A comparison of unit root test criteria

During the past fifteen years, the ordinary least squares estimator and the corresponding pivotal statistic have been widely used for testing the unit root hypothesis in autoregressive processes. Recently, several new criteriia, based on the maximum likelihood estimators and weighted symmetric estimators, have been proposed. In this article, we describe several different test criteria. Results from a Monte Carlo study that compares the power of the different criteria indicates that the new tests are more powerful against the stationary alternative. Of the procedures studied, the weighted symmetric estimator and the unconditional maximum likelihood estimator provide the most powerful tests against the stationary alternative. As an illustration, we analyze the quarterly change in busine;ss investories

Properties of estimators of the parameters of autoregressive time series

Assuming that the errors of an autoregressive process form a sequence of martingale differences, the limiting distribution of the least squares estimator is derived. The limiting distribution of the least squares estimator is normal if the roots of the characteristic equation are less than unity in absolute value. It is shown that the limiting distribution for the unit root case obtained under the assumption of independent errors holds for martingale errors;For samples of the size encountered in practice, the least squares estimators are biased. Using large sample theory, approximations to the bias in the least squares estimators of the parameters of a stationary autoregressive process due to estimation of the mean are derived. The bias expression is used to develop modifications of the least squares estimator. The modification is extended to include the case when exactly one of the roots of the characteristic equation is equal to one;Estimation of the parameters of an autoregressive process with a mean that is a function of time is considered. Approximate expressions for the bias of the least squares estimators that is due to estimating the mean function are derived. For the special case when the mean function is a polynomial in time, a reparametrization that isolates the bias is proposed. Using the approximate expressions, a method of modifying the least squares estimators is proposed. Methods are suggested for the seasonal autoregressive processes;Two Monte Carlo studies examining the small sample properties of various estimators of the parameters of second-order autoregressive processes are considered. A second-order autoregressive process with constant mean, and a second-order autoregressive process with mean function linear in time are considered. Generally speaking the modified estimators performed better than the least squares estimator

Novelty Detection in Airport Baggage Conveyor Gear-Motors Using Synchro-Squeezing Transform and Self-Organizing Maps

A powerful continuous wavelet transform based signal processing tool named Synchro-squeezing transform (SST) has recently emerged in the context of non-stationary signal processing. Founded upon the premise of time-frequency (TF) reassignment, its basic objective is to provide a sharper representation of signals in the TF plane. Additionally, it can also extract the individual components of a non-stationary multi-component signal, which makes it attractive for rotating machinery signals. This work utilizes the decomposing power of SST transform to extract useful components from gear-motor signals in relevant sub-bands, followed by the application of standard rotating machinery condition indicators. For timely detection of faults in airport baggage conveyor gear-motors, a novelty detection technique based on the concept of self-organizing maps (SOM) is applied on the condition indicators. This approach promises improved anomaly detection performance than that can be achieved by applying condition indicators and SOM directly to the inherently complex raw-data. Data collected from conveyor gear-motors provides a test bed to demonstrate the efficacy of the proposed approach

Automated Fault Diagnosis in Rotating Machinery

Rotating machinery are an important part of industrial equipment. Their components are subjected to harsh operating environments, and hence experience significant wear and tear. It is necessary that they function efficiently all the time in order to avoid significant monetary losses and down-time. Monitoring the health of such machinery components has become an essential part in many industries to ensure their continuous operation and avoiding loss in productivity. Traditionally, signal processing methods have been employed to analyze the vibration signals emitted from rotating machines. With time, the complexity of machinery components has increased, which makes the process of condition monitoring complex and time consuming, and consequently costly. Hence, a paradigm shift in condition monitoring methods towards data-driven approaches has recently taken place towards reducing complexity in estimation, where the monitoring of machinery is focused on purely data-driven methods. In this thesis, a novel data-driven framework to condition monitoring of gearbox is studied and illustrated using simulated and experimental vibration signals. This involves analyzing the signal, deriving feature sets and using machine learning algorithms to discern the condition of machinery. The algorithm is implemented on data from a drivetrain dynamics simulator (DDS), equipment designed by Spectraquest Inc. for academic and industrial research purposes. Datasets from pristine state and faulty gearboxes are collected and the algorithms are tested against this data. This framework has been developed to facilitate automated monitoring of machinery in industries, thus reducing the need for manual supervision and interpretation

MANAJEMEN MATERIAL PADA PROYEK KONSTRUKSI JEMBATAN (STUDI KASUS JEMBATAN LANDAK KOTA PONTIANAK)

Jembatan merupakan sarana penghubung antar daratan yang terbelah oleh aliran sungai atau lembah. Dengan adanya jembatan maka diharapkan dapat membantu keberlangsungan perekonomian masyarakat serta mendukung dan memperlancar pembangunan dalam berbagai bidang. Kegiatan pembangunan Proyek Duplikasi Jembatan Landak Kota Pontianak merupakan salah satu solusi pemerintah dalam mengurai kemacetan lalu lintas yang kerap terjadi di area Jembatan Landak I. Kompleksitas proses pembangunan jembatan di atas air dan ketersediaan material pada lokasi proyek menjadi alasan penting perlu adanya manajemen material yang sistematis. Proses pembangunan pada daerah padat memerlukan perencanaan manajemen material yang baik, agar proses penyediaan material tidak terhambat, sehingga tidak mengganggu pekerjaan dan dapat berjalan secara kontinyu. Adapun tujuan dalam penelitian ini antara lain, merancang jadwal pemesanan dan penggunaan material, merancang struktur organisasi yang mengurus manajemen material, merancang sistem manajemen material, serta membuat formulir-formulir yang diperlukan untuk kebutuhan manajemen material. Penelitian dimulai dengan mengidentifikasi material yang dibutuhkan dalam proses pembangunan jembatan serta waktu tempuh pengiriman material. Hasil dari penelitian berupa sebuah sistem serta formulir-formulir manajemen material dari tahap awal identifikasi material hingga laporan logistik. Keberadaan sistem dan formulir sangat membantu proses pekerjaan di lapangan.Kata kunci: manajemen material, konstruksi jembatan, jembatan landak, kota Pontiana

Multiple unit roots in periodic autoregression

In this paper we propose a model selection strategy for a univariate periodic autoregressive time series which involves tests for one or more unit roots and for parameter restrictions corresponding to seasonal unit roots and multiple unit roots at the zero frequency. Examples of models that are considered are variants of the seasonal unit roots model and the periodic integration model. We show that the asymptotic distributions of various test statistics are the same as well-known distributions which are already tabulated. We apply our strategy to three empirical series to illustrate its ease of use. We find that evidence for seasonal unit roots based on nonperiodic models disappears when periodic representations are considered

Multiple unit roots in periodic autoregression

In this paper we propose a model selection strategy for a univariate periodic autoregressive time series which involves tests for one or more unit roots and for parameter restrictions corresponding to seasonal unit roots and multiple unit roots at the zero frequency. Examples of models that are considered are variants of the seasonal unit roots model and the periodic integration model. We show that the asymptotic distributions of various test statistics are the same as well-known distributions which are already tabulated. We apply our strategy to three empirical series to illustrate its ease of use. We find that evidence for seasonal unit roots based on nonperiodic models disappears when periodic representations are considered

Multiple mechanisms contribute to lateral transfer of an organophosphate degradation (opd) island in Sphingobium fuliginis ATCC 27551

The complete sequence of pPDL2 (37,317 bp), an indigenous plasmid of Sphingobium fuliginis ATCC 27551 that encodes genes for organophosphate degradation (opd), revealed the existence of a site-specific integrase (int) gene with an attachment site attP, typically seen in Integrative Mobilizable Elements (IME). In agreement with this sequence information, site-specific recombination was observed between pPDL2 and an artificial plasmid having a temperature-sensitive replicon and a cloned attB site at the 3′ end of the seryl tRNA gene of Sphingobium japonicum. The opd gene cluster on pPDL2 was found to be part of an active catabolic transposon with mobile elements y4qE and Tn3 at its flanking ends. Besides the previously reported opd cluster, this transposon contains genes coding for protocatechuate dioxygenase and for two transport proteins from the major facilitator family that are predicted to be involved in transport and metabolism of aromatic compounds. A pPDL2 derivative, pPDL2-K, was horizontally transferred into Escherichia coli and Acinetobacter strains, suggesting that the oriT identified in pPDL2 is functional. A well-defined replicative origin (oriV), repA was identified along with a plasmid addiction module relB/relE that would support stable maintenance of pPDL2 in Sphingobium fuliginis ATCC 27551. However, if pPDL2 is laterally transferred into hosts that do not support its replication, the opd cluster appears to integrate into the host chromosome, either through transposition or through site-specific integration. The data presented in this study help to explain the existence of identical opd genes among soil bacteria