METHOD AND APPARATUS FOR AUTOMATED LINK FAILURE DETECTION IN NETWORKS USING MACHINE LEARNING

Techniques are presented for automatic link failure prediction and detection with an automatic troubleshooting capability to quickly identify switches/ports involved in the failure before the failure leads to a complete outage. A framework to predict the failure and easily handoff all routing protocols to an alternate path is provided. Such prediction helps a network to react before a failure occurs. Almost zero traffic loss during a failure may be achieved by predicting the failure in advance

Flux and Speed estimation of decoupled induction motor

This paper presents the rotor flux and speed estimation of induction motor using a novel technique. The induction motor model in rotor reference frame is considered. Controllers used for sensor less control of the drive. The estimation technique works well and the sensor less speed control scheme can achieve fast transient response as good as that of the induction motor with sensors and at the same time maintain a wide speed control range

Simulation for proposed DTN algorithm & Analysis

There are different simulation tools available for simulating the algorithms of mobile ad-hoc networks, and these tools are user friendly, means easy to work upon. In case of DTN algorithm implementation, these tool cannot work properly because of the frequent disconnection environment of nodes in DTN. We have used The ONE simulator [33] for implementing our proposed DTN algorithm

Routing algorithms classification & Proposed Routing Algorithm for DTN

This paper provides an introduction to Delay Tolerant Networks (DTN)alogorithms and would touch upon some basic classification. Continuous connectivity is difficult in today�s wireless world. The data preservation and security in challenged and intermittent network, is of paramount importance. In this paper, we will see how DTN provides detail classification and discription for further studies & application.an effective alternative. Security of data becomes important in disrupted networks; this paper would also discuss Praposed Routing algorithms with DTNs

FORCE COMPETENT EXHAUSTIVE COMPUTATION BASED ON BINARY MATRIX

Numerous studies have suggested efficient structures to reduce the ability use of the CS. Early termination techniques presented will be to eliminate redundant computations after locating the last error. Even though the two-step approach, generally, results in the rise in critical path delay and latency, the drawbacks are resolved within this brief by using a competent pipelined structure. This brief has presented a brand new low-power architecture for parallel CS. The traditional CS is decomposed into two steps to attain a substantial power saving by reduction of accessibility next step. For instance, within the situation of m = 14, 60% power saving is anticipated in contrast to the traditional architecture when the initial step processes three MSBs. It's suggested inside a practical realization to locate a better optimal bit width by investigating several candidate bit widths close to the bit width caused by the model. You should decide the number of l bits work for that former partial FFMs. The greater bits are examined within the former, the second partial FFMs is going to be utilized less producing a large power reduction, however the former partial FFM are affected in the elevated power dissipation, and the other way around. It's suggested inside a practical realization to locate a better optimal bit width by investigating several candidate bit widths close to the bit width caused by the model. The fundamental ideas behind the suggested technique may also be applied once the aspects of the set are kept in a memory protected with increased advanced ECCs. Additionally, a simplified form of the suggested approach may also be used for traditional BFs however in that situation, the proportion of errors that may be remedied is a lot lower. Experimental results reveal that the suggested architecture reduces as much as 50% power consumption in contrast to the traditional parallel CS. Otherwise we are able to lessen the dynamic switching power by disabling the second partial FFMs. Since each intermediate register holds certainly one of all possible GF elements, the second partial FFM is activated once every 2l clock cycles around the average

Customized News Filtering and Summarization System Based on Personal Interest

AbstractAbstract_ In the World Wide Web the information consists large amount of news contents. In Web intelligence Recommendation, filtering, and summarization of Web news have received much attention and also aims to find interesting news to the users .In this paper we present Customized news filtering and summarization system based on personal interest and it summarizes concise content for users .A user interest model induced by embedded learning component of CNFS and it also recommends customized news. Retrieving useful Web news involves both filtering and keyword extraction and also maintains key word knowledge base. The non-news content irrelevant to the news Webpage is filtered out .This extraction method substantially outperforms methods based on term frequency and lexical chains to represent semantic relation between words

Laparoscopic Treatment of Gastric Bezoar

Detailed in this report is the laparoscopic removal of a gastric bezoar through an anterior wall gastrotomy

Comparison of composition engines and identification of shortcomings with respect to cloud computing

Most workflow engines are currently not Cloud-aware. This is due to multiple reasons like no support for transparent scalability, no multi-tenancy support, no ability to store process related data in a Cloud storage, or no support for quality of service enforcements. Recently Cloud based workflow services appeared in the workflow landscape and promise to run workflows in the Cloud. This student reports evaluates current state of the art BPEL and BPMN workflow engines and Cloud based workflow services according to their Cloud- awareness and general workflow functionalities. Identified shortcomings are described and prioritized. As a result of this evaluation the workflow engine WSO2 Stratos is best suited for running workflows in the Cloud, but it lacks native clustering support and quality of service enforcement