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This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

The purpose of this paper is to focus on the reference model of a grid-like supply network that enables formulation of delivery routing and scheduling problems in the context of the periodic vehicle routing problem.

The conditions for seamless (collision-free) synchronization of periodically executed local transport processes presented in this paper guarantee cyclic execution of supply processes, thereby preventing traffic flow congestion.

Systems that satisfy this characteristic, cyclic deliveries executed along supply chains are given and what is sought is the number of vehicles needed to operate the local transport processes in order to ensure delivery from and to specific loading/unloading points on given dates. Determination of sufficient conditions guaranteeing the existence of feasible solutions that satisfy these constraints makes it possible to solve the considered class of problems online.

The computer experiments reported in this paper show the possibilities of practical application of the proposed approach in the construction of decision support systems for food supply chain management.

The aim of the present work is to develop a methodology for the synthesis of regularly structured supply networks that would ensure fixed cyclic execution of local transport processes. The proposed methodology, which implements sufficient conditions for the synchronization of local cyclic processes, allows one to develop a method for rapid prototyping of supply processes that satisfies the time windows constraints given.

The role of logistics service provider (LSP) is essential for efficient logistics service quality (LSQ) and supply chain management, especially in multimodal transport. Multimodal transport routes that use the Trans-Siberian Railway (TSR) play an important role in the supply chains of Northeast Asia. This paper aims to identify current conditions of TSR LSQ and propose improvements to enhance the competitiveness of traditional routes. Therefore, this study sheds light on and provides recommendations for various managerial strategies to LSPs in the context of the TSR. This study utilizes Importance-Performance Analysis (IPA) to measure levels of importance and performance of the logistics service of LSPs that provide multimodal transport services via the TSR from South Korea to Europe. This study identifies capabilities on the basis of five criteria (price, timeliness, reliability, equipment systems, and customer service) from a customers’ perspective. The results of the research indicate that operational improvements should be considered to activate TSR multimodal transport for northern logistics routes from the perspective of Korean shippers. Specific findings show that balanced development strategies are needed for logistics routes that have not yet been significantly activated, while implying that logistics costs could be reduced initially to satisfy shippers. This study presents an operational strategy for LSPs using the TSR in northern logistics through IPA methods. Furthermore, this research can help policymakers propose specific policies to revitalize the northern logistics of Korean logistics companies and to provide incentive supports for shippers.

How does the human brain absorb information and turn it into skills of its own in psychotherapy? In an attempt to answer this question, the authors will review the intricacies of processing channels in psychotherapy and propose the term transprocessing (as in transduction and processing combined) for the underlying mechanisms. Through transprocessing the brain processes multimodal memories and creates reparative solutions in the course of psychotherapy. Transprocessing is proposed as a stage-sequenced mechanism of deconstruction of engrained patterns of response. Through psychotherapy, emotional-cognitive reintegration and its consolidation is accomplished. This process is mediated by cellular and neural plasticity changes.

This systematic literature review focuses on the following future advanced information and communication technologies (ICTs) applied in the maritime transport of cargo: Internet of Things (IoT), big data, cloud computing and autonomous ships/vessels (including unmanned ships/vessels). The review question is: “RQ: In what context and by means of what mechanism does the implementation of future advanced ICTs have disruptive impact on maritime transport?”.

The paper complies with the methodological requirements of systematic reviews. The information analysis and synthesis are based on the CIMO logic, referring to the context (C), intervention (I), mechanism (M) and outcome (O) of the implementation of future advanced ICTs in maritime transport.

The review identifies the contextual factors and components of the mechanism that lead to the disruptive impact of different types of future advanced ICT interventions on maritime transport.

The review approaches only the most important future advanced ICTs that will disrupt maritime transport.

The maritime transport organizations should consider: intended outcome as intervention trigger; increased efficiency and responsiveness; benchmarking.

For the first time, the CIMO logic is applied in a systematic review focused on future advanced ICTs in maritime transport. The CIMO-DMT model is elaborated as a basis for further research. Ten directions of study are recommended in a future research agenda.

The aim of this study is to investigate subject independent emotion recognition capabilities of EEG and peripheral physiological signals namely: electroocoulogram (EOG), electromyography (EMG), electrodermal activity (EDA), temperature, plethysmograph and respiration. The experiments are conducted on both modalities independently and in combination. This study arranges the physiological signals in order based on the prediction accuracy obtained on test data using time and frequency domain features.

DEAP dataset is used in this experiment. Time and frequency domain features of EEG and physiological signals are extracted, followed by correlation-based feature selection. Classifiers namely – Naïve Bayes, logistic regression, linear discriminant analysis, quadratic discriminant analysis, logit boost and stacking are trained on the selected features. Based on the performance of the classifiers on the test set, the best modality for each dimension of emotion is identified.

 The experimental results with EEG as one modality and all physiological signals as another modality indicate that EEG signals are better at arousal prediction compared to physiological signals by 7.18%, while physiological signals are better at valence prediction compared to EEG signals by 3.51%. The valence prediction accuracy of EOG is superior to zygomaticus electromyography (zEMG) and EDA by 1.75% at the cost of higher number of electrodes. This paper concludes that valence can be measured from the eyes (EOG) while arousal can be measured from the changes in blood volume (plethysmograph). The sorted order of physiological signals based on arousal prediction accuracy is plethysmograph, EOG (hEOG + vEOG), vEOG, hEOG, zEMG, tEMG, temperature, EMG (tEMG + zEMG), respiration, EDA, while based on valence prediction accuracy the sorted order is EOG (hEOG + vEOG), EDA, zEMG, hEOG, respiration, tEMG, vEOG, EMG (tEMG + zEMG), temperature and plethysmograph.

Many of the emotion recognition studies in literature are subject dependent and the limited subject independent emotion recognition studies in the literature report an average of leave one subject out (LOSO) validation result as accuracy. The work reported in this paper sets the baseline for subject independent emotion recognition using DEAP dataset by clearly specifying the subjects used in training and test set. In addition, this work specifies the cut-off score used to classify the scale as low or high in arousal and valence dimensions. Generally, statistical features are used for emotion recognition using physiological signals as a modality, whereas in this work, time and frequency domain features of physiological signals and EEG are used. This paper concludes that valence can be identified from EOG while arousal can be predicted from plethysmograph.

The operating wagon records were produced from distinct railway information systems, which resulted in the wagon routing record with the same oriental destination (OD) was different. This phenomenon has brought considerable difficulties to the railway wagon flow forecast. Some were because of poor data quality, which misled the actual prediction, while others were because of the existence of another actual wagon routings. This paper aims at finding all the wagon routing locus patterns from the history records, and thus puts forward an intelligent recognition method for the actual routing locus pattern of railway wagon flow based on SST algorithm.

Based on the big data of railway wagon flow records, the routing metadata model is constructed, and the historical data and real-time data are fused to improve the reliability of the path forecast results in the work of railway wagon flow forecast. Based on the division of spatial characteristics and the reduction of dimension in the distributary station, the improved Simhash algorithm is used to calculate the routing fingerprint. Combined with Squared Error Adjacency Matrix Clustering algorithm and Tarjan algorithm, the fingerprint similarity is calculated, the spatial characteristics are clustering and identified, the routing locus mode is formed and then the intelligent recognition of the actual wagon flow routing locus is realized.

This paper puts forward a more realistic method of railway wagon routing pattern recognition algorithm. The problem of traditional railway wagon routing planning is converted into the routing locus pattern recognition problem, and the wagon routing pattern of all OD streams is excavated from the historical data results. The analysis is carried out from three aspects: routing metadata, routing locus fingerprint and routing locus pattern. Then, the intelligent recognition SST-based algorithm of railway wagon routing locus pattern is proposed, which combines the history data and instant data to improve the reliability of the wagon routing selection result. Finally, railway wagon routing locus could be found out accurately, and the case study tests the validity of the algorithm.

Before the forecasting work of railway wagon flow, it needs to know how many kinds of wagon routing locus exist in a certain OD. Mining all the OD routing locus patterns from the railway wagon operating records is helpful to forecast the future routing combined with the wagon characteristics. The work of this paper is the basis of the railway wagon routing forecast.

As the basis of the railway wagon routing forecast, this research not only improves the accuracy and efficiency for the railway wagon routing forecast but also provides the further support of decision-making for the railway freight transportation organization.

This paper deals with network configurations in liner shipping and inland transportation from a carrier's perspective. The cost efficiency of different possible network configurations in the foreland-hinterland continuum is discussed based on a cost model and on a qualitative analysis. It is demonstrated that the tendency towards cargo concentration in a limited number of ports has led to the redesign of collection and distribution networks in the hinterland. Further cargo bundling in the foreland-hinterland continuum towards even fewer ports and inland centres is only interesting from a cost perspective if considerable economies of scale and density can be realised in the associated hinterland networks. The more cost efficient the network becomes, the less convenient that network could be for the shippers ' needs in terms of frequency and flex ibility. As such, the future configuration of liner shipping networks and inland transport networks will largely depend on the balance of power between carriers and shippers.

A search and rescue incident is ultimately all about the location of the missing person; hence, geotechnical tools are critical in providing assistance to search planners. One critical role of Geographic Information Systems (GISs) is to define the boundaries that define the search area. The literature mostly focuses on ring- and area-based methods but lacks a linear/network approach. The purpose of this paper is to present a novel network approach that will benefit search planners by saving time, requires less data layers and provides better results.

The paper compares two existing models (Ring Model, Travel Time Cost Surface Model (TTCSM)) against a new network model (Travel Time Network Model) by using a case study from a mountainous area in Austria. Newest data from the International Search and Rescue Incident Database are used for all three models. Advantages and disadvantages of each model are evaluated.

Network analyses offer a fruitful alternative to the Ring Model and the TTCSM for estimating search areas, especially for regions with comprehensive trail/road networks. Furthermore, only few basic data are needed for quick calculation.

The paper supports GIS network analyses for wildland search and rescue operations to raise the survival chances of missing persons due to optimizing search area estimation.

The paper demonstrates the value of the novel network approach, which requires fewer GIS layers and less time to generate a solution. Furthermore, the paper provides a comparison between all three potential models.

The expected benefits of newly developed transportation infrastructures are the saving of travel time and further promoted transport economics. There is a need for a methodology of travel time estimation with acceptable robustness and practicability. Macroscopic fundamental diagram (MFD) represents the overall traffic performance at a network level by linking average flow, speed and density. MFD can be used to estimate network state and to describe various traffic management strategies. This study aims to describe the effect of new infrastructure development on the network performance using the MFD framework.

The scenarios of Islamabad Road network before and after the infrastructure construction were simulated, in which the floating car data set (FCD) for multiple modes was extracted. MFD has been formed for the whole region and partitioned region, which was divided on the basis of infrastructural changes. Moreover, this study has been extended to calculate travel time for multiple modes using the MFD results and the Bureau of Public Roads (BPR) function at a neighborhood level.

MFD results for the whole network showed that the speed of traffic improves after the construction of new infrastructure. The travel time estimates using MFD results were dependent on the speed estimates, whereas the estimates obtained using the BPR function were found to be dependent on the traffic volume variation during different intervals of the day. By using the FCD for multiple modes, travel time estimates for multiple modes were obtained. The BPR function method was found valid for estimating travel time of traffic stream only.

This paper innovatively investigates the change in network performance for pre-construction and post-construction scenarios using the MFD framework. In practice, the approach presented can be used by transportation agencies to evaluate the effect of different traffic management strategies and infrastructural changes.