Sparsity-Based Error Detection in DC Power Flow State Estimation

This paper presents a new approach for identifying the measurement error in the DC power flow state estimation problem. The proposed algorithm exploits the singularity of the impedance matrix and the sparsity of the error vector by posing the DC power flow problem as a sparse vector recovery problem that leverages the structure of the power system and uses $l_1$-norm minimization for state estimation. This approach can provably compute the measurement errors exactly, and its performance is robust to the arbitrary magnitudes of the measurement errors. Hence, the proposed approach can detect the noisy elements if the measurements are contaminated with additive white Gaussian noise plus sparse noise with large magnitude. The effectiveness of the proposed sparsity-based decomposition-DC power flow approach is demonstrated on the IEEE 118-bus and 300-bus test systems

Kebutuhan Dan Pencarian Informasi Oleh Siswa Di Perpustakaan Smk Negeri 11 Semarang

Penelitian ini mengkaji tentang kajian pemakai perpustakaan. Penelitian ini sendiri untuk mengetahui kebutuhan dan pencarian informasi siswa dalam menelusur informasi yang dilakukan di Perpustakaan SMK Negeri 11 Semarang. Permasalahan yang dikaji adalah bagaimana kebutuhan dan pencarian informasi siswa di Perpustakaan SMK Negeri 11.Penelitian ini merupakan penelitian diskriptif kuantitatif dengan bentuk studi kasus, dengan populasi sejumlah 1517 orang siswa dan sampel sejumlah 160 orang siswa. Untuk memperoleh data yang valid penulis menggunakan beberapa metode pengumpulan data yaitu menggunakan angket/ kuesioner, observasi, dan wawancara. Untuk mengkatagorikan tingkat gejala yang diamati yaitu kebutuhan dan pencarian informasi siswa di Perpustakaan SMK Negeri 11 adalah dengan distribusi frekuensi. Hasil penelitian ini menunjukkan bahwa siswa membutuhkan sumber dan sarana informasi yang lain. Hal tersebut ditunjukkan dengan sebagian besar tujuan mereka berkunjung ke Perpustakaan SMK Negeri 11 untuk mengerjakan tugas dari guru. Adapun motivasi untuk datang ke Perpustakaan SMK Negeri 11, sebagian besar adalah karena menyelesaikan tugas yang sedang dikerjakan. Jenis informasi yang dibutuhkan responden adalah mapel .Bentuk informasi berupa buku teks yang dibutuhkan di perpustakaan. Pemanfaatan bahan pustaka khususnya buku yang dipinjam pada umumnya adalah antara 2 sampai dengan 4 buku dalam satu bulan. Selanjutnya cara penelusuran informasi yang dilakukan oleh hampir setengah siswa adalah mencari sendiri langsung ketempat koleksi dan hamper setengah siswa bertanya langsung ke petugas perpustakaan. Untuk upaya pencarian informasi selain di perpustakaan SMK Negeri 11, setengah dari siswa adalah mencari informasi yang sejenis melalui internet. Alasan siswa mencari di tempat lain adalah koleksi tidak ada dan hamper setengah yang lain sebagai bahan perbandingan koleksi yang lain

Forecasting Remission Time of a Treatment Method for Leukemia as an Application to Statistical Inference Approach

In this paper, Weibull-Linear Exponential distribution (WLED) has been investigated whether being it is a well - fit distribution to a clinical real data. These data represent the duration of remission achieved by a certain drug used in the treatment of leukemia for a group of patients. The statistical inference approach is used to estimate the parameters of the WLED through the set of the fitted data. The estimated parameters are utilized to evaluate the survival and hazard functions and hence assessing the treatment method through forecasting the duration of remission times of patients. A two-sample prediction approach has been applied to obtain a predictive sample based on the Bayes estimates of the parameters. The statistical inference approach is applied to the case of censored data namely Type-II hybrid censoring scheme, which is common in clinical studies

Weibull-Linear Exponential Distribution and Its Applications

In this article, a new four-parameter lifetime distribution, namely, the Weibull-Linear exponential distribution is defined and studied. Several of its structural properties such as quartiles, moments, mean waiting time, mean residual lifetime, Renyi entropy, mode, and order statistics are derived. Based on the idea of the Weibull T − X family, the new density function of this model is developed. The model parameters, as well as some of the lifetime parameters (reliability and failure rate functions), are estimated using the maximum likelihood method. Asymptotic confidence intervals estimates of the model parameters are also evaluated by using the Fisher information matrix. Moreover, to construct the asymptotic confidence intervals of the reliability and failure rate functions, we need to find their variance of them, which are approximated by the delta method. A real data set is used to illustrate the application of the Weibull-Linear Exponential distribution

A "missing" family of classical orthogonal polynomials

We study a family of "classical" orthogonal polynomials which satisfy (apart from a 3-term recurrence relation) an eigenvalue problem with a differential operator of Dunkl-type. These polynomials can be obtained from the little $q$-Jacobi polynomials in the limit $q=-1$. We also show that these polynomials provide a nontrivial realization of the Askey-Wilson algebra for $q=-1$.Comment: 20 page

Self-aligned nanoscale SQUID on a tip

A nanometer-sized superconducting quantum interference device (nanoSQUID) is fabricated on the apex of a sharp quartz tip and integrated into a scanning SQUID microscope. A simple self-aligned fabrication method results in nanoSQUIDs with diameters down to 100 nm with no lithographic processing. An aluminum nanoSQUID with an effective area of 0.034 $\mu$m$^2$ displays flux sensitivity of 1.8$\cdot 10^{-6}$ $\Phi_0/\mathrm{Hz}^{1/2} and operates in fields as high as 0.6 T. With projected spin sensitivity of 65$\mu_B/\mathrm{Hz}^{1/2}$ and high bandwidth, the SQUID on a tip is a highly promising probe for nanoscale magnetic imaging and spectroscopy.Comment: 14 manuscript pages, 5 figure

Adaptive covariance estimation method for LiDAR-Aided multi-sensor integrated navigation systems

The accurate estimation of measurements covariance is a fundamental problem in sensors fusion algorithms and is crucial for the proper operation of filtering algorithms. This paper provides an innovative solution for this problem and realizes the proposed solution on a 2D indoor navigation system for unmanned ground vehicles (UGVs) that fuses measurements from a MEMS-grade gyroscope, speed measurements and a light detection and ranging (LiDAR) sensor. A computationally efficient weighted line extraction method is introduced, where the LiDAR intensity measurements are used, such that the random range errors and systematic errors due to surface reflectivity in LiDAR measurements are considered. The vehicle pose change is obtained from LiDAR line feature matching, and the corresponding pose change covariance is also estimated by a weighted least squares-based technique. The estimated LiDAR-based pose changes are applied as periodic updates to the Inertial Navigation System (INS) in an innovative extended Kalman filter (EKF) design. Besides, the influences of the environment geometry layout and line estimation error are discussed. Real experiments in indoor environment are performed to evaluate the proposed algorithm. The results showed the great consistency between the LiDAR-estimated pose chan

INS/GPS/LiDAR integrated navigation system for urban and indoor environments using hybrid scan matching algorithm

This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory