Linear Koszul Duality II - Coherent sheaves on perfect sheaves

In this paper we continue the study (initiated in a previous article) of linear Koszul duality, a geometric version of the standard duality between modules over symmetric and exterior algebras. We construct this duality in a very general setting, and prove its compatibility with morphisms of vector bundles and base change.Comment: Final version, to appear in JLMS. The numbering differs from the published version, and is the one used in our papers [MR2] and [MR3] from the bibliograph

LINEAR KOSZUL DUALITY AND AFFINE HECKE ALGEBRAS

n this paper we prove that the linear Koszul duality equivalence constructed in a previous paper provides a geometric realization of the Iwahori-Matsumoto involution of affine Hecke algebras

Explanatory debugging: Supporting end-user debugging of machine-learned programs

Many machine-learning algorithms learn rules of behavior from individual end users, such as task-oriented desktop organizers and handwriting recognizers. These rules form a “program” that tells the computer what to do when future inputs arrive. Little research has explored how an end user can debug these programs when they make mistakes. We present our progress toward enabling end users to debug these learned programs via a Natural Programming methodology. We began with a formative study exploring how users reason about and correct a text-classification program. From the results, we derived and prototyped a concept based on “explanatory debugging”, then empirically evaluated it. Our results contribute methods for exposing a learned program's logic to end users and for eliciting user corrections to improve the program's predictions

Perancangan Sistem Monitoring Pengambilan Keputusan Pemakaian Bahan Bakar Pada Kapal Berbasis Logika Fuzzy

Banyaknya kecurangan-kecurangan yang dilakukan oleh pihak manajemen kapal dengan melakukan pencurian dan penjualan bahan bakar pada saat kapal melakukan pelayaran membuat pihak manajemen kapal banyak mengalami kerugian tidak hanya itu belum adanya sistem monitoring pemakaian bahan bakar pada kapal secara langsung yang bisa diakses oleh pihak manajemen kapal. Sistem pengambilan keputusan yang dirancang menggunakan logika fuzzy dengan tipe mamdani dengan 5 variabel masukan yaitu Engine (Rpm), Load (Ton), laju aliran rata-rata (kg/h), SFOC (Specific Fuel Oil Consumption) (gram/kWh) dan jarak pelayaran (miles) dan variabel keluaran yaitu Fuel Oil Consumption. Keakuratan hasil sistem pengambilan keputusan dibandingkan dengan data aktual mencapai 96.38% dan sistem logika fuzzy yang dikembangkan dapat diaplikasikan dalam sistem monitoring konsumsi bahan bakar di kapal.Dari sistem monitoring yang dikembangkan bukan hanya berada pada pihak ABK (Anak Buah Kapal) tetapi juga berada di pihak manajemen pusat yang dapat memonitor pemakaian bahan bakar dan bisa mengambil langkah-langkah yang diperlukan untuk meningkatkan efisiensi pemakaian bahan bakar

Potential impact of multiple interventions on HIV incidence in a hyperendemic region in Western Kenya : a modelling study

Background: Multiple prevention interventions, including early antiretroviral therapy initiation, may reduce HIV incidence in hyperendemic settings. Our aim was to predict the short-term impact of various single and combined interventions on HIV spreading in the adult population of Ndhiwa subcounty (Nyanza Province, Kenya). Methods: A mathematical model was used with data on adults (15-59 years) from the Ndhiwa HIV Impact in Population Survey to compare the impacts on HIV prevalence, HIV incidence rate, and population viral load suppression of various interventions. These interventions included: improving the cascade of care (use of three guidelines), increasing voluntary medical male circumcision (VMMC), and implementing pre-exposure prophylaxis (PrEP) use among HIV-uninfected women. Results: After four years, improving separately the cascade of care under the WHO 2013 guidelines and under the treat-all strategy would reduce the overall HIV incidence rate by 46 and 58 %, respectively, vs. the baseline rate, and by 35 and 49 %, respectively, vs. the implementation of the current Kenyan guidelines. With conservative and optimistic scenarios, VMMC and PrEP would reduce the HIV incidence rate by 15-25 % and 22-28 % vs. the baseline, respectively. Combining the WHO 2013 guidelines with VMMC would reduce the HIV incidence rate by 35-56 % and combining the treat-all strategy with VMMC would reduce it by 49-65 %. Combining the WHO 2013 guidelines, VMMC, and PrEP would reduce the HIV incidence rate by 46-67 %. Conclusions: The impacts of the WHO 2013 guidelines and the treat-all strategy were relatively close; their implementation is desirable to reduce HIV spread. Combining several strategies is promising in adult populations of hyperendemic areas but requires regular, reliable, and costly monitoring

Visual Encoding of Dissimilarity Data via Topology-Preserving Map Deformation

We present an efficient technique for topology-preserving map deformation and apply it to the visualization of dissimilarity data in a geographic context. Map deformation techniques such as value-by-area cartograms are well studied. However, using deformation to highlight (dis)similarity between locations on a map in terms of their underlying data attributes is novel. We also identify an alternative way to represent dissimilarities on a map through the use of visual overlays. These overlays are complementary to deformation techniques and enable us to assess the quality of the deformation as well as to explore the design space of blending the two methods. Finally, we demonstrate how these techniques can be useful in several—quite different—applied contexts: travel-time visualization, social demographics research and understanding energy flowing in a wide-area power-grid

Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics

Dozens of new models on fixation prediction are published every year and compared on open benchmarks such as MIT300 and LSUN. However, progress in the field can be difficult to judge because models are compared using a variety of inconsistent metrics. Here we show that no single saliency map can perform well under all metrics. Instead, we propose a principled approach to solve the benchmarking problem by separating the notions of saliency models, maps and metrics. Inspired by Bayesian decision theory, we define a saliency model to be a probabilistic model of fixation density prediction and a saliency map to be a metric-specific prediction derived from the model density which maximizes the expected performance on that metric given the model density. We derive these optimal saliency maps for the most commonly used saliency metrics (AUC, sAUC, NSS, CC, SIM, KL-Div) and show that they can be computed analytically or approximated with high precision. We show that this leads to consistent rankings in all metrics and avoids the penalties of using one saliency map for all metrics. Our method allows researchers to have their model compete on many different metrics with state-of-the-art in those metrics: "good" models will perform well in all metrics.Comment: published at ECCV 201