Journal articles on the topic 'Reconnaissance fine'
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Song, Yucheng, Shuo Wang, Qing Li, Hongbin Mu, Ruyi Feng, Tian Tian, and Jinwen Tian. "Vehicle Target Detection Method for Wide-Area SAR Images Based on Coarse-Grained Judgment and Fine-Grained Detection." Remote Sensing 15, no. 13 (June 23, 2023): 3242. http://dx.doi.org/10.3390/rs15133242.
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The detection of vehicle targets in wide-area Synthetic Aperture Radar (SAR) images is crucial for real-time reconnaissance tasks and the widespread application of remote sensing technology in military and civilian fields. However, existing detection methods often face difficulties in handling large-scale images and achieving high accuracy. In this study, we address the challenges of detecting vehicle targets in wide-area SAR images and propose a novel method that combines coarse-grained judgment with fine-grained detection to overcome these challenges. Our proposed vehicle detection model is based on YOLOv5, featuring a CAM attention module, CAM-FPN network, and decoupled detection head, and it is strengthened with background-assisted supervision and coarse-grained judgment. These various techniques not only improve the accuracy of the detection algorithms, but also enhance SAR image processing speed. We evaluate the performance of our model using the Wide-area SAR Vehicle Detection (WSVD) dataset. The results demonstrate that the proposed method achieves a high level of accuracy in identifying vehicle targets in wide-area SAR images. Our method effectively addresses the challenges of detecting vehicle targets in wide-area SAR images, and has the potential to significantly enhance real-time reconnaissance tasks and promote the widespread application of remote sensing technology in various fields.
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Estrada-Claudio, Sylvia. "Les Rencontres internationales sur la santé des femmes : continuité et expression d’identités multiples." II Solidarités des militants : des figures du changement, no. 58 (February 6, 2008): 155–62. http://dx.doi.org/10.7202/017558ar.
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Résumé Au fil des années, les Rencontres internationales sur la santé des femmes (International Women and Health Meetings, ou IWHM) sont devenues l’un des principaux moments de rencontre pour les défenseurs de la santé des femmes ainsi que pour les universitaires, institutions financières et autres réseaux intervenant sur la santé et les droits génésiques des femmes. Le présent article soutient que c’est le mode d’organisation qui a permis aux militantes féministes chargées d’organiser les IWHM de s’adapter aux changements politiques survenus au fil du temps, en permettant l’expression et la reconnaissance des diverses identités (nationale, régionale, sexuelle, biologique). L’article retrace la manière dont la reconnaissance de ces identités a permis aux IWHM de survivre et fructifier comme organisation, et de demeurer à la fine pointe du discours sur les droits des femmes, en particulier leurs droits sexuels et génésiques.
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Lees, Brian G., Lu Yanchou, and John Head. "Reconnaissance Thermoluminescence Dating of Northern Australian Coastal Dune Systems." Quaternary Research 34, no. 2 (September 1990): 169–85. http://dx.doi.org/10.1016/0033-5894(90)90029-k.
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AbstractQuaternary lithostratigraphic units in coastal dunes have been dated at three locations in northern Australia, Cobourg Peninsula, Shelburne Bay, and Cape Flattery, by both radiocarbon dating of shell and organic carbon and thermoluminescence (TL) sediment dating. Both coarse fraction and fine fraction TL methods were used. Seventeen TL dates were measured. None of the TL dates contradict the ages given by radiocarbon. Where multiple TL dates were taken from a unit, they overlap within 2 standard deviation giving added confidence in the results. A phase of dune emplacement during the late Holocene (ca. 2700-1800 yr B.P.) was identified in two of the dune-fields, an early Holocene phase of dune emplacement (ca. 8600-7500 yr B.P.) in two of the dune-fields, and a late Pleistocene episode (ca. 24,000–17,000 yr B.P.) in both the Cape York dunefields. Three older units gave dates of about 29,000, 81,000, and 171,000 yr B.P., but these must be treated with caution.
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Bouchard, Nancy. "La reconnaissance de la dignité humaine interprétée à partir d’un modèle d’analyse de l’éducation éthique : un parcours en sept composantes." Éthique en éducation et en formation, no. 3 (January 24, 2018): 122–36. http://dx.doi.org/10.7202/1042940ar.
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Cet article examine les différentes composantes d’un modèle d’éducation éthique sous l’angle de la reconnaissance de la dignité humaine. Ce modèle, qui permet une lecture fine de l’éducation éthique dans un programme, se présente en sept composantes : trois composantes simples Éducation à la société (ES), Formation personnelle (FP) et Éducation à l’autre (EA) et quatre composantes à l’intersection de ces dernières (FP/EA, FP/ES, EA/ES et FP/EA/ES). Il a été développé dans le cadre de travaux menés sur l’éducation dans la francophonie. La recherche qualitative dont est issu ce modèle emprunte une logique inductive ancrée dans le corpus analysés. Au terme de l’examen des composantes de ce modèle, la conclusion est qu’une éducation éthique qui ferait de la dignité humaine un point de repère et une destination appellerait à une forme particulière de la reconnaissance de ladite dignité dans chacune des composantes dudit modèle.
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Chang, Wen-Jong, Sheng-Huoo Ni, An-Bin Huang, Yan-Hong Huang, and Yu-Zhang Yang. "Geotechnical reconnaissance and liquefaction analyses of a liquefaction site with silty fine sand in Southern Taiwan." Engineering Geology 123, no. 3 (November 2011): 235–45. http://dx.doi.org/10.1016/j.enggeo.2011.09.003.
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Zhao, Jiale, Bing Zhou, Guanglong Wang, Jiaju Ying, Jie Liu, and Qi Chen. "Spectral Camouflage Characteristics and Recognition Ability of Targets Based on Visible/Near-Infrared Hyperspectral Images." Photonics 9, no. 12 (December 9, 2022): 957. http://dx.doi.org/10.3390/photonics9120957.
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Hyperspectral imaging can simultaneously obtain the spatial morphological information of the ground objects and the fine spectral information of each pixel. Through the quantitative analysis of the spectral characteristics of objects, it can complete the task of classification and recognition of ground objects. The appearance of imaging spectrum technology provides great advantages for military target detection and promotes the continuous improvement of military reconnaissance levels. At the same time, spectral camouflage materials and methods that are relatively resistant to hyperspectral reconnaissance technology are also developing rapidly. In order to study the reconnaissance effect of visible/near-infrared hyperspectral images on camouflage targets, this paper analyzes the spectral characteristics of different camouflage targets using the hyperspectral images obtained in the visible and near-infrared bands under natural conditions. Two groups of experiments were carried out. The first group of experiments verified the spectral camouflage characteristics and camouflage effects of different types of camouflage clothing with grassland as the background; the second group of experiments verified the spectral camouflage characteristics and camouflage effects of different types of camouflage paint sprayed on boards and steel plates. The experiment shows that the hyperspectral image based on the near-infrared band has a good reconnaissance effect for different camouflage targets, and the near-infrared band is an effective “window” band for detecting and distinguishing true and false targets. However, the stability of the visible/near-infrared band detection for the target identification under camouflage paint is poor, and it is difficult to effectively distinguish the object materials under the same camouflage paint. This research confirms the application ability of detection based on the visible/near-infrared band, and points out the direction for the development of imaging detectors and camouflage materials in the future.
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Vijverberg, Thomas, Michiel Reneerkens, Han Winterwerp, Olaf Scholl, and Y. Haruna. "SEDIMENT DYNAMICS IN LAGOS HARBOUR - RECONNAISSANCE ON EFFECTS OF DREDGING." Coastal Engineering Proceedings 1, no. 33 (October 25, 2012): 75. http://dx.doi.org/10.9753/icce.v33.sediment.75.
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Due to economic growth, Lagos Harbour is expanding. Capital dredging is needed to allow larger vessels to call the port. As harbour siltation is already a problem, increase of maintenance dredging is a worry. In the past no data was available to understand the hydraulics and sediment transport to estimate maintenance dredging volumes. This paper presents the reconnaissance of the sediment dynamics in the harbour, based on field data and MIKE21 model simulations. Measurements of sediment concentration, salinity and flow velocity show that estuarine circulation occurs, transporting sediment from the ocean into the port. However, more upstream in the Commodore channel, at the location where dredging will be carried out, this circulation is small. Model simulations show that at that location, bed shear stresses are large, also after dredging. Therefore, fine sediment can not accumulate in the deepened areas and this will not result in large dredging volumes. Sand transport however can cause sedimentation, as bed forms can migrate. These mechanisms are also observed in initial sand transport simulations, but need to be studied further to fully understand the sediment dynamics in the harbour.
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Njau, Jackson K., and Leslea J. Hlusko. "Fine-tuning paleoanthropological reconnaissance with high-resolution satellite imagery: the discovery of 28 new sites in Tanzania." Journal of Human Evolution 59, no. 6 (December 2010): 680–84. http://dx.doi.org/10.1016/j.jhevol.2010.07.014.
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Bae, Gimin, and Janghyong Lee. "Explainable artificial intelligence models for enhancing classification reliability of ground weapon systems." Journal of Advances in Military Studies 6, no. 3 (December 28, 2023): 83–104. http://dx.doi.org/10.37944/jams.v6i3.216.
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This study focused on the development of a reliable artificial intelligence (AI) model to enhance the classification reliability of ground weapon systems for surveillance and reconnaissance applications. The proposed AI model overcomes the limited data availability of military objects such as tanks, canons, and multiple-launch rockets by leveraging transfer learning and fine-tuning techniques. A comprehensive evaluation of 35 deep learning models using the publicly available Military-Vehicles dataset on Kaggle identified MobileNet as the most suitable model for ground weapon system classification. The selected MobileNet model achieved an average F1 score of 92% when tested on a dataset comprising five types of ground-weapon systems. In addition, the application of the explainable AI technique Grad-CAM provided insights into the decision-making process of the proposed model and verified its reliability. Real-world evaluations using frames extracted from training videos demonstrated promising accuracy for tanks, canons, and multiple-launch rockets. However, challenges related to object occlusion and the absence of target objects in the images were observed, which resulted in misclassifications. Overall, this study contributes to the development of explainable and reliable AI models for enhancing the performance of ground surveillance and reconnaissance systems.
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Ranganai, Rubeni Tawanda, Moikwathai Moidaki, and James G. King. "Magnetic Susceptibility of Soils from Eastern Botswana: A Reconnaissance Survey and Potential Applications." Journal of Geography and Geology 7, no. 4 (December 2, 2015): 45. http://dx.doi.org/10.5539/jgg.v7n4p45.
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<p class="zhengwen">Soil magnetic properties measurements are relatively fast and inexpensive but have been proved to be sufficient for preliminary investigations in diverse socio-developmental issues. This paper presents results of a reconnaissance study of soil colour and magnetic susceptibility (c) in eastern Botswana, where ~80% of the population resides. The work is a first step to creating a database of rock and soil magnetic properties and to document spatial variations in magnetic properties in the country. These measurements are important as constraints for interpretation of available aeromagnetic data and can also be exploited for environmental soil research (pollution) and land-use planning (agriculture). The soils sampled include derivatives of varying types and provenance such as Archean gneissic granitoids, metamorphosed rocks (granulites), volcano-sedimentary assemblages, Karoo basalts, and alluvial sediments. A soil colour chart was used since soil colours and magnetic properties are diagnostic of its parent rock sources and weathering profiles. Soil magnetic susceptibilities were measured at both low frequency (0.46 MHz, clf) and high frequency (4.6 MHz, chf), thus allowing calculation of frequency-dependent susceptibility (cfd, cfd%) for detecting ultra-fine ferromagnetic minerals.</p>It was found that soils with Hues ranging from 7.5YR to 10YR have appreciable amount of magnetic materials and soils with Hues of 2.5YR are generally nonmagnetic. The results of soil magnetic susceptibility profiles show spatial variation closely related to the variation in basement rocks, which provides excellent evidence that the magnetic susceptibility variation reflects basement rocks or bedrock composition (soil parent material). In relation to the Botswana physiographic units, soils from the hardveld (Precambrian) show the highest susceptibilities, followed by those from the sandveld, with the lowest values being from the alluvial. The frequency dependent magnetic susceptibilities indicate the presence of ultra-fine super-paramagnetic minerals such as magnetite/maghemite. It is suggested that a systematic and continuous programme of rock and soil magnetic measurements would benefit various socio-economic and development priority sectors of Botswana. This also applies to many developing countries in Africa where soil physics and measurement of soil susceptibility in particular, is generally still at an embryonic stage.
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Ernst, W. G., and Katsushi Shirahata. "Reconnaissance Feasibility Study of Heavy-Mineral Suites in the Fine-Grained Matrix of Several Lithostratigraphic Terranes, Southern New Zealand." International Geology Review 38, no. 12 (December 1996): 1086–97. http://dx.doi.org/10.1080/00206819709465384.
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Pan, Chaofan, Runsheng Li, Qing Hu, Chaoyang Niu, Wei Liu, and Wanjie Lu. "Contrastive Learning Network Based on Causal Attention for Fine-Grained Ship Classification in Remote Sensing Scenarios." Remote Sensing 15, no. 13 (July 3, 2023): 3393. http://dx.doi.org/10.3390/rs15133393.
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Fine-grained classification of ship targets is an important task in remote sensing, having numerous applications in military reconnaissance and sea surveillance. Due to the influence of various imaging factors, ship targets in remote sensing images have considerable inter-class similarity and intra-class difference, which brings significant challenges to fine-grained classification. In response, we developed a contrastive learning network based on causal attention (C2Net) to improve the model’s fine-grained identification ability from local details. The asynchronous feature learning mode of “decoupling + aggregation” is adopted to reduce the mutual influence between local features and improve the quality of local features. In the decoupling stage, the feature vectors of each part of the ship targets are de-correlated using a decoupling function to prevent feature adhesion. Considering the possibility of false associations between results and features, the decoupled part is designed based on the counterfactual causal attention network to enhance the model’s predictive logic. In the aggregation stage, the local attention weight learned in the decoupling stage is used to carry out feature fusion on the trunk feature weight. Then, the proposed feature re-association module is used to re-associate and integrate the target local information contained in the fusion feature to obtain the target feature vector. Finally, the aggregation function is used to complete the clustering process of the target feature vectors and fine-grained classification is realized. Using two large-scale datasets, the experimental results show that the proposed C2Net method had better fine-grained classification than other methods.
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Guo, Linqing, Mingyang Du, Jingwei Xiong, Zilong Wu, and Jifei Pan. "Self-Supervised Representation Learning for Quasi-Simultaneous Arrival Signal Identification Based on Reconnaissance Drones." Drones 7, no. 7 (July 19, 2023): 475. http://dx.doi.org/10.3390/drones7070475.
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Reconnaissance unmanned aerial vehicles are specifically designed to estimate parameters and process intercepted signals for the purpose of identifying and locating radars. However, distinguishing quasi-simultaneous arrival signals (QSAS) has become increasingly challenging in complex electromagnetic environments. In order to address the problem, a framework for self-supervised deep representation learning is proposed. The framework consists of two phases: (1) pre-train an autoencoder. For learning the unlabeled QSAS representation, the ConvNeXt V2 is trained to extract features from masked time–frequency images and reconstruct the corresponding signal in both time and frequency domains; (2) transfer the learned knowledge. For downstream tasks, encoder layers are frozen, the linear layer is fine-tuned to classify QSAS under few-shot conditions. Experimental results demonstrate that the proposed algorithm can achieve an average recognition accuracy of over 81% with the signal-to-noise ratio in the range of −16∼16 dB. Compared to existing CNN-based and Transformer-based neural networks, the proposed algorithm shortens the time of testing by about 11× and improves accuracy by up to 21.95%.
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Ogunjinmi, Peter Damilola, Sung-Sik Park, Bubryur Kim, and Dong-Eun Lee. "Rapid Post-Earthquake Structural Damage Assessment Using Convolutional Neural Networks and Transfer Learning." Sensors 22, no. 9 (May 3, 2022): 3471. http://dx.doi.org/10.3390/s22093471.
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The adoption of artificial intelligence in post-earthquake inspections and reconnaissance has received considerable attention in recent years, owing to its exponential increase in computation capabilities and inherent potential in addressing disadvantages associated with manual inspections. Herein, we present the effectiveness of automated deep learning in enhancing the assessment of damage caused by the 2017 Pohang earthquake. Six classical pre-trained convolutional neural network (CNN) models are implemented through transfer learning (TL) on a small dataset, comprising 1780 manually labeled images of structural damage. Feature extraction and fine-tuning TL methods are trained on the image datasets. The performances of various CNN models are compared on a testing image dataset. Results confirm that the MobileNet fine-tuned model offers the best performance. Therefore, the model is further developed as a web-based application for classifying earthquake damage. The severity of damage is quantified by assigning damage assessment values, derived using the CNN model and gradient-weighted class activation mapping. The web-based application can effectively and automatically classify structural damage resulting from earthquakes, rendering it suitable for decision making, such as in resource allocation, policy development, and emergency response.
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Roche, Elise. "Ethnicisation ordinaire et relogement de bidonvilles : construire et gérer un « village d’insertion rom » en banlieue parisienne." Espaces et sociétés 190, no. 3 (February 13, 2024): 21–40. http://dx.doi.org/10.3917/esp.190.0021.
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Cet article aborde comment l’usage de la catégorie Rom pour désigner les habitants d’un bidonville constitue un élément de décision de le résorber. En quoi cette catégorie est-elle constitutive des modalités de relogement ? Partant de ces questions, l’analyse se fonde en particulier sur l’étude d’un cas de résorption de bidonville en région parisienne, à Saint-Denis (93), dans les années 2010. En s’inspirant des travaux de Nancy Fraser relatifs aux théories de la justice (justice redistributive et justice par reconnaissance), cette étude établit la façon dont le projet initial d’une municipalité visant à offrir des logements dignes à des habitants de bidonvilles conduit in fine à produire des habitations spécifiques. Elle entend ainsi contribuer à montrer comment le traitement ethnicisant des bidonvilles, hier comme aujourd’hui, aboutit à produire des logements spécifiques et à routiniser des politiques discriminatoires.
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Raina, A. "Morphology, mineralogy and classification of soils developed on different parent material in Mussoorie forest division, Uttarakhand, India." Indian Journal of Forestry 31, no. 4 (December 1, 2008): 533–40. http://dx.doi.org/10.54207/bsmps1000-2008-uvrw8c.
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Based on reconnaissance soil survey of Kempty Range of Mussoorie Forest Division, Uttarakhand, five soil profiles in different blocks were selected for determining their morphological, physicochemical and mineralogical characteristics. The morphological characteristics show considerable variation in the nature and degree of horizon development. Light and heavy mineral fractions constituted 70 and 30 per cent of total fine sand fractions respectively. Various minerals identified in the light sand fractions included quartz, feldspars and mica (muscovite). In all the pedons studied quartz was the dominating mineral. Heavy mineral fractions comprised opaque minerals, biotite the presence of low to moderate amount of weatherable minerals suggesting their podsolic nature. Clay fractions were characterized by micas and illite as the dominant clay mineral associated with appreciable amount of kaolinite and chlorite and the small amount of mixed layer silicate mineral, vermiculite, montimorillonite and quartz. Soils of the study area belonged to Typic Paleudoll (Kempty Block), Typic Argiudoll (Sainj Block), Typic Paleudult (Mailgarh Block), Typic Hapludult (Kheragarh Block) and Typic Argiudoll (Gandiyala Block). All these polypedons are members of fine loamy, mixed, messic family. These soils developed from different parent materials are in equilibrium with geogenic factors. Mollisols occur on limestone, dolomite, quartzite and slate whereas Ultisols occur on phyllite, shale, sandstone, quartzite, etc.
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Kaplan, H. H., D. E. Stillman, R. Hoover, T. Michaels, L. Fenton, and K. M. Primm. "Visible and Near-infrared Spectral Properties of Martian Slope Streaks." Planetary Science Journal 4, no. 12 (December 1, 2023): 232. http://dx.doi.org/10.3847/psj/ad037e.
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Abstract Martian slope streaks are large surface features with lower albedo than their surroundings that are one of the few active geologic processes occurring on Mars today. We investigated the slope streaks’ spectral properties using images from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) at nine sites, including three sites with observations over multiple years to enable time-series analysis. For each individual slope streak within each image, we determined the average spectra of each streak and of the slope immediately adjacent to account for changes in geology across a CRISM image or within slopes containing streaks. We find a trend where the visible spectral continuum (0.4–0.6 μm) is strongly negative for the darkest slope streaks, and the spectral continuum increases as the slope streaks fade, consistent across all sites and over multiple observations of the same site. We do not find absorption at 1.4 or 1.9 μm associated with hydration. In some slope streaks, we see evidence of Fe-bearing minerals, but these signatures are also found in the streak-free slope directly adjacent, suggesting that the streaks have a similar mineralogy to their surroundings. The spectral changes that we see are most consistent with changes in the fine dust component and support a dry flow mechanism whereby slope streaks are formed by processes that trigger dust removal from the slope in particular locations, with the streaks slowly fading as dust resettles on the surface.
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Mlayah, Ammar, Eduardo Anselmo Ferreira Da Silva, Nouri Hatira, Salah Jellali, Fethi Lachaal, Abdelkrim Charef, Fernando Noronha, and Chedly Ben Hamza. "Bassin d'oued Serrat : terrils et rejets domestiques, reconnaissance des métaux lourds et polluants, impact sur les eaux souterraines (nord-ouest de la Tunisie)." Revue des sciences de l’eau 24, no. 2 (October 4, 2011): 159–75. http://dx.doi.org/10.7202/1006109ar.
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Le présent travail visait à déterminer l'impact de rejets de deux mines de fer et de phosphates sur la qualité physicochimique de l'eau d'un système aquifère alluvial (nord-ouest de la Tunisie). Des échantillons de terrils, de sols ainsi que de l'eau de puits captant la nappe ont été prélevés et analysés. Les résultats d'analyses des échantillons de terrils ont montré que cette matrice renferme des concentrations remarquables en métaux lourds (essentiellement le Cd, Cr, Pb et Zn). Ces éléments métalliques ont été également détectés à des concentrations non négligeables dans la fraction fine des sols situés en aval des rejets miniers, suite à son transport éolien et hydrique. En ce qui concerne les eaux de la nappe, il s'avère que le transport des métaux issus des terrils est totalement atténué par les éléments constituant le sous-sol. Ces eaux, de bonne qualité géochimique, sont toutefois assez contaminées en nitrates dû aux pratiques agricoles intenses et à l'absence de systèmes d'assainissement urbains.
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Debruille, Jacques B., and Emmanuel Stip. "Syndrome de Capgras: Perspectives ouvertes par la neuropsychologie cognitive." Canadian Journal of Psychiatry 41, no. 4 (May 1996): 245–50. http://dx.doi.org/10.1177/070674379604100410.
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Objectif: Examiner la façon dont certaines idées, émises quant à la Physiopathologie du syndrome de Capgras (1), ont été mises à l'épreuve par des tests neuropsychologiques. Méthodes: Les données consistent en une trentaine d'études sélectionnées pour leur pertinence quant aux étapes cérébrales du traitement des visages chez les patients schizophrènes, les patients atteints du syndrome de Capgras, et les sujets normaux. Résultats: L'étude de ces travaux montre: a) qu'en ce qui concerne les patients, les auteurs se sont focalisés sur l'étape de traitement correspondant à la reconnaissance des visages per se; b) mais que l'on peut également étudier l'étape correspondant aux connaissances et croyances relatives aux personnes et évaluer l'existence du clivage proposé par de nombreux psychodynamiciens. Conclusions: Les vues provenant du champ de la neuropsychologie, comme du champ psychodynamique peuvent donc être mises à l'épreuve. En offrant le moyen d'élaborer des prédictions testables dans des protocoles expérimentaux, les méthodes de la neuropsychologie cognitive permettront, in fine, le rejet des idées erronées et la démonstration des idées justes. Nous militons pour que les méthodes soient appliquées au syndrome de Capgras comme à chacun des symptômes de schizophrénie.
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Hao, Shuai, Beiyi An, Hu Wen, Xu Ma, and Keping Yu. "A Heterogeneous Image Fusion Method Based on DCT and Anisotropic Diffusion for UAVs in Future 5G IoT Scenarios." Wireless Communications and Mobile Computing 2020 (June 27, 2020): 1–11. http://dx.doi.org/10.1155/2020/8816818.
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Unmanned aerial vehicles, with their inherent fine attributes, such as flexibility, mobility, and autonomy, play an increasingly important role in the Internet of Things (IoT). Airborne infrared and visible image fusion, which constitutes an important data basis for the perception layer of IoT, has been widely used in various fields such as electric power inspection, military reconnaissance, emergency rescue, and traffic management. However, traditional infrared and visible image fusion methods suffer from weak detail resolution. In order to better preserve useful information from source images and produce a more informative image for human observation or unmanned aerial vehicle vision tasks, a novel fusion method based on discrete cosine transform (DCT) and anisotropic diffusion is proposed. First, the infrared and visible images are denoised by using DCT. Second, anisotropic diffusion is applied to the denoised infrared and visible images to obtain the detail and base layers. Third, the base layers are fused by using weighted averaging, and the detail layers are fused by using the Karhunen–Loeve transform, respectively. Finally, the fused image is reconstructed through the linear superposition of the base layer and detail layer. Compared with six other typical fusion methods, the proposed approach shows better fusion performance in both objective and subjective evaluations.
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Murton, Julian B., Mary E. Edwards, Anatoly V. Lozhkin, Patricia M. Anderson, Grigoriy N. Savvinov, Nadezhda Bakulina, Olesya V. Bondarenko, et al. "Preliminary paleoenvironmental analysis of permafrost deposits at Batagaika megaslump, Yana Uplands, northeast Siberia." Quaternary Research 87, no. 2 (February 16, 2017): 314–30. http://dx.doi.org/10.1017/qua.2016.15.
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AbstractA megaslump at Batagaika, in northern Yakutia, exposes a remarkable stratigraphic sequence of permafrost deposits ~50–80 m thick. To determine their potential for answering key questions about Quaternary environmental and climatic change in northeast Siberia, we carried out a reconnaissance study of their cryostratigraphy and paleoecology, supported by four rangefinder 14C ages. The sequence includes two ice complexes separated by a unit of fine sand containing narrow syngenetic ice wedges and multiple paleosols. Overall, the sequence developed as permafrost grew syngenetically through an eolian sand sheet aggrading on a hillslope. Wood remains occur in two forest beds, each associated with a reddened weathering horizon. The lower bed contains high amounts of Larix pollen (>20%), plus small amounts of Picea and Pinus pumila, and is attributed to interglacial conditions. Pollen from the overlying sequence is dominated by herbaceous taxa (~70%–80%) attributed to an open tundra landscape during interstadial climatic conditions. Of three hypothetical age schemes considered, we tentatively attribute much of the Batagaika sequence to Marine Oxygen Isotope Stage (MIS) 3. The upper and lower forest beds may represent a mid–MIS 3 optimum and MIS 5, respectively, although we cannot discount alternative attributions to MIS 5 and 7.
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Tao, Yu, Jan-Peter Muller, Siting Xiong, and Susan J. Conway. "MADNet 2.0: Pixel-Scale Topography Retrieval from Single-View Orbital Imagery of Mars Using Deep Learning." Remote Sensing 13, no. 21 (October 21, 2021): 4220. http://dx.doi.org/10.3390/rs13214220.
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The High-Resolution Imaging Science Experiment (HiRISE) onboard the Mars Reconnaissance Orbiter provides remotely sensed imagery at the highest spatial resolution at 25–50 cm/pixel of the surface of Mars. However, due to the spatial resolution being so high, the total area covered by HiRISE targeted stereo acquisitions is very limited. This results in a lack of the availability of high-resolution digital terrain models (DTMs) which are better than 1 m/pixel. Such high-resolution DTMs have always been considered desirable for the international community of planetary scientists to carry out fine-scale geological analysis of the Martian surface. Recently, new deep learning-based techniques that are able to retrieve DTMs from single optical orbital imagery have been developed and applied to single HiRISE observational data. In this paper, we improve upon a previously developed single-image DTM estimation system called MADNet (1.0). We propose optimisations which we collectively call MADNet 2.0, which is based on a supervised image-to-height estimation network, multi-scale DTM reconstruction, and 3D co-alignment processes. In particular, we employ optimised single-scale inference and multi-scale reconstruction (in MADNet 2.0), instead of multi-scale inference and single-scale reconstruction (in MADNet 1.0), to produce more accurate large-scale topographic retrieval with boosted fine-scale resolution. We demonstrate the improvements of the MADNet 2.0 DTMs produced using HiRISE images, in comparison to the MADNet 1.0 DTMs and the published Planetary Data System (PDS) DTMs over the ExoMars Rosalind Franklin rover’s landing site at Oxia Planum. Qualitative and quantitative assessments suggest the proposed MADNet 2.0 system is capable of producing pixel-scale DTM retrieval at the same spatial resolution (25 cm/pixel) of the input HiRISE images.
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BASTIANELLI, Denis, Laurent BONNAL, Philippe BARRE, Serge NABENEZA, Paulo SALGADO, and Donato ANDUEZA. "La spectrométrie dans le proche infrarouge pour la caractérisation des ressources alimentaires." INRA Productions Animales 31, no. 3 (January 18, 2019): 237–54. http://dx.doi.org/10.20870/productions-animales.2018.31.2.2330.
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Le pilotage des systèmes d’élevage en vue d’une optimisation technique, économique et environnementale passe par une formulation des rations de plus en plus précise et nécessite donc une connaissance fine des aliments consommés par les animaux. La spectrométrie dans le proche infrarouge (SPIR), utilisée de façon croissante depuis les années 60, est une technique analytique permettant de caractériser rapidement des échantillons d’aliments ou de fourrages. Les premières applications concernaient la composition chimique des fourrages, mais il est également possible de développer des étalonnages pour une estimation de la valeur nutritive et de l’ingestion. Au-delà de ces mesures directes sur l’aliment, la SPIR peut être appliquée sur les fèces afin de caractériser l’alimentation d’animaux sur parcours. Le traitement conjoint des spectres des aliments et des fèces peut donner une vision de l’utilisation réellement faite des aliments par les animaux. D’autres utilisations possibles de la SPIR comme la traçabilité ou la classification des aliments ainsi que la reconnaissance botanique des végétaux dans les prairies sont aussi décrites. Les développements techniques actuels, et notamment la miniaturisation des spectromètres, permettent d’amener les instruments sur le terrain pour produire l’information au plus près de son utilisation. D’autres techniques spectroscopiques alternatives ou complémentaires à la SPIR comme la spectroscopie dans le moyen infrarouge, la spectroscopie Raman ou l’imagerie hyperspectrale permettront d’autres conditions de mesures et d’autres applications.
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Ayerbe, Cécile. "Innovations technologique et organisationnelle au sein de PME innovantes : complémentarité des processus, analyse comparative des mécanismes de diffusion." Revue internationale P.M.E. 19, no. 1 (February 16, 2012): 9–34. http://dx.doi.org/10.7202/1008488ar.
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Les entreprises développant des produits ou procédés nouveaux sont également reconnues comme innovantes en matière d’organisation. La reconnaissance de l’innovation organisationnelle constitue une avancée significative pour l’analyse des processus d’innovation et permet de dépasser l’approche fragmentaire, centrée exclusivement sur la technologie, qui a longtemps dominé. Elle introduit toutefois un certain nombre d’interrogations. Parmi ces questionnements, la complémentarité entre les innovations technologique et organisationnelle ainsi que l’étude comparative des mécanismes de diffusion de ces innovations apparaissent encore peu explorées. Nous nous sommes donc intéressée à ces deux volets afin de rendre compte de la complexité de la dynamique d’innovation dans son ensemble. Plus précisément, notre article se propose de répondre aux questions suivantes : Pour cela, nous avons eu recours à une analyse qualitative reposant sur une stratégie de cas multiples. Les PME innovantes ont été retenues comme terrain d’investigation. Les principaux résultats montrent l’existence de plusieurs phases, caractéristiques de l’évolution des différentes innovations réalisées par les PME sur longue période. Ils permettent en outre de relever les influences mutuelles entre innovations de différents types. De plus, l’étude des mécanismes de diffusion des innovations, visant aussi bien la technologie que l’organisation, autorise une compréhension plus fine de l’imbrication entre les différentes innovations réalisées par la PME et nous amène à repenser leurs liens en termes de « co-activation ».
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Nelson, Anna E., John L. Smellie, Mark Williams, and Jan Zalasiewicz. "Short Note: Late Miocene marine trace fossils from James Ross Island." Antarctic Science 20, no. 6 (June 2, 2008): 591–92. http://dx.doi.org/10.1017/s0954102008001429.
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Williams et al. (2006) reported asterozoans preserved in Late Miocene volcanic tuffs of the James Ross Island Volcanic Group. The material, from the north-west of James Ross Island at 64°01.9′S 58°20.07′W, was sourced from the newly named Asterozoan Buttress locality, and represented reconnaissance collecting. The volcaniclastic sediments in which the fossils are found are fine- to medium-grained volcanic sandstones with planar, laterally continuous beds 0.5–8 cm thick containing decimetre-scale ripple cross-lamination. In the absence of part and counterpart rock slabs, Williams et al. (2006) hypothesised that the fossils represented the external moulds of starfish or brittlestars pinioned by rapid sedimentation of volcanic tuffs. They noted that these tuffs represented a potential untapped source of fossil material for interpreting Neogene marine shelf environments on the northern Antarctic Peninsula. New fossil material collected at Asterozoan Buttress in February 2007 (by Anna Nelson) includes part and counterpart rock slabs, and demonstrates that the asterozoans are resting traces of animals, referable to the ichnogenus Asteriacites, and not external moulds of entombed animals (Fig. 1a & d). We reinterpret the ‘detached’ arm and ‘current-entrainment’ specimens of Williams et al. (2006, fig. 5c & d) as representing a possible scull mark and movement of the asterozoan across the sediment surface respectively (see Bell 2004, text-fig. 11 for comparison).
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Tao, Yu, Jan-Peter Muller, Susan J. Conway, and Siting Xiong. "Large Area High-Resolution 3D Mapping of Oxia Planum: The Landing Site for the ExoMars Rosalind Franklin Rover." Remote Sensing 13, no. 16 (August 18, 2021): 3270. http://dx.doi.org/10.3390/rs13163270.
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We demonstrate an end-to-end application of the in-house deep learning-based surface modelling system, called MADNet, to produce three large area 3D mapping products from single images taken from the ESA Mars Express’s High Resolution Stereo Camera (HRSC), the NASA Mars Reconnaissance Orbiter’s Context Camera (CTX), and the High Resolution Imaging Science Experiment (HiRISE) imaging data over the ExoMars 2022 Rosalind Franklin rover’s landing site at Oxia Planum on Mars. MADNet takes a single orbital optical image as input, provides pixelwise height predictions, and uses a separate coarse Digital Terrain Model (DTM) as reference, to produce a DTM product from the given input image. Initially, we demonstrate the resultant 25 m/pixel HRSC DTM mosaic covering an area of 197 km × 182 km, providing fine-scale details to the 50 m/pixel HRSC MC-11 level-5 DTM mosaic. Secondly, we demonstrate the resultant 12 m/pixel CTX MADNet DTM mosaic covering a 114 km × 117 km area, showing much more detail in comparison to photogrammetric DTMs produced using the open source in-house developed CASP-GO system. Finally, we demonstrate the resultant 50 cm/pixel HiRISE MADNet DTM mosaic, produced for the first time, covering a 74.3 km × 86.3 km area of the 3-sigma landing ellipse and partially the ExoMars team’s geological characterisation area. The resultant MADNet HiRISE DTM mosaic shows fine-scale details superior to existing Planetary Data System (PDS) HiRISE DTMs and covers a larger area that is considered difficult for existing photogrammetry and photoclinometry pipelines to achieve, especially given the current limitations of stereo HiRISE coverage. All of the resultant DTM mosaics are co-aligned with each other, and ultimately with the Mars Global Surveyor’s Mars Orbiter Laser Altimeter (MOLA) DTM, providing high spatial and vertical congruence. In this paper, technical details are presented, issues that arose are discussed, along with a visual evaluation and quantitative assessments of the resultant DTM mosaic products.
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Rodgers, LeRoy, Tony Pernas, Jed Redwine, Brooke Shamblin, and Shea Bruscia. "Multiscale Invasive Plant Monitoring: Experiences from the Greater Everglades Restoration Area." Weed Technology 32, no. 1 (December 10, 2017): 11–19. http://dx.doi.org/10.1017/wet.2017.106.
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AbstractObtaining spatially explicit, cost-effective, and management-relevant data on invasive plant distributions across large natural areas presents considerable challenges. This is especially true when multiple monitoring objectives exist, because the utility of different monitoring methodologies varies with scale, logistical considerations, and information needs. The Florida Everglades is a vast wetland landscape with widespread invasive plant infestations and multiple management jurisdictions. A multi-agency team Working Group conducted a workshop in 2013 to explore opportunities to enhance the performance of a regional weed control program. Among the most important developments occurring at this meeting was the recognition that relevant management questions are scale-dependent. This led the team to define multiple monitoring objectives. Essential for conveying the success of the weed management program is quantifying large-scale patterns of change, as are quantifying fine-scale patterns informing control activities, defining mechanisms of spread, recognizing accelerating rates of spread, and detecting patterns of occupancy immediately before management intervention. The group’s deliberation resulted in the emergence of a multiscale monitoring program utilizing several distinct monitoring protocols, including systematic landscape-level reconnaissance, a sample-based spatially stratified monitoring system, detailed inventories in planned treatment areas, and a set of methods focused solely on early detection and rapid response. Here we provide an overview of the Everglades multiscale invasive plant monitoring program, highlight benefits and challenges of each program component, and discuss how this program has improved regional invasive plant management.
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Xu, Xiangdong, Jiarong Wang, Ming Zhu, Haijiang Sun, Zhenyuan Wu, Yao Wang, Shenyi Cao, and Sanzai Liu. "UCDnet: Double U-Shaped Segmentation Network Cascade Centroid Map Prediction for Infrared Weak Small Target Detection." Remote Sensing 15, no. 15 (July 27, 2023): 3736. http://dx.doi.org/10.3390/rs15153736.
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In recent years, the development of deep learning has brought great convenience to the work of target detection, semantic segmentation, and object recognition. In the field of infrared weak small target detection (e.g., surveillance and reconnaissance), it is not only necessary to accurately detect targets but also to perform precise segmentation and sub-pixel-level centroid localization for infrared small targets with low signal-to-noise ratio and weak texture information. To address these issues, we propose UCDnet (Double U-shaped Segmentation Network Cascade Centroid Map Prediction for Infrared Weak Small Target Detection) in this paper, which completes “end-to-end” training and prediction by cascading the centroid localization subnet with the semantic segmentation subnet. We propose the novel double U-shaped feature extraction network for point target fine segmentation. We propose the concept and method of centroid map prediction for point target localization and design the corresponding Com loss function, together with a new centroid localization evaluation metrics. The experiments show that ours achieves target detection, semantic segmentation, and sub-pixel-level centroid localization. When the target signal-to-noise ratio is greater than 0.4, the IoU of our semantic segmentation results can reach 0.9186, and the average centroid localization precision can reach 0.3371 pixels. On our simulated dataset of infrared weak small targets, the algorithm we proposed performs better than existing state-of-the-art networks in terms of semantic segmentation and centroid localization.
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Mahmud, I., M. L. Garba, I. I. Ahmed, B. Onoja, A. Muhammad, and A. T. Dahiru. "VERY LOW FREQUENCY ELECTROMAGNETIC (VLF-EM) SURVEY FOR GROUNDWATER DEVELOPMENT IN BICHI/BAGWAI AREA, NORTH WESTERN NIGERIA." FUDMA JOURNAL OF SCIENCES 7, no. 5 (October 31, 2023): 318–27. http://dx.doi.org/10.33003/fjs-2023-0705-1977.
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Abstarct
Detailed Very Low Frequency Electromagnetic (VLF-EM) hydrogeophysical survey was undertaken to identify conductive zones and recommend potential areas for possible groundwater development in the Bichi area of Kano state northwestern Nigeria. Geologically, the area is characterized by porphyritic granite, coarse grained granite and medium to fine grained granite. The VLF-Electromagnetic method was adopted as a fast reconnaissance tool to map possible linear fractures. During the survey, measurements were taken at a station interval of 20 m along each profile line ranging from 0 – 420 m, making a total of six VLF-EM traverses which were mapped in the study area. The filtered components for both real and imaginary parts of the VLF-EM data were plotted against distance for each profile using the Karous–Hjelt filter® computer software to interpret and identify the top of linear fractures. The Very Low frequency (VLF) normal and filtered component anomalies identified ten (10) major geological interfaces suspected to be faults/fractured zones (f1 – f10). These suspected zones were marked as targets for future groundwater development in the area since these anomalous zones are areas of high conductivity and this parameter is one of the physical characteristics of water saturated zones. Therefore, this work has proven that VLF method is robust in tying down good locations for groundwater development in rural areas.
Keywords: Electromagnetic, Hydrogeophysical, Groundwater Development, Conductive Zones, Fault, Fractures.
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Uagoda, Rogério, André De Souza Avelar, and Ana Luiza Coelho Netto. "Depressões fechadas em relevo cárstico-quartzítico, bacia do Ribeirão Santana, médio vale do rio Paraíba do Sul." Anuário do Instituto de Geociências 29, no. 2 (January 1, 2006): 87–100. http://dx.doi.org/10.11137/2006_2_87-100.
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Karstic features generally develop in carbonatic rocks, but can also occur in siliciclastic rocks, as quartzites. The present research aims to create superficial morphology mapping and reconnaissance of karstic area deposits in quartzitic rocks. The study was developed in the hydrographic basin of the Ribeirão Santana (210 km²), mid-valley of the Preto river, a tributary of the Paraíba do Sul river, located between the states of Rio de Janeiro and Minas Gerais, Brazil. Aerial photographs at 1:25.000 scale were reconstituted in 3D environments, resulting in a planimetric and altitudinal map at 1:10.000 scale. Closed depressions, concavities with and without channels and deposits, were detached from these maps. Precise field topographic surveys at 1:500 scale resulted in planimetric and altitudinal maps related to identified forms. Also, soil samples were collected in the valley basins and depressions and analyzed according to their color, texture and grain morphoscopy criteria. Such study resulted in soil profiles for deposits confined at the bottoms of depressions and schematic representations of sediments from valley bottoms and slopes. The results indicate that the closed depressions a generally positioned at the limit of the drainage. In all sampler from the slope and fluvial valley bottom deposits the sand fraction predominates over fine particles, which were probably carried away in solution. Similar to the literature description, deep organic and/or hydromorphic profiles were found in depressions confined deposits. The present data can contribute to future geologic, hydrologic and geochemical characteristics to interpretet the origin and development of karstic features
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Bücker, Matthias, Adrián Flores Orozco, Jakob Gallistl, Matthias Steiner, Lukas Aigner, Johannes Hoppenbrock, Ruth Glebe, et al. "Integrated land and water-borne geophysical surveys shed light on the sudden drying of large karst lakes in southern Mexico." Solid Earth 12, no. 2 (February 24, 2021): 439–61. http://dx.doi.org/10.5194/se-12-439-2021.
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Abstract. Karst water resources play an important role in drinking water supply but are highly vulnerable to even slight changes in climate. Thus, solid and spatially dense geological information is needed to model the response of karst hydrological systems to such changes. Additionally, environmental information archived in lake sediments can be used to understand past climate effects on karst water systems. In the present study, we carry out a multi-methodological geophysical survey to investigate the geological situation and sedimentary infill of two karst lakes (Metzabok and Tzibaná) of the Lacandon Forest in Chiapas, southern Mexico. Both lakes present large seasonal lake-level fluctuations and experienced an unusually sudden and strong lake-level decline in the first half of 2019, leaving Lake Metzabok (maximum depth ∼25 m) completely dry and Lake Tzibaná (depth ∼70 m) with a water level decreased by approx. 15 m. Before this event, during a lake-level high stand in March 2018, we collected water-borne seismic data with a sub-bottom profiler (SBP) and transient electromagnetic (TEM) data with a newly developed floating single-loop configuration. In October 2019, after the sudden drainage event, we took advantage of this unique situation and carried out complementary measurements directly on the exposed lake floor of Lakes Metzabok and Tzibaná. During this second campaign, we collected time-domain induced polarization (TDIP) and seismic refraction tomography (SRT) data. By integrating the multi-methodological data set, we (1) identify 5–6 m thick, likely undisturbed sediment sequences on the bottom of both lakes, which are suitable for future paleoenvironmental drilling campaigns, (2) develop a comprehensive geological model implying a strong interconnectivity between surface water and karst aquifer, and (3) evaluate the potential of the applied geophysical approach for the reconnaissance of the geological situation of karst lakes. This methodological evaluation reveals that under the given circumstances, (i) SBP and TDIP phase images consistently resolve the thickness of the fine-grained lacustrine sediments covering the lake floor, (ii) TEM and TDIP resistivity images consistently detect the upper limit of the limestone bedrock and the geometry of fluvial deposits of a river delta, and (iii) TDIP and SRT images suggest the existence of a layer that separates the lacustrine sediments from the limestone bedrock and consists of collapse debris mixed with lacustrine sediments. Our results show that the combination of seismic methods, which are most widely used for lake-bottom reconnaissance, with resistivity-based methods such as TEM and TDIP can significantly improve the interpretation by resolving geological units or bedrock heterogeneities, which are not visible from seismic data. Only the use of complementary methods provides sufficient information to develop comprehensive geological models of such complex karst environments
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Zhao, W., X. Tong, H. Xie, Y. Jin, S. Liu, D. Wu, X. Liu, L. Guo, and Q. Zhou. "SIMULATION EXPERIMENT ON LANDING SITE SELECTION USING A SIMPLE GEOMETRIC APPROACH." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W1 (July 25, 2017): 213–18. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w1-213-2017.
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Safe landing is an important part of the planetary exploration mission. Even fine scale terrain hazards (such as rocks, small craters, steep slopes, which would not be accurately detected from orbital reconnaissance) could also pose a serious risk on planetary lander or rover and scientific instruments on-board it. In this paper, a simple geometric approach on planetary landing hazard detection and safe landing site selection is proposed. In order to achieve full implementation of this algorithm, two easy-to-compute metrics are presented for extracting the terrain slope and roughness information. Unlike conventional methods which must do the robust plane fitting and elevation interpolation for DEM generation, in this work, hazards is identified through the processing directly on LiDAR point cloud. For safe landing site selection, a Generalized Voronoi Diagram is constructed. Based on the idea of maximum empty circle, the safest landing site can be determined. In this algorithm, hazards are treated as general polygons, without special simplification (e.g. regarding hazards as discrete circles or ellipses). So using the aforementioned method to process hazards is more conforming to the real planetary exploration scenario. For validating the approach mentioned above, a simulated planetary terrain model was constructed using volcanic ash with rocks in indoor environment. A commercial laser scanner mounted on a rail was used to scan the terrain surface at different hanging positions. The results demonstrate that fairly hazard detection capability and reasonable site selection was obtained compared with conventional method, yet less computational time and less memory usage was consumed. Hence, it is a feasible candidate approach for future precision landing selection on planetary surface.
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Gao, Hongmin, Yao Yang, Chenming Li, Hui Zhou, and Xiaoyu Qu. "Joint Alternate Small Convolution and Feature Reuse for Hyperspectral Image Classification." ISPRS International Journal of Geo-Information 7, no. 9 (August 26, 2018): 349. http://dx.doi.org/10.3390/ijgi7090349.
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A hyperspectral image (HSI) contains fine and rich spectral information and spatial information of ground objects, which has great potential in applications. It is also widely used in precision agriculture, marine monitoring, military reconnaissance and many other fields. In recent years, a convolutional neural network (CNN) has been successfully used in HSI classification and has provided it with outstanding capacity for improving classification effects. To get rid of the bondage of strong correlation among bands for HSI classification, an effective CNN architecture is proposed for HSI classification in this work. The proposed CNN architecture has several distinct advantages. First, each 1D spectral vector that corresponds to a pixel in an HSI is transformed into a 2D spectral feature matrix, thereby emphasizing the difference among samples. In addition, this architecture can not only weaken the influence of strong correlation among bands on classification, but can also fully utilize the spectral information of hyperspectral data. Furthermore, a 1 × 1 convolutional layer is adopted to better deal with HSI information. All the convolutional layers in the proposed CNN architecture are composed of small convolutional kernels. Moreover, cascaded composite layers of the architecture consist of 1 × 1 and 3 × 3 convolutional layers. The inputs and outputs of each composite layer are stitched as the inputs of the next composite layer, thereby accomplishing feature reuse. This special module with joint alternate small convolution and feature reuse can extract high-level features from hyperspectral data meticulously and comprehensively solve the overfitting problem to an extent, in order to obtain a considerable classification effect. Finally, global average pooling is used to replace the traditional fully connected layer to reduce the model parameters and extract high-dimensional features from the hyperspectral data at the end of the architecture. Experimental results on three benchmark HSI datasets show the high classification accuracy and effectiveness of the proposed method.
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Obi L.E. and Uwanugo R.G. Uchejiora. "A geotechnical approach to gully erosion control and management at Inyishi, Ikeduru L.G.A., Imo State, Nigeria." World Journal of Advanced Engineering Technology and Sciences 1, no. 2 (December 30, 2020): 063–70. http://dx.doi.org/10.30574/wjaets.2020.1.2.0032.
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This research is aimed at appraising the root causes of gully erosion at Inyishi in Ikeduru Local Government Area of Imo State, Nigeria, and the possible geotechnical control and management techniques that could be applied in curbing the menace. In pursuance to these objectives, field and laboratory investigations were undertaken. The field works involved reconnaissance and chain surveys, and contouring of the gully catchments. It was observed that gullies were initiated in the research area by flow concentrations induced by environmental factors related to roads and aligned buildings constructed with inadequate drainage facilities upstream of the gully locations. Laboratory investigations carried out involved engineering analyses of soil samples collected at the gully sites and beds for the determination of the soils grain sizes, Atterberg limits, moisture content, specific gravity, permeability, shear strength and bulk density relations. A summary of the engineering properties of the soil revealed its poorly graded and sandy nature, its inadequate fine materials content, low liquid and plastic limits, which ranged between 35.80 to 42.20 % and 28.35 to 35.00 % respectively, as well as its low permeability index of 1 × 10-2cm/sec. These findings, coupled with the fact that the gully area was underlain with friable and cohesionless soil, with small time of concentration, which renders it easily disaggregated by runoff are pointers to the relative ease of water infiltration and seepage at the gully locations. The erosive power of the slope within the gully area was estimated by chain surveying of the entire catchment. The efficacy of natural local materials such as vetiver grass, wood shavings, palm kernel shells, coconut husk, bread fruit husk, dead plant mulch, etc. for the geotechnical works on gully erosion control and management was explored. General specifications on the geotechnics of managing the installed control works for their sustainable services were proffered.
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Tao, Yu, Siting Xiong, Susan J. Conway, Jan-Peter Muller, Anthony Guimpier, Peter Fawdon, Nicolas Thomas, and Gabriele Cremonese. "Rapid Single Image-Based DTM Estimation from ExoMars TGO CaSSIS Images Using Generative Adversarial U-Nets." Remote Sensing 13, no. 15 (July 22, 2021): 2877. http://dx.doi.org/10.3390/rs13152877.
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The lack of adequate stereo coverage and where available, lengthy processing time, various artefacts, and unsatisfactory quality and complexity of automating the selection of the best set of processing parameters, have long been big barriers for large-area planetary 3D mapping. In this paper, we propose a deep learning-based solution, called MADNet (Multi-scale generative Adversarial u-net with Dense convolutional and up-projection blocks), that avoids or resolves all of the above issues. We demonstrate the wide applicability of this technique with the ExoMars Trace Gas Orbiter Colour and Stereo Surface Imaging System (CaSSIS) 4.6 m/pixel images on Mars. Only a single input image and a coarse global 3D reference are required, without knowing any camera models or imaging parameters, to produce high-quality and high-resolution full-strip Digital Terrain Models (DTMs) in a few seconds. In this paper, we discuss technical details of the MADNet system and provide detailed comparisons and assessments of the results. The resultant MADNet 8 m/pixel CaSSIS DTMs are qualitatively very similar to the 1 m/pixel HiRISE DTMs. The resultant MADNet CaSSIS DTMs display excellent agreement with nested Mars Reconnaissance Orbiter Context Camera (CTX), Mars Express’s High-Resolution Stereo Camera (HRSC), and Mars Orbiter Laser Altimeter (MOLA) DTMs at large-scale, and meanwhile, show fairly good correlation with the High-Resolution Imaging Science Experiment (HiRISE) DTMs for fine-scale details. In addition, we show how MADNet outperforms traditional photogrammetric methods, both on speed and quality, for other datasets like HRSC, CTX, and HiRISE, without any parameter tuning or re-training of the model. We demonstrate the results for Oxia Planum (the landing site of the European Space Agency’s Rosalind Franklin ExoMars rover 2023) and a couple of sites of high scientific interest.
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Zhang, Zhichao, Hui Chen, Xiaoqing Yin, and Jinsheng Deng. "EAWNet: An Edge Attention-Wise Objector for Real-Time Visual Internet of Things." Wireless Communications and Mobile Computing 2021 (July 10, 2021): 1–15. http://dx.doi.org/10.1155/2021/7258649.
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With the upgrading of the high-performance image processing platform and visual internet of things sensors, VIOT is widely used in intelligent transportation, autopilot, military reconnaissance, public safety, and other fields. However, the outdoor visual internet of things system is very sensitive to the weather and unbalanced scale of latent object. The performance of supervised learning is often limited by the disturbance of abnormal data. It is difficult to collect all classes from limited historical instances. Therefore, in terms of the anomaly detection images, fast and accurate artificial intelligence-based object detection technology has become a research hot spot in the field of intelligent vision internet of things. To this end, we propose an efficient and accurate deep learning framework for real-time and dense object detection in VIOT named the Edge Attention-wise Convolutional Neural Network (EAWNet) with three main features. First, it can identify remote aerial and daily scenery objects fast and accurately in terms of an unbalanced category. Second, edge prior and rotated anchor are adopted to enhance the efficiency of detection in edge computing internet. Third, our EAWNet network uses an edge sensing object structure, makes full use of an attention mechanism to dynamically screen different kinds of objects, and performs target recognition on multiple scales. The edge recovery effect and target detection performance for long-distance aerial objects were significantly improved. We explore the efficiency of various architectures and fine tune the training process using various backbone and data enhancement strategies to increase the variety of the training data and overcome the size limitation of input images. Extensive experiments and comprehensive evaluation on COCO and large-scale DOTA datasets proved the effectiveness of this framework that achieved the most advanced performance in real-time VIOT object detection.
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Fontana, Sergio, and Fabrizio Felici. "Importazioni italiche in Tripolitania nella prima e media età imperiale." Libyan Studies 34 (2003): 65–84. http://dx.doi.org/10.1017/s0263718900003411.
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AbstractThe present contribution considers Italic imports into Tripolitania between the end of the 1st century BC and the 3rd century AD with special reference to the city of Lepcis Magna and its territory. The imports consist mainly of fine ceramic tableware and amphorae. The archaeological context is varied and highlights the diverse use of Italic goods. A wealth of information has been derived from the study of subterranean tombs excavated in the suburbs of Lepcis by the Libyan Department of Antiquities and by the University of Rome III mission. The assemblages consist of grave goods dated to between the middle of the first century BC and the 3rd century AD. Here we consider a sample of ten subterranean tombs not all of which have been published. They are located in the necropolis of the western suburbs of Lepcis with the exception of a tomb at Gelda, in the southern suburbs, and the Ganima tombs in the countryside to the east of Lepcis. Burial in subterranean tombs apparendy was reserved for the nobility while the majority of the population were buried in surface cemeteries often nearby. A contextual study of the early and middle Imperial period of the villa of Wadi er-Rsaf—excavated between 1995 and 1998—provided more data. Further surface reconnaissance surveys of various sample areas near Lepcis were carried out by the same mission in 1999-2000. Special emphases is placed on the survey in the Silin area on the coast some 15 km west of Lepcis and another inland in W Tareglat, now semi-desert, 40 km SE of Lepcis. The quality of the documentation is uneven but good enough to reveal the presence of Italic goods in different contexts: the ritual setting of a necropolis, everyday life in a prosperous suburban home, and rural settlements in the hinterland.
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Stringer, Mark E., Sarah Bastin, Christopher R. McGann, Claudio Cappellaro, Maya El Kortbawi, Rebecca McMahon, Liam M. Wotherspoon, et al. "Geotechnical aspects of the 2016 Kaikōura earthquake on the South Island of New Zealand." Bulletin of the New Zealand Society for Earthquake Engineering 50, no. 2 (June 30, 2017): 117–41. http://dx.doi.org/10.5459/bnzsee.50.2.117-141.
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The magnitude Mw7.8 ‘Kaikōura’ earthquake occurred shortly after midnight on 14 November 2016. This paper presents an overview of the geotechnical impacts on the South Island of New Zealand recorded during the post-event reconnaissance.
Despite the large moment magnitude of this earthquake, relatively little liquefaction was observed across the South Island, with the only severe manifestation occurring in the young, loose alluvial deposits in the floodplains of the Wairau and Opaoa Rivers near Blenheim. The spatial extent and volume of liquefaction ejecta across South Island is significantly less than that observed in Christchurch during the 2010-2011 Canterbury Earthquake Sequence, and the impact of its occurrence to the built environment was largely negligible on account of the severe manifestations occurring away from the areas of major development.
Large localised lateral displacements occurred in Kaikōura around Lyell Creek. The soft fine-grained material in the upper portions of the soil profile and the free face at the creek channel were responsible for the accumulation of displacement during the ground shaking. These movements had severely impacted the houses which were built close (within the zone of large displacement) to Lyell Creek. The wastewater treatment facility located just north of Kaikōura also suffered tears in the liners of the oxidation ponds and distortions in the aeration system due to ground movements.
Ground failures on the Amuri and Emu Plains (within the Waiau Valley) were small considering the large peak accelerations (in excess of 1g) experienced in the area. Minor to moderate lateral spreading and ejecta was observed at some bridge crossings in the area. However, most of the structural damage sustained by the bridges was a result of the inertial loading, and the damage resulting from geotechnical issues were secondary.
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Xu, He, Wenlong Zheng, Fengxuan Liu, Peng Li, and Ruchuan Wang. "Unmanned Aerial Vehicle Perspective Small Target Recognition Algorithm Based on Improved YOLOv5." Remote Sensing 15, no. 14 (July 17, 2023): 3583. http://dx.doi.org/10.3390/rs15143583.
Full textAbstract:
Small target detection has been widely used in applications that are relevant to everyday life and have many real-time requirements, such as road patrols and security surveillance. Although object detection methods based on deep learning have achieved great success in recent years, they are not effective in small target detection. In order to solve the problem of low recognition rate caused by factors such as low resolution of UAV viewpoint images and little valid information, this paper proposes an improved algorithm based on the YOLOv5s model, called YOLOv5s-pp. First, to better suppress interference from complex backgrounds and negative samples in images, we add a CA attention module, which can better focus on task-specific important channels while weakening the influence of irrelevant channels. Secondly, we improve the forward propagation and generalisation of the network using the Meta-ACON activation function, which adaptively learns to adjust the degree of linearity or nonlinearity of the activation function based on the input data. Again, the SPD Conv module is incorporated into the network model to address the problems of reduced learning efficiency and loss of fine-grained information due to cross-layer convolution in the model. Finally, the detection head is improved by using smaller, smaller-target detection heads to reduce missed detections. We evaluated the algorithm on the VisDrone2019-DET and UAVDT datasets and compared it with other state-of-the-art algorithms. Compared to YOLOv5s, mAP@.5 improved by 7.4% and 6.5% on the VisDrone2019-DET and UAVDT datasets, respectively, and compared to YOLOv8s, mAP@.5 improved by 0.8% and 2.1%, respectively. For improving the performance of the UAV-side small target detection algorithm, it will help to enhance the reliability and safety of UAVs in critical missions such as military reconnaissance, road patrol and security surveillance.
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Zhang, Yulian, Lihong Guo, Zengfa Wang, Yang Yu, Xinwei Liu, and Fang Xu. "Intelligent Ship Detection in Remote Sensing Images Based on Multi-Layer Convolutional Feature Fusion." Remote Sensing 12, no. 20 (October 12, 2020): 3316. http://dx.doi.org/10.3390/rs12203316.
Full textAbstract:
Intelligent detection and recognition of ships from high-resolution remote sensing images is an extraordinarily useful task in civil and military reconnaissance. It is difficult to detect ships with high precision because various disturbances are present in the sea such as clouds, mist, islands, coastlines, ripples, and so on. To solve this problem, we propose a novel ship detection network based on multi-layer convolutional feature fusion (CFF-SDN). Our ship detection network consists of three parts. Firstly, the convolutional feature extraction network is used to extract ship features of different levels. Residual connection is introduced so that the model can be designed very deeply, and it is easy to train and converge. Secondly, the proposed network fuses fine-grained features from shallow layers with semantic features from deep layers, which is beneficial for detecting ship targets with different sizes. At the same time, it is helpful to improve the localization accuracy and detection accuracy of small objects. Finally, multiple fused feature maps are used for classification and regression, which can adapt to ships of multiple scales. Since the CFF-SDN model uses a pruning strategy, the detection speed is greatly improved. In the experiment, we create a dataset for ship detection in remote sensing images (DSDR), including actual satellite images from Google Earth and aerial images from electro-optical pod. The DSDR dataset contains not only visible light images, but also infrared images. To improve the robustness to various sea scenes, images under different scales, perspectives and illumination are obtained through data augmentation or affine transformation methods. To reduce the influence of atmospheric absorption and scattering, a dark channel prior is adopted to solve atmospheric correction on the sea scenes. Moreover, soft non-maximum suppression (NMS) is introduced to increase the recall rate for densely arranged ships. In addition, better detection performance is observed in comparison with the existing models in terms of precision rate and recall rate. The experimental results show that the proposed detection model can achieve the superior performance of ship detection in optical remote sensing image.
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Turner, C. "33. How to steal a body." Clinical & Investigative Medicine 30, no. 4 (August 1, 2007): 45. http://dx.doi.org/10.25011/cim.v30i4.2793.
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You are a medical student in 1820, training in anatomy has now become a prerequisite to graduation but there are limited cadavers available for dissection. Could you be a body snatcher? What about if you only took unclaimed bodies? What if you didn’t actually excavate, just helped drive the wagon? What would be your conditions before you would turn to a life of crime? Keep in mind that just by “borrowing” the occasional body you would provide yourself with ample opportunities to learn anatomy and also easily afford your tuition.
If you do decide to go ahead and become a body snatcher you’re going to have to learn the classic modus operandi employed by the best in the business.
First of all you want to do some daytime reconnaissance by attending the burial to see if any booby traps are being set for potential body snatchers. Next, you return at night with a wagon and drop two men off at the burial site. They then start digging a 3’X3’ hole until they hit the coffin. The body is carefully extracted and any identifying clothing or jewelry is removed and put back in the coffin before being reburied.
Now you might be worried about retribution but you really don’t have much to fear. Townsfolk have been known to protest in front of medical schools but you’d have to deal with this even if you weren’t a body snatcher. If you end up going to court the worst that would happen is a fine that you could easily pay off by stealing another body or two.
Highet MJ. 2005. Body snatching and grave robbing: bodies for science. History and Anthropology 2005; 16(4):415-440.
MacGillivray R. Body snatching in Ontario. CBMH/BCHM 1988; 5:51-60.
Ross I, Ross CU. Body snatching in 19th Century Britain: from exhumation to murder. British Journal of Law and Society 1979; 6(1):108-118.
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Liu, Huanyu, Jiaqing Qiao, Lu Li, Lei Wang, Hongyu Chu, and Qingyu Wang. "Parallel CNN Network Learning-Based Video Object Recognition for UAV Ground Detection." Wireless Communications and Mobile Computing 2022 (April 14, 2022): 1–19. http://dx.doi.org/10.1155/2022/2701217.
Full textAbstract:
Video object recognition for UAV ground detection is widely used in target search, daily patrol, environmental reconnaissance, and other fields. So, we propose the novel parallel deep learning network with the ability of the global and local joint feature extraction for the UAV video target detection. This paper focuses on solving the problems of feature extraction and target background discrimination required by target discovery to realize target discovery. Break through the key problems of real-time target recognition, such as multiscale targets, high background complexity, many small targets, dense target arrangement, and multidirection, and put forward an optimized network scheme, aiming at the problem of multiscale of image target and aiming at the problem of large change of target scale in image. In the network, the corresponding targets with different sizes and different aspect ratios are matched to make the different targets match the closest, and then, the position of the detection box is fine-tuned by regression. For the special problem of image viewing angle and for the rotation invariance of the airborne down looking image of the target, the usual solution is through data enhancement; that is, through the rotation transformation of the training data, the neural network can learn the rotation invariance of the target. Aiming at the problem of multi-directional image target and aiming at the problems of large target aspect ratio, large target tilt angle, and changeable direction in the target, we propose to use the tilt detection frame instead of the ordinary rectangular detection frame. Aiming at the problem of dense arrangement of image targets and aiming at a large number of densely arranged targets in the image, a feature refining module is proposed, which can effectively improve the detection performance of the detector for densely arranged targets. The experimental results shows that the proposed algorithm achieves more than 10% on the target detection accuracy with focal length change of 1-10 times. The detection accuracy meets the requirements of practical application.
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Chen, Man, Kun Xu, Enping Chen, Yao Zhang, Yifei Xie, Yahao Hu, and Zhisong Pan. "Semantic Attention and Structured Model for Weakly Supervised Instance Segmentation in Optical and SAR Remote Sensing Imagery." Remote Sensing 15, no. 21 (November 1, 2023): 5201. http://dx.doi.org/10.3390/rs15215201.
Full textAbstract:
Instance segmentation in remote sensing (RS) imagery aims to predict the locations of instances and represent them with pixel-level masks. Thanks to the more accurate pixel-level information for each instance, instance segmentation has enormous potential applications in resource planning, urban surveillance, and military reconnaissance. However, current RS imagery instance segmentation methods mostly follow the fully supervised paradigm, relying on expensive pixel-level labels. Moreover, remote sensing imagery suffers from cluttered backgrounds and significant variations in target scales, making segmentation challenging. To accommodate these limitations, we propose a semantic attention enhancement and structured model-guided multi-scale weakly supervised instance segmentation network (SASM-Net). Building upon the modeling of spatial relationships for weakly supervised instance segmentation, we further design the multi-scale feature extraction module (MSFE module), semantic attention enhancement module (SAE module), and structured model guidance module (SMG module) for SASM-Net to enable a balance between label production costs and visual processing. The MSFE module adopts a hierarchical approach similar to the residual structure to establish equivalent feature scales and to adapt to the significant scale variations of instances in RS imagery. The SAE module is a dual-stream structure with semantic information prediction and attention enhancement streams. It can enhance the network’s activation of instances in the images and reduce cluttered backgrounds’ interference. The SMG module can assist the SAE module in the training process to construct supervision with edge information, which can implicitly lead the model to a representation with structured inductive bias, reducing the impact of the low sensitivity of the model to edge information caused by the lack of fine-grained pixel-level labeling. Experimental results indicate that the proposed SASM-Net is adaptable to optical and synthetic aperture radar (SAR) RS imagery instance segmentation tasks. It accurately predicts instance masks without relying on pixel-level labels, surpassing the segmentation accuracy of all weakly supervised methods. It also shows competitiveness when compared to hybrid and fully supervised paradigms. This research provides a low-cost, high-quality solution for the instance segmentation task in optical and SAR RS imagery.
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Wu, Falin, Tianyang Hu, Yu Xia, Boyi Ma, Saddam Sarwar, and Chunxiao Zhang. "WDFA-YOLOX: A Wavelet-Driven and Feature-Enhanced Attention YOLOX Network for Ship Detection in SAR Images." Remote Sensing 16, no. 10 (May 15, 2024): 1760. http://dx.doi.org/10.3390/rs16101760.
Full textAbstract:
Ships are important targets for modern naval warfare detection and reconnaissance. The accurate detection of ships contributes to the maintenance of maritime rights and interests and the realisation of naval strategy. Synthetic Aperture Radar (SAR) image detection tasks play a vital role in ship detection, which has consistently been a research hotspot in the field of SAR processing. Although significant progress has been achieved in SAR ship detection techniques using deep learning methods, some challenges still persist. Natural images and SAR images significantly diverge in imaging mechanisms and scattering characteristics. In complex background environments, ships exhibit multiscale variations and dense arrangements, and numerous small-sized ships may be present, culminating in false or missed detections. To address these issues, we propose a novel SAR ship detection network, namely, a Wavelet-Driven Feature-Enhanced Attention–You Only Look Once X (WDFA-YOLOX) network. Firstly, we propose a Wavelet Cascade Residual (WCR) module based on the traditional image processing technique wavelet transform, which is embedded within an improved Spatial Pyramid Pooling (SPP) module, culminating in the formation of the effective wavelet transform-based SPP module (WSPP). The WSPP compensates for the loss of fine-grained feature information during pooling, enhancing the capability of the network to detect ships amidst complex background interference. Secondly, a Global and Local Feature Attention Enhancement (GLFAE) module is proposed, leveraging a parallel structure that combines convolutional modules with transformer modules to reduce the effect of irrelevant information and effectively strengthens valid features associated with small-sized ships, resulting in a reduction in false negatives in small-sized ship detection. Finally, a novel loss function, the Chebyshev distance-generalised IoU loss function, is proposed to significantly enhance both the precision of the detection box and the network convergence speed. To support our approach, we performed thorough experiments on the SSDD and HRSID, achieving an average precision (AP) of 99.11% and 96.20%, respectively, in ship detection. The experimental results demonstrate that WDFA-YOLOX has significant advantages in terms of detection accuracy, generalisation capability, and detection speed and can effectively realise more accurate detection in SAR images, consistently exhibiting superior performance and application value in SAR ship detection.
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Heverin, Thomas, Elsa Deitz, Eve Cohen, and Jordana Wilkes. "Development and Analysis of a Reconnaissance-Technique Knowledge Graph." International Conference on Cyber Warfare and Security 18, no. 1 (February 28, 2023): 128–36. http://dx.doi.org/10.34190/iccws.18.1.1041.
Full textAbstract:
Penetration testing involves the use of many tools and techniques. The first stage of penetration testing involves conducting reconnaissance on a target organization. In the reconnaissance phase, adversaries use tools to find network data, people data, company/organization data, and attack data to generate a risk assessment about a target to determine where initial weaknesses may be. Although a small number of tools can be used to conduct many of reconnaissance tasks, including Shodan, Nmap, Recon-ng, Maltego, Metasploit, Google and more, each tool holds an abundance of specific techniques that can be used. Furthermore, each technique uses unique syntax. For example, Nmap holds over 600 scripts that make up its Nmap Scripting Engine. Depending on the type of device targeted, Nmap scripts can scan for ports, operating systems, IP addresses, hostnames and more. As another example, Maltego operates over 150 transforms or modules that collect data on organizations, files and people. Understanding which reconnaissance tool, techniques within those tools, and the syntax for each technique represents a highly complex task. MITRE ATT&CK, a widely accepted framework, models tactics and techniques within the tactics to help users make sense of adversarial behaviours. The tactic of reconnaissance is modelled in ATT&CK as well as its techniques. However, the explicit links between reconnaissance techniques are not modelled. Our research focused on the development of an ontology called Recontology to model the domain of reconnaissance. Recontology was then used to form Reconnaissance-Technique Graph (RT-Graph) to model 102 reconnaissance techniques and the directional links between the techniques. We used exploratory data analysis (EDA) methods including a graph spatial-layout algorithm and several graph-statistical algorithms to examine RT-Graph. We also used EDA to find critical techniques within the graph. Patterns across the results are discussed as well as implications for real-world uses of RT-Graph.
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Ванкевич, П., and Н. Фтомин. "ТРАНСФОРМАЦІЯ СИГНАЛІВ ГЕНЕРОВАНИХ СЕНСОРАМИ ВОЛОКОННОЇ ОПТИКИ В СИСТЕМАХ ПОПЕРЕДЖЕННЯ ВОГНЕВОГО УРАЖЕННЯ." Collection of scientific works of Odesa Military Academy, no. 20 (December 14, 2023): 125–30. http://dx.doi.org/10.37129/2313-7509.2023.20.125-130.
Full textAbstract:
An actual problem today is the improvement of a mobile optical reconnaissance system designed to detect snipers, observers, artillery correctors, including camouflaged ones equipped with optical sights. With the help of optical surveillance devices, it is possible to detect and estimate the distance to them, the principle of operation of which is based on the use of the physical effect of light reflection, which consists in the ability of optical systems to reflect probing radiation in the reverse direction at an angle close to the angle of its incidence, that is, illumination by a laser and capture of the reflected image, as well as the processing of this signal. The study of the processes of the propagation of laser radiation in the atmosphere (including in a turbulent environment) is given considerable attention in connection with the wide application of lasers in systems operating through the atmosphere. Indeed, the accuracy of laser devices of a wide range of applications (geodetic, in weapons systems and military equipment, portable, mounted in the system of combat equipment of a serviceman performing special tasks, etc.), spatial and temporal separation of laser locators, the possibility and accuracy of determining environmental parameters by remote laser methods can be estimated only taking into account the fluctuations of the field of optical beams. Keywords: combat tasks, optical reconnaissance, sniper, conical diffraction, diffraction grating, signal element, laser, sensor.
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Bubniak, Ihor, Andriy Bubniak, Yevhenii Shylo, Mariia Oliinyk, and Mykola Bihun. "GEODESY, CARTOGRAPHY AND AERIAL PHOTOGRAPHY." GEODESY, CARTOGRAPHY AND AERIAL PHOTOGRAPHY 97,2023, no. 97 (2023): 5–15. http://dx.doi.org/10.23939/istcgcap2023.97.005.
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The aim of this work is to study the Turka quarry using terrestrial laser scanning, as well as to build a 3D model of the object. Method. The study of the outcrop was carried out with terrestrial laser scanning. The article describes the principles of operation of laser sensors and provides a classification of error sources. It also emphasizes the importance of achieving the maximum accuracy specified by scanner manufacturers. The location of the researched object. The studied quarry is located on the northern outskirts of the city of Turka, Lviv region. From the geological point of view, the object is situated in the Outer Ukrainian Carpathians that belong to the Carpathian mountain system. The inactive quarry is structurally confined to the north-western part of the Krosno nappe of the Ukrainian Carpathians. The characteristic Turka (Krosno) type of cross-section of the Oligocene-Miocene age is exposed in the walls of the quarry. This is a layering of massive packs of gray fine-grained sandstones with argillites and siltstones which are broken with joints. The joints are filled with longitudinal, transverse and differently oriented veins. They are often wedged out. Their thickness ranges from a few mm to 55 mm or more. Slickensides and leaching are observed along the cracks. The research results make it possible to analyze the geological structure without being directly near the object. The paper provides a workflow diagram of the terrestrial scanning workflow. This includes object reconnaissance, establishing and determining the coordinates of reference and control points. It also involves performing terrestrial 3D scanning, photographing an object, creating a cloud of points based on laser scanning data, developing a mash model based on point clouds and digital images. The accuracy of the mash model was defined by comparison of the coordinates of the control points obtained from the mash model and tacheometric survey. The absolute spatial difference does not exceed five centimeters. The scientific novelty and practical significance are in the creation of a virtual model of the Turka quarry. For the first time, terrestrial laser scanning technology was used for the research of this object. As a result, a 3D model was obtained, which can be used for further research in the field of geology, in particular structural geology, sedimentology, mineral reserve calculations and geotourism.
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Early, Bryan R., and Erik Gartzke. "Spying from Space: Reconnaissance Satellites and Interstate Disputes." Journal of Conflict Resolution 65, no. 9 (March 23, 2021): 1551–75. http://dx.doi.org/10.1177/0022002721995894.
Full textAbstract:
Despite considerable interest and debate, it has proven surprisingly difficult to demonstrate a systematic link between technological change and patterns of war and peace. At least part of the challenge may reside in finding the right place to “look” for such relationships. Technological change alters what nations can do to one another (capabilities), but in ways that are typically reflected by deals (diplomatic bargains) rather than actions. We theorize that reconnaissance satellites have revolutionized the use of information gleaned from spying in ways that discourage states from engaging in serious conflicts with one another. We analyze the impact of reconnaissance satellites on high-casualty militarized interstate disputes (MIDS) between dyads from 1950 to 2010. We find that when either the potential aggressor or target in a dyad possess reconnaissance satellites, they are significantly less likely to become involved in serious MIDs. This effect is especially powerful when both states possess reconnaissance satellites.
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Long, Guo Qing, and Xiao Ping Zhu. "Cooperative Area Coverage Reconnaissance Method for Multi-UAV System." Advanced Materials Research 383-390 (November 2011): 4141–46. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.4141.
Full textAbstract:
Aiming to find a solution, the method of cooperative area coverage reconnaissance for Multi-UAV system is proposed by combining centralized preplanning with distributed partial online replanning. In the preplanning, grid disintegration is applied to divide the area to be reconnoitered into task sequence of nodes and fuzzy C-means clustering algorithm is applied to conduct space distribution of task nodes; the online partial replanning is that the left UAVs automatically complete the unfinished task of the failed UAV, using the membership matrix got by clustering algorithm as a unified standard, which ensures that so long as one UAV does not fail, the reconnaissance task can be normally carried on. The simulation results show that this method, simple yet with a high robustness, can effectively solve the problem of multi-UAV cooperative area coverage reconnaissance.
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Michenka, Karel. "Způsob stanovení požadavků na bezosádkové pozemní vozidla pro vedení průzkumu a sledování." Vojenské reflexie 16, no. 2 (2021): 86–100. http://dx.doi.org/10.52651/vr.a.2021.2.86-100.
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The article deals with the possible determination of obtaining information method and data to find the requirements for unmanned ground vehicles for reconnaissance and surveillance units. The article emphasizes the specification of general capabilities and features of reconnaissance and surveillance, which serve to define the requirements for unmanned ground vehicles. For the same reason, the article examines the individual environments that may affect the determination of requirements. Using the example of methods using cognitive maps, the mutual correlation of the researched issue is shown.