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Class imbalance learning, which exists in many domain problem datasets, is an important research topic in data mining and machine learning. One-class classification techniques, which aim to identify anomalies as the minority class from the normal data as the majority class, are one representative solution for class imbalanced datasets. Since one-class classifiers are trained using only normal data to create a decision boundary for later anomaly detection, the quality of the training set, i.e. the majority class, is one key factor that affects the performance of one-class classifiers.

In this paper, we focus on two data cleaning or preprocessing methods to address class imbalanced datasets. The first method examines whether performing instance selection to remove some noisy data from the majority class can improve the performance of one-class classifiers. The second method combines instance selection and missing value imputation, where the latter is used to handle incomplete datasets that contain missing values.

The experimental results are based on 44 class imbalanced datasets; three instance selection algorithms, including IB3, DROP3 and the GA, the CART decision tree for missing value imputation, and three one-class classifiers, which include OCSVM, IFOREST and LOF, show that if the instance selection algorithm is carefully chosen, performing this step could improve the quality of the training data, which makes one-class classifiers outperform the baselines without instance selection. Moreover, when class imbalanced datasets contain some missing values, combining missing value imputation and instance selection, regardless of which step is first performed, can maintain similar data quality as datasets without missing values.

The novelty of this paper is to investigate the effect of performing instance selection on the performance of one-class classifiers, which has never been done before. Moreover, this study is the first attempt to consider the scenario of missing values that exist in the training set for training one-class classifiers. In this case, performing missing value imputation and instance selection with different orders are compared.

Data mining is widely considered necessary in many business applications for effective decision-making. The importance of business data mining is reflected by the existence of numerous surveys in the literature focusing on the investigation of related works using data mining techniques for solving specific business problems. The purpose of this paper is to answer the following question: What are the widely used data mining techniques in business applications?

The aim of this paper is to examine related surveys in the literature and thus to identify the frequently applied data mining techniques. To ensure the recent relevance and quality of the conclusions, the criterion for selecting related studies are that the works be published in reputed journals within the past 10 years.

There are 33 different data mining techniques employed in eight different application areas. Most of them are supervised learning techniques and the application area where such techniques are most often seen is bankruptcy prediction, followed by the areas of customer relationship management, fraud detection, intrusion detection and recommender systems. Furthermore, the widely used ten data mining techniques for business applications are the decision tree (including C4.5 decision tree and classification and regression tree), genetic algorithm, k-nearest neighbor, multilayer perceptron neural network, naïve Bayes and support vector machine as the supervised learning techniques and association rule, expectation maximization and k-means as the unsupervised learning techniques.

The originality of this paper is to survey the recent 10 years of related survey and review articles about data mining in business applications to identify the most popular techniques.

The purpose of this paper is to explore the role of mediation and moderation mechanisms between firm-level effects of transformational leadership (TFL) on unit-level performance across levels.

The authors used surveys to collect data from 800 senior managers at the firm level and 1,377 unit managers from 800 units of 100 firms from semiconductors, optoelectronics, computer electronics, and telecommunications industries. The industries were chosen because these firms focus on expanding their businesses and encourage extensive knowledge sharing among the firms and at all levels within the organizations.

In this study, the authors theorized that firm-level effects of TFL on unit-level performance across levels were positively related to unit-level performance. Unit-level knowledge sharing mediates the positive relationship between firm-level TFL and unit-level performance. A cross-level interaction effect of firm-level TFL and unit-level absorptive capacity showed that a positive unit-level absorptive capacity enhanced firm-level influence of TFL on unit-level knowledge sharing. Unit-level absorptive capacity moderates the positive relationship between unit-level knowledge sharing and unit-level performance.

First, the authors attempt to integrate the leadership and knowledge management research by exploring the critical mediator of unit-level knowledge sharing in explaining the effects of firm-level TFL on employees’ performance at the unit level. This approach is important because it extends the research areas of the two fields, and also clarifies issues regarding how and why TFL at the top of the organization positively impacts the performance of employees at a lower level of the organizational hierarchy. Second, the effectiveness of firm-level TFL depends on the absorptive capacity of each unit. The importance of absorptive capacity and the consequences of leadership behaviors have been emphasized in studies.

The aim of this study was to conduct a systematic literature review (SLR) on vlog marketing. The focus was to analyse the major themes in this field and provide insights for future research directions.

The authors reviewed a total of 49 peer-reviewed publications that include the search terms “vlog” or “video blog” in their titles, keywords and abstracts, retrieved from digital databases Scopus and Web of Science, up to the end of July 2023. Thematic analysis was used to examine and synthesise the articles.

The authors found 19 sub-themes and identified four major themes that emerged from the literature: (1) endorsement outcomes, (2) vlogger characteristics, (3) consumer credibility and (4) vlog content crafting.

There are many unanswered questions in the literature, suggesting that vlog marketing research is still in its infancy, and that in-depth further studies are required for a more comprehensive understanding of the field. This study has identified potential avenues for future research that may contribute to the existing body of knowledge and valuable insights on vlog marketing.

Whilst the impact of motives on sports attendance has received due scholarly attention, one context that appears to have been overlooked is the growing trend towards playing domestic league fixtures in an international setting. The purpose of this paper is to address this oversight by exploring how four different categories of motives distinguished attendees from non-attendees for an Australian Rules football game played in New Zealand.

A stadium-intercept method at a St Kilda home game was used for the purposes of data collection. In total, 2,000 survey invitations had been distributed. Of these, 381 usable online surveys were received. The resulting data were analysed using structural equation modelling.

This study found that the lower fans’ expectations of their team winning, the less likely they were to travel internationally to watch their team play. Furthermore, it also support that sport tourism is influenced not only by the event itself but also non-event attractions offered by the host destination image.

The limitation applies to the research context in which the respondents were selected from one of the two competing teams.

This study confirms the importance of “special occasion” and highlights that an Australian Football League game played in New Zealand on ANZAC Day should continue to serve as a special occasion due to the historical significance of that day.

The results from this study confirm the importance of adding a fourth category of motives – contextual factors – to the existing list of push, pull and sports motives. The findings also support the obvious distinction between attending a domestic event vs attending an international one.

Sustainable urban rail transit requires noise barriers. However, these barriers’ durability varies due to the differing aerodynamic impacts they experience. The purpose of this paper is to investigate the aerodynamic discrepancies of trains when they meet within two types of rectangular noise barriers: fully enclosed (FERNB) and semi-enclosed with vertical plates (SERNBVB). The research also considers the sensitivity of the scale ratio in these scenarios.

A 1:16 scaled moving model test analyzed spatiotemporal patterns and discrepancies in aerodynamic pressures during train meetings. Three-dimensional computational fluid dynamics models, with scale ratios of 1:1, 1:8 and 1:16, used the improved delayed detached eddy simulation turbulence model and slip grid technique. Comparing scale ratios on aerodynamic pressure discrepancies between the two types of noise barriers and revealing the flow field mechanism were done. The goal is to establish the relationship between aerodynamic pressure at scale and in full scale.

The aerodynamic pressure on SERNBVB is influenced by the train’s head and tail waves, whereas for FERNB, it is affected by pressure wave and head-tail waves. Notably, SERNBVB's aerodynamic pressure is more sensitive to changes in scale ratio. As the scale ratio decreases, the aerodynamic pressure on the noise barrier gradually increases.

A train-meeting moving model test is conducted within the noise barrier. Comparison of aerodynamic discrepancies during train meets between two types of rectangular noise barriers and the relationship between the scale and the full scale are established considering the modeling scale ratio.

This study aims to understand the influence of raceway surface topography on the temperature rise characteristics of silicon nitride (Si₃N₄) full ceramic ball bearing and improve its service life.

The arithmetic average height S_a, skewness S_sk and kurtosis S_ku in the three-dimensional surface roughness parameters are used to quantitatively characterize the surface topography of the raceway after superfinishing. The bearing life testing machine is used to test the Si₃N₄ full ceramic ball bearing using polytetrafluoroethylene (PTFE) cage under dry friction conditions, and the self-lubricating full ceramic ball bearing heat generation model is established.

With the decrease of S_a and S_sk on the raceway surface and the increase of S_ku, the average height of the raceway surface decreases, and the peaks and valleys tend to be symmetrically distributed on the average surface, and the surface texture becomes tighter. This kind of raceway surface topography is beneficial to form a thin and uniform filamentous PTFE transfer film with a wide coverage area on the raceway surface based on consuming less cage materials and improving the temperature rise characteristics of hot isostatic pressing silicon nitride full ceramic ball bearings.

The research results provide a theoretical basis for the reasonable selection of Si₃N₄ ring raceway processing technology and have important significance for improving the working characteristics and service life of Si₃N₄ full ceramic ball bearings under dry friction conditions.

This paper aims to introduce a prototype system called SAFQuery (Simple And Flexible Query interface). In many existing Web search interfaces, simple and advanced query processes are treated separately that cannot be issued interchangeably. In addition, after several rounds of queries for specific information need(s), it is possible that users might wish to re-examine the retrieval results corresponding to some previous queries or to slightly modify some of the specific queries issued before. However, it is often hard to remember what queries have been issued. These factors make the current Web search process not very simple or flexible.

In SAFQuery, the simple and advanced query strategies are integrated into a single interface, which can easily formulate query specifications when needed in the same interface. Moreover, query history information is provided that displays the past query specifications, which can help with the memory load.

The authors' experiments by user evaluation show that most users had a positive experience when using SAFQuery. Specifically, it is easy to use and can simplify the Web search task.

The proposed prototype system provides simple and flexible Web search strategies. Particularly, it allows users to easily issue simple and advanced queries based on one single query interface, interchangeably. In addition, users can easily input previously issued queries without spending time to recall what the queries are and/or to re-type previous queries.

The purpose of this study is to investigate the effects of load and rotation speed on dry sliding of silicon nitride, including a series of tribological behaviors (friction coefficient, wear rate, temperature rise, etc.) and wear mechanism. Through the analysis of the above characteristics, the influence law of load and speed on them and the internal relationship between them are determined, and then the best comprehensive performance parameters of silicon nitride full-ceramic spherical plain bearings in dry sliding are predicted, which can provide guidance for the operation condition of silicon nitride full-ceramic spherical plain bearings in dry sliding.

The experimental study of different loads and rotation speeds under dry friction conditions was carried out by the using ball-disk sliding test method.

With the increase of load, the friction coefficient of silicon nitride friction pair and the wear rate of silicon nitride ball decrease continuously. With the increase of rotation speed, the friction coefficient of silicon nitride friction pair first increases and then decreases, and the wear of silicon nitride ball first increases and then decreases. With the increase of load and rotation speed, the wear mechanism eventually changes to adhesive wear.

Because of the low timeliness and inefficiency of bearing experiments, this work adopts a simple ball-disk model to comprehensively explore the influence rules of different conditions, which provides a theoretical basis for the subsequent practical application of silicon nitride full-ceramic spherical plain bearings.

While the Internet has emerged as a retail force to be reckoned with, its’ success is dependent, at least in part, on other promotional tools. One such tool is permission email marketing (PEM). Operating within the framework of the Technology Acceptance Model (TAM), this study explores the influence of PEM on the perceived value derived from Internet shopping.

Data were collected through an online survey in Melbourne, Australia. Utilising a sample of 338 consumers, the resulting data was analysed using structural equation modelling.

The results of the study indicate that PEM positively influences the perceived usefulness, ease of use and enjoyment derived from shopping online. Furthermore, it also serves to reduce the perceived risk. PEM serves as an important extension of the TAM, with the findings from this study highlighting not only what the sources of online shopping value are, but also how they can be influenced.

The limitation applies to the research context in which the study was carried out – fashion shopping.

The study confirms the importance of PEM and highlights to retailers that they have another important tool at their disposal.

This study highlights the importance of PEM and support the proposition that its key source of value lies in providing information that the consumer wants. Such relevance is the key of distinction between PEM and SPAM. Despite the rapid growth of Internet shopping in Australia, very few online shopping studies have been conducted in an Australian context. This study helps to address such an oversight.