Retinal Dysplasia Mimicking Retinoblastoma.

Retinal dysplasia represents a congenital disorder characterized by abnormal proliferation of retinal tissue causing leukocoria. We present a case of an infant with bilateral leukocoria, clinically diagnosed as retinoblastoma, followed by enucleation of the left eye. Microscopy however, demonstrated retinal dysplasia consisting of a disorderly proliferation of retinal tissue with formation of rosettes, mimicking retinoblastoma. Microscopic features that aid in differentiating this lesion from retinoblastoma are discussed

Follow Up of treated cases of Appendicular Mass and Abscess and Ascertaining the role of Interval Appendicectomy

BACKGROUND: An appendicular mass is one of the common complications seen in patients presenting a few days later after the onset of acute appendicitis. There is no consensus on the optimum treatment of this potentially dangerous condition. The purpose of this dissertation is to analyse the follow up cases of treated cases of appendicular mass and abscess and ascertaining the role of interval appendicectomy, to analyse and compare the clinical response of appendicular mass and abscess treated conservatively and surgically (drainage), to assess the role of interval appendicectomy and its benefit during the follow up of these cases. METHODS: A proforma for study of all consecutive patients of APPENDICULAR MASS AND ABSCESS will be used. The presentation, clinical findings and the management will be documented. RESULT AND CONCLUSION: The practice of doing routine interval appendicectomy in a conservatively managed complicated appendicitis in a asymptomatic case during follow up is questionable due to following factors: 1. High conversion rate, 2. High complication rate, 3. Long hospital stay, 4. Low recurrence rate. 5. Non significant histopathology in some cases

Android Encrypted Network Traffic to Identify User Actions

Network forensics is a sub-branch of digital forensics relating to the monitoring and analysis of computer network traffic for the purposes of information gathering, legal evidence. Unlike other areas of digital forensics, network investigations deal with volatile and dynamic information. Network traffic is transmitted and then lost, so network forensics is often a pro-active investigation. Network forensics generally has two uses. The first, relating to security, involves monitoring a network for anomalous traffic and identifying intrusions. The second form relates to law enforcement. In this case analysis of captured network traffic can include tasks such as reassembling transferred files, searching for keywords and parsing human communication such as emails or chat sessions. Nowadays use of mobile apps to communicate with friends. Not only communication purpose it gets information about sensitive topics such as diseases, sexual or religious preferences, etc. Numerous worries have been raised about the capabilities of these portable devices to occupy the privacy of users actually becoming “tracking devices”. Above problem they influence in our work to find solution using machine learning techniques. It is used to protect the content of a packet. Our framework analyzes the network communications and leverages information available in TCP/IP packets like IP addresses and ports, together with other information like the size, the direction, and the timing. Our system, for each app they ?rst pre-process a dataset of network packets labeled with the user actions that originated them, they cluster them in ?ow typologies that represent recurrent network ?ows, and ?nally it analyze them in order to create a training set that will be used to feed a classi?er. The trained classi?er will then be able to classify new traf?c traced. Our approach results shows it accuracy and precision more than 95% for most of the considered actions

Organize Cloud Data Access Privilege and Anonymity with Fully Nameless Attribute-Based Encryption

Cloud computing may be a computing ideas that allows once needed and low maintenance usage of resources, however the info is shares to some cloud servers and varied privacy connected issues emerge from it. Various schemes based on the Attribute-Based Encryption have been proposed to secure the cloud storage. However, most work focuses on the data contents privacy and the access control, while less attention is paid to the privilege control and the identity privacy. In this paper, we present a semianonymous privilege control scheme AnonyControl to address not only the data privacy, but also the user identity privacy in existing access control schemes. Anony Control decentralizes the central authority to limit the identity leakage and thus achieves semianonymity. Besides, it also generalizes the file access control to the privilege control, by which privileges of all operations on the cloud data can be managed in a fine-grained manner. Our security analysis shows that both AnonyControl and AnonyControl-F are secure under the decisional bilinear Diffie–Hellman assumption, and our performance evaluation exhibits the feasibility of our schemes

Effective Utilization and Conversion of Spent Distillery Liquid to Valuable Products Using an Intensified Technology of Two-stage Biological Sequestration

The potential of Cladosporium cladosporioides and Phormidium valdernium in treating spent distillery liquid in a two-stage sequential step was investigated. During the batch experiment, a maximum decolourisation of 68.5 % and 81.37 % COD reduction was achieved in the first-stage bioreactor. Further, the spent wash from bioreactor was treated with cyanobacteria in the second stage and resulted in COD reduction (3,652 mg L–1) of 89.5 % and 92.7 % decolorization, respectively. Biodegradation was confirmed using HPLC analysis, and the products released during the degradation in the two stages were identified using GC-MS analysis, and found to be 2-octenyl acetate, 1,6-heptadiene from the fungi and oxotetrahydrofuran, hexadecane from cyanobacteria which in turn reveals the fact that the sequential treatment was through the mechanism of biodegradation and not by adsorption. The results imply that sequential treatment using the combination of fungi and cyanobacteria resulted in better degradation and decolourisation for the distillery spent wash

Limited Failure Censored Life Test Sampling Plan in Burr Type X Distribution

The Burr type X distribution is considered as a life time random variable of a product whose lots are to be decided for acceptance or otherwise on the basis of sample lifetimes drawn from the lot. The sample is divided into various groups in order to develop a group sampling plan in such a way that the life testing experiment is terminated as soon as the first failure in each group is observed. The acceptance criterion based on the theory of order statistics is proposed and is shown to be more economical than a criterion proposed in the earlier similar works

NYMBLE: Servers Overcrowding Disobedient Users in Anonymizing Networks

If a user wants to connect to a server has to provide his credentials where as some of the user (avoids to enter their original credentials) connect through anonymizing network such tor browser. Internet services can be accessed privately through anonymizing networks like Tor. A set of routers are used to achieve this in order to hide the identity of client from server. The advent of anonymizing networks assured that users could access internet services with complete privacy avoiding any possible hindrance. IP was being shown everywhere, To advertisers and other places, even from SPAM who compromised users identity. Anonymizing networks such as Tor allow users to access Internet services privately by using a series of routers to hide the client’s IP address from the server. In order to allow users to access Internet services privately, anonymizing networks like Tor uses a series of routers to hide the client’s IP address from the server. Anonymizing networks such as Tor allow users to access Internet services privately by using a series of routers to hide the client’s IP address from the server

Prediction of Leaf Diseases by using Machine Learning Techniques-A New Approach to Applied Informatics

Applied Informatics is a new emerging field which encompasses information technology and other areas of science. Many Automatic detection of a plant disease is proving their benefits in more fields of plant leaves. Proposed work focus on using machine learning techniques with multilayer Perceptron and simple K-Means algorithm for predicting sugarcane leaf disease by using Weka tool and the obtained results are promising