it is, how to successfully integrate it with legacy operations. Additionally, the models provide the basis for which a formal stakeholder analysis can take place. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ottoman Legacy Studies (OMAD) / Osmanlı Mirası Araştırmaları Dergisi is the property of Journal of Ottoman Legacy Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Considering the significant growth rate of populations in urban areas, public transport has become vital to urban living. Promoting the culture of Mobility as a Service (MaaS) among travelers has become unavoidable to address climatic challenges, particularly the global warming phenomenon. To encourage the use of public transport, it is important to introduce innovative IT solutions to the ecosystem of TSPs (Transport Service Providers) backed by an in-depth analysis to meet the expectations and the needs of the TSPs and the travelers. Building on the work from a previous paper, which introduced an assessment methodology based on the calculation of the effectiveness of IT solutions to meet traveler's needs and expectations, this paper presents the results of an intersectional assessment by applying this methodology with data collected in six demo sites (Athens, Barcelona, Liberec, Osijek, Padua, and Warsaw). This paper will help to understand better this quantitative assessment methodology, and especially help IT developers and TSPs understand better how to apply it to their IT solutions. Results of this assessment show which of these IT solutions (functionalities) are worth investment, considering the satisfaction level of both TSPs and travelers. This assessment methodology is scalable to other demo sites and datasets in further developments. [ABSTRACT FROM AUTHOR]

The problems that cause public transportation are less desirable because the railway network is still very limited, public transportation services still need to be improved, full integration has not been realized and the development of Transit Oriented Development cannot be implemented. The purpose of this study was to determine whether the service model and public policy were successful, therefore the study used variables, namely; Perceived Quality; Trust; Passenger Satsfaction; Perceived Value; Passenger Preference; Passenger Loyalty, Behavior Intention to Purchase and Transit Oriented Development as moderation and Passenger preference as intervening variables. Data analysis methods in this study include Importance and Performance Analysis (IPA), and Structural Equation Model (SEM) with the help of the SMART PLS 4 program and this study used a sample of 400 respondents, namely train users. Based on the results of the analysis that Perceived quality, Passenger satisfaction, Trust, Passenger preference and Passenger loyalty can have a positive and significant influence on behavior intention to purchase but Perceived value does not have a significant influence then with the development of transit-oriented development can have a significant influence on loyalty and behavior intention to purchase. In Importance performance analysis to improve service performance, namely unhindered train travel, high reliability, integrated and single ticket system. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Historia Económica / Journal of Iberian & Latin American Economic History is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Huge regenerative braking (RB) energy is generated in the AC traction power supply system (TPSS) which is related to safe operation and comprehensive energy utilisation. For the RB energy utilisation, the authors propose a railway regenerative braking power conditioner (RBPC) with no energy storage system (ESS) integrated which is located at the end of the power sections between adjacent traction substations (TSSs). First, the RB characteristics are studied based on a large amount of measured data, and the load power states are classified according to the load powers of adjacent power sections. Then, the RB energy utilisation scheme, transferring the RB power to the adjacent power section where traction power exists, has been studied. Moreover, a dual closed‐loop control strategy for a back‐to‐back converter is adopted to achieve RB energy utilisation. Finally, a case study and an engineering application are carried out. The results have verified the feasibility of this method, which can illustrate that more than half of the RB energy can be mutually utilised in adjacent power sections. [ABSTRACT FROM AUTHOR]

In urban railway systems, the timetable guides the section operation of the single train and the arrangement of the train group to meet the dual needs of cost and passengers. This paper proposes a two‐objective train operation optimization based on eco‐driving and timetabling to restore a more realistic scene, including a method level and an objective level. For the method level, the speed curve optimization of the single train and the timetable optimization of the train group are adopted jointly. For the objective level, both the total energy consumption of the train group and the consuming time of passengers are considered. A hybrid solution strategy based on quadratic programming and improved artificial bee colony algorithm is proposed. A hardware‐in‐the‐loop platform is built to carry out validation experiments. Both the cases in general hours and special hours are verified based on the actual data from Beijing Metro Line 15. The results show that both the energy consumption and the passenger consuming time are reduced simultaneously. Correspondingly, the speed curve and the time distribution of the timetable are individually optimized based on the fluctuating passenger flow. [ABSTRACT FROM AUTHOR]

In order to ensure punctual and robust service, it is vital to have a good understanding of the current performance of a railway network. Several approaches to doing so exist but lack the ability to compare both service and station performance in a single dimension. The study presented here proposes the use of the Rasch analysis technique within an operational context to compare the relative dwell time performance of stations and services. To do so, we make use of data from commuter trains in Sweden and the UK. The results from the study suggest that the method can be used to study dwell times on a line level and can capture the variability in dwell times. Assessing the model output also shows that the approach adequately reflects the expected variability in both service performance and station difficulty. Comparing the model output to more commonly used indicators for dwell time, we find that the Rasch analysis allows us to better identify cases where planners can make adjustments to reduce the likelihood of dwell time delays. In addition to this, we highlight that a common assumption that more passengers lead to worse dwell times does not hold. Having more in-depth insights into where dwell time performance is troublesome can help planners to make more informed decisions which helps towards improving overall dwell time performance, reducing delays, and improving the attractiveness of trains as a mode of transport.

In this article, the author refers to the Agreement on Friendly Relations and Cooperation between Mongolia and the Russian Federation of 1993, the Ulaanbaatar Declaration of 2000, the Moscow Declaration of 2006, the Declaration on the Development of Strategic Partnership between Mongolia and the Russian Federation of 2009, and "Agreement between Mongolia and Russia on friendly relations and comprehensive strategic partnership" of 2019. Some current issues of relations between the two countries are analyzed by analyzing legal documents and other agreements. Монгол-Оросын хооронд байгуулсан гэрээ хэлэлцээрүүдийн зарим асуудлуудад хийсэн дүн шинжилгээ Хураангуй: Энэхүү өгүүлэлд зохиогч 1993 оны “Монгол Улс, ОХУ-ын найрсаг харилцаа, хамтын ажиллагааны тухай гэрээ”, 2000 оны “Улаанбаатарын тунхаглал”, 2006 оны Москвагийн тунхаглал, 2009 оны “Монгол Улс, ОХУ-ын хооронд Стратегийн түншлэл хөгжүүлэх тухай тунхаглал”, 2019 оны “Найрсаг харилцаа, иж бүрэн стратегийн түншлэлийн тухай Монгол Улс, ОХУ-ын хоорондын гэрээ” зэрэг хоёр орны харилцааг иж бүрэн стратегийн түншлэлийн хэмжээнд хүргэсэн, эрхзүйн үндэс суурь болсон баримт бичгүүд болоод бусад гэрээ хэлэлцээрүүдэд анализ хийх замаар хоёр орны харилцааны зарим тулгамдсан асуудлуудыг судлан шинжлэв. Түлхүүр үг: гэрээ, хэлэлцээр, Монгол-Оросын харилцаа, Оросын үл хөдлөх хөрөнгө, их өр, төмөр зам

In the 1880s, Portuguese colonial authorities promoted the construction of railways in Angola. In this article, I analyse this historical process from the point of view of the concept of critical infrastructure. I argue that the absence of railways in Angola was a cause for concern and fostered a sense of urgency among Portuguese colonialists, as it could jeopardize the imperial project. Additionally, railways were considered critical to solidify Portuguese authority over Angolan territory and to develop the exploitation of local resources. During construction and operation, these infrastructures developed several vulnerabilities (both financial and technical) that could limit their potential. Portuguese decision-makers were forced to find solutions to strengthen the resilience of their railways. This article offers a new perspective on the colonial railways in Angola, through a literature review and the use of several primary sources.

Brake pads significantly affect the braking performance of railways under both normal and emergency operating conditions. In previous studies, brake pads were made using the hand lay-up method and produced the best properties on specimens with epoxy, rice husk, Al2O3 and Fe2O3 compositions of 50%, 20%, 15% and 15%. However, the resulting density does not meet the density standard set by PT Industri Kereta Api Indonesia (PT INKA), which is 1.7–2.4 g/cm3. To date, there has been limited research into the utilization of the compression hot molding method for the production of asbestos-free composite friction materials composed of epoxy, rice husk, Al2O3 and Fe2O3 for railway applications. In this study, we aimed to determine the effect of compression molding temperature on the characterization of composite brake pads for railway applications. The brake pad specimens were made of epoxy resin, rice husk, Al2O3 and Fe2O3 with a composition of 50%, 20%, 15% and 15%, respectively. The manufacture of composites in this study used the compression molding method with a pressure of 20 MPa for 15 min holding time. The mold temperature used were 80, 100, 120 ℃. Density, hardness, tensile, wear, thermal gravimetric analysis (TGA) and differential scanning calorimetry (DSC) tests were performed to evaluate the properties of the specimens obtained. The results demonstrated that an increase in molding temperature improved the characterization of the brake pads, with the best results achieved at a molding temperature of 120 ℃ (SP-3 specimen). SP-3 specimens had the best density, hardness, tensile properties and thermal properties compared to other specimens.

Abstract With the rapid development of high‐speed railway, the auto‐transformer traction network (ATN) is also expanding. However, due to the improved performance of electric multiple units (EMUs) and the non‐linear relationship between impedance and ground fault distance, distance protection has limited coverage and cannot accurately locate the fault distance by measuring impedance. This paper presents a model of the ATN considering the presence of EMUs, which effectively demonstrates the characteristics of current distribution under the ground faults. Furthermore, a ground fault identification method based on multi‐terminal currents is proposed to enhance the accuracy of fault identification and differentiate faults and EMUs. The mapping relationship between current distribution and fault location is derived, and an accurate fault location method is proposed. Compared to existing methods, this method is not affected by EMUs and AT parameters. The fault identification and location scheme for ATN employs multi‐terminal synchronous information. Finally, through simulation and experimental setups, case studies have been conducted to verify the accuracy and robustness of the proposed method in various fault scenarios. Certainly, this research has significant application prospects in fault analysis and detection for HSR.

Abstract The auto‐passing neutral section (ANS), applied in the traction substation or section post (SP), is one of the effective methods to improve the continuity of power supply, and the electromagnetic transient is the key issue impacting its application value. An equivalent switching circuit is established to reveal the causes of the electromagnetic transient. The suppression methods for reducing transient overvoltage and inrush current are proposed, adopting an improved RLC filter to suppress the transient overvoltage with low active power loss, and a switching strategy to minimize magnetic flux variation. The correctness of the proposed methods has been confirmed by simulation and experimental results, which can improve the transient performance and increase the practicality of the ANS.

When a wheel passes over a rail surface irregularity, the resulting vehicle excitations lead to the application of additional system forces to both the track and the vehicle. These forces contribute to an accelerated track geometry deterioration, which in turn results in increased costs. In a recent paper, a clear correlation between the presence of rail irregularities and poor track geometry quality was demonstrated. Rail surface irregularities thereby were quantified by raw data of a chord-based optical measurement system mounted on the regular track recording vehicle in Austria. This paper deals with deconvolution of the recorded data in order to guarantee irregularity quantification without any distortion. Two different deconvolution approaches are developed and validated by additional measurements. Using the deconvoluted data, previously published evaluations were repeated, and the impact of using deconvoluted data instead of chord values was analysed. The correlation between short-wave effects and track geometry quality can not only be confirmed; it is even stronger than predicted by the chord data. The results of the analysis demonstrate that irregularities with amplitudes exceeding 0.08 mm contribute to an accelerated deterioration in track geometry. Amplitudes of a greater severity result in track geometry levels that are up to 120% inferior to the average.