An Ant Colony Algorithm for Roads Extraction in High Resolution SAR Images

This paper presents a method for the detection of roads in high resolution Synthetic Aperture Radar (SAR) images using an Ant Colony Algorithm (ACA). Roads in a high resolution SAR image can be modeled as continuously straight line segments of roadsides that possess width. In our method, line segments which represent the candidate positions for roadsides are first extracted from the image using a line segments extractor, and next the roadsides are accurately detected by grouping those line segments. For this purpose, we develop a method based on an ACA. We combine perceptual grouping factors with it and try to reduce its overall computational cost by a region growing method. In this process, a selected initial seed is grown into a finally grouped segment by the iterated ACA process, which considers segments only in a search region. Finally to detect roadsides as smooth curves, we introduce the photometric constraints in ant colony algorithm as external energy in a modified snake model to extract geometric roadsides model. We applied our method to some parts of TerraSAR-x images that have a resolution of about 1 m. The experimental results show that our method can accurately detect roadsides from high resolution SAR images

An approximated Snake Function for Road Extraction from digital images

This paper proposes an optimized mathematical model (Snake-ant) for linear feature extraction from satellite images. The model first uses the Ant Colony Optimization (ACO) to establish a pheromone matrix that represents the pheromone information at each pixel position of the image, according to the movements of a number of ants which are sent to move on the image. Next pheromone matrix is used in the snake model as external energy to extract the linear features like roads edges in image. Snake is a parametric curve which is allowed to deform from some arbitrary initial location toward the desired final location by minimizing an energy function based on the internal and external energy. Our approach is validated by a series of tests on satellite images

Spectral estimation model for linear displacement and vibration monitoring with GBSAR system

In recent years, there has been a growing interest in the development of ground-based Synthetic Aperture Radars (GBSAR) for the purpose of monitoring structural displacements. GBSAR offers high-resolution monitoring over a wide area and can capture data every few minutes. However, compact high-frequency multiple input multiple output (MIMO) radars have emerged as an alternative for monitoring sub-second displacements, such as structural vibrations. MIMO radar has sub-second acquisition interval. However, it has limited cross-range resolution compared to GBSAR, and interference between antennas and presence of multiple scatterers in the scene can cause strong sidelobes in the processed data. On the other hand, GBSAR utilizes a long synthetic aperture to achieve high cross-range resolution. However, due to its longer data acquisition time compared to MIMO radar, conventional methods are insufficient for detecting scatterers’ sub-second displacements that occur during the data acquisition process. This study proposes a method to effectively monitor sub-second or sub-minute displacements using GBSAR signals. The proposed method enhances the conventional radar interferometric processes by employing spectral estimation, allowing for multi-dimensional detection of targets’ azimuth angle, linear displacement, and vibrational characteristics. Consequently, this method improves both the processing of MIMO radar data and enables high-resolution fast displacement monitoring from GBSAR signals. The paper presents the theoretical details and mathematical formulations of the proposed method for both MIMO radar and GBSAR imaging modes. To evaluate the effectiveness of the proposed method, numerical simulations and real experiments are conducted. The experimental results validate the capability of the proposed method in both GBSAR and MIMO configuration modes for high-resolution monitoring of fast linear displacements and vibrations. The results exhibit promising signal-to-noise ratio (SNR) and peak-to-sidelobe ratio (PSLR) values

Micro-vibration monitoring of pipelines using millimetre-wave MIMO radar

To ensure pipelines’ safety it is essential to have a regular and accurate monitoring system to inspect the behaviour of pipelines over time to prevent potential damage. This paper explores the capability of a millimetre-wave multiple-input multiple-output (MIMO) radar system for micro-vibration monitoring of pipelines. Compared to the conventional radars, MIMO radar provides cross-range resolution, while still being capable of monitoring a scene with sub-second data acquisition intervals. This makes it a non-contact system suitable for fast displacement and vibration monitoring. However, the application of MIMO radars has not been fully investigated and analysed for structural monitoring, especially for pipeline vibrations. In this study, a dense time-series of MIMO radar data was collected and processed by proposing a framework based on persistent scatterer interferometry to obtain a map of pipeline vibrations. Experiments were conducted in a controlled environment consisting of both functional and inactive water pipelines. The results showed that the system could detect displacements from micrometre up to sub-millimetre levels, with a displacement error of less than 3 μm. Additionally, the radar could identify the dominant frequencies of 24.375 and 24.500 Hz even in pipelines with very small vibration patterns. These results validate the high potential of millimetre-wave MIMO radar systems for non-contact monitoring of micro-vibrations in pipelines.</p

Enveloping lie algebras of low dimensional leibniz algebras.

We calculate the enveloping Lie algebras of Leibniz algebras of dimensions two and three. We show how these Lie algebras could be used to distinguish non-isomorphic (nilpotent) Leibniz algebras of low dimension in some cases. These results could be used to associate geometric objects (loop spaces) to low dimensional Leibniz algebras

The investigation of the relationship between citizen participation and organizational citizenship behavior in the Gachsaran’s municipality

This study has tried to examine the relationship between two variables as citizen participation and organizational citizenship behavior in the Gachsaran’s municipality. Participation is of urban life’s requirements and it is realized when the burgher has converted from individual life and with a sense of collective responsibility to citizens. In order to meet the needs of urban development and advertence to the posterity’s share, therefore, we should plan the administration of the urban life’s affair on the basis of a systematic pattern of planning with the meaningful, informed and voluntary participation of citizens

Estimation of atmospheric temperature and humidity profiles from MODIS data and radiosond data using artificial neural network

The aim of this study is to test the quality of the neural network for retrieving the temperature and humidity by comparison with the radiosond values and a linear regression method. Remote sensed images give useful information about the atmosphere. In this article, MODIS data is used to retrieve temperature and humidity profiles of the atmosphere. Two methods of linear regression and artificial neural network are used to retrieve the temperature and humidity profiles. A multilayer feed-forward neural network is tested to estimate the desired geophysical profiles. Retrievals are validated by comparison with coincident radiosond profiles

Determining the relationship between annual EPS and stock trading volume based on expectancy theory

To overcome the shortcomings and deficiencies in the efficient market theory, financial literacy needed approaches to be more consistent with the empirical evidences. Therefore, some activities called non-expecting utility theories “non-EU” were proposed and other models were also proposed in order to answer empirical evidences. One of the most important theories is the Expectancy Theory. In descriptive model of expectancy theory, investors maximize their value function. Schifrin and Stedman (1985) have changed the expectancy theory to a wider theoretical framework with investment approach, which is called disposition effect. Disposition effect states that investors sell shares in the position of profit sooner and keep shares in the position of loss for a long time. This study examines the explanation of annual EPS in stock trading volume based on disposition theory in Tehran Stock Exchange. To achieve this goal, two hypotheses were proposed: 1) there is a meaningful relationship between positive surprises of EPS and trading volume, 2) there is no meaningful relationship between negative surprise of EPS and trading volume. The results indicate that the relationship between annual EPS and stock trading volume is based on disposition theory. And according to the results of the research hypotheses, there is disposition effect in Iran

Determining the relationship between annual EPS and stock trading volume based on expectancy theory

To overcome the shortcomings and deficiencies in the efficient market theory, financial literacy needed approaches to be more consistent with the empirical evidences. Therefore, some activities called non-expecting utility theories “non-EU” were proposed and other models were also proposed in order to answer empirical evidences. One of the most important theories is the Expectancy Theory. In descriptive model of expectancy theory, investors maximize their value function. Schifrin and Stedman (1985) have changed the expectancy theory to a wider theoretical framework with investment approach, which is called disposition effect. Disposition effect states that investors sell shares in the position of profit sooner and keep shares in the position of loss for a long time. This study examines the explanation of annual EPS in stock trading volume based on disposition theory in Tehran Stock Exchange. To achieve this goal, two hypotheses were proposed: 1) there is a meaningful relationship between positive surprises of EPS and trading volume, 2) there is no meaningful relationship between negative surprise of EPS and trading volume. The results indicate that the relationship between annual EPS and stock trading volume is based on disposition theory. And according to the results of the research hypotheses, there is disposition effect in Iran