Privacy Preserving Multi-Server k-means Computation over Horizontally Partitioned Data

The k-means clustering is one of the most popular clustering algorithms in data mining. Recently a lot of research has been concentrated on the algorithm when the dataset is divided into multiple parties or when the dataset is too large to be handled by the data owner. In the latter case, usually some servers are hired to perform the task of clustering. The dataset is divided by the data owner among the servers who together perform the k-means and return the cluster labels to the owner. The major challenge in this method is to prevent the servers from gaining substantial information about the actual data of the owner. Several algorithms have been designed in the past that provide cryptographic solutions to perform privacy preserving k-means. We provide a new method to perform k-means over a large set using multiple servers. Our technique avoids heavy cryptographic computations and instead we use a simple randomization technique to preserve the privacy of the data. The k-means computed has exactly the same efficiency and accuracy as the k-means computed over the original dataset without any randomization. We argue that our algorithm is secure against honest but curious and passive adversary.Comment: 19 pages, 4 tables. International Conference on Information Systems Security. Springer, Cham, 201

Efecto de herbicidas post-emergentes aplicados en distintos estados del cultivo de trigo (Triticum aestivum L.) cv. Buck Arrayán y Buck Charrúa

Se evaluó el comportamiento de los herbicidas Bromoximil; Dicamba + Metsulfurón Metil; Dicamba + MCPA; Terutrina + Triasulfurón y Piclorán + Metsulfurón Metil aplicados en estado de ápices vegetativos; 2,4-0 + Oicamba; Bromoximil y Dicamba + MCPA aplicados en el estado previo a la espiguilla terminal diferenciada y 2,4-0 + Piclorán y 2,4-0 + Dicamba aplicados en el estado posterior a la espiguilla terminal diferenciada sobre los cultivares Buck Arrayán y Buck Charrúa. Las dosis de aplicación fueron las habituales de marbete de esos productos. Estos tratamientos se contrastaron contra dos testigos: con malezas y sin malezas durante todo el ciclo del cultivo. Las malezas con muy bajo nivel de infestación no provocaron pérdidas de rendimiento del cultivo, ni afectaron los componentes del rendimiento en ambos cultivares. Los herbicidas no produjeron mayores diferencias entre sí en el grado de eficacia de control de malezas; sólo se detectó una ligera tendencia a mejor control cuando más tempranas fueron las aplicaciones. La producción de los dos cultivares no se vio afectada con las aplicaciones de cualquiera de los herbicidas en los distintos estados del mismo, ni aún con las realizadas después de haber alcanzado el estado de espiguilla terminal diferenciada. Tampoco se registraron modificaciones de los componentes de rendimiento. Los datos del ensayo se contraponen con las recomendaciones habituales de uso de herbicidas hormonales y con lo obtenido en otros trabajos. Ninguna de las variables medidas en este experimento resultaron satisfactorias para explicar tales discrepancias.Director: Ing. Agr. Fernando O. García. Cátedra de Terapéutica Vegetal, Facultad de Agronomía, UNLpam

Automatic detection of crop rows in maize fields with high weeds pressure

This paper proposes a new method, oriented to crop row detection in images from maize fields with high weed pressure. The vision system is designed to be installed onboard a mobile agricultural vehicle, i.e. submitted to gyros, vibrations and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of three main processes: image segmentation, double thresholding, based on the Otsu’s method, and crop row detection. Image segmentation is based on the application of a vegetation index, the double thresholding achieves the separation between weeds and crops and the crop row detection applies least squares linear regression for line adjustment. Crop and weed separation becomes effective and the crop row detection can be favorably compared against the classical approach based on the Hough transform. Both gain effectiveness and accuracy thanks to the double thresholding that makes the main finding of the paper

Automatic segmentation of relevant textures in agricultural images

One important issue emerging strongly in agriculture is related with the automatization of tasks, where the optical sensors play an important role. They provide images that must be conveniently processed. The most relevantimage processing procedures require the identification of green plants, in our experiments they come from barley and corn crops including weeds, so that some types of action can be carried out, including site-specific treatments with chemical products or mechanical manipulations. Also the identification of textures belonging to the soil could be useful to know some variables, such as humidity, smoothness or any others. Finally, from the point of view of the autonomous robot navigation, where the robot is equipped with the imaging system, some times it is convenient to know not only the soil information and the plants growing in the soil but also additional information supplied by global references based on specific areas. This implies that the images to be processed contain textures of three main types to be identified: green plants, soil and sky if any. This paper proposes a new automatic approach for segmenting these main textures and also to refine the identification of sub-textures inside the main ones. Concerning the green identification, we propose a new approach that exploits the performance of existing strategies by combining them. The combination takes into account the relevance of the information provided by each strategy based on the intensity variability. This makes an important contribution. The combination of thresholding approaches, for segmenting the soil and the sky, makes the second contribution; finally the adjusting of the supervised fuzzy clustering approach for identifying sub-textures automatically, makes the third finding. The performance of the method allows to verify its viability for automatic tasks in agriculture based on image processin

Global overview of the management of acute cholecystitis during the COVID-19 pandemic (CHOLECOVID study)

Background: This study provides a global overview of the management of patients with acute cholecystitis during the initial phase of the COVID-19 pandemic. Methods: CHOLECOVID is an international, multicentre, observational comparative study of patients admitted to hospital with acute cholecystitis during the COVID-19 pandemic. Data on management were collected for a 2-month study interval coincident with the WHO declaration of the SARS-CoV-2 pandemic and compared with an equivalent pre-pandemic time interval. Mediation analysis examined the influence of SARS-COV-2 infection on 30-day mortality. Results: This study collected data on 9783 patients with acute cholecystitis admitted to 247 hospitals across the world. The pandemic was associated with reduced availability of surgical workforce and operating facilities globally, a significant shift to worse severity of disease, and increased use of conservative management. There was a reduction (both absolute and proportionate) in the number of patients undergoing cholecystectomy from 3095 patients (56.2 per cent) pre-pandemic to 1998 patients (46.2 per cent) during the pandemic but there was no difference in 30-day all-cause mortality after cholecystectomy comparing the pre-pandemic interval with the pandemic (13 patients (0.4 per cent) pre-pandemic to 13 patients (0.6 per cent) pandemic; P = 0.355). In mediation analysis, an admission with acute cholecystitis during the pandemic was associated with a non-significant increased risk of death (OR 1.29, 95 per cent c.i. 0.93 to 1.79, P = 0.121). Conclusion: CHOLECOVID provides a unique overview of the treatment of patients with cholecystitis across the globe during the first months of the SARS-CoV-2 pandemic. The study highlights the need for system resilience in retention of elective surgical activity. Cholecystectomy was associated with a low risk of mortality and deferral of treatment results in an increase in avoidable morbidity that represents the non-COVID cost of this pandemic

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans – anteaters, sloths, and armadillos – have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with 24 domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, ten anteaters, and six sloths. Our dataset includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data-paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the south of the USA, Mexico, and Caribbean countries at the northern portion of the Neotropics, to its austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n=5,941), and Cyclopes sp. has the fewest (n=240). The armadillo species with the most data is Dasypus novemcinctus (n=11,588), and the least recorded for Calyptophractus retusus (n=33). With regards to sloth species, Bradypus variegatus has the most records (n=962), and Bradypus pygmaeus has the fewest (n=12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other datasets of Neotropical Series which will become available very soon (i.e. Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans dataset

Efecto de herbicidas post-emergentes aplicados en distintos estados del cultivo de trigo (Triticum aestivum L.) cv. Buck Arrayán y Buck Charrúa

Se evaluó el comportamiento de los herbicidas Bromoximil; Dicamba + Metsulfurón Metil; Dicamba + MCPA; Terutrina + Triasulfurón y Piclorán + Metsulfurón Metil aplicados en estado de ápices vegetativos; 2,4-0 + Oicamba; Bromoximil y Dicamba + MCPA aplicados en el estado previo a la espiguilla terminal diferenciada y 2,4-0 + Piclorán y 2,4-0 + Dicamba aplicados en el estado posterior a la espiguilla terminal diferenciada sobre los cultivares Buck Arrayán y Buck Charrúa. Las dosis de aplicación fueron las habituales de marbete de esos productos. Estos tratamientos se contrastaron contra dos testigos: con malezas y sin malezas durante todo el ciclo del cultivo. Las malezas con muy bajo nivel de infestación no provocaron pérdidas de rendimiento del cultivo, ni afectaron los componentes del rendimiento en ambos cultivares. Los herbicidas no produjeron mayores diferencias entre sí en el grado de eficacia de control de malezas; sólo se detectó una ligera tendencia a mejor control cuando más tempranas fueron las aplicaciones. La producción de los dos cultivares no se vio afectada con las aplicaciones de cualquiera de los herbicidas en los distintos estados del mismo, ni aún con las realizadas después de haber alcanzado el estado de espiguilla terminal diferenciada. Tampoco se registraron modificaciones de los componentes de rendimiento. Los datos del ensayo se contraponen con las recomendaciones habituales de uso de herbicidas hormonales y con lo obtenido en otros trabajos. Ninguna de las variables medidas en este experimento resultaron satisfactorias para explicar tales discrepancias. Director: Ing. Agr. Fernando O. García. Cátedra de Terapéutica Vegetal, Facultad de Agronomía, UNLpam

A vision-based method for weeks identification through the Bayesian decision theory

Abstract: One of the objectives of precision agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. This paper outlines an automatic computer vision-based approach for the detection and differential spraying of weeds in corn crops. The method is designed for post-emergence herbicide applications where weeds and corn plants display similar spectral signatures and the weeds appear irregularly distributed within the crop’s field. The proposed strategy involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based measuring relationships between crop and weeds. The decision making determines the cells to be sprayed based on the computation of a posterior probability under a Bayesian framework. The a priori probability in this framework is computed taking into account the dynamic of the physical system (tractor) where the method is embedded. The main contributions of this paper are: (1) the combination of the image segmentation and decision making processes and (2) the decision making itself which exploits a previous knowledge which is mapped as the a priori probability. The performance of the method is illustrated by comparative analysis against some existing strategies.Peer reviewe

Development of a control concept for catalyst regeneration by coke combustion

Hydrocarbon processes are frequently accompanied by catalyst deactivation through coke deposition on the catalyst surface. A control strategy is proposed for catalyst regeneration in a novel dehydrogenation process designed to be operated in a cyclic production—regeneration mode. The task of the controller is to ensure complete regeneration while maintaining strict limits regarding regeneration time and maximum temperature. The major challenge arises from the uncertainty in the total amount and the spatial distribution of coke loading. The problem is tackled by a model-based approach. This includes a modular analysis of the open-loop behavior and a consistent controller configuration. Copyright © 2011 Elsevier Ltd. All rights reserved. [accessed January 19th 2012