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This paper aims to investigate the friction and wear properties of Cr-Ni-Mo-V steel against 440C stainless steel under both water and water–silica mixture lubricant.

The Cr-Ni-Mo-V steel specimens were taken from a forged steel brake disc with the process of quenching at 900°C and tempering at 600°C. The tribological testing was performed using a contact configuration of ball-on-flat with a liquid cell according to the ASTM standard. Detailed examinations on the worn surface were analyzed using a scanning electron microscope.

The results indicate that the friction coefficient and friction damage of the steel sliding under water–silica mixture are higher than those under water. The friction coefficient decreases with increasing load and increases with the sliding speed for the two lubricants. The mass wear rate presents a rising trend with both sliding load and speed. The wear mechanisms of the Cr-Ni-Mo-V steel sliding under the two lubricants are oxidation wear, abrasive wear and fatigue wear.

Because of the chosen tribological testing approach, the research results could not describe the tribological performance of the brake disc accurately during actual braking process of the high-speed train. Therefore, researchers are encouraged to test the proposed propositions further.

This study shows that the tribology behavior of the Cr-Ni-Mo-V steel with water or water–silica mixture lubrications helps the industrial firms and academicians to work on the wear of the brake disc in rainwater or wet environment.

From the perspective of any nation, rural areas generally present a comparable set of problems, such as a lack of proper healthcare, education, living conditions, wages and market opportunities. Some nations have created and developed the concept of smart villages during the previous few decades, which effectively addresses these issues. The landscape of traditional agriculture has been radically altered by digital agriculture, which has also had a positive economic impact on farmers and those who live in rural regions by ensuring an increase in agricultural production. We explored current issues in rural areas, and the consequences of smart village applications, and then illustrate our concept of smart village from recent examples of how emerging digital agriculture trends contribute to improving agricultural production in this chapter.

The purpose of this paper is to prepare a water-resistant adhesive (SA) from soy flour (SF) with less water-soluble components.

Defatted SF was suspended and stirred in water. Then, the pH of dispersion was adjusted to a predetermined value (i.e. 8, 9 or 10) by the addition of 2M sodium hydroxide (NaOH) solution. After stirring at a predetermined temperature (25°C, 35°C, 45°C) for different time (1 h, 2 h, 3 h), the 2M hydrochloric acid (HCl) solution was added in a dropwise manner into the dispersion until the pH value was adjusted to 4.5. Then, the dispersion was centrifuged at 6,000 rpm for 2 min. The obtained precipitate with less water-soluble components was used as an adhesive (SA) directly.

SA had a wet strength of 1.02 MPa when used for the fabrication of poplar plywood. Polyvinyl alcohol (PVA) solution was applied to improve the tack of SAs to wood surface and the viscosities of SAs were decreased from 10,200 cP to 4,100 cP at room temperature after the PVA addition. The soy proteins in SAs were not denatured to a large extent according to the differential scanning calorimetry and light microscopy. The remained multilevel structures of soy protein played a positive contribution to the water resistance of SAs, and the bond lines of cured SAs were much more stable than those of the cured SF and soy protein concentrate (SPC).

The fluidity and solid content of soy adhesives is much lower than formaldehyde adhesives. Further investigations are needed to improve the fluidity of soy adhesives with high solid contents.

Novel water-resistant soy adhesives were provided.

The purpose of this paper is to present an integrated data-driven framework for processing and analyzing large-scale vehicle maintenance records to get more comprehensive understanding on vehicle quality.

We propose a framework for vehicle quality analysis based on maintenance record mining and Bayesian Network. It includes the development of a comprehensive dictionary for efficient classification of maintenance items, and the establishment of a Bayesian Network model for vehicle quality evaluation. The vehicle design parameters, price and performance of functional systems are modeled as node variables in the Bayesian Network. Bayesian Network reasoning is then used to analyze the influence of these nodes on vehicle quality and their respective importance.

A case study using the maintenance records of 74 sport utility vehicle (SUV) models is presented to demonstrate the validity of the proposed framework. Our results reveal that factors such as vehicle size, chassis issues and engine displacement, can affect the chance of vehicle failures and accidents. The influence of factors such as price and performance of engine and chassis show explicit regional differences.

Previous research usually focuses on limited maintenance records from a single vehicle producer, while our proposed framework enables efficient and systematic processing of larger-scale maintenance records for vehicle quality analysis, which can support auto companies, consumers and regulators to make better decisions in purchase choice-making, vehicle design and market regulation.

The study aims to develop recommendations for optimal Internet of things (IoT) based solutions for a smart precision irrigation automation platform using morphological thinking (MT). The smart irrigation system (SIS) can be applied for green roof and green wall (GRGW) design by studying the relationships and configurations that will be analyzed, listed and synthesized, representing “solutions spaces” and their possibilities.

The research examines studying various cases of SIS; and assessing and analyzing the identified case studies through a decision support system (DSS) considering several factors regarding IoT, plant characteristics, monitoring, irrigation system and schedule, climate, cost and sensors used.

To develop recommendations for optimal IoT-based solutions for a smart precision irrigation automation platform.

The research paper analyzes and proposes a simultaneous solution to two conflicting problems. On the one hand, the paper proposes to apply greening of walls and roofs in hot arid regions, which will achieve greater environmental comfort. However, this is extremely difficult to implement in hot arid regions, since there is an objective problem – a lack of water. At the same time, the paper proposes the most rational approaches to organizing an irrigation system with the lowest water consumption and the highest efficiency for landscaping. Accordingly, this paper focuses on evaluating different types of SIS about the hot-arid climate in Qatar. The study aims to develop recommendations for optimal IoT-based solutions for a smart precision irrigation automation platform, which can be applied for green wall and roof design.