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In this paper, a data mining approach is proposed for monitoring the conditions leading to a rail wheel high impact load. The proposed approach incorporates logical analysis of data (LAD) and ant colony optimization (ACO) algorithms in extracting patterns of high impact loads and normal loads from historical railway records. In addition, the patterns are employed in establishing a classification model used for classifying unseen observations. A case study representing real-world impact load data is presented to illustrate the impact of the proposed approach in improving railway services.

Application of artificial intelligence and machine learning approaches becomes an essential tool in improving the performance of railway transportation systems. By using these approaches, the knowledge extracted from historical data can be employed in railway assets monitoring to maintain the assets in a reliable state and to improve the service provided by the railway network.

Results achieved by the proposed approach provide a prognostic system used for monitoring the conditions surrounding rail wheels. Incorporating this prognostic system in surveilling the rail wheels indeed results in better railway services as trips with no-delay or no-failure can be realized. A comparative study is conducted to evaluate the performance of the proposed approach versus other classification algorithms. In addition to the highly interpretable results obtained by the generated patterns, the comparative study demonstrates that the proposed approach provides classification accuracy higher than other common machine learning classification algorithms.

The methodology followed in this research employs ACO algorithm as an artificial intelligent technique and LDA as a machine learning algorithm in analyzing wheel impact load alarm-collected datasets. This new methodology provided a promising classification model to predict future alarm and a prognostic system to guide the system while avoiding this alarm.

This paper aims to address the urban mobility and traffic congestion problem under environmental dynamics to improve mobility and reduce traffic congestion using system dynamics (SD) simulation and scenarios.

SD simulation was used to analyze urban mobility and traffic congestion. Data were collected from the Transportation Department of Surabaya City. Several scenarios to improve urban mobility and reduce traffic congestion were developed by modifying the structures and parameters of the model.

Several factors influence urban mobility, including modal split, trip frequency, delay performance and the ratio of public transport supply and demand. Urban mobility, daily traffic and road capacity are some factors that affect traffic congestion. Scenarios can be designed based on the assumptions of the proposed strategy.

The study was conducted at Surabaya City, East Java, Indonesia, which is the fourth most-congested city in the world.

By implementing several strategies (mass rapid transit and bus rapid transit development and public transport delay reduction), mobility performance is projected to be improved by 70.34-92.96%. With this increased mobility, traffic congestion is projected to decline by 52.5-65.8%.

The novel contributions of this research are: formulating relationships between several variables; modeling dynamic behavior of urban mobility and traffic congestion; and building scenario models to improve mobility and reduce traffic congestion in Surabaya. With the increase in urban mobility and the decrease in average daily traffic, traffic congestion could be reduced by a minimum of 57.6% and a maximum of 69%.

To reduce the time of flight rescheduling, reduce the total delay cost of all flights to a minimum and put forward more references for passengers to take flights, this paper aims to mainly study the recovery of flights affected by snow disaster within the minimum delay time.

The temporal and spatial network flight recovery model is used to optimize all flights of various types of aircraft, and the adjusted flight schedule based on minute delay time is obtained. In addition, for passenger travel flights, the impact of passenger delay cost on the total delay time is minimized as an objective function to calculate the passenger delay cost.

In this paper, the actual departure time of aircraft is sorted in ascending order. Up to five planes can take off from the runway every 5 min, and the 10-min decision interval is successively delayed. The actual arrival time is sorted by the same method and the sequential delay is calculated to obtain the adjusted flight schedule. As a result, it takes less time to reschedule flights.

In this paper, heuristic algorithm is used to adjust the schedule of delayed flights flexibly, which is convenient for manual modification. This decision method has good robustness and can partially adjust the interrupted flights without affecting other scheduled flights while maintaining the stable operation of the whole plan, greatly improving the efficiency of civil aviation operations and reducing the impact of flight delays.

In this chapter, we discuss the impact of business trips on travelers and their families from the perspective of respite, thus embedding business trips in stress theories. We begin by reviewing the literature on respite and recovery. Focusing on the role of travelers’ resources, we relate the phenomenon of business trips to conservation of resources (COR) and job demands-resource (JD-R) theories. We then discuss the negative and positive characteristics and outcomes of business trips. We offer evidence from interviews with business travelers regarding the special characteristics and consequences of business trips. We summarize by addressing the question of whether business trips are a special kind of respite.

Convivo is a VoIP system designed to provide reliable voice communication for poor quality networks, especially those found in rural areas of the developing world. Convivo introduces an original approach to maintain voice communication interaction in the presence of poor network performance: an Interface‐ Adaptation mechanism that adjusts the user interface to reduce the impact of high latency and low bandwidth networks. Interface modes facilitate turn taking for high latency connections, and help to sustain voice communication even with extremely low bandwidth or high error rates. An evaluation of the system, conducted in a rural community in the Dominican Republic, found that Interface‐Adaptation helped users to maintain voice communication interaction as network performance degrades. Transitions from full duplex to voice messaging were found particularly valuable. Initial results suggest that as users get more experience with the application they would like to manually control transitions based on feedback provided by the application and their own perceived voice quality.

The goals of this review are to identify key theories, constructs and themes in the international business travel (IBT) literature and to propose a model based on findings, theories and constructs drawn from adjacent research literature.

The authors reviewed the business travel (BT) literature to identify conceptual and empirical articles on IBT published from 1990 to 2022. Only 53 publications were suitable for review. The authors reviewed them using an open coding system.

The IBT literature is dispersed across several disciplines that use different methods, focus on different aspects of travel and emphasize different positive and negative outcomes that IBT engenders. The publications employed a diverse range of methods, including review and conceptual (11), quantitative (28) and qualitative methods (14). The samples were diverse in country, age, marital status and tenure. Many publications were descriptive and exploratory. The few that based their research on theory focused on two stress theories: Job Demands-Resources (JD-R) theory and conservation of resources (COR) theory.

Experimental and longitudinal designs are needed to reduce the causal ambiguity of this body of mostly correlational and cross-sectional research. The authors discuss the impact of emerging advances in virtual global communication technology on the future of IBT.

More research is needed on positive aspects of IBT. Human resource (HR) people should be aware of these issues and are encouraged to decrease the deleterious aspects of the international trips and increase the positive ones.

Increasing well-being of international business travelers is important for the travelers, their families and the organization.

This is the first IBT review focused on the theoretical underpinnings of research in the field. The authors offer a model for IBT and introduce adjustment and performance as important constructs in IBT research. The authors encompass crossover theory to add the reciprocal impact of travelers and spouses and label IBT a “double-edge sword” because it arouses both positive and negative outcomes.