O Efeito dos Componentes das Demonstrações Contábeis da Auditoria na Prevenção e Detecção de Fraudes

This is an analysis of the audit factors of the financial statements on prevention and detection of fraud. The present study is a type of applied research and correlation. The samples are 140 expert managers of the audit organization who were selected using the Cochran formula. In the process of gathering information, the researcher carried out a questionnaire that the experts, through the CVI-CVR indicators, approved with a validity equal to 0.87 and 0.99, and approved their reliability equivalent to 0.79, which indicates the convenience of the questionnaire. To analyze the data, the Kolmogorov-Smirnov and Wilk Shapiro tests were applied to analyze the normality of the data, the Pearson coefficient to analyze hypotheses and multiple regression to express the predictive value of the dependent variable using independent variables. All the factors of the financial audit states have a positive effect in the detection and prevention of fraud. In addition, the results of the multiple regression show that among all the factors, the financial transparency factor with a coefficient (0.794) is the most effective factor and the control factor with the coefficient (0.492) is the least important factor,Therefore, the importance of financial transparency, internal control, professional behavior of the audit, planning and supervision reduces the amount of fraud and avoids financial statements.Este es un análisis de los factores de auditoría de los estados financieros sobre prevención y detección de fraude. El presente estudio es un tipo de investigación aplicada y de correlación. Las muestras son 140 gerentes expertos de la organización de auditoría que se seleccionaron mediante la fórmula de Cochran. En el proceso de recopilación de información, el investigador realizó un cuestionario que los expertos por medio de los indicadores CVI-CVR aprobaron con una validez igual a 0.87 y 0.99, y aprobaron su confiabilidad que equivale a 0.79, lo que indica la comodidad del cuestionario. Para analizar los datos, se aplicaron las pruebas de Kolmogorov-Smirnov y Wilk Shapiro para analizar la normalidad de los datos, el coeficiente de Pearson para analizar hipótesis y regresión múltiple para expresar el valor predictivo de la variable dependiente mediante variables independientes. Todos los factores de los estados de auditoría financiera tienen un efecto positivo en la detección y prevención del fraude. Además, los resultados de la regresión múltiple muestran que entre todos los factores, el factor de transparencia financiera con un coeficiente (0.794) es el factor más efectivo y el factor de control con el coeficiente (0.492) es el factor menos importante,Por consiguiente, la importancia de la transparencia financiera, el control interno, el comportamiento profesional de la auditoría, la planificación y la supervisión reduce la cantidad de fraude y evita los estados financieros.Esta é uma análise dos fatores de auditoria das demonstrações financeiras sobre prevenção e detecção de fraude. O presente estudo é um tipo de pesquisa aplicada e correlação. As amostras são 140 gerentes especialistas da organização de auditoria que foram selecionados usando a fórmula Cochran. No processo de recolha de informação, o investigador realizou um questionário que os especialistas através dos indicadores CVI-CVR adoptada com um período de validade igual a 0,87 e 0,99, e aprovado a sua fiabilidade equivalente a 0,79, que indica o conforto do questionário. Para analisar os dados, o teste de Kolmogorov-Smirnov e Shapiro-Wilk foram aplicados para analisar a normalidade dos dados, o coeficiente de Pearson para analisar hipóteses e regressão múltipla para expressar o valor preditivo da variável dependente com variáveis independentes. Todos os fatores dos estados de auditoria financeira têm um efeito positivo na detecção e prevenção de fraudes. Além disso, os resultados do programa de regressão múltipla que entre todos os factores, a transparência financeira fator com um coeficiente (0794) é o coeficiente de fator e factor de controlo mais eficaz (0492) é o factor menos importante,Portanto, a importância da transparência financeira, do controle interno, do comportamento profissional da auditoria, do planejamento e da supervisão reduz a quantidade de fraudes e evita as demonstrações financeiras

A Scenario-Based and Game-Based Geographical Information System (GIS) Approach for Earthquake Disaster Simulation and Crisis Mitigation

The current research study aims to introduce the experience of implementing a serious game using the concept of game-based GIS approach for crisis management during earthquake disasters. In this study, we aimed to develop a game-based GIS approach and examine its efficiency for simulating earthquake rescue management in Tabriz city. In designing this game, typical scenario-based, game-based GIS methods and techniques were employed, and the proposed approach was applied to crisis management. To achieve this goal, we addressed the technical details regarding the development and implementation of the scenario-based and game-based GIS approach. Based on the results, game-based simulations can be considered an efficient approach for disaster simulation and can improve the skills of rescue teams. The outcome of this application is an intellectual game that almost all users at any age can play, and the game can challenge their ability to solve critical issues. The results are critical for explaining the effectiveness of rescue teams and crisis management facilities. As we intended to develop an approach for the simulation of earthquake disasters and emergency responses, we therefore conclude that the results of this study can also be employed to improve the skills of rescue teams and citizens for dealing with crises resulting from earthquake disasters. As a result of this research, the developed tool is published, together with this paper, as an open source and can be employed for any scenario-based analysis in other case studies. By presenting a-state-of-the-art approach, the results of this research study can provide significant contribution to further the development of GIScience and its applications for disaster and risk mitigation and management.Deutsche Forschungsgemein-schaft (DFG, German Research Foundation)Open Access Publication Fund of Humboldt-Universität zu BerlinPeer Reviewe

A GIS-Based Spatiotemporal Impact Assessment of Droughts in the Hyper-Saline Urmia Lake Basin on the Hydro-Geochemical Quality of Nearby Aquifers

Urmia Lake is a hyper-saline lake in northwestern Iran that has been drying up since 2005. The main objective of this study was to evaluate the water quality in aquifers that are the main source of fresh water for the eastern plains Urmia Lake, which has been drying up due to intensive land use/cover changes and climate change. We evaluated hydro-geochemical data and factors contributing to aquifer pollution and quality variation for nine aquifers in the vicinity of Urmia Lake during the dry and wet seasons from 2000–2020. Our methodology was based on the analysis of 10 years of data from 356 deep and semi-deep wells using GIS spatial analysis, multivariate statistical analysis, and agglomerative hierarchical clustering. We developed a Water Quality Index (WQI) for spatiotemporal assessment of the status of the aquifers. In doing so, we highlighted the value of combining Principal Component Analysis (PCA), WQI, and GIS to determine the hydro-geochemical attributes of the aquifers. We found that the groundwater in central parts of the study area was unsuitable for potable supplies. Anthropogenic sources of contamination, such as chemical fertilizers, industrial waste, and untreated sewage water, might be the key factors causing excessive concentrations of contaminants affecting the water quality. The PCA results showed that over 80% of the total variance could be attributed to two principal factors for most aquifers and three principal factors for two of the aquifers. We employed GIS-based spatial analysis to map groundwater quality in the study area. Based on the WQI values, approximately 48% of groundwater samples were identified as poor to unsuitable for drinking purposes. Results of this study provide a better hydro-geochemical understanding of the multiple aquifers that require preventive action against groundwater damage. We conclude that the combined approach of using a multivariate statistical technique and spatial analysis is effective for determining the factors controlling groundwater quality.University of TabrizAlexander von Humboldt FoundationHumboldt-Universität zu BerlinPeer Reviewe

QADI as a New Method and Alternative to Kappa for Accuracy Assessment of Remote Sensing-Based Image Classification

Classification is a very common image processing task. The accuracy of the classified map is typically assessed through a comparison with real-world situations or with available reference data to estimate the reliability of the classification results. Common accuracy assessment approaches are based on an error matrix and provide a measure for the overall accuracy. A frequently used index is the Kappa index. As the Kappa index has increasingly been criticized, various alternative measures have been investigated with minimal success in practice. In this article, we introduce a novel index that overcomes the limitations. Unlike Kappa, it is not sensitive to asymmetric distributions. The quantity and allocation disagreement index (QADI) index computes the degree of disagreement between the classification results and reference maps by counting wrongly labeled pixels as A and quantifying the difference in the pixel count for each class between the classified map and reference data as Q. These values are then used to determine a quantitative QADI index value, which indicates the value of disagreement and difference between a classification result and training data. It can also be used to generate a graph that indicates the degree to which each factor contributes to the disagreement. The efficiency of Kappa and QADI were compared in six use cases. The results indicate that the QADI index generates more reliable classification accuracy assessments than the traditional Kappa can do. We also developed a toolbox in a GIS software environment.University of Tabriz, International and Academic Cooperation DirectionAlexander Von Humboldt FoundationPeer Reviewe

Remote sensing for crop residue cover recognition: A review

Nowadays, using of conservation tillage instead of conventional tillage has been changing attitudes from conventional agriculture to sustainable agriculture. The tillage method affects directly soil and water quality. Actions relative to optimized agricultural management such as conservation tillage methods has adopted at recent years by agronomists and agricultures, due to agricultural and environment advantages. These advantages consist of soil and water quality improving, wind and water erosion prevention, evaporation reduction, soil surface temperature reduction, greenhouse gases reduction, fuel consumption reduction, and etc. In conversation tillage, more than 30% agricultural production residues remain on the ground. For evaluation of residues cover in the fields, information of crop residue obtain from line-transect method. This method has great accuracy, but it is very time consuming and costly for large areas. Remote sensing using satellite information processing can help the researchers to gather the data from the field and the extraction the information. Tillage indices and textural features are two most applicable approach in remote sensing crop residue cover assessment. The aim of this paper was to study of conservation tillage advantages and remote sensing methods to residue cover crop measurement at vast regions through satellite imagery.

Impacts of the Urmia Lake Drought on Soil Salinity and Degradation Risk: An Integrated Geoinformatics Analysis and Monitoring Approach

Recent improvements in earth observation technologies and Geographical Information System (GIS) based spatial analysis methods require us to examine the efficiency of the different data-driven methods and decision rules for soil salinity monitoring and degradation mapping. The main objective of this study was to analyze the environmental impacts of the Lake Urmia drought on soil salinity and degradation risk in the plains surrounding the hyper-saline lake. We monitored the impacts of the lake drought on soil salinity by applying spatiotemporal indices to time-series satellite images (1990–2020) in Google Earth Engine environment. We also computed the soil salinity ratio to validate the results and determine the most efficient soil salinity monitoring techniques. We then mapped the soil degradation risk based on GIS spatial decision-making methods. Our results indicated that the Urmia Lake drought is leading to the formation of extensive salt lands, which impact the fertility of the farmlands. The land affected by soil salinity has increased from 2.86% in 1990 to 16.68% in 2020. The combined spectral response index, with a performance of 0.95, was the most efficient image processing method to assess soil salinity. The soil degradation risk map showed that 38.45% of the study area has a high or very high risk of degradation, which is a significant threat to food production. This study presents an integrated geoinformation approach for time-series soil salinity monitoring and degradation risk mapping that supports future studies by comparing the efficiency of different methods as state of the art. From a practical perspective, the results also provide key information for decision-makers, authorities, and local stakeholders in their efforts to mitigate the environmental impacts of lake drought and sustain the food production to sustain the 7.3 million residents.University of TabrizAlexander von Humboldt Foundatio

Scenario-based analysis of the impacts of lake drying on food production in the Lake Urmia Basin of Northern Iran

In many parts of the world, lake drying is caused by water management failures, while the phenomenon is exacerbated by climate change. Lake Urmia in Northern Iran is drying up at such an alarming rate that it is considered to be a dying lake, which has dire consequences for the whole region. While salinization caused by a dying lake is well understood and known to influence the local and regional food production, other potential impacts by dying lakes are as yet unknown. The food production in the Urmia region is predominantly regional and relies on local water sources. To explore the current and projected impacts of the dying lake on food production, we investigated changes in the climatic conditions, land use, and land degradation for the period 1990–2020. We examined the environmental impacts of lake drought on food production using an integrated scenario-based geoinformation framework. The results show that the lake drought has significantly affected and reduced food production over the past three decades. Based on a combination of cellular automaton and Markov modeling, we project the food production for the next 30 years and predict it will reduce further. The results of this study emphasize the critical environmental impacts of the Urmia Lake drought on food production in the region. We hope that the results will encourage authorities and environmental planners to counteract these issues and take steps to support food production. As our proposed integrated geoinformation approach considers both the extensive impacts of global climate change and the factors associated with dying lakes, we consider it to be suitable to investigate the relationships between environmental degradation and scenario-based food production in other regions with dying lakes around the world

A GIS-Based Spatiotemporal Modelling of Urban Traffic Accidents in Tabriz City during the COVID-19 Pandemic

The main aim of the present study was to investigate the spatiotemporal trends of urban traffic accident hotspots during the COVID-19 pandemic. The severity index was used to determine high-risk areas, and the kernel density estimation method was used to identify risk of traffic accident hotspots. Accident data for the time period of April 2018 to November 2020 were obtained from the traffic police of Tabriz (Iran) and analyzed using GIS spatial and network analysis procedures. To evaluate the impacts of COVID-19, we used the seasonal variation in car accidents to analyze the change in the total number or urban traffic accidents. Eventually, the sustainability of urban transport was analyzed based on the demographic and land use data to identify the areas with a high number of accidents and its respective impacts for the local residences. Based on the results, the lockdown measures in response to the pandemic have led to significant reductions in road traffic accidents. From the perspective of urban planning, the spatiotemporal urban traffic accident analysis indicated that areas with high numbers of elderly people and children were most affected by car accidents. As we identified the hotspots of urban traffic accidents and evaluated their spatiotemporal correlation with land use and demography characteristics, we conclude that the results of this study can be used by urban managers and support decision making to improve the situation, so that fewer accidents will happen in the future.Deutsche Forschungsgemein-schaft (DFG, German Research Foundation)Open Access Publication Fund of Humboldt-Universität zu BerlinAlexander Von Humboldt Foundation via the experienced researcher fellowship of the first author at the Humboldt-Universität zu Berlin, GermanyPeer Reviewe

GIS modeling of firebase of urban gas distribution networks and seismic effects in its intensification (Case study: District 1 of Tabriz Municipality)

Today, about 60% of the world's energy resources are oil and gas. Due to the different methods of transporting crude oil and its products, the largest share of the transfer of these resources is through the transmission pipeline lines. The present study aims to model the GIS model of fire-based urban gas distribution networks and the seismic effects of Tabriz in intensifying fire. For this purpose, multi-criteria decision-making methods (MCDA) with geographic information systems (GIS) were used. Also, to determine the importance of the relationship between criteria and sub-criteria and their relative importance coefficient, the FANP model was used. And 20 sub-criteria were studied to study the vulnerability to gas network fires. To determine the effect of seismicity of Tabriz city on fire in urban gas distribution networks, the seismic hazard zoning map of Tabriz city was compared with the output map of the present study and it was determined that the most vulnerability in both seismic hazard maps and fire zoning map The gas network is in the northern and northwestern part of the area, which is a worn and marginal part of the city. Residential use with 70.63 hectares with the most damage from the fire of urban gas distribution networks due to earthquake intensification is in the first place. Considering the high risk of fire in urban gas networks, in the region, especially the worn-out and marginal structures, it is necessary to organize these structures and carry out protective operations of gas transmission lines in the mentioned issues. Also, according to the results of the research, the complexity and length of gas transmission lines in the suburban fabric of the city are high, so it is recommended to use polyethylene pipes in these areas, which have a high resistance to steel pipes

Importance of vegetation index in codling moth Cydia pomonella distribution modeling

Codling moth, Cydia pomonella L. (Lepidoptera: Tortricidae) is the key insect pest of apple orchards in Iran. This study was conducted in the main apple-growing regions of East Azarbaijan Province to generate potential habitat suitability maps of C. pomonella using MaxEnt modeling and to determine the importance of vegetation index in improving the accuracy of these models. Field surveys for collecting the occurrence data of codling moth were conducted during three growing seasons, 2017 - 2019. The activity of codling moth adult males was monitored using delta-shaped traps baited with female sex pheromone. Fifteen environmental variables were considered as potential predictors for estimating codling moth distribution. These variables were categorized into topographic, climatic, and remote sensing variables. A MaxEnt modeling algorithm was used to predict the distribution of codling moth. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). By using the topographic, climatic, and topographic+climatic variables, the AUC values were 0.840, 0.951, and 0.938, respectively. The model including normalized difference vegetation index (NDVI) had the highest AUC value (0.99), which strongly supports model predictive power and indicates the importance of vegetation index in codling moth distribution modeling. NDVI was the most contributed variable in the model followed by precipitation of September, slope, minimum temperature of May, and mean temperature of April. The distribution map obtained in MaxEnt provides an important tool for identifying potential risk zones of codling moth. This map can assist managers in forecasting and planning control measures and therefore, effective management of current infestations of codling moth