The Effect of Time Pressure, Task Complexity and Litigation Risk on Auditors’ Reliance on Decision Aids

Auditors’ reliance on decision aids has been the subject of much research in the decision-aid literature. Extant literature shows that auditors are somewhat reluctant to rely on decision aids throughout the audit process, despite potential improvement in decision accuracy. The objective of this study is to empirically examine the extent to which auditors’ reliance on decision aids is associated with the perceived levels of time pressure, task complexity and litigation risk—decision aid reliance factors that have been understudied in the auditing literature. In a 2 x 2 x 2 between-subjects experimental design, the independent variables were manipulated as follows: time pressure (high, low), task complexity (high, low) and litigation risk (high, low). The dependent variable reflects the level of reliance on a decision aid. Study results indicate a positive relationship between each of the three factors and decision aid reliance. A three-way interaction was also indicated, suggesting that the joint effect of litigation risk and task complexity depends on the level of perceived time pressure. Study findings hold implications for both practicing auditors and audit researchers, particularly in the increasingly litigious environment in which auditors are immersed

A CNN-LSTM-based Deep Learning Approach for Driver Drowsiness Prediction

Abstract: The development of neural networks and machine learning techniques has recently been the cornerstone for many applications of artificial intelligence. These applications are now found in practically all aspects of our daily life. Predicting drowsiness is one of the most particularly valuable of artificial intelligence for reducing the rate of traffic accidents. According to earlier studies, drowsy driving is at responsible for 25 to 50% of all traffic accidents, which account for 1,200 deaths and 76,000 injuries annually. The goal of this research is to diminish car accidents caused by drowsy drivers. This research tests a number of popular deep learning-based models and presents a novel deep learning-based model for predicting driver drowsiness using a combination of convolutional neural networks (CNN) and Long-Short-Term Memory (LSTM) to achieve results that are superior to those of state-of-the-art methods. Utilizing convolutional layers, CNN has excellent feature extraction abilities, whereas LSTM can learn sequential dependencies. The National Tsing Hua University (NTHU) driver drowsiness dataset is used to test the model and compare it to several other current models as well as state-of-the-art models. The proposed model outperformed state-of-the-art models, with results up to 98.30% for training accuracy and 97.31% for validation accuracy

A CNN-LSTM-based Deep Learning Approach for Driver Drowsiness Prediction

Abstract: The development of neural networks and machine learning techniques has recently been the cornerstone for many applications of artificial intelligence. These applications are now found in practically all aspects of our daily life. Predicting drowsiness is one of the most particularly valuable of artificial intelligence for reducing the rate of traffic accidents. According to earlier studies, drowsy driving is at responsible for 25 to 50% of all traffic accidents, which account for 1,200 deaths and 76,000 injuries annually. The goal of this research is to diminish car accidents caused by drowsy drivers. This research tests a number of popular deep learning-based models and presents a novel deep learning-based model for predicting driver drowsiness using a combination of convolutional neural networks (CNN) and Long-Short-Term Memory (LSTM) to achieve results that are superior to those of state-of-the-art methods. Utilizing convolutional layers, CNN has excellent feature extraction abilities, whereas LSTM can learn sequential dependencies. The National Tsing Hua University (NTHU) driver drowsiness dataset is used to test the model and compare it to several other current models as well as state-of-the-art models. The proposed model outperformed state-of-the-art models, with results up to 98.30% for training accuracy and 97.31% for validation accuracy

Electronic And Paper Document Retention And Auditors’ Responsibilities

The issue of the destruction of documents raises many ethical and legal problems for the auditing profession. Such an issue needs to be examined more closely to explore its ethical and legal implications, and to address the more technical issue of how to retrieve the destroyed electronic documents. The purpose of this research paper is twofold. The first is to examine the auditors’ ethical responsibilities regarding the retention of the electronic and paper documents related to an audit engagement, using the Enron case as a practical case for analysis. The second is to discuss methods of retrieving different types of destroyed electronic documents

Modelling, Analysis and Design of Optimised Electronic Circuits for Visible Light Communication Systems

This thesis explores new circuit design techniques and topologies to extend the bandwidth of visible light communication (VLC) transmitters and receivers, by ameliorating the bandwidth-limiting effects of commonly used optoelectronic devices. The thesis contains detailed literature review of transmitter and receiver designs, which inspired two directions of work. The first proposes new designs of optically lossless light emitting diode (LED) bandwidth extension technique that utilises a negative capacitance circuit to offset the diode’s bandwidth-limiting capacitance. The negative capacitance circuit was studied and verified through newly developed mathematical analysis, modelling and experimental demonstration. The bandwidth advantage of the proposed technique was demonstrated through measurements in conjunction with several colour LEDs, demonstrating up to 500% bandwidth extension with no loss of optical power. The second direction of work enhances the bandwidth of VLC receivers through new designs of ultra-low input impedance transimpedance amplifiers (TIAs), designed to be insensitive to the high photodiode capacitances (Cpd) of large area detectors. Moreover, the thesis proposes a new circuit, which modifies the traditional regulated cascode (RGC) circuit to enhance its bandwidth and gain. The modified RGC amplifier efficiently treats significant RGC inherent bandwidth limitations and is shown, through mathematical analysis, modelling and experimental measurements to extend the bandwidth further by up to 200%. The bandwidth advantage of such receivers was demonstrated in measurements, using several large area photodiodes of area up to 600 mm^2, resulting in a substantial bandwidth improvement of up to 1000%, relative to a standard 50 Ω termination. An inherent limitation of large area photodiodes, associated with internal resistive elements, was identified and ameliorated, through the design of negative resistance circuits. Altogether, this research resulted in a set of design methods and practical circuits, which will hopefully contribute to wider adoption of VLC systems and may be applied in areas beyond VLC

Relative permeability upscaling for heterogeneous reservoir models

Detailed geological models usually contain multi-million grid cells, which makes the running of reservoir simulation difficult and time consuming. Therefore, reducing the number of grid cells, and in turn averaging reservoir properties within them, is desirable in order to make running simulations more feasible. Averaging reservoir properties within the coarse cells is usually referred to as upscaling, which can be achieved using different methods. Many upscaling techniques have been introduced in the literature. However, developing a practical and robust upscaling method has been a research topic for a long time. In this thesis, some of the upscaling methods, their application and limitations are presented. Special attention is given to two phase upscaling methods as they are within the scope of this project. Afterwards, a new two phase upscaling method, called Transmissibility Weighted Relative permeabilities (TWR), is proposed to upscale relative permeability curves in heterogeneous reservoirs. Also, a new method to generate well pseudos is introduced as a means of adjusting well results. The TWR method and the well pseudos were tested using synthetic 2D and 3D water flood models for different conditions in order to check the method’s performance. The results showed that the upscaled relative permeability curves (pseudo functions) succeeded in compensating for sub-grid heterogeneity and numerical dispersion so that the coarse models reproduced the fine models results. In order to make the use of the pseudo functions feasible in practice, a new method to group them, based on curve fitting of Chierici (1984) functional models, was introduced. Calculations of the TWR pseudos and the well pseudos were performed by writing C++ codes to do so. The grouping of the pseudos was accomplished using a non-linear regression solver

Ecofriendly regioselective one-pot synthesis of chromeno[4,3-d][1,2,4]triazolo[4,3-a]pyrimidine derivatives

The reaction between 2-mercapto-3H-chromeno[4,3-d]pyrimidine-4,5-dione (1) or its 2-methylthio derivative (7) with hydrazonoyl halides (2) in dioxane under ultrasound irradiation in the presence of chitosan yielded chromeno[4,3-d][1,2,4]triazolo[4,3-a]pyrimidine derivatives (5a-r). On the other hand, the reaction of compound 1 with the appropriate active chloromethylene compounds (9b, h and m) followed by coupling the products with benzenediazonium chloride afforded the azo coupling products which converted in situ to compound 5. The reaction mechanism was proposed and the structure of the newly synthesized compounds were established on the basis of spectral data (Mass, IR, 1H and 13C NMR) and elemental analyses

The Correlation between the Value of Mortgage-Backed Securities & the Value of FTSE 100 Shares Price Index: September 2013 Prices

Using the latest information and prices for mortgage-backed securities in September 2013 this analytical piece tests the correlation between the value of these instruments and the value of the FTSE 100 share price index.The correlation between the value of mortgage-backed securities and the value of FTSE 100 shares price index