Search results

Ontology of a domain mainly consists of a set of concepts and their semantic relations. It is typically constructed and maintained by using ontology editors with substantial human intervention. It is desirable to perform the task automatically, which has led to the development of ontology learning techniques. One of the main challenges of ontology learning from the text is to identify key concepts from the documents. A wide range of techniques for key concept extraction have been proposed but are having the limitations of low accuracy, poor performance, not so flexible and applicability to a specific domain. The propose of this study is to explore a new method to extract key concepts and to apply them to literature in the nuclear domain.

In this article, a novel method for key concept extraction is proposed and applied to the documents from the nuclear domain. A hybrid approach was used, which includes a combination of domain, syntactic name entity knowledge and statistical based methods. The performance of the developed method has been evaluated from the data obtained using two out of three voting logic from three domain experts by using 120 documents retrieved from SCOPUS database.

The work reported pertains to extracting concepts from the set of selected documents and aids the search for documents relating to given concepts. The results of a case study indicated that the method developed has demonstrated better metrics than Text2Onto and CFinder. The method described has the capability of extracting valid key concepts from a set of candidates with long phrases.

The present study is restricted to literature coming out in the English language and applied to the documents from nuclear domain. It has the potential to extend to other domains also.

The work carried out in the current study has the potential of leading to updating International Nuclear Information System thesaurus for ontology in the nuclear domain. This can lead to efficient search methods.

This work is the first attempt to automatically extract key concepts from the nuclear documents. The proposed approach will address and fix the most of the problems that are existed in the current methods and thereby increase the performance.

The purpose of this study is to investigate the effects of propeller thrust with two different duct configurations. Propellers in a quadcopter play an indispensable role in generating the necessary thrust and torque to keep the drone flying and manoeuvring. Based on the specific purpose of the unmanned aerial vehicle, both the altitude and attitude can be varied by the amount of thrust produced.

This paper deals with the generation of three numerical models such as plain rotor, rotor with fixed duct and rotor with rotating duct and the comparison of their amount of generated thrust. The plain rotor numerical analysis was compared with the experimental results. The rotor taken for the analysis was 15 mm*5.5 mm TAROT 650. Thrust was measured for all models at four different angular speeds, such as 2,500 rpm, 4,000 rpm, 5,500 rpm and 7,000 rpm.

Due to the suction pressure gradient on the duct inlet surface, the additional amount of lift is produced, and it is the best way of increasing propulsion efficiency and its aerodynamic performance as it reduces the tip loss at the tip of the propeller. The turbulence model taken for the numerical analysis was k−ε.

The rotating duct is expected to provide additional thrust by the increased upward force due to the rotation of duct. The rotating duct produced the optimal results between the plain model and ducted model. At the highest speed of 7,000 rpm, the ducted propeller produced 24.97 N, and the rotating duct propeller produced 23.89 N, whereas the plain propeller produced 23 N thrust. Nearly 8.6% of the thrust improvement is observed in duct and 3.87% in rotating duct.

The purpose of the study is to find the effect of convergent and divergent section length on the exit flow characteristics. Converging-diverging (CD) nozzle design can be difficult because of the necessity for precise geometry and an understanding of compressible fluid flow dynamics. To obtain the ideal supersonic speeds, it is challenging to make sure that the flow chokes at the throat, where the Mach number approaches one and then expands appropriately in the diverging region. The design needs to take into consideration things like the relationship between the area and Mach number, the impact of various pressure ratios and the flow’s isentropic interactions.

An ideal thrust production is achieved through the effective acceleration of exhaust gases through proper nozzle design. This paper numerically investigates impact of convergent, divergent length and nozzle pressure ratio on the exit Mach Number of CD nozzle supersonic jet. Exit Mach Number 1.6 convergent-divergent nozzle was used. In total, five cases were taken as the length of the both the convergent-divergent sections were modified with 50% of increment and decrement in its base length. At four different NPR, the analysis was carried out in over-expanded, correctly expanded and under-expanded conditions. The NPR used were 2, 3.2, 4 and 5.

From the results, it is found that the convergent length linearly affects the exit Mach number, while the divergent length variation is not in order. Both the decreased and increased divergent length reduce the supersonic jet exit Mach number. The subsonic region is not majorly affected by the length. There is no rapid change in the flow properties whether the length is reduced or increased. Maximum of 2% to 3% variation is only noticed. On the contrary, a small change in supersonic region or divergent section makes major modification in the flow.

To achieve the desired Mach number, not only the area of the nozzle but also the length affects it. In terms of divergent angle and area ratio, only most of the studies on nozzle have been focused. This study aims to find the impact of convergent length and divergent length on the exit Mach number. This could be used in a wide range of applications, including laser cutting, thermal spraying, gas turbines for power generation, rocket and jet engines, supersonic wind tunnels and turbo chargers in automotive engineering, because of their capacity to accelerate fluids to supersonic speeds.

Leaders can guide and direct their subordinates and even be a source of inspiration for their subordinates in order to carry out the work in an organization effectively and efficiently. In the light of current approaches, many different definitions of leadership, including paradoxical leadership and digital leadership, have been made. In the literature, no research has been found on the types of leadership for current approaches and the subject of spirituality in the workplace. Moreover, although some individuals have leadership qualities, they may not prefer to be leaders. In this chapter, it will be examined how the subject of spirituality contributes to encouraging individuals to lead and activate the power within them, and what kind of leadership (spiritual, authentic, servant, destructive, etc.) has a relationship with the subject of spirituality in the workplace.

Aligning industrial operations with sustainable development has become a pressing need for organizations, as they recognize the mounting environmental challenges, social inequalities and resources scarcity. The transformations brought by the industry 4.0 have revolutionized supply chain operations to achieve sustainability and circularity. The aim of this chapter is to explore and map the supply chain 4.0 opportunities for sustainability. An extensive literature review of theoretical and empirical studies linking the supply chain 4.0 technologies and sustainability is conducted. Descriptive and content analysis are employed to scrutinize and categorize the knowledge extracted from the literature. Then, a conceptual framework is developed to highlight the role that each technology plays in promoting sustainability and circularity in the context of supply chain. This study provides new perspectives for theoretical researches and guide decision-makers to implement sustainability-based technologies in the supply chain 4.0. Future research can investigate the opportunities of supply chain 5.0 for social sustainability and circular business model.

Over the next decade, humanity is going to face big environmental problems, and considering these serious issues, businesses are adopting environmentally responsible practices. To put forward specific measures to achieve a more prosperous environmental future, this study aims to develop an environment-based perspective framework by integrating the Internet of Things (IoT) technology into a sustainable automotive supply chain (SASC).

The study presents a conceptual environmental framework – based on 29 factors constituting four stakeholders' rectifications – that holistically assess the SASC operations as part of the ReSOLVE model utilizing IoT. Then, experts from the SASC, IoT and sustainability areas participated in two rigorous rounds of a Delphi study to validate the framework.

The results indicate that the conceptual environmental framework proposed would help companies enhance the connectivity between major IoT tools in SASC, which would help develop congruent strategies for inducing sustainable growth.

This study adds value to existing knowledge on SASC sustainability and digitalization in the context where the SASC is under enormous pressure, competitiveness and increased variability.

The purpose of this paper is to investigate the friction and wear mechanisms in copper-based self-lubricating composites with MoS₂ as the lubricating phase, which provides a theoretical basis for subsequent research on high-performance copper-based self-lubricating materials.

Friction tests were performed at a speed of 100 r/min, a load of 10 N, a friction radius of 5 mm and a sliding speed of 30 min. Friction experiments were carried out at RT-500°C. The phase composition of the samples was characterized by X-ray diffraction of Cu Ka radiation, and the microstructure, morphology and elemental distribution were characterized by scanning electron microscopy and energy dispersive spectroscopy. Reactants and valences formed during the wear process were analyzed by X-ray photoelectron spectroscopy.

The addition of MoS₂ can effectively improve friction-reducing and anti-wear action of the matrix, which is beneficial to form a lubricating film on the sliding track. After analyzing different changing mechanism of the sliding tracks, the oxides and sulfides of MoS₂, MoO₂, Cu₂O, CuO and Ni(OH)₂ were detected to form a synergetic lubricating film on the sliding track, which is responsible for the excellent tribological properties from room to elevated temperature.

For self-lubrication Cu–Sn–Ni–MoS₂ material in engineering field, there are still few available references on high-temperature application.

This paper provides a theoretical basis for the following research on copper-based self-lubricating materials with high performance.

With this statement, the authors hereby certify that the manuscript is the results of their own effort and ability. They have indicated all quotes, citations and references. Furthermore, the authors have not submitted any essay, paper or thesis with similar content elsewhere. No conflict of interest exits in the submission of this manuscript.

This study aims to investigate the impact of sustainable supply chain practices on sustainability performance in North American and Canadian firms in a business-to-business (B2B) context, specifically focusing on the mediating role of emerging technologies. It aims to deepen the understanding of this complex relationship, contributing to both theoretical knowledge and practical applications.

This study collected data from supply chain managers in the USA and Canada using a mixed-methods approach that includes partial least squares structural equation modeling (PLS-SEM), necessary condition analysis (NCA) and importance-performance map analysis (IPMA). PLS-SEM was utilized to model the relationships between sustainable practices, emerging technologies and sustainability performance. NCA identified the essential conditions required for sustainability performance, while IPMA was used to assess the importance and performance of different constructs, helping to pinpoint areas where the managerial focus can yield the most significant improvements.

This study reveals that sustainable supply chain practices (SSCP) alone do not directly lead to enhanced sustainability performance. SSCP includes product design, procurement, investment recovery and social sustainability. Sustainability performance includes economic, environmental and social performance. Instead, adopting specific emerging technologies, particularly artificial intelligence, wearable devices and virtual reality, is crucial. A significant threshold identified is these technologies’ 80% adoption rate for substantial performance improvements. Furthermore, this study distinguishes the varying impacts of different technologies on economic, social and environmental aspects of sustainability.

This research offers new insights by showing that emerging technologies fully mediate the relationship between SSCP and performance. It expands on existing literature by detailing the specific impacts of various technologies, moving beyond the generalized approach seen in prior research. Specific impacts of emerging digital technologies on SSCP and performance remain underexplored in a B2B environment, and this research aims to address this gap.

This work presents the results of a case study aimed at revitalizing an agricultural equipment manufacturing consortium facing prolonged losses. The purpose of this paper is to enhance productivity and profitability by identifying and eliminating waste within the manufacturing processes. The study uses lean principles and tools to achieve this objective.

The study begins with the creation of a questionnaire, administered to the consortium to gather insights. The questionnaire responses serve as a foundation for pinpointing critical areas in need of immediate attention. To tackle the challenge of demand forecasting without customer data, a demand forecasting model is introduced. Value stream mapping (VSM) is used to identify and highlight process inefficiencies and waste. The findings are further analyzed using a Pareto chart to prioritize waste reduction efforts. Based on these insights, the study proposes alternative manufacturing methods and waste elimination strategies. A multiphase lean framework is developed as a step-by-step roadmap for implementing lean manufacturing.

The study identifies a broken process flow within the consortium’s manufacturing processes and highlights areas of waste through VSM. The Pareto chart analysis reveals the most significant waste areas requiring immediate intervention. Recommendations for process improvements and waste reduction strategies are provided to the consortium.

This study contributes to the field by applying lean principles and tools to address the unique challenges faced by an agricultural equipment manufacturing consortium. The integration of a demand forecasting model and the development of a multiphase lean framework offer innovative approaches to enhancing productivity and profitability in this context.

This study aims to proposed that blockchain helps the organization improve supply chain (SC) performance by improving integration, agility and security through real-time information sharing, end-to-end visibility, transparency, data management, immutability, irrevocable information and cyber-security platforms.

This study has made an initial effort toward proposing a framework that shows the problems and challenges for the O&G SC under its segments (upstream, midstream and downstream) and provides the interlink among blockchain properties for SCM problems. SC managers were selected for survey questionnaires from the Pakistan O&G industries.

This study analyzes the impact of blockchain-enabled SC on firm performance with an understanding of the SC robustness capabilities as a mediator. The result revealed that the SC manager believes that the blockchain-enabled SC has a positive and significant on firm performance and robustness capabilities.

Blockchain technology is reflected as high-tech to support the firm process, responses and methods. The technology helps eliminate bottlenecks, avoid uncertainties and improve decision-making, leading to improved SC functions. This study guides managers about the potential problems of existing SC and how blockchain solves SC problems more effectively.

The oil and gas (O&G) sectors are neglected by researchers, and there are limited studies on O&G supply chain management (SCM). Additionally, no empirical evidence suggests implementing blockchain for O&G as a solution for potential problems. Furthermore, present the roadmap to other industries those having complex SC networks for the implication of blockchain to improve the SC performance.