Topological analysis of scalar fields with outliers

Given a real-valued function $f$ defined over a manifold $M$ embedded in $\mathbb{R}^d$, we are interested in recovering structural information about $f$ from the sole information of its values on a finite sample $P$. Existing methods provide approximation to the persistence diagram of $f$ when geometric noise and functional noise are bounded. However, they fail in the presence of aberrant values, also called outliers, both in theory and practice. We propose a new algorithm that deals with outliers. We handle aberrant functional values with a method inspired from the k-nearest neighbors regression and the local median filtering, while the geometric outliers are handled using the distance to a measure. Combined with topological results on nested filtrations, our algorithm performs robust topological analysis of scalar fields in a wider range of noise models than handled by current methods. We provide theoretical guarantees and experimental results on the quality of our approximation of the sampled scalar field

PENGARUH MODEL PEMBELAJARAN COMPETENCY BASED TRAINING TERHADAP HASIL BELAJAR PEMBUATAN PROTOTYPE PRODUK BARANG/JASA INSTALASI MOTOR LISTRIK PADA SISWA KELAS X1 TITL SMK NEGERI 2 KUPANG

Penelitian ini bertujuan untuk mengetahui: (1) Apakah ada pengaruh model pembelajaranCompetency Based Training terhadap hasil belajar pembuatan prototype produk barang/jasa instalasi motorlistrik pada siswa X1 TITL SMK Negeri 2 Kupang .(2) Sejauh manakah pengaruh model pembeajaranCompetency Based Training terhadap hasil belajar pembuatan prototype produk barang/jasa instalasi motorlistrik pada siswa X1 TITL SMK Negeri 2 Kupang. Metode penelitian yang digunakan dalam penelitian inieksperimen, desain rencangan penelitian yaitu Quasi-Experimental Design. Hasil penelitian menunjukkanbahwa model pembelajaran competency based training berpengaruh sebesar 40,0% dan > (4,762> 2,032) dan P value < α sebesar (0,000 < 0,05), maka dapat disimpulkan bahwa ada pengaruh secarasignifikan antara model pembelajaran competency based training terhadap hasil belajar siswa. Untuk variabelmodel pembelajaran direct learning berpengaruh sebesar 34,6 % dengan nilai > (4,244 > 2,032 ) P value < α sebesar (0,000 < 0,05) maka dapat disimpulkan bahwa ada pengaruh secara signifikan antaramodel pembelajaran direct learning terhadap hasil belajar. Untuk mengetahui sejauh manakah pengaruhmodel pembelajaran competency based training terhadap hasil belajar siswa dapat dilihat dari hasilperhitungan yang telah dilakukan menunjukkan bahwa selisih antara kedua model pembelajaran dalammeningkatkan hasil belajar peserta didik sebesar 5,4%. Sehingga dari hasil pengujian Independent Sample TTest maka diperoleh = 5,053 dan didapatkan nilai = 1.994 dengan df = 70, karena Nilai >(3,362 > 1,994) dengan nilai Signifikansi (2-tailed) sebesar 0,00 < 0,05 maka terdapat perbedaan yangsignifikan antara model pembelajaran competency based training dan model pembelajaran direct learningterhadap hasil belajar siswa

Robust Framework for PET Image Reconstruction Incorporating System and Measurement Uncertainties

In Positron Emission Tomography (PET), an optimal estimate of the radioactivity concentration is obtained from the measured emission data under certain criteria. So far, all the well-known statistical reconstruction algorithms require exactly known system probability matrix a priori, and the quality of such system model largely determines the quality of the reconstructed images. In this paper, we propose an algorithm for PET image reconstruction for the real world case where the PET system model is subject to uncertainties. The method counts PET reconstruction as a regularization problem and the image estimation is achieved by means of an uncertainty weighted least squares framework. The performance of our work is evaluated with the Shepp-Logan simulated and real phantom data, which demonstrates significant improvements in image quality over the least squares reconstruction efforts

Acyl Amidines by Pd-Catalyzed Aminocarbonylation : One-Pot Cyclizations and C-11 Labeling

A protocol for the carbonylative synthesis of acyl amidines from aryl halides, amidines, and carbon monoxide catalyzed by Pd(0) is reported herein. Notably, carbon monoxide is generated ex situ from a solid CO source, and several productive palladium ligands were identified with complementary benefits and substrate scope. Furthermore, sequential one-pot, two-step protocols for the synthesis of 1,2,4-triazoles and 1,2,4-oxadiazoles via acyl amidine intermediates are reported. In addition, this approach was extended to isotopic labeling using [11C]carbon monoxide to allow, for the first time, synthesis of 11C-labeled acyl amidines as well as a 11C-labeled 1,2,4-oxadiazole

Acyl Amidines by Pd-Catalyzed Aminocarbonylation: One-Pot Cyclizations and ¹¹C Labeling

A protocol for the carbonylative synthesis of acyl amidines from aryl halides, amidines, and carbon monoxide catalyzed by Pd(0) is reported herein. Notably, carbon monoxide is generated ex situ from a solid CO source, and several productive palladium ligands were identified with complementary benefits and substrate scope. Furthermore, sequential one-pot, two-step protocols for the synthesis of 1,2,4-triazoles and 1,2,4-oxadiazoles via acyl amidine intermediates are reported. In addition, this approach was extended to isotopic labeling using [11C]carbon monoxide to allow, for the first time, synthesis of 11C-labeled acyl amidines as well as a 11C-labeled 1,2,4-oxadiazole