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This paper explores the different insider employee-led cyber frauds (IECF) based on the recent large-scale fraud events of prominent Indian banking institutions. Examining the different types of fraud and appropriate control measures will protect the banking industry from fraudsters. In this study, we identify and classify Cyber Fraud (CF), map the severity of the fraud on a scale of priority, test the mitigation effectiveness, and propose optimal mitigation measures. The identification and classification of CF losses were based on a literature review and focus group discussions with risk and vigilance officers and cyber cell experts. The CF was analyzed using secondary data. We predicted and prioritized CF based on machine learning-derived Random Forest (RF). An efficient fraud mitigation model was developed based on an offender-victim-centric approach. Mitigation is advised both before and after fraud occurs. Through the findings of this research, banks and fraud investigators can prevent CF by detecting it quickly and controlling it on time. This study proposes a structured, sustainable CF mitigation plan that protects banks, employees, regulators, customers, and the economy, thus saving time, resources, and money. Further, these mitigation measures will improve the reputation of the Indian banking industry and ensure its survival. [ABSTRACT FROM AUTHOR]

Project-based learning is among the most common learning approaches aimed at conveying professional standards and best practices to students in programming courses. However, team projects commonly impose problems related to responsibility sharing, such as low effort or inequality in contributions. This paper presents a collaborative programming assessment system featuring a code quality assessment function with specific metrics to measure individual contributions. Student engagement data is used to detect nonconformities in collaboration using a learning analytical approach. Latent profile analysis was used to detect four theoretical team profiles differentiated by team effort (2 levels) and within-team collaboration (2 levels). We demonstrated the efficacy of assessing code to evaluate team dynamics and student behaviour, wherein efforts to resolve coding style failures can be used as a proxy by which to estimate the taskwork awareness of team members. Submission data from 146 students in 41 web-programming projects revealed four behavioural patterns that could potentially hinder the effective functioning of programming teams: free-riding, social loafing, the bystander effect, and lone wolves. We also demonstrated the applicability of automated programming assessment systems to the monitoring of learning progress, thereby facilitating timely interventions to correct difficulties at the team level. [ABSTRACT FROM AUTHOR]

The objective of this paper is to highlight the role that perceived cost, computer self-efficacy and the technology acceptance model (TAM) constructs have in e-training adoption in the Nigerian civil service. With the use of the SmartPLS 2.0 M3 software, a framework that included perceived cost, computer self-efficacy and TAM constructs (perceived usefulness (PU) and perceived ease of use (PEOU)) was tested on 450 heads of departments. Scales on perceived cost, computer self-efficacy, PU and PEOU developed by previous studies were modified accordingly and used. This paper found perceived cost to have a significant effect on e-training adoption. Computer self-efficacy was statistically insignificant through PEOU. In addition, PEOU had an indirect effect through PU. Therefore, only PU of the TAM constructs indicated strong predictive strength in e-training adoption. This paper showed that with e-training adoption, facilities such as computers can be put in place, which can improve the outlook of the civil service. In addition, the cost that is usually associated with traditional training can be reduced, increasing the opportunity to invest in other aspects of the civil service which can help in adding to the overall performance. Relationships were examined in this paper, which were shown to be favourable to e-training adoption in the Nigerian civil service. [ABSTRACT FROM PUBLISHER]

Many critical aspects affect the correct operation of a Brain Computer Interface. The term 'BCIilliteracy' describes the impossibility of using a BCI paradigm. At present, a universal solution does not exist and seeking innovative protocols to drive a BCI is mandatory. This work presents a meta-analytic review on recent advances in emotions recognition with the perspective of using emotions as voluntary, stimulus-independent, commands for BCIs. 60 papers, based on electroencephalography measurements, were selected to evaluate what emotions have been most recognised and what brain regions were activated by them. It was found that happiness, sadness, anger and calm were the most recognised emotions. Relevant discriminant locations for emotions recognition and for the particular case of discrete emotions recognition were identified in the temporal, frontal and parietal areas. The meta-analysis was mainly performed on stimulus-elicited emotions, due to the limited amount of literature about self-induced emotions. The obtained results represent a good starting point for the development of BCI driven by emotions and allow to: (1) ascertain that emotions are measurable and recognisable one from another (2) select a subset of most recognisable emotions and the corresponding active brain regions. [ABSTRACT FROM AUTHOR]

Human computation games (HCGs) utilise human intelligence for the purpose of problem solving through games. Recently, HCGs have increased in popularity within various application areas. A proper system of describing such games is necessary in order to obtain a better understanding of the current body of work and identify new opportunities for future research directions. To date, however, there is little research conducted in understanding how such games could be classified in a systematic manner. Past classification schemes rely either on quality or entertainment aspects of these games. In order to have a deeper understanding of such games, this study argues that they should be classified via different dimensions. As a starting point, this paper reviews existing literature on HCGs and then develops a typology consisting of 12 dimensions and related strategies. This typology provides a holistic view of HCGs, and provides a common understanding of the domain among researchers and designers. The typology will help researchers to better understand the nature and consequences of HCGs, and designers better identify strengths and weaknesses of different strategies for each dimension, thus facilitating the creation of entertaining and effective HCGs. [ABSTRACT FROM PUBLISHER]