Iranian Angle to Non-Audit Services: Some Empirical Evidence

The purpose of this paper is to show different Iranian accountants’ as well shareholders’ ideas on Non-audit services and their effects on audit independence in Iran. In other words, in this paper the authors have attempted to deal with this question: does providing non-audit services by an Iranian auditor impair audit independence? And in order to gather usable data a suitable questionnaire was designed and developed. The results of this study show that the participants strongly believe that non-audit services may impair audit independence. It is interesting to note that, although the auditors offer to clients non-audit services, they believe that offering such services leads to audit independence being questionable. Further, the result reveals that literate participants moderately agree that NAS has a negative effect on audit independence, however illiterate participants strongly agree that NAS has a negative affect on audit independence. This paper is the first paper which includes two groups of participants: the first group is auditors in general, or we can call them academiciana with pretensions to having auditing literacy and the second group is non- academician, including stakeholders who may not have auditing literacy skills. This may useful for future studies regarding the non-audit service and its effect on audit independence.auditor, independence, non-audit services, Iran

Spatial and spatio-temporal point patterns on linear networks

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsThe last decade witnessed an extraordinary increase in interest in the analysis of network related data and trajectories. This pervasive interest is partly caused by a strongly expanded availability of such datasets. In the spatial statistics field, there are numerous real examples such as the locations of traffic accidents and geo-coded locations of crimes in the streets of cities that need to restrict the support of the underlying process over such linear networks to set and define a more realistic scenario. Examples of trajectories are the path taken by moving objects such as taxis, human beings, animals, etc. Intensity estimation on a network of lines, such as a road network, seems to be a surprisingly complicated task. Several techniques published in the literature, in geography and computer science, have turned out to be erroneous. We propose several adaptive and non-adaptive intensity estimators, based on kernel smoothing and Voronoi tessellation. Theoretical properties such as bias, variance, asymptotics, bandwidth selection, variance estimation, relative risk estimation, and adaptive smoothing are discussed. Moreover, their statistical performance is studied through simulation studies and is compared with existing methods. Adding the temporal component, we also consider spatio-temporal point patterns with spatial locations restricted to a linear network. We present a nonparametric kernel-based intensity estimator and develop second-order characteristics of spatio-temporal point processes on linear networks such as K-function and pair correlation function to analyse the type of interaction between points. In terms of trajectories, we introduce the R package trajectories that contains different classes and methods to handle, summarise and analyse trajectory data. Simulation and model fitting, intensity estimation, distance analysis, movement smoothing, Chi maps and second-order summary statistics are discussed. Moreover, we analyse different real datasets such as a crime data from Chicago (US), anti-social behaviour in Castell´on (Spain), traffic accidents in Medell´ın (Colombia), traffic accidents in Western Australia, motor vehicle traffic accidents in an area of Houston (US), locations of pine saplings in a Finnish forest, traffic accidents in Eastbourne (UK) and one week taxi movements in Beijing (China)

On locally finite dimensional traces

We resolve three open questions on approximation properties of traces on \C-algebras. We answer two questions raised by Nate Brown by showing that locally finite dimensional (LFD) traces form a convex set and that they are automatically uniformly LFD on locally reflexive \C-algebras. We prove that all the traces on the reduced \C-algebra $C^*_r(\Gamma)$ of a discrete amenable ICC group $\Gamma$ are uniformly LFD, and conclude that $C^*_r(\Gamma)$ is strong-NF in the sense of Blackadar-Kirchberg in this case. This partially answers another open question raised by Brown.Comment: 8 pages, comments are welcome

Marked spatial point processes: current state and extensions to point processes on linear networks

Within the applications of spatial point processes, it is increasingly becoming common that events are labeled by marks, prompting an exploration beyond the spatial distribution of events by incorporating the marks in the undertaken analysis. In this paper, we first consider marked spatial point processes in $\R^2$, where marks are either integer-valued, real-valued, or object-valued, and review the state-of-the-art to analyze the spatial structure and type of interaction/correlation between marks. More specifically, we review cross/dot-type summary characteristics, mark-weighted summary characteristics, various mark correlation functions, and frequency domain approaches. Second, we propose novel cross/dot-type higher-order summary characteristics, mark-weighted summary characteristics, and mark correlation functions for marked point processes on linear networks. Through a simulation study, we show that ignoring the underlying network gives rise to erroneous conclusions about the interaction/correlation between marks. Finally, we consider two applications: the locations of two types of butterflies in Melbourne, Australia, and the locations of public trees along the street network of Vancouver, Canada, where trees are labeled by their diameters at breast height.Comment: submitted for publicatio

Bimodal network architectures for automatic generation of image annotation from text

Medical image analysis practitioners have embraced big data methodologies. This has created a need for large annotated datasets. The source of big data is typically large image collections and clinical reports recorded for these images. In many cases, however, building algorithms aimed at segmentation and detection of disease requires a training dataset with markings of the areas of interest on the image that match with the described anomalies. This process of annotation is expensive and needs the involvement of clinicians. In this work we propose two separate deep neural network architectures for automatic marking of a region of interest (ROI) on the image best representing a finding location, given a textual report or a set of keywords. One architecture consists of LSTM and CNN components and is trained end to end with images, matching text, and markings of ROIs for those images. The output layer estimates the coordinates of the vertices of a polygonal region. The second architecture uses a network pre-trained on a large dataset of the same image types for learning feature representations of the findings of interest. We show that for a variety of findings from chest X-ray images, both proposed architectures learn to estimate the ROI, as validated by clinical annotations. There is a clear advantage obtained from the architecture with pre-trained imaging network. The centroids of the ROIs marked by this network were on average at a distance equivalent to 5.1% of the image width from the centroids of the ground truth ROIs.Comment: Accepted to MICCAI 2018, LNCS 1107

A Survey of Perceptions and Expectations of Citizens from Improvement of Villages to City and Its Effect on the Quality of Urban Services

One of the most important factors that citizens are faced after turning a village to a city is the quality of presented services from urban management. The present study aimed to obtain an exact description of the distance between perceptions and expectations of citizens of Fazel Abad of the quality of urban services.  The study is descriptive-survey by field method. Study population is all citizens of Fazel Abad city using urban services and the sample size based on Cochran’s formula is 375 and they were studied by simple random method. The study findings showed that there was a significant difference between perceptions and expectations of citizens to presenting urban services and the highest gap mean (-3.31) of social indices and the lowest gap mean (-1.21) were dedicated to environmental indices

Designing a Novel High Performance Four-to-Two Compressor Cell Based on CNTFET Technology for Low Voltages

Compressor cell is often placed in critical path of multiplier circuits to perform partial product summation. Therefore it plays a significant role in determining the entire performance of multiplier and digital system. Respecting to the necessity of low power design for portable electronic, designing a low power and high performance compressors seems to be a good solution to overcome of these problems for computations. In this paper a novel high performance four-to-two compressor cell is proposed using Carbon Nanotube Field Effect Transistors (CNTFETs) technology. The new cell is based on Majority Function, NOR, and NAND gates. The main advantage of proposed design in comparison with former cells is the ease of obtaining CARRY output by means of Majority function. Simulations have been done with 32nm technology node using Synopsys HSPICE software. Simulation results confirm the priority of the proposed cell compared to other state-of-the-art four-to-two compressor cells