Search results

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

This corpus-based study provides a descriptive account of the distribution of the polysemous noun nafs in two Arabic varieties, Modern Standard Arabic (MSA) and Classical Arabic (CA). The research objective is to survey the use of nafs as a reflexive marker in local binding domains and as a self-intensifier in NP-adjoined positions.

The consulted corpora are Timespamped JSI Web corpus for MSA and Quran corpus for CA. While attending to corpora size differences, MSA and CA exhibit a pattern of difference and similarity in nafs diffusion.

In the modern variety, nafs is pervasively used as reflexive marker in canonical binding domains, along with a less frequent, yet notable, intensifier user, and these uses are partially and cautiously attributed to the specific genre in which they occur. In CA, nafs is mainly recurrent as a polysemous noun, along with extensive use as a reflexive marker in local binding settings. As an intensifier, nafs is totally non-existent in the CA corpus, in the same way as it is in absentia in VP-constituent extraction in MSA.

Examining whether nafs, as a reflexive marker, deviates from canonical binding in Arabic the way English reflexive pronouns do. Building a general account of this distribution is relevant in understanding the explicit (syntactic) and implicit (discourse-based) dimensions of reflexive marker and self-intensifier processing and interpretation in Arabic as a first and second language.

The present study was designed to examine the measurement of the Emotionally Intelligent Leadership (EIL) construct and to provide evidence of validation for the multidimensional Emotionally Intelligence Leadership for Students: Inventory 2.0 (EILS:I 2.0). The EILS:I 2.0 is a self-report assessment of emotionally intelligent leadership in the context of a student environment. The results of two confirmatory factory analyses of two independent samples of data from students across the United States provide support for a 19-factor model of EIL and the construct validity of the EILS:I 2.0. These results provide leadership educators evidence that use of the EILS:I 2.0 will result in the measurement of 19 capacities of EIL in students. Implications of these findings for leadership educators and directions for future research are discussed.

This paper aims to understand the most efficient hotel system and why efficiency varies across years and between the two differing types of hotel businesses in Turkey.

A data envelopment analysis (DEA) analysis was used to characterise the efficiency of all-inclusive (AI) and bed and breakfast (B&B) hotel businesses with one output (total revenue) and three inputs (labour, food and capital costs). The Malmquist approach is then used to discern changes in total efficiency (TTE) and intertemporal shifts in the efficiency frontier (technological change (Tch)).

The results reveal that the AI hotel operates at 100% efficiency in the summer and year-round. The B&B hotel business operates at 89.6% with variable constant returns to scale during the summer and with 100% efficiency. The results of the Malmquist approach indicate that the total factor productivity grew in the years 2015, 2016, 2018 and 2019, while the other years were marked by inefficiency. Such increases were due to technical efficiency change (TEch) and Tch, which means that managerial and allocative efficiency (AE) were barely achieved. Slight differences were noted in the two time periods (all year and summer), suggesting that the scale of hotel businesses is prepared to operate all year round, and this calls for strategies to mitigate seasonality.

As to avenues for future research, the limitations of this study are threefold. First, the hotel businesses are not parallel in terms of the duration of their service offerings. Future research may consider including an AI hotel business that is in operation for the whole year. Second, businesses in Turkey are sceptical about sharing their data as it is considered confidential. However, to better generalise the results and encourage hoteliers to consider the positive outcomes of such analysis, the number of observations could be increased by considering more hotel businesses in both categories. Third, a mixture of data representing businesses operating in various countries may reflect if the efficiency scores vary internationally.

Overall, AI hotel businesses are more attractive but less efficient than B&B. Furthermore, the external crisis impacts the efficiency of hotel businesses meaning that hotel managers could keep on exploring AI, perhaps educating their hosts not to waste or not offer huge quantities. Hotel managers may also need to enlarge their seasonal activities to ensure more efficiency.

Despite the intentions of AI hotel businesses to increase their profitability with a lower level of service quality, this study shows that the AI hotel business is very attractive but not so efficient due to the higher propensity of guests to consume food and beverages in excess that compromises the definition of efficiency as zero waste. AI is very attractive for family groups or those seeking the pleasure of relaxation at seaside resorts and is also very popular in Turkey. On the other hand, the B&B hotel business is more efficient but less attractive.

The contributions of this paper are threefold. First, the authors analysed the efficiency and inefficiency of hotel businesses within nine years of operations. During this period, Turkey experienced first a tourism boom (2011–2014) followed by stagnation and subsequently a sharp decline due to political instability resulting in an (in)direct impact on tourism (2015–2019). Second, the authors compared the efficiency and inefficiency of AI and B&B hotel businesses. Third, the authors examined the effects of hotel management factors to ensure efficiency.

The main objectives of collective forest tenure reform in China are to stimulate rural households to invest in forestry management, protect the ecosystem and improve their livelihood. By constructing the unbalanced panel data of household investment, this study discusses the dynamic changes and influencing factors of household investment, which will lay a foundation for further research and provide a reference for decision-making.

Based on 3,500 samples from rural households in the provinces of Fujian, Hunan, Yunnan, Shaanxi, Jiangxi, Gansu, and Liaoning collected during field investigations from 2010 to 2015, this study conducts an empirical analysis of the household investment in forestry management and its factors with nonbalanced panels.

According to the analysis, the average investment in forestry management per household from 2010 to 2015 fluctuates greatly; the age of the householder, increased forestry area, subsidies, joining professional cooperatives, and forest tenure mortgage show positive effects on achieving the objectives.

The discussions are drawn from the study that supporting policies such as the forest tenure transfer system, professional cooperatives, financial services and subsidies should be further improved to sustain a positive in the forestry industry.

As the world faces a new health crisis threatening people with the spread of Covid-19, this study aims to summarize the key information of Covid-19 related to disease characteristics, diagnosis, treatment and prevention along with the lessons learned from Thailand.

The narrative review was synthesized from various sources such as the World Health Organization; Centers for Disease Control and Prevention; Ministry of Public Health and other related news; articles in ScienceDirect, PubMed, Google Scholar; and the author's perspective regarding the lessons learned from Thailand with keywords of “Covid-19” and “Coronavirus” from January to August 2020. Google Trends was used to set common questions.

Covid-19 is the seventh family of coronaviruses that cause various symptoms related to respiratory systems. The disease can be treated through general and symptomatic treatment, by using antiviral drugs. As of July 2020, there are four potential vaccine candidates ChAdOx1 nCoV-19, mRNA-1273, Ad5-nCOV and BNT162b1. The recommendations for Covid-19 prevention are physical distancing, face masks, eye protection and hand washing. Thailand is now considered as low-risk for Covid-19 possibly because of (1) soft policy by government actions, (2) village health volunteers, (3) integration of technology and (4) fact-based communications.

This study summarized the key points about Covid-19, clarified some misunderstandings and shared strategic actions from Thailand, which can be adapted according to the different capacities and situations in other countries.

The study empirically investigates whether the board of directors' expertise in the focal firm's industry has implications for innovation input. Additionally, it explores how this relationship is shaped by the CEO's educational level and background in the technology area.

The article tests the hypothesized relationships through the Arellano–Bond generalized method of moment estimators, proxying innovation input by R&D to total sales. Moreover, it analyses a sample of privately-held Italian medium and large high-tech companies observed over four years by relying on a unique hand-collected dataset.

The research documents an inverted U-shaped relationship between board industry expertise and innovation input and shows that such curvilinear effect is moderated by the CEO's educational level and technology background. Specifically, while the curvilinear slope is less steep for highly educated CEO, it becomes steeper in the presence of technology trained CEO.

The paper recommends how to shape the board human capital as a meaningful driver of board effectiveness and innovation. Additionally, it calls the managerial attention towards the interaction and the interplay between board industry expertise and CEO education as able to influence the above-mentioned outcome.

While previous studies have focused on the linear and positive effect of board industry expertise on innovation, this research advances current knowledge in innovation management literature by testing the presence of a curvilinear relationship. Moreover, by exploring the moderating effect of CEO education, the paper provides a comprehensive picture on the interplay among board industry expertise, CEO educational training and innovation input.

Mobile phone-based human activity recognition (HAR) consists of inferring user’s activity type from the analysis of the inertial mobile sensor data. This paper aims to mainly introduce a new classification approach called adaptive k-nearest neighbors (AKNN) for intelligent HAR using smartphone inertial sensors with a potential real-time implementation on smartphone platform.

The proposed method puts forward several modification on AKNN baseline by using kernel discriminant analysis for feature reduction and hybridizing weighted support vector machines and KNN to tackle imbalanced class data set.

Extensive experiments on a five large scale daily activity recognition data set have been performed to demonstrate the effectiveness of the method in terms of error rate, recall, precision, F1-score and computational/memory resources, with several comparison with state-of-the art methods and other hybridization modes. The results showed that the proposed method can achieve more than 50% improvement in error rate metric and up to 5.6% in F1-score. The training phase is also shown to be reduced by a factor of six compared to baseline, which provides solid assets for smartphone implementation.

This work builds a bridge to already growing work in machine learning related to learning with small data set. Besides, the availability of systems that are able to perform on flight activity recognition on smartphone will have a significant impact in the field of pervasive health care, supporting a variety of practical applications such as elderly care, ambient assisted living and remote monitoring.

The purpose of this study is to build and test an accurate offline model by using only a compact training data that can reduce the computational and memory complexity of the system. This provides grounds for developing new innovative hybridization modes in the context of daily activity recognition and smartphone-based implementation. This study demonstrates that the new AKNN is able to classify the data without any training step because it does not use any model for fitting and only uses memory resources to store the corresponding support vectors.

Perceived benefits of building information modelling (BIM) have been discussed for some time, but cost–benefit benchmarking has been inconsistent. The purpose of this paper is to investigate BIM feasibility and evaluate investment worth to elucidate and develop the current understanding of BIM merit. The aim of the study is to propose a research agenda towards a more holistic perspective of BIM use incorporating quantifying investment return.

An in-depth examination of research patterns has been conducted to identify challenges in the assessment of the investment value and return on investment (ROI) for BIM in the construction industry. A total of 75 research articles were considered for the final literature review. An evaluation of the literature is conducted using a combination of bibliometric analysis and systematic reviews.

This study, which analysed 75 articles, unveils key findings in quantifying BIM benefits, primarily through ROI calculation. Two major research gaps are identified: the absence of a standardized BIM ROI method and insufficient exploration of intangible benefits. Research focus varies across phases, emphasizing design and construction integration and exploring post-construction phases. The study categorizes quantifiable factors, including productivity, changes and rework reduction, requests for information reduction, schedule efficiency, safety, environmental sustainability and operations and facility management. These findings offer vital insights for researchers and practitioners, enhancing understanding of ’BIM’s financial benefits and signalling areas for further exploration in construction.

The ’study’s outcomes offer the latest insights for researchers and practitioners to create effective approaches for quantifying ’BIM’s financial benefits. Additionally, the proposed research agenda aims to improve the current limited understanding of BIM feasibility and investment worth evaluation. Results of the study could assist practitioners in overcoming limitations associated with BIM investment and economic evaluations in the construction industry.