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Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

The purpose of this study is to present an analysis of the Islamic good governance concept and means known as Al-Siyasah Al-Syar’iyyah as a principle and approach for combating corruption. This literature review aims to synthesize extant literature that discusses the determinants of integrity and how to prevent and combat corruption based on the Al-Siyasah Al-Syar’iyyah perspective.

A systematic search was conducted on a literature review based on Scopus and referred journals from Google Scholar databases. A manual search on Google Scholar was performed to identify additional relevant studies. Studies were selected based on the predetermined criteria. They were thematically examined using content analysis.

The study found that most of the 45 works of the literature, (41 studies and four chapters) suggested that corruption should be considered a sin and that education of Al-Siyasah Al-Syar’iyyah’s perspective against corruption, emphasizing the principle of piety, the institutionalization of justice and accountability, good governance performance with an emphasis on its belief in self-accountability and justice, is the means to combat corruption.

This study is unique in that it focuses on locating material on battling corruption from the standpoint of Al-Siyasah Al-Syar’iyyah. Based on the al-Quran, the Sunnah and the best practices of Muslim rulership, this notion provides an epistemological, ethical and ontological stance in Islam.

Currently, Mauritius is adopting landfilling as the main waste management method, which makes the waste sector the second biggest emitter of greenhouse gas (GHG) in the country. This presents a challenge for the island to attain its commitments to reduce its GHG emissions to 30% by 2030 to cater for SDG 13 (Climate Action). Moreover, issues like eyesores caused by littering and overflowing of bins and low recycling rates due to low levels of waste segregation are adding to the obstacles for Mauritius to attain other SDGs like SDG 11 (Make Cities & Human Settlements Inclusive, Safe, Resilient & Sustainable) and SDG 12 (Guarantee Sustainable Consumption & Production Patterns). Therefore, together with an optimisation of waste collection, transportation and sorting processes, it is important to establish a solid waste characterisation to determine more sustainable waste management options for Mauritius to divert waste from the landfill. However, traditional waste characterisation is time consuming and costly. Thus, this chapter consists of looking at the feasibility of adopting machine learning to forecast the solid waste characteristics and to improve the solid waste management processes as per the concept of smart waste management for the island of Mauritius in line with reducing the current challenges being faced to attain SDGs 11, 12 and 13.

Given the importance of teacher leadership in influencing, motivating and inspiring student learning engagement and associated learning outcomes, a robust instrument to assess this construct is critical. Although there are some teacher leadership instruments available in existing literature, efforts to adapt robust psychometric instruments to measure teachers' leadership practices in Ethiopian higher education institutions have been limited. Therefore, this study attempted to address this gap by adapting the Teacher Leadership Scale (TLS) based on the Multifactor Leadership Questionnaire (MLQ-5X) and validating its psychometric properties for use in higher education settings.

Using a cross-sectional design, the study involved 409 undergraduate university students who were randomly selected from public universities. Factor analytic methodologies, including exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), were used to analyze the data collected.

The result confirmed a set of 36 items arranged in nine factors, which have a theoretically supported factor structure, excellent model fit and robust evidence for validity, and reliability and measurement invariance. These results demonstrate that the scale is a strong psychometric tool for measuring the leadership profile and practice of higher education teachers.

It can be concluded that the TLS can assist stakeholders in several ways. Researchers can benefit from the scale to measure teachers' leadership practices and predict their influence on student learning outcomes. In addition, the scale can help practitioners and policymakers collect relevant data to rethink teacher professional development initiatives, leadership training programs and other practices aimed at improving teacher leadership effectiveness.

With the rapid development of the sharing economy in manufacturing industries, manufacturers and the equipment suppliers frequently share capacity through the third-party platform. This paper aims to study influences of manufacturers sharing capacity on the supplier and to analyze whether the supplier shares capacity as well as its influences.

This paper deals with conditions that the supplier and manufacturers share capacity through the third-party platform, and the third-party platform competes with the supplier in equipment sales. Considering the heterogeneity of the manufacturer's earning of unit capacity usage and the production efficiency of manufacturer's usage strategies, this paper constructs capacity sharing game models. Then, model equilibrium results under different sharing scenarios are compared.

The results show that when the production or maintenance cost is high, manufacturers sharing capacity simultaneously benefits the supplier, the third-party platform and manufacturers with high earnings of unit capacity usage. When both the rental efficiency and the production cost are low, or both the rental efficiency and the production cost are high, the supplier simultaneously sells equipment and shares capacity. The supplier only sells equipment in other cases. When both the rental efficiency and the production cost are low, the supplier’s sharing capacity realizes the win-win-win situation for the supplier, the third-party platform and manufacturers with moderate earnings of unit capacity usage.

This paper innovatively examines supplier's selling and sharing decisions considering manufacturers sharing capacity. It extends the research on capacity sharing and is important to supplier's operational decisions.

This study empirically documents the effect of ambiguity on stock returns in a major emerging market along with the ambiguity attitudes under various market conditions.

Ambiguity is measured as the volatility of return probability distributions extracted from high frequency intraday data via a method developed by Brenner and Izhakian (2018). The impact of ambiguity is then tested on stock market returns.

The results show that ambiguity is a priced factor in Turkish stock market with a positive premium that is distinct from risk premium. In contrast with the findings in the US market, the investors in Turkey show an increasing level of ambiguity aversion as expected probability of favorable returns deviate from the mean value. The investors are effectively ambiguity neutral in lateral markets. The results are robust to testing with higher moments, sentiment measures and under recession conditions.

This study contributes to empirically documenting ambiguity and ambiguity aversion in a major emerging market along with the opportunity to observe international differences in ambiguity attitudes.

The rapidly growing e-commerce industry with its special characteristics brings new challenges to the optimization of the supply chain and inventory management. This study aims to investigate the inventory-related optimization of an e-marketplace official store that works on a business-to-customer system when cashback promotion is used to attract more customers. Also, it proposes a new inventory model to maximize the e-commerce profit by optimizing the cashback amount and delivery period.

The proposed model assumes that customer demand is a function of price and delivery time and that price is affected by the cashback amount. The e-commerce operator has a profit-sharing contract with an e-payment company that facilitates the payment. E-commerce also builds collaboration under a cost-sharing contract with a supplier to ensure product delivery. A mathematical model is developed and the related theories are investigated. A numerical example illustrates the validity of the model and a sensitivity analysis is carried out to give useful insights.

A new inventory model for an e-market system has been introduced which shows the impact of a cashback promotion on the e-commerce business. This study shows that managers can optimize the cashback amount and its delivery time to get the maximum profit. In certain cases, the manager may set a high cashback amount (e.g. 100%) to attract customers to place more orders.

This study presents a new inventory model for today’s fast-growing e-commerce business; therefore, the results contribute to the understanding of promotion program practices and inventory management and provide insights to develop efficient e-commerce managerial decisions.

Risk reporting in financial reports has a positive impact on the company and its stakeholders. The purpose of this research is to present a literature review using the bibliometric method with the title we used is Risk Reporting, and the keywords are risk disclosure, risk reporting, stakeholders, and stakeholder theory. Data processing in this chapter uses Publish or Perish (PoP) software and Vos Viewers. This study uses the Google Scholar database. The researcher scanned the journal by using Scimagojr.com to view the journal quartile. Before the search was revised, there were 230 papers from 1991 to 2021 (30 years). Researchers will see the development of risk reporting from several sides, such as the country of origin of the researcher, the type of industry that reports risk, the research methods that have been used so far, and the analysis used for reporting risk.

Since there is lack of studies in determine factors that affecting enjoyment sentiment when using online learning system, this study aims to explore the antecedents of perceived online learning enjoyment by using extended technology acceptance model (TAM) and its effect on behavioral intentions (BIN) among higher education institutions students.

The research framework was empirically evaluated using a cross-sectional research design and the data was collected from 715 undergraduate students from public higher education institutions in Malaysia using an online survey method. A structural equation modeling using partial least square method was used to examine the hypothesized model.

The results of partial least squares structural equation modeling indicated that the main predictive variables of TAM along with the extended variables were significantly influence the perceived online learning enjoyment. Meanwhile, the analysis also identified that perceived online learning enjoyment can significantly generate positive BIN for using online learning platforms as well as it also plays as a significant mediator role.

This study has significant implications for higher education institutions that wish to develop online learning environment for their students by providing answers to higher education institutions on how to successfully use the learning management system to assist students' learning performance from the aspect of online learning enjoyment sentiment.

This study is remarkable because it is the first attempt to explore the effect of these five predictors on students' learning enjoyment toward online learning platforms and subsequently on BIN to use this learning platforms, especially in the context of Malaysian higher education system. It is also unique in the way to extend the use of TAM predictive variables with others variables to produce more informative results about the study. Hence, this study also has a new contribution in the literature in the domain of digital learning.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.