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Class overlap in imbalanced datasets is the most common challenging situation for researchers in the fields of deep learning (DL) machine learning (ML), and big data (BD) based applications. Class overlap and imbalance data intrinsic characteristics negatively affect the performance of classification models. The data level, algorithm level, ensemble, and hybrid methods are the most commonly used solutions to reduce the biasing of the standard classification model towards the majority class. The data level methods change the distribution of class instances thus, increasing the information loss and overfitting. The algorithm-level methods attempt to modify its structure which gives more weight to the misclassified minority class instances in the learning phases. However, the changes in the algorithm are less compatible for the users. To overcome the issues in these methods, an in-depth discussion on the state-of-the-art methods is required and thus, presented here. In this survey, we presented a detailed discussion of the existing methods to handle class overlap in imbalanced datasets with their advantages, disadvantages, limitations, and key performance metrics in which the method shown outperformed. The detailed comparative analysis mainly of recent years’ papers discussed and summarized the research gaps and future directions for the researchers in ML, DL, and BD-based applications.

Purpose The purpose of this paper is to develop and empirically validate items on social isolation. The comprehensive literature review of existing studies on the measures of social isolation, loneliness and the related construct was conducted. The paper seeks to conceptualize, validate and present items to measure social isolation. Design/methodology/approach The paper is based on theoretical and empirical investigation of the measures of social isolation, loneliness and related constructs such as social others, social loneliness and feeling of sociability. The items were generated through theoretical exploration of previous literature and later modified. The author examined the items through exploratory factor analysis, confirmatory factor analysis and further checked for external criterion validity. Data collected from 128 individuals, in India, were examined to design and validate the scale. Findings The finding of the paper is a ten-item social isolation scale. Using structural equation modeling, we have found extraversion and well-being significantly associated with final items in the present study, confirming the external quality of the scale. Practical implications Organizations may benefit by close examination of the presence of social isolation in employees along with providing support and assistance to employees so as to reduce negative consequences of social isolation and can address the well-being of the employee. Originality/value There is a dearth of developed and validated measures of social isolation in the literature. The study reveals the conceptualization and empirical validation of measures of social isolation in the Indian context so that researchers can move forward to develop theories on social isolation.

Purpose This study aims to quantitatively review previous empirical studies on leadership style and safety culture using meta-analysis and identify the most influential leadership style across organizations. Further, the moderating effect of riskiness in the organizational process on the relationship between leadership style and safety culture was also done. Design/methodology/approach The authors conducted a systematic literature review and applied meta-analysis based on 24 empirical studies to calculate the effect size for the relationships between leadership style and safety culture. Findings A substantial effect size between leadership style and safety culture (r = 0.50). It was interesting to note the significant relationship between leadership and safety culture, irrespective of high- and low-risk organizations. Moreover, empowering leadership style (r = 0.60) emerged as the most influential leadership style across all organizations and in high-risk organizations. Originality/value The meta-analysis established leadership as an essential antecedent of safety culture and suggests implications for future research and practice related to safety and leadership.

Purpose The purpose of this paper is to empirically exhibit the moderating effect of learner interaction (LI) on motivation to learn (MTL), mobile learning (ML) and online learning climate (OLC), so as to bring in enhanced rigour to the virtual knowledge dissemination during the times of crisis. Design/methodology/approach A total of 784 valid responses were considered for the confirmatory factor analysis to test the proposed hypotheses. Findings The study found that MTL and ML contributed to improved OLC and high LI moderated the positive relationship between MTL, ML and OLC. LI also directly contributed to an improved OLC. Practical implications Measures need to be designed to crowbar motivation to ensure heightened interaction of learners, to gear up the ML reach soaring heights achieving a dynamic OLC. Acclimatization of the OLC will be the visionary solution to tackle learning disruption during today’s pandemic times and also many other challenges to come in near-far future. Originality/value The current study established the moderating role of LI in influencing OLC, and also motivating facilitator’s for designing upgraded content, and thereby fuelling the intention to learn.

Purpose The article presents an overview of the Human Resources Information Systems (HRIS) and its relevance in the current organizational context. It broadly captures the advantages of HRIS and the significant challenges involved in its implementation and succeeding stages. Design/methodology/approach A string of research articles in the domain is reviewed for the briefing. Findings HRIS is salient in supplementing various Human Resource (HR) functions ranging from HR planning to performance management. It can act as a catalyst in establishing the significance of HR in strategic decision making. It helps managers to effectively store large amounts of employee data and draw inferences from it to make pro-employee decisions. However, despite being relevant in HR functions, HRIS is often surrounded by concerns like employee privacy breach and misuse of information. Originality/value The article showcases the transformation of the Human Resource function to strengthen its strategic position in the organization and sustain HR professionals. Adoption of HRIS helps to convert HR to a data-driven function.

Multicore processing is advantageous over single core processors in the present highly advanced time critical applications. The tasks in real time applications need to be completed within the prescribed deadlines. Based on this philosophy, the proposed paper discusses the concept of load balancing algorithms in such a way that the work load is equally distributed amongst all cores in the processor. The equal distribution of work load amongst all the cores will result in enhanced utilization and increase in computing speed of application with all the deadlines met. In the heuristic based load balanced algorithm (HBLB), the best task from the set of tasks is selected using the feasibility check window and is assigned to the core. The application of HBLB reduces imbalance among the cores and results in lesser migration leading to low migration overhead. By utilizing all the cores of the multicore system, the computing speed of the application increases tremendously which results in the increase in efficiency of the system. The present paper also discusses the improved version of HBLB, known as Improved_Heuristic Based Load Balancing (Improved_HBLB), which focuses on further reducing the imbalance and the number of backtracks as compared to HBLB algorithm. It was observed that Improved_HBLB gives approximately 10% better results over the HBLB algorithm.

In past decade, wireless sensor networks have gained attention by researchers, manufacturers as well as the users for remotely monitoring tasks and effective data gathering in diverse environment. The wireless sensor nodes are tiny battery powered devices having limited lifetime, hence for longevity and reliability, the foremost concern is minimizing energy consumption and maximizing network lifetime while designing protocols and applications. In this paper, we review the main design issues based on the model of wireless sensor networks: structure-free and structured for data collection and aggregation where role of clustering and routing is discussed for energy conservation and enhancing network lifetime. These design strategies are the foundation of any networking protocol from the energy saving point of view. A comprehensive tabular overview of different approaches under structure-free and structured wireless sensor networks for data collection and aggregation, clustering and routing is presented with key issues.

Now day’s computer network is an essential part of our life. Day by day, there is a high increment in the uses of computer network applications such email, bloggers, internet group, forums, conference, youtube and online TV. The exponential increment in video applications traffic, there increases challenges of computer network and it faces various problems like shortage of memory, link failure, slow processor, time out etc. These problems may lead to network congestion. Multicast is efficient system which handles the video traffic but it also suffers with congestion problem due to design vulnerability. Many researchers are working in this burning issue and they provided various solutions such as source based, receiver based and hybrid one. In this paper, we propose an efficient multicast congestion control approach which suggests the efficient joining, leaving operation based on adaptive throughput. The simulated results show that proposed scheme provides better throughput at various parameters.

Vehicular ad hoc network (VANET) assists in improving road safety, traveller comfort, and intelligent transportation systems to a great extent. Dedicated short-range communications technology is specially designed for VANET to form communication among vehicles and vehicles to infrastructure. The lack of router devices in the flat vehicle-to-vehicle network structure of VANET may raise complicated issues like scalability, resource scarcity, reliability, and hidden terminal problem inside the network. The concept of vehicle clustering is introduced in VANET to improve network performance by handling all such issues. This paper provides an in-depth classification of clustering protocols in VANET based on their design objectives. Two broad categories, generalized and application dependent, are considered to review on clustering protocols in VANET. In generalized clustering protocol, cluster design aims to achieve their primary objective, i.e., the formation of a robust cluster having a long sustainable life, While in application dependent clustering protocols, cluster design aims to improve the performance of specific applications (i.e., target tracking, traffic estimation, misbehaviour detection, privacy preservation, certificate revocation, etc.) on various performance metrics. After this, the paper explores essential research contributions of each category comprehensively. Detailed analysis of existing research contributions is also provided after comparing them on many important metrics. Finally, the merits and demerits of existing protocols are also listed. Our attempt to encourage researchers of the concerned field by providing an extensive analysis of clustering in VANET.

With the rapid growth of social media platforms, digitization of official records, and digital publication of articles, books, magazines, and newspapers, lots of data are generated every day. This data is a foundation of information and contains a vast amount of text that may be complex, ambiguous, redundant, irrelevant, and unstructured. Therefore, we require tools and methods that can help us understand and automatically summarize the vast amount of generated text. There are mainly two types of approaches to perform text summarization: abstractive and extractive. In Abstractive Text Summarization, a concise summary is generated by including the salient features of the input documents and paraphrasing documents using new sentences and phrases. While in Extractive Text Summarization, a summary is produced by selecting and combining the most significant sentences and phrases from the source documents. The researchers have given numerous techniques for both kinds of text summarization. In this work, we classify Extractive Text Summarization approaches and review them based on their characteristics, techniques, and performance. We have discussed the existing Extractive Text Summarization approaches along with their limitations. We also classify and discuss evaluation measures and provide the research challenges faced in Extractive Text Summarization.