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Caterpillars are the developmental stage of the flying insect called butterfly. The moths are the beautiful creature of earth which comes under the class of insects. They are recognized by their beautiful and colorful forewings body and legs. Caterpillars are the larval stage of the moth which are found in the leaf and stem of the plants when the moth laid eggs on the leaves after their mating. Caterpillar after fully developed from its eggs draw out a flimsy, soft cocoon made up of dark coarse silk on leaves and stem for their shelter. Caterpillar is also a beautiful creature that is found with different colors and strips with spines and urticating hair in their body for releasing venom for self-defense from external predators. The present study works on the detection and classification of the caterpillar using image processing with a k-NN classifier.This research help in characterizing the type of caterpillar image classification for particular three classes such as accuracy of Buck Moth Caterpillar, the accuracy of Saddleback Caterpillar, and the accuracy of Io moth Caterpillar. The following stages have been considered are preprocessing, segmentation, feature extraction, and classification methods using K- Nearest Neighbor classifier. The present investigation results that SYMLET5 analysis works well in the classification of the caterpillar with an accuracy of 96% using K- Nearest Neighbor classifier compare with other measures during investigation and analysis.

Continued improvements on existing reconstruction methods are vital to the success of high-energy physics experiments, such as the IceCube Neutrino Observatory. In IceCube, further challenges arise as the detector is situated at the geographic South Pole where computational resources are limited. However, to perform real-time analyses and to issue alerts to telescopes around the world, powerful and fast reconstruction methods are desired. Deep neural networks can be extremely powerful, and their usage is computationally inexpensive once the networks are trained. These characteristics make a deep learning-based approach an excellent candidate for the application in IceCube. A reconstruction method based on convolutional architectures and hexagonally shaped kernels is presented. The presented method is robust towards systematic uncertainties in the simulation and has been tested on experimental data. In comparison to standard reconstruction methods in IceCube, it can improve upon the reconstruction accuracy, while reducing the time necessary to run the reconstruction by two to three orders of magnitude., Comment: 39 pages, 15 figures, submitted to Journal of Instrumentation; added references

Introduction: The introduction of foreign bodies into the rectum is a frequent practice considered as proctological emergency. Objective: We report our experience in trauma by a foreign body in the rectum during over 20 years in the Thoraco-abdominal Trauma Surgery Service of Civil Hospital Fray Antonio Alcalde of Guadalajara, Jalisco, Mexico. Materials and Methods : Retrospective cross-sectional study (1999-2018) carried out with data recorded in the hospital’s archives., patients of both sex with a age rank of 15 to 91 years were included. Results: There were a total of 194 patients, including 169 males and 25 females, with a predominant age range from 30-44 years with 75 cases (38%). The incidence was between 1999 and 2010 of 4.0 ± 2.1 patients per year, against 15.4 ± 8.8 cases between 2011-2018. Proctorrhage was the predominant sign (56 patients), followed by foreign-body sensation (49 patients) and abdominal pain (41 patients). Diagnosis was based mainly on digital rectal examination (100%) and plain abdominal x-ray (94%). Manual extraction was performed in 82 % of the cases, laparotomy 10 cases (5%) and colonoscopy in 5 cases (2.5%). The main complication was mucosal tear in 50 cases (57%), skin and mucosa tear in 12 cases (14%), and perforation in 8 cases (9%). Conclusions: The frequency of foreign bodies into the rectum is increasing and constitutes a real challenge for the surgeon due to the enormous diversity of variables. Key words: Trauma, Foreign body, Rectum

This article details a novel technique in the treatment of a symptomatic thoracoabdominal aneurysm (TAA) involving the visceral segment and an infrarenal abdominal aortic aneurysm. The patient was treated in a 2-staged hybrid approach combining an endovascular repair of the infrarenal segment, followed by open TAA repair. The large visceral arteries were revascularized using expanded polytetrafluoroethylene GORE Hybrid Vascular Graft (GHVG) and a Gradual Funneling Technique with Dacron graft. This method assured a complete hemostatic seal and minimized visceral ischemic time. To our knowledge, this is the first case of sutureless visceral artery revascularization using GHVG reported in the literature.

It is well known that neighbor discovery is a critical component of proactive routing protocols in wireless ad hoc networks. However there is no formal study on the performance of proposed neighbor discovery mechanisms. This paper provides a detailed model of key performance metrics of neighbor discovery algorithms, such as node degree and the distribution of the distance to symmetric neighbors. The model accounts for the dynamics of neighbor discovery as well as node density, mobility, radio and interference. The paper demonstrates a method for applying these models to the evaluation of global network metrics. In particular, it describes a model of network connectivity. Validation of the models shows that the degree estimate agrees, within 5% error, with simulations for the considered scenarios. The work presented in this paper serves as a basis for the performance evaluation of remaining performance metrics of routing protocols, vital for large scale deployment of ad hoc networks.

It is well known that topology information from nodes that are many hops away has little impact on the selection of the next hop. Hazy-sighted routing and fish-eye routing attempt to take advantage of this behavior in order to reduce overhead without impacting path stretch, which is the increase in the number of hops a packet travels as a result of stale topology information. However, these previous efforts failed to quantify the impact of their approach on path stretch. This paper develops a model of the path stretch as a function of stale topology information. To this end, we find a Markov model that describes the quality of packet forwarding, where jumps occur with some probability whenever the topology changes. From this Markov model, a precise model of path stretch can be derived, and a new and less optimistic view of hazy-sighted flooding emerges.

OLSR is one of the most well developed routing protocols for MANETs. OLSR as a link state routing protocol relies on its flooding mechanism to disseminate topology information to all nodes in the network. However, the performance of the flooding algorithm is poorly understood. In this paper models of key performance metrics of this algorithm are presented. Specifically, it describes a model for the control overhead generated by the flooding algorithm and a model of efficiency in terms of network coverage. The models are validated against simulations. The results presented in this paper have significant implications for the standardization process.

It is well known that neighbor discovery is a critical component of proactive routing protocols in wireless ad hoc networks. However there is no formal study on the performance of proposed neighbor discovery mechanisms. This paper provides a detailed model of key performance metrics of neighbor discovery algorithms, such as node degree and the distribution of the distance to symmetric neighbors. The model accounts for the dynamics of neighbor discovery as well as node density, mobility, radio and interference. The paper demonstrates a method for applying these models to the evaluation of global network metrics. In particular, it describes a model of network connectivity. Validation of the models shows that the degree estimate agrees, within 5% error, with simulations for the considered scenarios. The work presented in this paper serves as a basis for the performance evaluation of remaining performance metrics of routing protocols, vital for large scale deployment of ad-hoc networks.

In the design of many proactive routing protocols for MANETs, it is often assumed that topology information is disseminated instantly and error free. Exceptions include hazy-sighted routing, which deliberately delay the dissemination of topology information such that the average time from when a node learns about a change in topology depends on the distance from the node to where the topology information changed. However, the analysis of hazy-sighted routing neglects the impact of this delay. This paper explores the impact of delayed topology information to the probability of routing loops formation and and packet loss.

The concept of Active Queue Management (AQM), broadly used in Internet Congestion Control, has been recently introduced to ad hoc wireless networks as a means to mitigate the severe TCP unfairness across flows. In particular, Neighborhood RED (NRED) has been proposed as an extension to the Random Early Detection (RED) mechanism with the goal of ensuring fair bandwidth allocation across flows in the networks. NRED provides improvements but suffers from limitations that can make its broad implementation difficult. This paper describes two fundamental principles governing neighborhood congestion among TCP flows in ad hoc wireless networks which are exploited to develop an improved control mechanism. The first principle indicates that the likelihood of the channel being captured by a node grows exponentially with the disparity between the node's channel utilization and the expected utilization level. The second principle indicates that traditional random packet marking in NRED leads to reduced fairness across flows, pointing to a simple dropping/marking strategy based on the concept of error diffusion where packet marks are spread apart as homogeneously as possible. The power of these fundamental principles is demonstrated in a Congestion Control scheme referred to as Neighborhood Diffusion Early Marking (NDEM) which results in a more efficient bandwidth distribution compared to NRED.

The introduction of thoracic endografts has revolutionized the management of thoracic aortic disease. Currently, endografts are not FDA-approved for treating thoracic aortic injury (TAI). We report a case of TAI who presented in hemorrhagic shock and preoperative cardiac arrest who was successfully treated with large volume resuscitation, closed chest cardiac massage, exploratory laparotomy, and thoracic endografting.

This paper will present the work to be done on the sites “Plazuelas” and “Peralta”, both in Guanajuato, Mexico. The objective is to develop an archaeocustical characterization of the archaeological areas, as well as the musical instruments found in these sites. Furthermore, an ethnomusicologic and historiographic investigation will be done. In adition, it will present the methodology and protocol to be followed in this investigation.