Comment: Monitoring Networked Applications With Incremental Quantile Estimation

Comment: Monitoring Networked Applications With Incremental Quantile Estimation [arXiv:0708.0302]Comment: Published at http://dx.doi.org/10.1214/088342306000000619 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Evaluation of an Abnormal Urinalysis in the Asymptomatic Patient

Physicians are occasionally presented with the problem of evaluating a patient who has an abnormal urinalysis but who has no other sign or symptom of genitourinary (GU) tract disease. For example, patients may present with hematuria, pyuria or slight proteinuria, but they may have no other clinical or laboratory abnormality to suggest glomerulonephritis, renal failure, urinary tract infection, obstruction, hypertension, or stones. There are a wide variety of lesions which may produce such isolated abnormalities, and a rational approach is indispensable in preparing an efficient and definitive diagnostic plan

Using data network metrics, graphics, and topology to explore network characteristics

Yehuda Vardi introduced the term network tomography and was the first to propose and study how statistical inverse methods could be adapted to attack important network problems (Vardi, 1996). More recently, in one of his final papers, Vardi proposed notions of metrics on networks to define and measure distances between a network's links, its paths, and also between different networks (Vardi, 2004). In this paper, we apply Vardi's general approach for network metrics to a real data network by using data obtained from special data network tools and testing procedures presented here. We illustrate how the metrics help explicate interesting features of the traffic characteristics on the network. We also adapt the metrics in order to condition on traffic passing through a portion of the network, such as a router or pair of routers, and show further how this approach helps to discover and explain interesting network characteristics.Comment: Published at http://dx.doi.org/10.1214/074921707000000058 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Management of the Nephrotic Syndrome

The nephrotic syndrome represents one of the major clinical problems in nephrology. It is usually defined as the constellation of clinical findings which includes edema, massive proteinuria, low serum albumin, high serum cholesterol, and the presence of oval fat bodies in the urine. However, if we focus on the primary disturbance in the patient, that is, massive proteinuria, the nephrotic syndrome may be defined more simply as the clinical and metabolic consequences of persistent and massive proteinuria. The other manifestations listed in the classic definition are all inconstant and secondary to this loss of protein and may be found in other clinical disorders. Proteinuria is considered massive when it is greater than 3.5 mg/kg body weight per day, and persistent when present for many weeks or months. For diagnosis of the nephrotic syndrome, 24-hour urine protein excretion must be measured; a spot measurement is inadequate because some patients with massive proteinuria produce occasional specimens with little or no protein

Internationalization of K-12 Schools Through the Eyes of Public School Principals

Today’s teacher education students have more opportunities than ever to incorporate study abroad into their degree and licensure requirements. This Capstone examines the value that public school principals place on internationalization, especially when it comes to hiring teachers. I approached this qualitative study utilizing action research through case studies. Data was gathered by conducting six in-depth interviews. Of these, three are current principals and three have been principals their entire careers and are now retired. The main research question is; what value do principals in Wake County, North Carolina place on global competence of teacher job applicants? The findings answer much more than this question and indicate that there is a growing emphasis on global awareness in public schools. Despite the emphasis on global awareness, there is no common understanding of what that term actually means or what it looks like in the classroom. Regardless of these inconsistencies, principals place a high value on international experiences when it comes to hiring teachers. Implications for professional practice as a result of this research include a demonstrated need for consistency and structure for internationalizing the public school system. Further, this research is useful for teacher candidates and teacher education institutions to gain a deeper understanding of how to gain a competitive edge through impactful global experiences

Selfish Network Creation with Non-Uniform Edge Cost

Network creation games investigate complex networks from a game-theoretic point of view. Based on the original model by Fabrikant et al. [PODC'03] many variants have been introduced. However, almost all versions have the drawback that edges are treated uniformly, i.e. every edge has the same cost and that this common parameter heavily influences the outcomes and the analysis of these games. We propose and analyze simple and natural parameter-free network creation games with non-uniform edge cost. Our models are inspired by social networks where the cost of forming a link is proportional to the popularity of the targeted node. Besides results on the complexity of computing a best response and on various properties of the sequential versions, we show that the most general version of our model has constant Price of Anarchy. To the best of our knowledge, this is the first proof of a constant Price of Anarchy for any network creation game.Comment: To appear at SAGT'1

Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees

Deep Reinforcement Learning (DRL) has achieved impressive success in many applications. A key component of many DRL models is a neural network representing a Q function, to estimate the expected cumulative reward following a state-action pair. The Q function neural network contains a lot of implicit knowledge about the RL problems, but often remains unexamined and uninterpreted. To our knowledge, this work develops the first mimic learning framework for Q functions in DRL. We introduce Linear Model U-trees (LMUTs) to approximate neural network predictions. An LMUT is learned using a novel on-line algorithm that is well-suited for an active play setting, where the mimic learner observes an ongoing interaction between the neural net and the environment. Empirical evaluation shows that an LMUT mimics a Q function substantially better than five baseline methods. The transparent tree structure of an LMUT facilitates understanding the network's learned knowledge by analyzing feature influence, extracting rules, and highlighting the super-pixels in image inputs.Comment: This paper is accepted by ECML-PKDD 201

Comments on the nature of persistence in dendrochronologic records with implications for hydrology and climatology [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Jurate Landwehr discussed the use of surrogate hydrologic records, specifically dendrochronologic records, to study the nature of persistence which is characteristic of hydrologic phenomenon. These proxy records are generally considered to correspond to such hydrologic measures as mean annual discharge but are much longer in length than directly measured hydrologic records. Consequently, they allow one to explore questions pertaining to the structure of candidate stochastic processes with greater validity than permitted by the latter

Greedy Selfish Network Creation

We introduce and analyze greedy equilibria (GE) for the well-known model of selfish network creation by Fabrikant et al.[PODC'03]. GE are interesting for two reasons: (1) they model outcomes found by agents which prefer smooth adaptations over radical strategy-changes, (2) GE are outcomes found by agents which do not have enough computational resources to play optimally. In the model of Fabrikant et al. agents correspond to Internet Service Providers which buy network links to improve their quality of network usage. It is known that computing a best response in this model is NP-hard. Hence, poly-time agents are likely not to play optimally. But how good are networks created by such agents? We answer this question for very simple agents. Quite surprisingly, naive greedy play suffices to create remarkably stable networks. Specifically, we show that in the SUM version, where agents attempt to minimize their average distance to all other agents, GE capture Nash equilibria (NE) on trees and that any GE is in 3-approximate NE on general networks. For the latter we also provide a lower bound of 3/2 on the approximation ratio. For the MAX version, where agents attempt to minimize their maximum distance, we show that any GE-star is in 2-approximate NE and any GE-tree having larger diameter is in 6/5-approximate NE. Both bounds are tight. We contrast these positive results by providing a linear lower bound on the approximation ratio for the MAX version on general networks in GE. This result implies a locality gap of $\Omega(n)$ for the metric min-max facility location problem, where n is the number of clients.Comment: 28 pages, 8 figures. An extended abstract of this work was accepted at WINE'1

Coalition Resilient Outcomes in Max k-Cut Games

We investigate strong Nash equilibria in the \emph{max $k$-cut game}, where we are given an undirected edge-weighted graph together with a set $\{1,\ldots, k\}$ of $k$ colors. Nodes represent players and edges capture their mutual interests. The strategy set of each player $v$ consists of the $k$ colors. When players select a color they induce a $k$-coloring or simply a coloring. Given a coloring, the \emph{utility} (or \emph{payoff}) of a player $u$ is the sum of the weights of the edges $\{u,v\}$ incident to $u$, such that the color chosen by $u$ is different from the one chosen by $v$. Such games form some of the basic payoff structures in game theory, model lots of real-world scenarios with selfish agents and extend or are related to several fundamental classes of games. Very little is known about the existence of strong equilibria in max $k$-cut games. In this paper we make some steps forward in the comprehension of it. We first show that improving deviations performed by minimal coalitions can cycle, and thus answering negatively the open problem proposed in \cite{DBLP:conf/tamc/GourvesM10}. Next, we turn our attention to unweighted graphs. We first show that any optimal coloring is a 5-SE in this case. Then, we introduce $x$-local strong equilibria, namely colorings that are resilient to deviations by coalitions such that the maximum distance between every pair of nodes in the coalition is at most $x$. We prove that $1$-local strong equilibria always exist. Finally, we show the existence of strong Nash equilibria in several interesting specific scenarios.Comment: A preliminary version of this paper will appear in the proceedings of the 45th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM'19