Identifying factors/latent constructs deemed to influence internal audit effectiveness (IAE), through identifying variables used as measures of effectiveness and hypothesising which variables have a statistically significant relationship with IAE was the primary objective. Secondary objectives involved exploring the perceptions and viewpoints of internal auditing and providing general recommendations. To achieve the above objectives, questionnaires were remitted to internal auditors (IA) in various countries, receiving 402 final valid responses. Exploratory factor analysis (EFA) was carried out to identify new latent variables/constructs, with confirmatory factor analysis (CFA) in structural equation modelling (SEM) utilised to confirm these factors. The EFA process identified 7 latent factors, with 5 being confirmed through SEM. These factors, confirmed the positive influence of 8/16 hypotheses with 3/16 having partial confirmation, 4/16 not achieving any statistically significant evidence and 1/16 having negative influence. Risk Management, IA size, competency, management support, External Audit (EA) and Audit Committee (AC) cooperation, follow-up process, and control environment were all deemed to positively influence IA effectiveness. Independence, objectivity, and standard adherence achieved partial confirmation of their positive influence. Audit quality, Big Data, scope limitations and public/private organisations achieved no statistically significant results on their influence, while outsourcing was deemed to negatively influence effectiveness.

We describe the speech activity detection (SAD), speaker diarization (SD), and automatic speech recognition (ASR) experiments conducted by the Behavox team for the Interspeech 2020 Fearless Steps Challenge (FSC-2). A relatively small amount of labeled data, a large variety of speakers and channel distortions, specific lexicon and speaking style resulted in high error rates on the systems which involved this data. In addition to approximately 36 hours of annotated NASA mission recordings, the organizers provided a much larger but unlabeled 19k hour Apollo-11 corpus that we also explore for semi-supervised training of ASR acoustic and language models, observing more than 17% relative word error rate improvement compared to training on the FSC-2 data only. We also compare several SAD and SD systems to approach the most difficult tracks of the challenge (track 1 for diarization and ASR), where long 30-minute audio recordings are provided for evaluation without segmentation or speaker information. For all systems, we report substantial performance improvements compared to the FSC-2 baseline systems, and achieved a first-place ranking for SD and ASR and fourth-place for SAD in the challenge.

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Objective: This study aims to investigate the significance of health insurance in the context of India's growing population, with a particular focus on Uttar Pradesh, the country's most populous state. By examining various factors, such as the cost of health insurance in relation to its perceived benefits, the study seeks to understand the drivers behind health insurance uptake in the state. The importance of health insurance is underscored by the high cost of quality healthcare and the prevalent lack of awareness regarding its benefits. This paper emphasizes the need for health insurance and explores the reasons behind individuals' reluctance to prioritize its benefits over short-term gains. Methods: A mixed-methods approach was employed in this study. Quantitative data was collected to gauge the impact of cost on health insurance adoption and to assess how an individual's income influences their perception of health insurance. Surveys using Google Forms were administered in urban areas to obtain numerical data reflecting the general population's views on the current situation and their willingness to purchase health insurance. The sample comprised 402 respondents from Uttar Pradesh, representing diverse age groups, social backgrounds, and income levels. Data from the National Family Health Survey and the National Sample Survey Office were used as reference points to determine the prevalence of insurance uptake and to evaluate the representativeness of the sample. Results: The findings suggest that the cost factor, specifically the cost of health insurance premiums and the longterm returns they offer, remains the primary determinant of health insurance adoption. Practical Implications: This research underscores the importance of health insurance in the Indian society and identifies the factors influencing individuals' decisions to purchase a policy. Furthermore, the study proposes that making health insurance more affordable and raising awareness among the population could address the issue of low uptake. Consequently, this work aims to heighten awareness of health insurance's importance among Uttar Pradesh residents and recommend that policy makers implement strategies to make it more accessible, thereby influencing public behavior.