On generalized processor sharing and objective functions: analytical framework

Today, telecommunication networks host a wide range of heterogeneous services. Some demand strict delay minima, while others only need a best-effort kind of service. To achieve service differentiation, network traffic is partitioned in several classes which is then transmitted according to a flexible and fair scheduling mechanism. Telecommunication networks can, for instance, use an implementation of Generalized Processor Sharing (GPS) in its internal nodes to supply an adequate Quality of Service to each class. GPS is flexible and fair, but also notoriously hard to study analytically. As a result, one has to resort to simulation or approximation techniques to optimize GPS for some given objective function. In this paper, we set up an analytical framework for two-class discrete-time probabilistic GPS which allows to optimize the scheduling for a generic objective function in terms of the mean unfinished work of both classes without the need for exact results or estimations/approximations for these performance characteristics. This framework is based on results of strict priority scheduling, which can be regarded as a special case of GPS, and some specific unfinished-work properties in two-class GPS. We also apply our framework on a popular type of objective functions, i.e., convex combinations of functions of the mean unfinished work. Lastly, we incorporate the framework in an algorithm to yield a faster and less computation-intensive result for the optimum of an objective function

The 'Parekh Report' - national identities with nations and nationalism

‘Multiculturalists’ often advocate national identities. Yet few study the ways in which ‘multiculturalists’ do so and in this article I will help to fill this gap. I will show that the Commission for Multi-Ethnic Britain’s report reflects a previously unnoticed way of thinking about the nature and worth of national identities that the Commission’s chair, and prominent political theorist, Bhikhu Parekh, had been developing since the 1970s. This way of thinking will be shown to avoid the questionable ways in which conservative and liberal nationalists discuss the nature and worth of national identities while offering an alternative way to do so. I will thus show that a report that was once criticised for the way it discussed national identities reflects how ‘multiculturalists’ think about national identities in a distinct and valuable way that has gone unrecognised

In vitro antimicrobial activity of Trapa natans L. fruit rind extracted in different solvents

Trapa natans L. fruit rind was extracted in different solvents with increasing polarity; 1,4-dioxan, chloroform, acetone,  imethylformamide, ethanol and water. The extractive yield ranged from 0.62 –12.62%. The antibacterial activity of all the extracts was determined by agar disc diffusion method. Maximum antibacterial activity was observed against Gram negative bacteria. The resistant Gram negative strains were C. fruendii, E. aerogenes, E. coli, P. vulgaris, P. aeruginosa and S. typhimurium. Amongst Gram positive bacteria, M. flavus was the most susceptible bacteria and B. subtilis was most resistant. The moulds showed better antifungal activity than yeast. A. niger was the most resistant fungal strain. The best antimicrobial activity was with 1,4-dioxan extract and the least activity was with petroleum ether extract. The inhibitory effects of the extracts were comparable with the standard antimicrobics used. This work has highlighted the antimicrobial effects of fruit rind of Trapa natans L.on some of the medically important pathogens

A Novel Noninvasive Method to Assess Left Ventricular −dP/dt Using Diastolic Blood Pressure and Isovolumic Relaxation Time

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96727/1/echo12042.pd

Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence

Data in the form of pairwise comparisons arises in many domains, including preference elicitation, sporting competitions, and peer grading among others. We consider parametric ordinal models for such pairwise comparison data involving a latent vector $w^* \in \mathbb{R}^d$ that represents the "qualities" of the $d$ items being compared; this class of models includes the two most widely used parametric models--the Bradley-Terry-Luce (BTL) and the Thurstone models. Working within a standard minimax framework, we provide tight upper and lower bounds on the optimal error in estimating the quality score vector $w^*$ under this class of models. The bounds depend on the topology of the comparison graph induced by the subset of pairs being compared via its Laplacian spectrum. Thus, in settings where the subset of pairs may be chosen, our results provide principled guidelines for making this choice. Finally, we compare these error rates to those under cardinal measurement models and show that the error rates in the ordinal and cardinal settings have identical scalings apart from constant pre-factors.Comment: 39 pages, 5 figures. Significant extension of arXiv:1406.661

Basic Endoscopic Findings — Normal and Pathological Findings

Since its inception, colonoscopy has evolved to become the cornerstone for colorectal imaging. The increasing indications for endoscopic evaluation and potential therapeutic intervention parallels technological advances and the expanding diagnostic and therapeutic capabilities of colonoscopy. The diagnostic and therapeutic yield of colonoscopy is highly user dependent. Thus, it is essential for the clinical endoscopist to perform a thorough endoscopic evaluation and be cognizant of normal and pathologic findings. This review details normal and pathologic endoscopic findings in a variety of disease states that are often encountered by the clinical endoscopist including colon polyps, inflammatory bowel disease, and infectious and non-infectious colitides. In addition, we review the diagnostic and therapeutic role of colonoscopy in the evaluation of an acute lower gastrointestinal bleed

Review of Techniques for Predicting Epileptic Seizure using EEG Signals

Epilepsy is a disorder that is characterized by seizures. Seizures are caused due to unusual electrical activity in the brain. Electroencephalogram (EEG) is used to read brain signal in form of 5 sub-bands viz. Alpha, Beta, Gamma, Theta and Delta. The features within each of theses sub-bands can be analysed and processed upon to predict the onset of a seizure. By accurate prediction of seizures, we can take preventive measures such as providing medication to reduce the severity of suffering of the patient. This pape r reviews the different techniques by which we can predict the onset of epileptic seizure using EEG signals. Each method utilizes one or more sub-bands of the EEG signal and classifies the patient records based on the features extracted through that set of sub-bands. Every method uses a different way to extract the sub bands. Also different classification algorithms are used in every method. We compare t e performance of each technique and analyse their efficacy

A Survey on Internet Traffic Measurement and Analysis

As the number of Internet users increasing rapidly in this world, Internet traffic is also increased. In computer network traffic measurement is the process of measuring the amount and type of traffic on a particular network. Internet traffic measurement and analysis are mostly used to characterize and analysis of network usage and user behaviour, but faces the problem of scalability under the explosive growth of Internet traffic and high speed access. It is not easy to handle Tera and Pera-byte traffic data with single server. Scalable Internet traffic measurement and analysis is difficult because a large dataset requires matching commutating and storage resources. To analyse this traffic multiple tools are available. But they do not perform well when the traffic data size increase. As data grows it is necessary to increase the necessary infrastructure to process it. The distributed File System can be used for this purpose, but it has certain limitation such as scalability, availability and fault tolerant. Hadoop is popular parallel processing framework that is widely used for working with large datasets and it is an open source distributed computing platform having MapReduce for distributed processing and HDFS to store huge amount of data. In future work we will present a Hadoop-based traffic monitoring system that perform a multiple types of analysis on large amount of internet traffic in a scalable manner Keywords- Traffic monitoring, Hadoop, MapReduce, HDFS, NetFlow

Vital bleaching for children with dental anomalies: EAPD members’ survey

AIM Understand EAPD members’ practices of vital bleaching for children with dental anomalies. METHODS An anonymous online survey sent via EAPD in January 2019, consisting of 13 questions with possible multiple answers and free text. RESULTS 110 responses from 24 countries were obtained. The majority worked in hospitals/universities (n = 69, 63%) or private practices (n = 50, 46%) and were specialists (n = 62, 57%) or senior academics (n = 35, 32%). Most respondents (n = 74 68%) did not provide vital bleaching for children. 88 respondents (80%) belonged to EU: of these, 46 (52%) were not aware of bleaching regulations. For respondents who provided bleaching 26 (72%) undertook home bleaching, using 10% carbamide peroxide (n = 21, 58%), most commonly for 2 weeks (n = 14, 39%), following establishment of the permanent dentition (n = 21, 58%). Deciding factors included: extent (n = 27, 75%) and shade (n = 26, 72%) of discolouration and child being teased by peers (n = 23, 64%). Main reasons for not bleaching included: concerns with side effects (n = 41; 55%) and not agreeing with bleaching (n = 23, 31%). Dentists who did not bleach managed a range of conditions, most frequently molar-incisor hypomineralisation (n = 57; 77%). The majority provided composite restorations with removal of tooth structure (n = 50; 68%) with a number opting for no treatment (n = 27, 37%). CONCLUSION This study shows wide variations in treatment of children’s dental anomalies across Europe. Fears of adverse effects and personal beliefs seemed to be the main deterrents to bleaching in children. Clinicians who provided bleaching tended to opt for more conservative techniques and to take children’s concerns into consideration

Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

In this paper, we present Anagram, a content anomaly detector that models a mixture of high-order n-grams (n > 1) designed to detect anomalous and suspicious network packet payloads. By using higher- order n-grams, Anagram can detect significant anomalous byte sequences and generate robust signatures of validated malicious packet content. The Anagram content models are implemented using highly efficient Bloom filters, reducing space requirements and enabling privacy-preserving cross-site correlation. The sensor models the distinct content flow of a network or host using a semi- supervised training regimen. Previously known exploits, extracted from the signatures of an IDS, are likewise modeled in a Bloom filter and are used during training as well as detection time. We demonstrate that Anagram can identify anomalous traffic with high accuracy and low false positive rates. Anagram’s high-order n-gram analysis technique is also resilient against simple mimicry attacks that blend exploits with normal appearing byte padding, such as the blended polymorphic attack recently demonstrated in. We discuss randomized n-gram models, which further raises the bar and makes it more difficult for attackers to build precise packet structures to evade Anagram even if they know the distribution of the local site content flow. Finally, Anagram-’s speed and high detection rate makes it valuable not only as a standalone sensor, but also as a network anomaly flow classifier in an instrumented fault-tolerant host-based environment; this enables significant cost amortization and the possibility of a symbiotic feedback loop that can improve accuracy and reduce false positive rates over time