Prochlo: Strong Privacy for Analytics in the Crowd

The large-scale monitoring of computer users' software activities has become commonplace, e.g., for application telemetry, error reporting, or demographic profiling. This paper describes a principled systems architecture---Encode, Shuffle, Analyze (ESA)---for performing such monitoring with high utility while also protecting user privacy. The ESA design, and its Prochlo implementation, are informed by our practical experiences with an existing, large deployment of privacy-preserving software monitoring. (cont.; see the paper

A Cost-based Optimizer for Gradient Descent Optimization

As the use of machine learning (ML) permeates into diverse application domains, there is an urgent need to support a declarative framework for ML. Ideally, a user will specify an ML task in a high-level and easy-to-use language and the framework will invoke the appropriate algorithms and system configurations to execute it. An important observation towards designing such a framework is that many ML tasks can be expressed as mathematical optimization problems, which take a specific form. Furthermore, these optimization problems can be efficiently solved using variations of the gradient descent (GD) algorithm. Thus, to decouple a user specification of an ML task from its execution, a key component is a GD optimizer. We propose a cost-based GD optimizer that selects the best GD plan for a given ML task. To build our optimizer, we introduce a set of abstract operators for expressing GD algorithms and propose a novel approach to estimate the number of iterations a GD algorithm requires to converge. Extensive experiments on real and synthetic datasets show that our optimizer not only chooses the best GD plan but also allows for optimizations that achieve orders of magnitude performance speed-up.Comment: Accepted at SIGMOD 201

Growth and yield response of garlic (Allium sativum l.) varieties to nitrogen fertilizer rates at Gantaafeshum, northern Ethiopia

Garlic (Allium sativum L.) is one of the most important vegetable crops produced in Tigray region; however, farmers are producing the crop from the available cultivars without or with very low rates of nitrogen fertilizer. The cultivars produced in the region were not evaluated in comparison to improved varieties to the response of nitrogen fertilizer. Therefore, this experiment was conducted during 2014/2015 in Gantaafeshum district in Tigray region with objectives of assessing the effect of nitrogen rates on yield and yield related traits of garlic cultivars and thereby identifying adaptable and high yielding cultivars with higher market demand. Seven garlic cultivars (three improved, three locally introduced and one local) and four N fertilizer rates (0, 41, 82, 123 kg N ha-1) were arranged as 7 x 4 factorial treatments and laid out as a randomized complete block design with three replications. All yield and yield related traits were significantly influenced by the interaction of cultivar and nitrogen fertilizer except leaf length (cm), leaf number per plant, bulb length (cm) and sizes of bulbs and cloves of different categories that were significantly influenced either by both cultivar and nitrogen or one of these. The highest total yield was obtained from the cultivar Bora 1 (12.61 t ha-1) at the rate of 82 kg N ha-1 but the yield decreased to 12.27t ha-1 as the nitrogen level increased to 123 kg N ha-1. The lowest yield was recorded from the local cultivar Guahgot (5.31 t ha-1) without N fertilizer application. The quality was determined based on number of marketable bulbs and weight of cloves.Bora-1 had 44.44 and 20% of bulbs categorized under medium and large categories, respectively. This cultivar had also the highest proportion of marketable cloves categorized under medium (27.10%) and large (33.80%) clove categories. The cost benefit analysis indicated that cultivar Felegdaero followed by Bora 1 both at 41kg N ha-1 rates had maximum marginal economic return of 148.24 and 135.84, respectively. Therefore, it is possible to suggest the advantage of growing cultivar Bora-1 at 82 kg N ha-1followed by Tsedey and Felegdaero varieties both in combination of 123 kg N ha-1at Guahgot, Gantaafeshum district and in other areas having similar agro-ecology

Poincare recurrences and transient chaos in systems with leaks

In order to simulate observational and experimental situations, we consider a leak in the phase space of a chaotic dynamical system. We obtain an expression for the escape rate of the survival probability applying the theory of transient chaos. This expression improves previous estimates based on the properties of the closed system and explains dependencies on the position and size of the leak and on the initial ensemble. With a subtle choice of the initial ensemble, we obtain an equivalence to the classical problem of Poincare recurrences in closed systems, which is treated in the same framework. Finally, we show how our results apply to weakly chaotic systems and justify a split of the invariant saddle in hyperbolic and nonhyperbolic components, related, respectively, to the intermediate exponential and asymptotic power-law decays of the survival probability.Comment: Corrected version, as published. 12 pages, 9 figure

Karakteristik Kemiskinan dan Penanggulangannya di Kabupaten Sidoarjo

This article aims to analyze and to describe the characteristics of poverty as wellas reduction policies/programs in Sidoarjo Regency. The location of this exploratory studyis conducted in Sidoarjo Regency. Basic argument is caused Sidoarjo Regency Regencyhas the lowest poverty rate in East Java as well as get pro poor award from Indonesiangovernment in 2011 and 2012. The subjects of this study as many as thirty people withthe key informants Vice Regent of Sidoarjo. Data is collected through interviews to allinformants. Then its data is coded and analyzed through grounded analyzing techniquesfrom Strauss and Corbin. The results show that poverty characteristic in Sidoarjo Regencyis caused cultural in both rural and urban area. Implementation of existing povertyreduction programs are still not optimal and targeted

Pengaruh Jarak Tanam Dan Teknik Pengendalian Gulma Pada Pertumbuhan Dan Hasil Tanaman Ubi Jalar (Ipomoea Batatas L.)

Penelitian bertujuan untuk mempelajari pengaruh kombinasi berbagai jarak tanam dan metode pengendalian gulma pada pertumbuhan dan hasil tanaman ubi jalar. Penelitian dilaksanakan pada bulan Juli sampai bulan November 2012 di Dusun Bulakunci, Desa Nogosari, Kecamatan Pacet Kabupaten Mojokerto. Penelitian menggunakan Rancangan Acak Kelompok (RAK) yang terdiri dari 2 kombinasi perla-kuan yaitu Jarak Tanam (J) dan teknik pengendalian gulma (G) yang diulang 3 kali. Pada jarak tanam ada Jarak tanam 75 x 20 cm (J1) dan Jarak tanam 75 x 30 cm (J2), dan pada metode pengendalian gulma ada Tanpa pengendalian gulma (G0), Bebas gulma (G1), Penyiangan 40 hst (G2), Aplikasi herbisida pra-tumbuh oksifluorfen 1 l ha-1 (G3) dan Aplikasi herbisida pra-tumbuh oksifluorfen 1 l ha-1 dan penyiangan 40 hst (G4). Hasil penelitian menunjukkan bahwa penanaman ubi jalar dengan jarak tanam 70 x 20 cm dengan metode pengendalian gulma kombinasi antara penyemprotan herbisida pra-tumbuh oksifluorfen 1 liter ha-1 dan penyiangan 40 hst sangat efektif dalam mengendalikan gulma serta mampu me-ningkatkan pertumbuhan ubi jalar jika dibandingkan tanpa pengendalian gulma, penyiangan 40 hst maupun penyemprotan herbisida pra-tumbuh oksifluorfen 1 l ha-1. Penggunaan jarak tanam ubi jalar 70 x 30 cm menghasilkan jumlah hasil dan bobot segar tanaman yang lebih tinggi dari jarak tanam 70 x 20 cm

Using Flow Specifications of Parameterized Cache Coherence Protocols for Verifying Deadlock Freedom

We consider the problem of verifying deadlock freedom for symmetric cache coherence protocols. In particular, we focus on a specific form of deadlock which is useful for the cache coherence protocol domain and consistent with the internal definition of deadlock in the Murphi model checker: we refer to this deadlock as a system- wide deadlock (s-deadlock). In s-deadlock, the entire system gets blocked and is unable to make any transition. Cache coherence protocols consist of N symmetric cache agents, where N is an unbounded parameter; thus the verification of s-deadlock freedom is naturally a parameterized verification problem. Parametrized verification techniques work by using sound abstractions to reduce the unbounded model to a bounded model. Efficient abstractions which work well for industrial scale protocols typically bound the model by replacing the state of most of the agents by an abstract environment, while keeping just one or two agents as is. However, leveraging such efficient abstractions becomes a challenge for s-deadlock: a violation of s-deadlock is a state in which the transitions of all of the unbounded number of agents cannot occur and so a simple abstraction like the one above will not preserve this violation. In this work we address this challenge by presenting a technique which leverages high-level information about the protocols, in the form of message sequence dia- grams referred to as flows, for constructing invariants that are collectively stronger than s-deadlock. Efficient abstractions can be constructed to verify these invariants. We successfully verify the German and Flash protocols using our technique

The Case for Learned Index Structures

Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not. In this exploratory research paper, we start from this premise and posit that all existing index structures can be replaced with other types of models, including deep-learning models, which we term learned indexes. The key idea is that a model can learn the sort order or structure of lookup keys and use this signal to effectively predict the position or existence of records. We theoretically analyze under which conditions learned indexes outperform traditional index structures and describe the main challenges in designing learned index structures. Our initial results show, that by using neural nets we are able to outperform cache-optimized B-Trees by up to 70% in speed while saving an order-of-magnitude in memory over several real-world data sets. More importantly though, we believe that the idea of replacing core components of a data management system through learned models has far reaching implications for future systems designs and that this work just provides a glimpse of what might be possible