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Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is important. Unfortunately, the traditional use of water by humans for agricultural purposes contradicts the concept of optimal consumption. Therefore, designing and implementing a mechanized irrigation system is of the highest importance. This system includes hardware equipment such as liquid altimeter sensors, valves and pumps which have a failure phenomenon as an integral part, causing faults in the system. Naturally, these faults occur at probable time intervals, and the probability function with exponential distribution is used to simulate this interval. Thus, before the implementation of such high-cost systems, its evaluation is essential during the design phase.

The proposed approach included two main steps: offline and online. The offline phase included the simulation of the studied system (i.e. the irrigation system of paddy fields) and the acquisition of a data set for training machine learning algorithms such as decision trees to detect, locate (classification) and evaluate faults. In the online phase, C5.0 decision trees trained in the offline phase were used on a stream of data generated by the system.

The proposed approach is a comprehensive online component-oriented method, which is a combination of supervised machine learning methods to investigate system faults. Each of these methods is considered a component determined by the dimensions and complexity of the case study (to discover, classify and evaluate fault tolerance). These components are placed together in the form of a process framework so that the appropriate method for each component is obtained based on comparison with other machine learning methods. As a result, depending on the conditions under study, the most efficient method is selected in the components. Before the system implementation phase, its reliability is checked by evaluating the predicted faults (in the system design phase). Therefore, this approach avoids the construction of a high-risk system. Compared to existing methods, the proposed approach is more comprehensive and has greater flexibility.

By expanding the dimensions of the problem, the model verification space grows exponentially using automata.

Unlike the existing methods that only examine one or two aspects of fault analysis such as fault detection, classification and fault-tolerance evaluation, this paper proposes a comprehensive process-oriented approach that investigates all three aspects of fault analysis concurrently.

In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.

Ad hoc mobile networks are commonplace in every aspect of our everyday life. They become essential in many industries and have uses in logistics, science and the military. However, because they operate mostly in open spaces, they are exposed to a variety of dangers. The purpose of this study is to introduce a novel method for detecting the MAC layer misbehavior.

The proposed novel approach is based on exponential smoothing for throughput prediction to address this MAC layer misbehavior. The real and expected throughput are processed using an exponential smoothing algorithm to identify this attack, and if these metrics exhibit a trending pattern, an alarm is then sent.

The effect of the IEEE 802.11 MAC layer misbehavior on throughput was examined using the NS-2 network simulator, as well as the approval of our novel strategy. The authors have found that a smoothing factor value that is near to 0 provides a very accurate throughput forecast that takes into consideration the recent history of the updated values of the real value. As for the smoothing factor values that are near to 1, they are used to identify MAC layer misbehavior.

According to the authors’ modest knowledge, this new scheme has not been proposed in the state of the art for the detection of greedy behavior in mobile ad hoc networks.

This paper aims to provide a bibliometric review and visualisation analysis of the literature on Sustainable Stock Indices (SSI) between January 2001 and March 2022. The purpose of performing this bibliometric analysis is to empirically report the trend, intellectual structure, knowledge development directions and identify prospective research topics in the area of SSI.

A total of 222 publications were selected after evaluating, identifying and synthesising the extensive publications using the Preferred Reporting Items for the Systematic Reviews and Meta-Analyses (PRISMA) approach. The articles were extracted from the databases of SCOPUS, Web of Science and Google Scholar. The study uses VOSviewer and RStudio software to answer four research questions.

The results signify that there has been a considerable increase in the level of research considering SSI. Further, the study shows that SSI is among the top five trending keywords in the research related to finance and environment. Most papers considered as a sample for this study are based on Dow Jones Sustainable Indices. Noteworthy, very few economies are participating in this research domain, and the significant contribution is from the developed countries.

The present review paper may assist the researchers in identifying the trending research topics in this domain. It may serve as a roadmap for several further studies in the area.

This study is unique in terms of reviewing the literature based on SSI. Further, it provides a holistic view of the current trend, global position and research hotspots of SSI, which has important implications for future research.

The aim of this paper is to review the literature on the prediction of cutting tool life. Tool life is typically estimated by predicting the time to reach the threshold flank wear width. The cutting tool is a crucial component in any machining process, and its failure affects the manufacturing process adversely. The prediction of cutting tool life by considering several factors that affect tool life is crucial to managing quality, cost, availability and waste in machining processes.

This study has undertaken the critical analysis and summarisation of various techniques used in the literature for predicting the life or remaining useful life (RUL) of the cutting tool through monitoring the tool wear, primarily flank wear. The experimental setups that comprise diversified machining processes, including turning, milling, drilling, boring and slotting, are covered in this review.

Cutting tool life is a stochastic variable. Tool failure depends on various factors, including the type and material of the cutting tool, work material, cutting conditions and machine tool. Thus, the life of the cutting tool for a particular experimental setup must be modelled by considering the cutting parameters.

This submission discusses tool life prediction comprehensively, from monitoring tool wear, primarily flank wear, to modelling tool life, and this type of comprehensive review on cutting tool life prediction has not been reported in the literature till now. The future suggestions provided in this review are expected to provide avenues to solve the unexplored challenges in this field.

The overview of FOLIO in this paper will include a description of its background and development, architecture, work structure, benefits and core features. It will detail how FOLIO handles the challenges libraries confront and how it makes library administration more effective and integrated.

This paper conducted a comprehensive literature search using Google Scholar and ProQuest databases to identify relevant literature on FOLIO library management systems, open-source library systems and library services platforms. It screened and selected relevant literature related to FOLIO’s architecture, features, implementation, community involvement and impacts on libraries. The selected literature was organised into a systematic structure, and analysed and synthesised information was selected from studies. Critically reviewing the literature, insights from libraries, users or FOLIO developers were integrated, and data analysis was if accessible. This research paper was organised logically, presenting a coherent flow of information.

A strong alternative for conventional proprietary systems is the use of FOLIO as an open-source library management system. The versatility, usability and affordability of the platform have the potential to revolutionise library services and improve the entire library experience for both staff and users. FOLIO is a revolutionary tool that gives libraries the resources they need to succeed in the digital era as they continue to adjust to the shifting information landscape. The unique open-source platform FOLIO is expected to continue to succeed and improve through the library community’s collaborative efforts and continuous research and development.

Despite FOLIO’s growing popularity, empirical research on user attitudes and perceptions of them is still in its early stages. This paper is one of the first scholarly studies to attempt a thorough forecast of FOLIO adoption in technologically advanced libraries.

Housing is one of the basic necessities of humankind for survival and purchasing a home is often a substantial milestone. Individuals exhibit complex behaviour influenced by various factors while making decisions related to the purchase of residential properties. While most of the earlier studies have focused on understanding the purchasing behaviour of home buyers’ in developed countries, the research is limited on this topic in developing countries such as India. The booming information technology industry has rapidly increased the demand for residential properties among the migrant population in Bengaluru, India’s largest technology hub. Real estate developers strive to meet the requirements of prospective customers through innovative ways but face challenges in a competitive market.

It is essential to understand the factors influencing home buyers’ purchase attitudes for increasing property sales. However, a lack of research on this subject is identified in the emerging city of Bengaluru. This study aims to analyse the determinants of home buying decisions for potential investors in Bengaluru through structural equation modelling to provide insights for the real estate industry to construct houses as per their customers’ needs.

It was found that housing amenities, financial aspects, location conveniences and marketing services significantly influenced home buyers’ purchase decisions, whereas housing features do not.

The findings of this study offer valuable insights for governmental bodies to implement appropriate policies and for builders to design properties with features that cater to the target population, thereby promoting sustainable growth in the real estate industry.

Purpose: The prominence of quality education for building sustainable development is undeniable and is distinctly pointed out in 1 of the 14 sustainable development goals (SDGs). In the same context, this study intends to investigate the role of university commitment, perceived organisational prestige, student satisfaction, and perceived employability in enhancing sustainability in higher education.

Need of the Study: To evaluate how student satisfaction mediates the relationship between university commitment, perceived organisational prestige, and perceived employability with sustainable university institutes.

Methodology: An adapted questionnaire was used in this study to capture the perception of 458 management graduates selected through the purposive sampling method. Partial least squares structural equation modelling (PLS-SEM) technique was used to analyse the data with the help of Smart PLS software.

Findings: The results of this study show that student satisfaction is the strongest predictor of sustainable university institutes. University commitment was found to lead to student satisfaction significantly. Furthermore, student satisfaction wasn’t found to play the role of mediator in the proposed model.

Practical Implications: This study aims to fulfil theoretical, research, and management implications for students, higher education institutes (HEIs), and policymakers. HEIs are recommended to instil university commitment, perceived organisational prestige and student satisfaction via various practices and amendments in their curriculum. Students are recommended to enhance their perceived employability to achieve career sustainability.

The paper aims to provide an investigation about the effect of weft yarn type on thermal comfort and air permeability properties of Lyocell blended drapery fabrics.

The paper evaluates the effect of weft yarn type on thermal comfort and air permeability properties of Lyocell blended drapery fabrics. Twill drapery fabrics with 18 Tex linen warp yarn where two types of weft yarns were utilized respectively with the order of “A” yarn and “B” yarn. 58 Tex Lyocell Linen blended first weft yarn (A yarn) was kept constant and the second weft yarn (B yarn) varied in different yarn structures and yarn count. Thermal comfort properties such as thermal conductivity, thermal resistivity, thermal absorptivity, fabric thickness were measured by means of Alambeta device. Correlation matrix between the thermal properties was also displayed. Air permeability results were obtained by using SDL Atlas Digital Air Permeability Tester Model M 021 A. One way analysis of variance (ANOVA) test was performed in order to investigate the effect of weft yarn type on thermal comfort and air permeability properties of Lyocell blended drapery fabrics.

In this paper, weft yarn type was found as a significant factor on some of the thermal comfort properties such as thermal conductivity, thermal resistivity, thermal absorptivity, fabric thickness and on the air permeability properties.

There are limited works related to evaluation of some thermal comfort and air permeability properties of Lyocell blended drapery fabrics.

The agriculture sector is crucial for all economies, especially the developing ones. However, agricultural production is influenced by government intervention, which outshines the significant role of good governance indicators in agricultural productivity. In addition to this, the major climate changes also posed various challenges and led to water shortages and yield losses. Thus affecting agricultural production. In this paper, we address the issue by determining the association between state governance and agricultural productivity in N-11 countries.

Panel data have been collected from 2000 to 2021 through the Governance Indicator, World Development Indicator and World Bank databases. For data analysis, the researcher has utilized the autoregressive distributed lag (ARDL) estimations.

Through ARDL estimations, it is suggested that corruption (CC), employment in agriculture (EAG), political stability and violence absence (PS), rule of law (RL), regulatory equality (RQ) and water quality (WQ) significantly impact agricultural productivity (AGP) in the long run. In the short run, the impact of RL on AGP has been significant.

This study follows the method of data collection from secondary sources, which hinders the effectiveness of this study as, on the basis of the respective data, the potential of the researcher to get specific answers to research questions has been affected. Also, this study examines the context of N-11 countries from 2000 to 2021, which exerts a geographical limitation. While exploring the association between state governance and agricultural productivity, this study neglects the internal aspects of implementing state policies in firms.

On practical grounds, the significant association demonstrated by this study encourages agricultural firms to keenly consider state policies to gain sustainable agricultural development. Moreover, this study encourages agricultural firms to efficiently follow governance policies for efficient productivity. The outcomes of the study have shown that agricultural employment and governance infrastructure can efficiently enhance agricultural productivity. Besides, as per the results, water quality also positively impacts agricultural productivity; thus, relevant steps can be taken by the agricultural sector to improve the quality of water.