ANALIZA RIZIKA OD PADA KROVINE I PREDVIĐANJE OŠTEĆENJA PODRUČJA PRI RUDARENJU UGLJENA POVLAČENJEM ŠIROKOGA ČELA

This study presents a model based on rock engineering systems (RES) to evaluate the risk of roof falls and determine damaged regions, using recorded roof falls, prior to mining with a retreat from a longwall face. In this regard, a case study was considered to examine the model. The results showed that the level of determined risk has an acceptable correlation with the special roof fall (SRF), with R-squared value (R2) equal to 0.792 for all estimated vulnerability indexes (VIs) in considered longwall panels. By investigating and comparing the evaluated values of VI in considered panels and their corresponding recorded roof falls, damaged regions were distinguished from undamaged regions. Based on these investigations, four classes including safe, moderate, danger, and critical regions were determined to identify the safe and damaged regions prior to the mining operation. The results of the research showed that the identification of damaged regions is feasible to provide a detailed operation plan to control roof falls in longwall mining faces through the developed approach. The RES-based model could be used for the same conditions and the presented methodology could be applied to other parts in underground coal mines.U ovome radu prikazan je model utemeljen na sustavima inženjerskih stijena za procjenu rizika od urušavanja (pada) krovine i određivanje oštećenih područja primjenom zabilježenih padova krovine, prije rudarenja metodom širokoga čela. Razmatrana je studija slučaja koja je ispitala model. Rezultati su pokazali da je razina utvrđenoga rizika imala relativno prihvatljivu korelaciju i kompatibilnost s posebnim padom krovine (PPK), s koeficijentom determinacije (R2) jednakim 0,792 za sve procijenjene indekse ranjivosti (IR) u razmatranim područjima rudarenja. Istražujući i uspoređujući procijenjene vrijednosti indeksa ranjivosti na razmatranim područjima i pripadajućim zabilježenim padovima krovine, otkrivena su oštećena područja unutar onih neoštećenih. Na temelju tih istraživanja izvedene su četiri klase: sigurno, umjereno, opasno i kritično područje, radi identificiranja sigurnih, umjereno opasnih i kritičnih područja prije rudarskih operacija. Rezultati istraživanja pokazali su da je identificiranje štetnih područja razvijenim pristupom prikladno za izradu detaljnoga operativnoga plana za kontrolu pada krovine na širokom čelu. Konačno, model temeljen na inženjerskim sustavima stijena može se koristiti i drugdje za iste uvjete, a predstavljena metodologija može se primijeniti i na ostale dijelove podzemnih rudnika ugljena

Polarization Optimization for the Detection of Multiple Persistent Scatterers Using SAR Tomography

The detection of multiple interfering persistent scatterers (PSs) using Synthetic Aperture Radar (SAR) tomography is an efficient tool for generating point clouds of urban areas. In this context, detection methods based upon the polarization information of SAR data are effective at increasing the number of PSs and producing high-density point clouds. This paper presents a comparative study on the effects of the polarization design of a radar antenna on further improving the probability of detecting persistent scatterers. For this purpose, we introduce an extension of the existing scattering property-based generalized likelihood ratio test (GLRT) with realistic dependence on the transmitted/received polarizations. The test is based upon polarization basis optimization by synthesizing all possible polarimetric responses of a given scatterer from its measurements on a linear orthonormal basis. Experiments on both simulated and real data show, by means of objective metrics (probability of detection, false alarm rate, and signal-to-noise ratio), that polarization waveform optimization can provide a significant performance gain in the detection of multiple scatterers compared to the existing full-polarization-based detection method. In particular, the increased density of detected PSs at the studied test sites demonstrates the main contribution of the proposed method

First Demonstration of Space-Borne Polarization Coherence Tomography for Characterizing Hyrcanian Forest Structural Diversity

Structural diversity is recognized as a complementary aspect of biological diversity and plays a fundamental role in forest management, conservation, and restoration. Hence, the assessment of structural diversity has become a major effort in the primary international processes, dealing with biodiversity and sustainable forest management. Because of prohibitive costs associated with the ground measurements of forest structure, despite their high accuracy, space-borne polarization coherence tomography (PCT) can introduce an alternative approach given its ability to provide a vertical reflectivity profile and spatiotemporal resolutions related to detecting forest structural changes. In this study, for the first time ever, the potential of space-borne PCT was evaluated in a broad-leaved Hyrcanian forest of Iran over 308 circular sample plots with an area of 0.1 ha. Two aspects of horizontal structure diversity, including standard deviation of diameter at breast height (σdbh) and the number of trees (N), were predicted as important characteristics in wood production and biomass estimation. In addition, the performance of prediction algorithms, including multiple linear regression (MLR), k-nearest neighbors (k-NN), random forest (RF), and support vector regression (SVR) were compared. We addressed the issue of temporal decorrelation in space-borne PCT utilizing the single-pass TanDEM-X interferometer. The data were acquired in standard DEM mode with single polarization of HH. Consequently, airborne laser scanning (ALS) was used to estimate initial values of height hv and ground phase φ0. The Fourier–Legendre series was used to approximate the relative reflectivity profile of each pixel. To link the relative reflectivity profile averaged within each plot with corresponding ground measurements of σdbh and N, thirteen geometrical and physical parameters were defined (P1−P13). Leave-one-out cross validation (LOOCV) showed a better performance of k-NN than the other algorithms in predicting σdbh and N. It resulted in a relative root mean square error (rRMSE) of 32.80%, mean absolute error (MAE) of 4.69 cm, and R2* of 0.25 for σdbh, whereas only 22% of the variation in N was explained using the PCT algorithm with an rRMSE of 41.56%. This study revealed promising results utilizing TanDEM-X data even though the accuracy is still limited. Hence, an entire assessment of the used framework in characterizing the reflectivity profile and the possible effect of the scale is necessary for future studies

First Demonstration of Space-Borne Polarization Coherence Tomography for Characterizing Hyrcanian Forest Structural Diversity

Structural diversity is recognized as a complementary aspect of biological diversity and plays a fundamental role in forest management, conservation, and restoration. Hence, the assessment of structural diversity has become a major effort in the primary international processes, dealing with biodiversity and sustainable forest management. Because of prohibitive costs associated with the ground measurements of forest structure, despite their high accuracy, space-borne polarization coherence tomography (PCT) can introduce an alternative approach given its ability to provide a vertical reflectivity profile and spatiotemporal resolutions related to detecting forest structural changes. In this study, for the first time ever, the potential of space-borne PCT was evaluated in a broad-leaved Hyrcanian forest of Iran over 308 circular sample plots with an area of 0.1 ha. Two aspects of horizontal structure diversity, including standard deviation of diameter at breast height (σdbh) and the number of trees (N), were predicted as important characteristics in wood production and biomass estimation. In addition, the performance of prediction algorithms, including multiple linear regression (MLR), k-nearest neighbors (k-NN), random forest (RF), and support vector regression (SVR) were compared. We addressed the issue of temporal decorrelation in space-borne PCT utilizing the single-pass TanDEM-X interferometer. The data were acquired in standard DEM mode with single polarization of HH. Consequently, airborne laser scanning (ALS) was used to estimate initial values of height hv and ground phase φ0. The Fourier–Legendre series was used to approximate the relative reflectivity profile of each pixel. To link the relative reflectivity profile averaged within each plot with corresponding ground measurements of σdbh and N, thirteen geometrical and physical parameters were defined (P1−P13). Leave-one-out cross validation (LOOCV) showed a better performance of k-NN than the other algorithms in predicting σdbh and N. It resulted in a relative root mean square error (rRMSE) of 32.80%, mean absolute error (MAE) of 4.69 cm, and R2* of 0.25 for σdbh, whereas only 22% of the variation in N was explained using the PCT algorithm with an rRMSE of 41.56%. This study revealed promising results utilizing TanDEM-X data even though the accuracy is still limited. Hence, an entire assessment of the used framework in characterizing the reflectivity profile and the possible effect of the scale is necessary for future studies

Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990-2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was 1·94 (1·76–2·12). No regions met suggested thresholds for progress. Interpretation: Sub-Saharan Africa had both the highest HIV burden and the greatest progress between 1990 and 2019. The number of incident cases and deaths in males and females approached parity in 2019, although there remained more females with HIV than males with HIV. Globally, the HIV epidemic is far from the UNAIDS benchmarks on progress metrics. Funding: The Bill & Melinda Gates Foundation, the National Institute of Mental Health of the US National Institutes of Health (NIH), and the National Institute on Aging of the NIH

On the Assessment of Non-Local Multi-Looking in Detection of Persistent Scatterers Using SAR Tomography

Synthetic aperture radar (SAR) tomography has shown great potential in multi-dimensional monitoring of urban infrastructures and detection of their possible slow deformations. Along this line, undeniable improvements in SAR tomography (TomoSAR) detection framework of multiple permanent scatterers (PSs) have been observed by the use of a multi-looking operation that is the necessity for data’s covariance matrix estimation. This paper attempts to further analyze the impact of a robust multi-looking operation in TomoSAR PS detection framework and assess the challenging issues that exist in the estimation of the covariance matrix of large stack data obtained from long interferometric time series acquisition. The analyses evaluate the performance of non-local covariance matrix estimation approaches in PS detection framework using the super-resolution multi-looked Generalized Likelihood Ratio Test (GLRT). Experimental results of multi-looking impact assessment are provided using two datasets acquired by COSMO-SkyMED (CSK) and TerraSAR-X (TSX) over Tehran, Iran, and Toulouse, France, respectively. The results highlight that non-local estimation of the sample covariance matrix allows revealing the presence of the scatterers, that may not be detectable using the conventional local-based framewor

The General Aspects of Killing in Iran's Criminal Law: From Legal Changes to Legal-Judicial Challenges

Murder, as one of the major crimes in all legal systems, also faces severe criminal penalties in Iranian criminal law. According to the Islamic Penal Code of Iran, according to Islamic teachings, the provision of retribution for a victim or his progeny, which requires their request and has a private aspect, was designated as the only response to the crime. Given the lack of demand or impossibility of retribution, the legislator responds to public opinion and expects the perpetrator to be punished for disrupting public order and security or for fear of embarrassing the perpetrator or others, as a general punishment. The punishment is gradual and supplemental in various laws. Despite the legislator's efforts to develop the public aspect of all murder cases, there are significant legal and judicial challenges in this area that require coherence in criminal policy and review of regulations. In addition to reviewing legal developments, this article discusses the legal and judicial challenges and proposes a review of criminal policy and regulatory reform

Speckle Reduction in SAR Images

High-resolution synthetic aperture radar (SAR) systems with various imaging modalities, including polarimetric, interferometric, multi-frequency, and multi-temporal information, are widely used in Earth observation and remote sensing. The occurrence of speckle in SAR images, however, affects the performance of all image processing techniques and may thus prevent full exploitation for various applications. Over the past 40 years, speckle reduction methods have been developed in the literature, highlighting the importance of this topic. Despite this extensive knowledge, speckle removal is still an open problem that is far from being fully solved. In this chapter, a comprehensive overview of despeckling methods for single and multi-channel SAR images is given and specifications of the different methods are pointed out. It provides an overview of nonlocal filtering techniques, focusing on the definition of the similarity measures between two noisy patches in an image. Different filtering performance evaluation methods are presented to evaluate denoised images. These methods focus on the use of reference and referenceless metrics, where the former are commonly used to evaluate results on synthetic datasets for which a reference is available, while the latter define denoising indicators that are useful for evaluating denoising performance on real datasets. The chapter further includes several experiments that are conducted with real SAR data, while it discusses the effectiveness of denoising techniques. Finally, upcoming speckle reduction methods based upon machine learning, such as deep learning, are discussed as a new generation of despeckling techniques

Structural displacement monitoring using ground-based synthetic aperture radar

This study develops a ground-based synthetic aperture radar (GBSAR) imaging system and interferometric processing framework for structural health monitoring (SHM). Radar remote sensing for displacement monitoring plays a vital role in SHM. Radar sensors and, more specifically, GBSAR systems have gained more attention in recent studies due to their capability to overcome the limitations of other contact or non-contact SHM sensors. This paper proposes a three-dimensional SAR imaging system and advanced signal processing scheme to extract continuous (fast) displacement components, such as structural vibrations, and discontinuous (slow) displacements, such as subsidence or uplift, using SAR time-series datasets. Using controlled experiments, this study shows that the developed GBSAR can monitor sub-millimeter displacements with high spatial resolution and 0.02 mm precision in the LOS direction. Moreover, several simulations are carried out to evaluate the proposed displacement monitoring algorithms. Accordingly, the proposed continuous monitoring framework can measure fast LOS displacements with better than 0.03 mm precision by reducing the effects of radar movement, clutters, and disturbances. Also, evaluations on a simulated monitoring scene at 20 m from the GBSAR’s LOS show that the proposed discontinuous displacement monitoring algorithm can estimate 3D displacement vectors with sub-millimeter precision. The results show that the developed GBSAR can be used for repeat-pass LOS displacement monitoring and the proposed algorithms demonstrate high potential for measuring continuous sub-second LOS displacements and long-term 3D displacement vectors