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The purpose of this paper is to assess the application of graph coloring and domination to solve the airline-scheduling problem. Graph coloring and domination in graphs have plenty of applications in computer, communication, biological, social, air traffic flow network and airline scheduling.

The process of merging the concept of graph node coloring and domination is called the dominator coloring or the χ_d coloring of a graph, which is defined as a proper coloring of nodes in which each node of the graph dominates all nodes of at least one-color class.

The smallest number of colors used in dominator coloring of a graph is called the dominator coloring number of the graph. The dominator coloring of line graph, central graph, middle graph and total graph of some generalized Petersen graph P_(n ,1) is obtained and the relation between them is established.

The dominator coloring number of certain graph is obtained and the association between the dominator coloring number and domination number of it is established in this paper.

The inhibition efficiency of N‐cetyl‐N,N,N‐trimethylammonium bromide (CTAB), a cationic surfactant, in controlling the corrosion of carbon steel in an aqueous solution containing 60ppm Cl^–, in the absence and presence of Zn²⁺ and also calcium gluconate (CG), had been evaluated by the weight‐loss method. Weight‐loss studies revealed that the behaviour of CTAB changed when its concentration is ≥ 150ppm. Organisation of assembly of CTAB molecules is expected to take place at this critical concentration. The protective film has been analysed using FTIR spectra. In the presence of CTAB, the protective film consists of Fe²⁺‐CTAB complex. In the presence of CTAB and Zn²⁺, the protective film consists of Fe²⁺‐CTAB complex and Zn(OH)₂. In the presence of CTAB and calcium gluconate, the protective film consists of Fe²⁺‐CTAB complex, Fe²⁺‐gluconate complex and Ca(OH)₂.

Because of the extensive user coverage of news sites and apps, greater social and commercial value can be realized if users can access their favourite news as easily as possible. However, news has a timeliness factor; there are serious cold start and data sparsity in news recommendation, and news users are more susceptible to recent topical news. Therefore, this study aims to propose a personalized news recommendation approach based on topic model and restricted Boltzmann machine (RBM).

Firstly, the model extracts the news topic information based on the LDA2vec topic model. Then, the implicit behaviour data are analysed and converted into explicit rating data according to the rules. The highest weight is assigned to recent hot news stories. Finally, the topic information and the rating data are regarded as the conditional layer and visual layer of the conditional RBM (CRBM) model, respectively, to implement news recommendations.

The experimental results show that using LDA2vec-based news topic as a conditional layer in the CRBM model provides a higher prediction rating and improves the effectiveness of news recommendations.

This study proposes a personalized news recommendation approach based on an improved CRBM. Topic model is applied to news topic extraction and used as the conditional layer of the CRBM. It not only alleviates the sparseness of rating data to improve the efficient in CRBM but also considers that readers are more susceptible to popular or trending news.

This paper aims to evaluate the inhibitive potential of borage flowers’ aqueous extract (BFAE), Borago officinalis L., against the corrosion of mild steel in 1.0 M phosphoric acid.

Evaluation was carried out by chemical hydrogen evolution (HE), mass loss (ML) and electrochemical potentiodynamic polarization (PDP) measurements. SEM-EDX analysis also was used to confirm the existence of the adsorbed film.

It was found that the inhibition efficiency of BFAE increases with the increase in its concentration, but decreases with the increase in temperature. The potentiodynamic polarization curves indicated that BFAE acts as a mixed-type inhibitor with a predominantly anodic action. The adsorption of BFAE on mild steel surface was found to obey Langmuir and thermodynamic-kinetic adsorption isotherms by forming a thin film on the metal surface. SEM-EDX analysis confirms the corrosion inhibition ability of BFEA in 1.0 M H₃PO₄ by forming a thin film on mild steel surface. In this study, the inhibitive action of BFAE components is discussed on the basis of the physical adsorption mechanism. The same results were obtained for both the freshly prepared extract and the one that kept in a refrigerator for one year.

This paper indicates that BFAE can act as a good inhibitor for the corrosion of mild steel in 1.0 M H₃PO₄ even after one year of preparation.

This paper aims to study how knowledge management (KM) practices are carried out in learning organisations. It seeks to find out; how learning organisations carry out KM practices and whether there are any specific KM attributes that differentiate high learning organisations from low learning organisations.

The research is carried out in two information technology (IT) organisations. Qualitative data obtained from these two organisations are analysed using the grounded theory approach.

Four themes of KM process emerged after the data were subjected to grounded theory analysis. These are: knowledge creation, knowledge sharing, knowledge up‐gradation, and knowledge retention. The two sample organisations were compared on these dimensions. Two concepts emerged from this comparison, namely, knowledge enablers and knowledge inhibitors.

The paper attempts to find out the pattern of KM systems in two learning organisations (high learning and low learning). The findings shed some light on different themes of KM existent in low and high learning organisations and how they differ in their KM attributes.

This study aims to investigate the influence of consumer value on women’s attitudes towards their intention to adopt menstrual cups. Drawing on consumer value theory, the research seeks to provide an empirical investigation of value-attitude-behaviour, an extant exploration of value concept in behaviour.

Data for this study was collected through survey questionnaires administered to 304 Indian women and analysed using partial least squares structural equation modelling.

The study’s finding indicate that emotional values (EVs) significantly predict women’s attitudes towards their intention to use menstrual cups. In addition, the desire for knowledge, price and quality considerations and awareness of the environmental impact were also found to influence women’s attitudes towards their behavioural intention to adopt menstrual cups.

This study contributes valuable empirical evidence supporting the importance of consumer values in shaping attitudes and behavioural intentions towards menstrual cups in a social marketing context. By understanding the role of EVs, social marketers can design more effective campaigns to encourage the adoption of menstrual cups. Promoting the sustainable aspects of menstrual cups, such as reduced environmental wastage, can further facilitate behaviour change among women.

This study demonstrates the value-attitude-behaviour framework, which has been a subject of very little research in the context of menstrual cup adoption in a developing country.

The purpose of this paper is to focus on predicting the pressure drop in fluidized dense phase pneumatic conveying of fine particles through pipelines by modelling the solids friction factor in terms of non-dimensional parameters using experimental data of definite pipeline configuration. Finally, the model is to be tested for a different pipeline configuration.

Solids friction factor has been expressed in terms of certain non-dimensional parameters such as density ratio, solids loading ratio and mean particle diameter to pipe diameter ratio, and a certain number of coefficients and exponents. Experimental data of five conveying materials (two types of fly ash, two types of alumina and one type of cement meal) for a pipeline configuration of diameter 53 mm and length 173 m and another conveying material EPS dust for two pipeline configurations (69-mm diameter, 168-m long; 105-mm diameter, 168-m long) have been used to calculate the unknown coefficients or exponents of the mathematical model for solids friction factor.

The developed model gives the best results in predicting the pressure drop for the pipelines that are less than 173-m long, but the model shows a large error for the pipelines more than 173-m long.

Current research will be helpful for the researchers to model the process of pneumatic conveying through long distances.

The method will be helpful in conveying powder materials through long distances in cement or brick industry, alumina industry.

Fly ash piles over at the nearby places of thermal power plants. Pneumatic conveying is the best method for transporting the fly ash from the location of power plants to the nearby brick industries or cement industries.

Solid friction factor has been presented in terms of four non-dimensional parameters and evaluated the accuracy in predicting the pressure drop for two different pipeline configurations.

The purpose of this paper is to study the inhibition effect of Tween‐40 on the corrosion of cold rolled steel (CRS) in 1.0‐8.0 M HCl over the temperature range of 20‐50°C. It also aims to make an attempt to correlate both thermodynamic parameters and kinetic parameters with the inhibition effect.

The inhibition efficiencies of Tween‐40 are investigated by weight loss and potentiodynamic polarization methods.

Tween‐40 acts as a good inhibitor in 1.0 M HCl, and inhibition efficiency increases with the inhibitor concentration, while it decreases with HCl concentration and temperature. The adsorption of inhibitor on the CRS surface obeys the Langmuir adsorption isotherm equation. The inhibition effect is satisfactorily explained by both thermodynamic and kinetic parameters. Polarization curves show that Tween‐40 is a mixed‐type inhibitor in hydrochloric acid.

The experimental data have been treated with adsorption theory and kinetic equations successfully. Both the thermodynamic and kinetic parameters can be obtained, and used in explaining the inhibition effect satisfactorily.

Study on knowledge-based systems for scientific publications is growing very broadly. However, most of these studies do not explicitly discuss the knowledge management (KM) component as knowledge management system (KMS) implementation. This background causes academic institutions to face challenges in developing KMS to support scholarly publication cycle (SPC). Therefore, this study aims to develop a new KMS conceptual model, Identify critical components and provide research gap opportunities for future KM studies on SPC.

This study used a systematic literature review (SLR) method with the procedure from Kitchenham et al. Then, the SLR results are compiled into a conceptual model design based on a framework on KM foundations and KM solutions. Finally, the model design was validated through interviews with related field experts.

The KMS for SPC focuses on the discovery, sharing and application of knowledge. The majority of KMS use recommendation systems technology with content-based filtering and collaborative filtering personalization approaches. The characteristics data used in KMS for SPC are structured and unstructured. Metadata and article abstracts are considered sufficiently representative of the entire article content to be used as a search tool and can provide recommendations. The KMS model for SPC has layers of KM infrastructure, processes, systems, strategies, outputs and outcomes.

This study has limitations in discussing tacit knowledge. In contrast, tacit knowledge for SPC is essential for scientific publication performance. The tacit knowledge includes experience in searching, writing, submitting, publishing and disseminating scientific publications. Tacit knowledge plays a vital role in the development of knowledge sharing system (KSS) and KCS. Therefore, KSS and KCS for SPC are still very challenging to be researched in the future. KMS opportunities that might be developed further are lessons learned databases and interactive forums that capture tacit knowledge about SPC. Future work potential could identify other types of KMS in academia and focus more on SPC.

This study proposes a novel comprehensive KMS model to support scientific publication performance. This model has a critical path as a KMS implementation solution for SPC. This model proposes and recommends appropriate components for SPC requirements (KM processes, technology, methods/techniques and data). This study also proposes novel research gaps as KMS research opportunities for SPC in the future.

Phishing is one of the major threats affecting businesses worldwide in current times. Organizations and customers face the hazards arising out of phishing attacks because of anonymous access to vulnerable details. Such attacks often result in substantial financial losses. Thus, there is a need for effective intrusion detection techniques to identify and possibly nullify the effects of phishing. Classifying phishing and non-phishing web content is a critical task in information security protocols, and full-proof mechanisms have yet to be implemented in practice. The purpose of the current study is to present an ensemble machine learning model for classifying phishing websites.

A publicly available data set comprising 10,068 instances of phishing and legitimate websites was used to build the classifier model. Feature extraction was performed by deploying a group of methods, and relevant features extracted were used for building the model. A twofold ensemble learner was developed by integrating results from random forest (RF) classifier, fed into a feedforward neural network (NN). Performance of the ensemble classifier was validated using k-fold cross-validation. The twofold ensemble learner was implemented as a user-friendly, interactive decision support system for classifying websites as phishing or legitimate ones.

Experimental simulations were performed to access and compare the performance of the ensemble classifiers. The statistical tests estimated that RF_NN model gave superior performance with an accuracy of 93.41 per cent and minimal mean squared error of 0.000026.

The research data set used in this study is publically available and easy to analyze. Comparative analysis with other real-time data sets of recent origin must be performed to ensure generalization of the model against various security breaches. Different variants of phishing threats must be detected rather than focusing particularly toward phishing website detection.

The twofold ensemble model is not applied for classification of phishing websites in any previous studies as per the knowledge of authors.