Pendeteksian Outlier pada Regresi Nonlinier dengan Metode statistik Likelihood Displacement

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Siti Tabi'atul Hasanah

2012-11-01

Full Text Available Outlier is an observation that much different (extreme from the other observational data, or data can be interpreted that do not follow the general pattern of the model. Sometimes outliers provide information that can not be provided by other data. That's why outliers should not just be eliminated. Outliers can also be an influential observation. There are many methods that can be used to detect of outliers. In previous studies done on outlier detection of linear regression. Next will be developed detection of outliers in nonlinear regression. Nonlinear regression here is devoted to multiplicative nonlinear regression. To detect is use of statistical method likelihood displacement. Statistical methods abbreviated likelihood displacement (LD is a method to detect outliers by removing the suspected outlier data. To estimate the parameters are used to the maximum likelihood method, so we get the estimate of the maximum. By using LD method is obtained i.e likelihood displacement is thought to contain outliers. Further accuracy of LD method in detecting the outliers are shown by comparing the MSE of LD with the MSE from the regression in general. Statistic test used is Λ. Initial hypothesis was rejected when proved so is an outlier.

Baseline Estimation and Outlier Identification for Halocarbons

Science.gov (United States)

Wang, D.; Schuck, T.; Engel, A.; Gallman, F.

2017-12-01

The aim of this paper is to build a baseline model for halocarbons and to statistically identify the outliers under specific conditions. In this paper, time series of regional CFC-11 and Chloromethane measurements was discussed, which taken over the last 4 years at two locations, including a monitoring station at northwest of Frankfurt am Main (Germany) and Mace Head station (Ireland). In addition to analyzing time series of CFC-11 and Chloromethane, more importantly, a statistical approach of outlier identification is also introduced in this paper in order to make a better estimation of baseline. A second-order polynomial plus harmonics are fitted to CFC-11 and chloromethane mixing ratios data. Measurements with large distance to the fitting curve are regard as outliers and flagged. Under specific requirement, the routine is iteratively adopted without the flagged measurements until no additional outliers are found. Both model fitting and the proposed outlier identification method are realized with the help of a programming language, Python. During the period, CFC-11 shows a gradual downward trend. And there is a slightly upward trend in the mixing ratios of Chloromethane. The concentration of chloromethane also has a strong seasonal variation, mostly due to the seasonal cycle of OH. The usage of this statistical method has a considerable effect on the results. This method efficiently identifies a series of outliers according to the standard deviation requirements. After removing the outliers, the fitting curves and trend estimates are more reliable.

Spatial Outlier Detection of CO2 Monitoring Data Based on Spatial Local Outlier Factor

OpenAIRE

Liu Xin; Zhang Shaoliang; Zheng Pulin

2015-01-01

Spatial local outlier factor (SLOF) algorithm was adopted in this study for spatial outlier detection because of the limitations of the traditional static threshold detection. Based on the spatial characteristics of CO2 monitoring data obtained in the carbon capture and storage (CCS) project, the K-Nearest Neighbour (KNN) graph was constructed using the latitude and longitude information of the monitoring points to identify the spatial neighbourhood of the monitoring points. Then ...

Outlier Ranking via Subspace Analysis in Multiple Views of the Data

DEFF Research Database (Denmark)

Muller, Emmanuel; Assent, Ira; Iglesias, Patricia

2012-01-01

, a novel outlier ranking concept. Outrank exploits subspace analysis to determine the degree of outlierness. It considers different subsets of the attributes as individual outlier properties. It compares clustered regions in arbitrary subspaces and derives an outlierness score for each object. Its...... principled integration of multiple views into an outlierness measure uncovers outliers that are not detectable in the full attribute space. Our experimental evaluation demonstrates that Outrank successfully determines a high quality outlier ranking, and outperforms state-of-the-art outlierness measures....

Socio economic determinants of health insurance in India: the case of Hyderabad city

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J. Yellaiah

2012-09-01

Full Text Available Health has been declared as a fundamental human right in India and several other countries. Theoretical works as well as empirical evidences clearly show the positive linkage between good health and economic development. The policy concern in developing countries including India is not only to reach the entire population with adequate healthcare services, but also to secure an acceptable level of health for all the people through the application of primary healthcare programs. Health insurance is one of the most important aspects of health care management system. This paper identifies the socio economic determinants of demand for health insurance in India taking Hyderabad as the case. For this purpose, a sample survey has been conducted taking 200 sample units in Hyderabad city. The logistic model has been used to identify the determinants of health insurance. We conclude that the main determinants of demand for health insurance in Hyderabad are the occupation, income, health expenditure and awareness. The other variables such as the age and education are positively associated with demand for health insurance but are not statistically significant. In view of these findings, some policy suggestions are made.

Selection of tests for outlier detection

NARCIS (Netherlands)

Bossers, H.C.M.; Hurink, Johann L.; Smit, Gerardus Johannes Maria

Integrated circuits are tested thoroughly in order to meet the high demands on quality. As an additional step, outlier detection is used to detect potential unreliable chips such that quality can be improved further. However, it is often unclear to which tests outlier detection should be applied and

Benign breast diseases: experience at isra university hospital, hyderabad, pakistan

International Nuclear Information System (INIS)

Memon, W.; Mannan, A.; Gilani, R.

2017-01-01

To determine the frequency of Benign Breast Disease (BBD) in Isra University Hospital Hyderabad. Methodology: This prospective, descriptive study was carried out at Isra University Hospital Hyderabad, Pakistan from January 2014 and January 2016. Data including age, presenting complaints, clinical examination, histopathological examination and treatment given were all collected from patients presenting in surgery department with breast complaints and recorded. All patients with breast malignancy and trauma of breast were excluded from the study. Data were analyzed using SPSS v. 17. Results: A total of 105 patients with benign breast disease admitted during the study period. Mean age of patients was 30 years (range 13-65). Fibroadenoma was the most common diagnosis in 45(42%), followed by fibrocystic disease 25(23%), breast abscesses 15(14%), sebaceous cyst 10(9.5%), duct ectasia 4(3.8%) and Phylloides 2(1.9%) cases. Conclusion: Fibroadenoma was the most common BBD followed by fibrocystic disease with presentation of either discrete mass or mastalgia. (author)

A Modified Approach for Detection of Outliers

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Iftikhar Hussain Adil

2015-04-01

Full Text Available Tukey’s boxplot is very popular tool for detection of outliers. It reveals the location, spread and skewness of the data. It works nicely for detection of outliers when the data are symmetric. When the data are skewed it covers boundary away from the whisker on the compressed side while declares erroneous outliers on the extended side of the distribution. Hubert and Vandervieren (2008 made adjustment in Tukey’s technique to overcome this problem. However another problem arises that is the adjusted boxplot constructs the interval of critical values which even exceeds from the extremes of the data. In this situation adjusted boxplot is unable to detect outliers. This paper gives solution of this problem and proposed approach detects outliers properly. The validity of the technique has been checked by constructing fences around the true 95% values of different distributions. Simulation technique has been applied by drawing different sample size from chi square, beta and lognormal distributions. Fences constructed by the modified technique are close to the true 95% than adjusted boxplot which proves its superiority on the existing technique.

Detection of Outliers in Regression Model for Medical Data

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Stephen Raj S

2017-07-01

Full Text Available In regression analysis, an outlier is an observation for which the residual is large in magnitude compared to other observations in the data set. The detection of outliers and influential points is an important step of the regression analysis. Outlier detection methods have been used to detect and remove anomalous values from data. In this paper, we detect the presence of outliers in simple linear regression models for medical data set. Chatterjee and Hadi mentioned that the ordinary residuals are not appropriate for diagnostic purposes; a transformed version of them is preferable. First, we investigate the presence of outliers based on existing procedures of residuals and standardized residuals. Next, we have used the new approach of standardized scores for detecting outliers without the use of predicted values. The performance of the new approach was verified with the real-life data.

Outlier Detection Techniques For Wireless Sensor Networks: A Survey

NARCIS (Netherlands)

Zhang, Y.; Meratnia, Nirvana; Havinga, Paul J.M.

2008-01-01

In the field of wireless sensor networks, measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are

An MEF-Based Localization Algorithm against Outliers in Wireless Sensor Networks.

Science.gov (United States)

Wang, Dandan; Wan, Jiangwen; Wang, Meimei; Zhang, Qiang

2016-07-07

Precise localization has attracted considerable interest in Wireless Sensor Networks (WSNs) localization systems. Due to the internal or external disturbance, the existence of the outliers, including both the distance outliers and the anchor outliers, severely decreases the localization accuracy. In order to eliminate both kinds of outliers simultaneously, an outlier detection method is proposed based on the maximum entropy principle and fuzzy set theory. Since not all the outliers can be detected in the detection process, the Maximum Entropy Function (MEF) method is utilized to tolerate the errors and calculate the optimal estimated locations of unknown nodes. Simulation results demonstrate that the proposed localization method remains stable while the outliers vary. Moreover, the localization accuracy is highly improved by wisely rejecting outliers.

Stratification-Based Outlier Detection over the Deep Web.

Science.gov (United States)

Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

2016-01-01

For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web.

Good and Bad Neighborhood Approximations for Outlier Detection Ensembles

DEFF Research Database (Denmark)

Kirner, Evelyn; Schubert, Erich; Zimek, Arthur

2017-01-01

Outlier detection methods have used approximate neighborhoods in filter-refinement approaches. Outlier detection ensembles have used artificially obfuscated neighborhoods to achieve diverse ensemble members. Here we argue that outlier detection models could be based on approximate neighborhoods...... in the first place, thus gaining in both efficiency and effectiveness. It depends, however, on the type of approximation, as only some seem beneficial for the task of outlier detection, while no (large) benefit can be seen for others. In particular, we argue that space-filling curves are beneficial...

Construction of composite indices in presence of outliers

OpenAIRE

Mishra, SK

2008-01-01

Effects of outliers on mean, standard deviation and Pearson’s correlation coefficient are well known. The Principal Components analysis uses Pearson’s product moment correlation coefficients to construct composite indices from indicator variables and hence may be very sensitive to effects of outliers in data. Median, mean deviation and Bradley’s coefficient of absolute correlation are less susceptible to effects of outliers. This paper proposes a method to obtain composite indices by maximiza...

Exploring Outliers in Crowdsourced Ranking for QoE

OpenAIRE

Xu, Qianqian; Yan, Ming; Huang, Chendi; Xiong, Jiechao; Huang, Qingming; Yao, Yuan

2017-01-01

Outlier detection is a crucial part of robust evaluation for crowdsourceable assessment of Quality of Experience (QoE) and has attracted much attention in recent years. In this paper, we propose some simple and fast algorithms for outlier detection and robust QoE evaluation based on the nonconvex optimization principle. Several iterative procedures are designed with or without knowing the number of outliers in samples. Theoretical analysis is given to show that such procedures can reach stati...

Stratification-Based Outlier Detection over the Deep Web

OpenAIRE

Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S.; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

2016-01-01

For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribu...

Mining Outlier Data in Mobile Internet-Based Large Real-Time Databases

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Xin Liu

2018-01-01

Full Text Available Mining outlier data guarantees access security and data scheduling of parallel databases and maintains high-performance operation of real-time databases. Traditional mining methods generate abundant interference data with reduced accuracy, efficiency, and stability, causing severe deficiencies. This paper proposes a new mining outlier data method, which is used to analyze real-time data features, obtain magnitude spectra models of outlier data, establish a decisional-tree information chain transmission model for outlier data in mobile Internet, obtain the information flow of internal outlier data in the information chain of a large real-time database, and cluster data. Upon local characteristic time scale parameters of information flow, the phase position features of the outlier data before filtering are obtained; the decision-tree outlier-classification feature-filtering algorithm is adopted to acquire signals for analysis and instant amplitude and to achieve the phase-frequency characteristics of outlier data. Wavelet transform threshold denoising is combined with signal denoising to analyze data offset, to correct formed detection filter model, and to realize outlier data mining. The simulation suggests that the method detects the characteristic outlier data feature response distribution, reduces response time, iteration frequency, and mining error rate, improves mining adaptation and coverage, and shows good mining outcomes.

Remote sensing and gis based wheat crop acreage and yield estimation of district hyderabad, pakistan

International Nuclear Information System (INIS)

Siyal, A.

2015-01-01

Pre-harvest reliable and timely yield forecast and area estimates of cropped area is vital to planners and policy makers for making important and timely decisions with respect to food security in a country. The present study was conducted to estimate the wheat cropped area and crop yield in Hyderabad District, Pakistan from the Landsat 8 satellite imagery for Rabi 2013-14 and ground trothing. The required imagery of district Hyderabad was acquired from GLOVIS and was classified with maximum likelihood algorithm using ArcGIS 10.1. The classified image revealed that in district Hyderabad wheat covered 10,210 hectares (9.74% of total area) during Rabi season 2013-14 against 15,000 hectares (14.3% of total area) reported by Crop reporting Services (CRS), Sindh which is 30% less than that of reported by CRS. A positive linear relation between the wheat crop yield and the peak NDVI with coefficient of determination R2 = 0.91 was observed. Crop area and yield forecast through remote sensing is easy, cost effective, quick and reliable hence this technology needs to be introduced and propagated in the concerned government departments of Pakistan. (author)

Using Person Fit Statistics to Detect Outliers in Survey Research

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John M. Felt

2017-05-01

Full Text Available Context: When working with health-related questionnaires, outlier detection is important. However, traditional methods of outlier detection (e.g., boxplots can miss participants with “atypical” responses to the questions that otherwise have similar total (subscale scores. In addition to detecting outliers, it can be of clinical importance to determine the reason for the outlier status or “atypical” response.Objective: The aim of the current study was to illustrate how to derive person fit statistics for outlier detection through a statistical method examining person fit with a health-based questionnaire.Design and Participants: Patients treated for Cushing's syndrome (n = 394 were recruited from the Cushing's Support and Research Foundation's (CSRF listserv and Facebook page.Main Outcome Measure: Patients were directed to an online survey containing the CushingQoL (English version. A two-dimensional graded response model was estimated, and person fit statistics were generated using the Zh statistic.Results: Conventional outlier detections methods revealed no outliers reflecting extreme scores on the subscales of the CushingQoL. However, person fit statistics identified 18 patients with “atypical” response patterns, which would have been otherwise missed (Zh > |±2.00|.Conclusion: While the conventional methods of outlier detection indicated no outliers, person fit statistics identified several patients with “atypical” response patterns who otherwise appeared average. Person fit statistics allow researchers to delve further into the underlying problems experienced by these “atypical” patients treated for Cushing's syndrome. Annotated code is provided to aid other researchers in using this method.

Comparing the Entrepreneurial Ecosystems for Technology Startups in Bangalore and Hyderabad, India

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M H Bala Subrahmanya

2017-07-01

Full Text Available Technology startups are gaining increasing attention from policy makers the world over because they are seen as a means of encouraging innovations, spurring the development of new products and services, and generating employment. Technology startups tend to thrive when inserted in a conducive entrepreneurial ecosystem. Therefore, ecosystem promotion is being given increasing policy support. However, the emergence and structure of entrepreneurial ecosystems for technology startups have hardly been traced and examined in detail. In India, Bangalore occupies a unique position in the startup world, and Hyderabad is fast emerging as one of the promising startup hubs in the country. Given this background, we set out to explore and examine the structure, evolution, and growth of ecosystems for technology startups in the context of Bangalore and Hyderabad. Both the ecosystems emerged due to the initial foundation laid in the form of government–industry–academia triple helix and their interactions leading to the emergence of a modern industrial cluster followed by an information technology and biotechnology cluster, which then led to R&D cluster serving both the cities. These three clusters together, gradually and steadily, facilitated an entrepreneurial ecosystem for technology startups to emerge. The ecosystem operates within the triple helix model and has a nucleus with two outer layers: i an inner layer of primary (indispensable factors and ii an outer layer of supplementary (secondary factors. Through the analysis of the experiences of Bangalore and Hyderabad and their ecosystem evolution, its structure, and components, we derive key lessons for others within and beyond India.

SU-F-T-97: Outlier Identification in Radiation Therapy Knowledge Modeling

Energy Technology Data Exchange (ETDEWEB)

Sheng, Y [Duke University, Durham, NC (United States); Ge, Y [University of North Carolina at Charlotte, Charlotte, NC (United States); Yuan, L; Yin, F; Wu, Q [Duke University Medical Center, Durham, NC (United States); Li, T [Thomas Jefferson University, Philadelphia, PA (United States)

2016-06-15

Purpose: To investigate the impact of outliers on knowledge modeling in radiation therapy, and develop a systematic workflow for identifying and analyzing geometric and dosimetric outliers using pelvic cases. Methods: Four groups (G1-G4) of pelvic plans were included: G1 (37 prostate cases), G2 (37 prostate plus lymph node cases), and G3 (37 prostate bed cases) are all clinical IMRT cases. G4 are 10 plans outside G1 re-planned with dynamic-arc to simulate dosimetric outliers. The workflow involves 2 steps: 1. identify geometric outliers, assess impact and clean up; 2. identify dosimetric outliers, assess impact and clean up.1. A baseline model was trained with all G1 cases. G2/G3 cases were then individually added to the baseline model as geometric outliers. The impact on the model was assessed by comparing leverage statistic of inliers (G1) and outliers (G2/G3). Receiver-operating-characteristics (ROC) analysis was performed to determine optimal threshold. 2. A separate baseline model was trained with 32 G1 cases. Each G4 case (dosimetric outliers) was then progressively added to perturb this model. DVH predictions were performed using these perturbed models for remaining 5 G1 cases. Normal tissue complication probability (NTCP) calculated from predicted DVH were used to evaluate dosimetric outliers’ impact. Results: The leverage of inliers and outliers was significantly different. The Area-Under-Curve (AUC) for differentiating G2 from G1 was 0.94 (threshold: 0.22) for bladder; and 0.80 (threshold: 0.10) for rectum. For differentiating G3 from G1, the AUC (threshold) was 0.68 (0.09) for bladder, 0.76 (0.08) for rectum. Significant increase in NTCP started from models with 4 dosimetric outliers for bladder (p<0.05), and with only 1 dosimetric outlier for rectum (p<0.05). Conclusion: We established a systematic workflow for identifying and analyzing geometric and dosimetric outliers, and investigated statistical metrics for detecting. Results validated the

Traffic Analysis and Road Accidents: A Case Study of Hyderabad using GIS

International Nuclear Information System (INIS)

Bhagyaiah, M; Shrinagesh, B

2014-01-01

Globalization has impacted many developing countries across the world. India is one such country, which benefited the most. Increased, economic activity raised the consumption levels of the people across the country. This created scope for increase in travel and transportation. The increase in the vehicles since last 10 years has put lot of pressure on the existing roads and ultimately resulting in road accidents. It is estimated that since 2001 there is an increase of 202 percent of two wheeler and 286 percent of four wheeler vehicles with no road expansion. Motor vehicle crashes are a common cause of death, disability and demand for emergency medical care. Globally, more than 1 million people die each year from traffic crashes and about 20-50 million are injured or permanently disabled. There has been increasing trend in road accidents in Hyderabad over a few years. GIS helps in locating the accident hotspots and also in analyzing the trend of road accidents in Hyderabad

Deteksi Outlier Transaksi Menggunakan Visualisasi-Olap Pada Data Warehouse Perguruan Tinggi Swasta

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Gusti Ngurah Mega Nata

2016-07-01

Full Text Available Mendeteksi outlier pada data warehouse merupakan hal penting. Data pada data warehouse sudah diagregasi dan memiliki model multidimensional. Agregasi pada data warehouse dilakukan karena data warehouse digunakan untuk menganalisis data secara cepat pada top level manajemen. Sedangkan, model data multidimensional digunakan untuk melihat data dari berbagai dimensi objek bisnis. Jadi, Mendeteksi outlier pada data warehouse membutuhkan teknik yang dapat melihat outlier pada data yang sudah diagregasi dan dapat melihat dari berbagai dimensi objek bisnis. Mendeteksi outlier pada data warehouse akan menjadi tantangan baru.        Di lain hal, Visualisasi On-line Analytic process (OLAP merupakan tugas penting dalam menyajikan informasi trend (report pada data warehouse dalam bentuk visualisasi data. Pada penelitian ini, visualisasi OLAP digunakan untuk deteksi outlier transaksi. Maka, dalam penelitian ini melakukan analisis untuk mendeteksi outlier menggunakan visualisasi-OLAP. Operasi OLAP yang digunakan yaitu operasi drill-down. Jenis visualisasi yang akan digunakan yaitu visualisasi satu dimensi, dua dimensi dan multi dimensi menggunakan tool weave desktop. Pembangunan data warehouse dilakukan secara button-up. Studi kasus dilakukan pada perguruan tinggi swasta. Kasus yang diselesaikan yaitu mendeteksi outlier transaki pembayaran mahasiswa pada setiap semester. Deteksi outlier pada visualisasi data menggunakan satu tabel dimensional lebih mudah dianalisis dari pada deteksi outlier pada visualisasi data menggunakan dua atau multi tabel dimensional. Dengan kata lain semakin banyak tabel dimensi yang terlibat semakin sulit analisis deteksi outlier yang dilakukan. Kata kunci — Deteksi Outlier,  Visualisasi OLAP, Data warehouse

Treatment of Outliers via Interpolation Method with Neural Network Forecast Performances

Science.gov (United States)

Wahir, N. A.; Nor, M. E.; Rusiman, M. S.; Gopal, K.

2018-04-01

Outliers often lurk in many datasets, especially in real data. Such anomalous data can negatively affect statistical analyses, primarily normality, variance, and estimation aspects. Hence, handling the occurrences of outliers require special attention. Therefore, it is important to determine the suitable ways in treating outliers so as to ensure that the quality of the analyzed data is indeed high. As such, this paper discusses an alternative method to treat outliers via linear interpolation method. In fact, assuming outlier as a missing value in the dataset allows the application of the interpolation method to interpolate the outliers thus, enabling the comparison of data series using forecast accuracy before and after outlier treatment. With that, the monthly time series of Malaysian tourist arrivals from January 1998 until December 2015 had been used to interpolate the new series. The results indicated that the linear interpolation method, which was comprised of improved time series data, displayed better results, when compared to the original time series data in forecasting from both Box-Jenkins and neural network approaches.

A Geometrical-Statistical Approach to Outlier Removal for TDOA Measurements

Science.gov (United States)

Compagnoni, Marco; Pini, Alessia; Canclini, Antonio; Bestagini, Paolo; Antonacci, Fabio; Tubaro, Stefano; Sarti, Augusto

2017-08-01

The curse of outlier measurements in estimation problems is a well known issue in a variety of fields. Therefore, outlier removal procedures, which enables the identification of spurious measurements within a set, have been developed for many different scenarios and applications. In this paper, we propose a statistically motivated outlier removal algorithm for time differences of arrival (TDOAs), or equivalently range differences (RD), acquired at sensor arrays. The method exploits the TDOA-space formalism and works by only knowing relative sensor positions. As the proposed method is completely independent from the application for which measurements are used, it can be reliably used to identify outliers within a set of TDOA/RD measurements in different fields (e.g. acoustic source localization, sensor synchronization, radar, remote sensing, etc.). The proposed outlier removal algorithm is validated by means of synthetic simulations and real experiments.

A Note on optimal estimation in the presence of outliers

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John N. Haddad

2017-06-01

Full Text Available Haddad, J. 2017. A Note on optimal estimation in the presence of outliers. Lebanese Science Journal, 18(1: 136-141. The basic estimation problem of the mean and standard deviation of a random normal process in the presence of an outlying observation is considered. The value of the outlier is taken as a constraint imposed on the maximization problem of the log likelihood. It is shown that the optimal solution of the maximization problem exists and expressions for the estimates are given. Applications to estimation in the presence of outliers and outlier detection are discussed and illustrated through a simulation study and analysis of trade data

INCREMENTAL PRINCIPAL COMPONENT ANALYSIS BASED OUTLIER DETECTION METHODS FOR SPATIOTEMPORAL DATA STREAMS

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A. Bhushan

2015-07-01

Full Text Available In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

Detection of additive outliers in seasonal time series

DEFF Research Database (Denmark)

Haldrup, Niels; Montañés, Antonio; Sansó, Andreu

The detection and location of additive outliers in integrated variables has attracted much attention recently because such outliers tend to affect unit root inference among other things. Most of these procedures have been developed for non-seasonal processes. However, the presence of seasonality......) to deal with data sampled at a seasonal frequency and the size and power properties are discussed. We also show that the presence of periodic heteroscedasticity will inflate the size of the tests and hence will tend to identify an excessive number of outliers. A modified Perron-Rodriguez test which allows...... periodically varying variances is suggested and it is shown to have excellent properties in terms of both power and size...

Environmental problems attributed due to increased road traffic intensity in Hyderabad city

International Nuclear Information System (INIS)

Memon, Z.; Ansari, A.K.

2001-01-01

Hyderabad is a historical city, so roads are not so wide to cater the present intensity of traffic, hence it is facing transportation problems. No any attempt of traffic management and control has been made in this regard to solve the acute problem of city. Some of the typical problems can be stated as poor driving, encroachments, unsystematic parking on roads, improper road markings and road sings, inadequate road geometry and inadequate control system at intersections etc. This study involves measurement of vehicles flow at five sites of Hyderabad city, and assessment of health hazards on human being due to noise congestion, improper road planning coupled with old city streets converted into roads which are now insufficient for present traffic density, resulting disturbance to pedestrians and dwellers who are living near by road for smooth walk. Motor vehicles, however, play a vital role in the field of public and goods transportation and this survey shows that there are about 726 vehicles operating per hour at the five sites in the city. (author)

SURFACE WATER AND GROUND WATER QUALITY MONITORING FOR RESTORATION OF URBAN LAKES IN GREATER HYDERABAD, INDIA

Science.gov (United States)

Mohanty, A. K.

2009-12-01

SURFACE WATER AND GROUND WATER QUALITY MONITORING FOR RESTORATION OF URBAN LAKES IN GREATER HYDERABAD, INDIA A.K. Mohanty, K. Mahesh Kumar, B. A. Prakash and V.V.S. Gurunadha Rao Ecology and Environment Group National Geophysical Research Institute, (CSIR) Hyderabad - 500 606, India E-mail:atulyakumarmohanty@yahoo.com Abstract: Hyderabad Metropolitan Development Authority has taken up restoration of urban lakes around Hyderabad city under Green Hyderabad Environment Program. Restoration of Mir Alam Tank, Durgamcheruvu, Patel cheruvu, Pedda Cheruvu and Nallacheruvu lakes have been taken up under the second phase. There are of six lakes viz., RKPuramcheruvu, Nadimicheruvu (Safilguda), Bandacheruvu Patelcheruvu, Peddacheruvu, Nallacheruvu, in North East Musi Basin covering 38 sq km. Bimonthly monitoring of lake water quality for BOD, COD, Total Nitrogen, Total phosphorous has been carried out for two hydrological cycles during October 2002- October 2004 in all the five lakes at inlet channels and outlets. The sediments in the lake have been also assessed for nutrient status. The nutrient parameters have been used to assess eutrophic condition through computation of Trophic Status Index, which has indicated that all the above lakes under study are under hyper-eutrophic condition. The hydrogeological, geophysical, water quality and groundwater data base collected in two watersheds covering 4 lakes has been used to construct groundwater flow and mass transport models. The interaction of lake-water with groundwater has been computed for assessing the lake water budget combining with inflow and outflow measurements on streams entering and leaving the lakes. Individual lake water budget has been used for design of appropriate capacity of Sewage Treatment Plants (STPs) on the inlet channels of the lakes for maintaining Full Tank Level (FTL) in each lake. STPs are designed for tertiary treatment i.e. removal of nutrient load viz., Phosphates and Nitrates. Phosphates are

Elimination of some unknown parameters and its effect on outlier detection

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Serif Hekimoglu

Full Text Available Outliers in observation set badly affect all the estimated unknown parameters and residuals, that is because outlier detection has a great importance for reliable estimation results. Tests for outliers (e.g. Baarda's and Pope's tests are frequently used to detect outliers in geodetic applications. In order to reduce the computational time, sometimes elimination of some unknown parameters, which are not of interest, is performed. In this case, although the estimated unknown parameters and residuals do not change, the cofactor matrix of the residuals and the redundancies of the observations change. In this study, the effects of the elimination of the unknown parameters on tests for outliers have been investigated. We have proved that the redundancies in initial functional model (IFM are smaller than the ones in reduced functional model (RFM where elimination is performed. To show this situation, a horizontal control network was simulated and then many experiences were performed. According to simulation results, tests for outlier in IFM are more reliable than the ones in RFM.

Application of median-equation approach for outlier detection in geodetic networks

Directory of Open Access Journals (Sweden)

Serif Hekimoglu

Full Text Available In geodetic measurements some outliers may occur sometimes in data sets, depending on different reasons. There are two main approaches to detect outliers as Tests for outliers (Baarda's and Pope's Tests and robust methods (Danish method, Huber method etc.. These methods use the Least Squares Estimation (LSE. The outliers affect the LSE results, especially it smears the effects of the outliers on the good observations and sometimes wrong results may be obtained. To avoid these effects, a method that does not use LSE should be preferred. The median is a high breakdown point estimator and if it is applied for the outlier detection, reliable results can be obtained. In this study, a robust method which uses median with or as a treshould value on median residuals that are obtained from median equations is proposed. If the a priori variance of the observations is known, the reliability of the new approch is greater than the one in the case where the a priori variance is unknown.

Detection of outliers in gas centrifuge experimental data

International Nuclear Information System (INIS)

Andrade, Monica C.V.; Nascimento, Claudio A.O.

2005-01-01

Isotope separation in a gas centrifuge is a very complex process. Development and optimization of a gas centrifuge requires experimentation. These data contain experimental errors, and like other experimental data, there may be some gross errors, also known as outliers. The detection of outliers in gas centrifuge experimental data may be quite complicated because there is not enough repetition for precise statistical determination and the physical equations may be applied only on the control of the mass flows. Moreover, the concentrations are poorly predicted by phenomenological models. This paper presents the application of a three-layer feed-forward neural network to the detection of outliers in a very extensive experiment for the analysis of the separation performance of a gas centrifuge. (author)

A Pareto scale-inflated outlier model and its Bayesian analysis

OpenAIRE

Scollnik, David P. M.

2016-01-01

This paper develops a Pareto scale-inflated outlier model. This model is intended for use when data from some standard Pareto distribution of interest is suspected to have been contaminated with a relatively small number of outliers from a Pareto distribution with the same shape parameter but with an inflated scale parameter. The Bayesian analysis of this Pareto scale-inflated outlier model is considered and its implementation using the Gibbs sampler is discussed. The paper contains three wor...

Displaying an Outlier in Multivariate Data | Gordor | Journal of ...

African Journals Online (AJOL)

... a multivariate data set is proposed. The technique involves the projection of the multidimensional data onto a single dimension called the outlier displaying component. When the observations are plotted on this component the outlier is appreciably revealed. Journal of Applied Science and Technology (JAST), Vol. 4, Nos.

A NOTE ON THE CONVENTIONAL OUTLIER DETECTION TEST PROCEDURES

Directory of Open Access Journals (Sweden)

JIANFENG GUO

Full Text Available Under the assumption of that the variance-covariance matrix is fully populated, Baarda's w-test is turn out to be completely different from the standardized least-squares residual. Unfortunately, this is not generally recognized. In the limiting case of only one degree of freedom, all the three types of test statistics, including Gaussian normal test, Student's t-test and Pope's Tau-test, will be invalid for identification of outliers: (1 all the squares of the Gaussian normal test statistic coincide with the goodness-of-fit (global test statistic, even for correlated observations. Hence, the failure of the global test implies that all the observations will be flagged as outliers, and thus the Gaussian normal test is inconclusive for localization of outliers; (2 the absolute values of the Tau-test statistic are all exactly equal to one, no matter whether the observations are contaminated. Therefore, the Tau-test cannot work for outlier detection in this situation; and (3 Student's t-test statistics are undefined.

Detecting isotopic ratio outliers

Science.gov (United States)

Bayne, C. K.; Smith, D. H.

An alternative method is proposed for improving isotopic ratio estimates. This method mathematically models pulse-count data and uses iterative reweighted Poisson regression to estimate model parameters to calculate the isotopic ratios. This computer-oriented approach provides theoretically better methods than conventional techniques to establish error limits and to identify outliers.

Detecting isotopic ratio outliers

International Nuclear Information System (INIS)

Bayne, C.K.; Smith, D.H.

1986-01-01

An alternative method is proposed for improving isotopic ratio estimates. This method mathematically models pulse-count data and uses iterative reweighted Poisson regression to estimate model parameters to calculate the isotopic ratios. This computer-oriented approach provides theoretically better methods than conventional techniques to establish error limits and to identify outliers

Primary Education in Delhi, Hyderabad and Kolkata: Governance by Resignation, Privatisation by Default

NARCIS (Netherlands)

J.E. Mooij (Jos); J. Jalal (Jennifer)

2009-01-01

textabstract1. Introduction As described in the earlier chapters, one of the entry points in our study of urban governance was the supply and demand of services. Education is one important service that we studied in three of the four cities (Delhi, Hyderabad and Kolkata). Our focus was on primary

A statistical test for outlier identification in data envelopment analysis

Directory of Open Access Journals (Sweden)

Morteza Khodabin

2010-09-01

Full Text Available In the use of peer group data to assess individual, typical or best practice performance, the effective detection of outliers is critical for achieving useful results. In these ‘‘deterministic’’ frontier models, statistical theory is now mostly available. This paper deals with the statistical pared sample method and its capability of detecting outliers in data envelopment analysis. In the presented method, each observation is deleted from the sample once and the resulting linear program is solved, leading to a distribution of efficiency estimates. Based on the achieved distribution, a pared test is designed to identify the potential outlier(s. We illustrate the method through a real data set. The method could be used in a first step, as an exploratory data analysis, before using any frontier estimation.

Adjusted functional boxplots for spatio-temporal data visualization and outlier detection

KAUST Repository

Sun, Ying

2011-10-24

This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio-temporal dependence and the 1.5 times the 50% central region empirical outlier detection rule. Then, we propose to simulate observations without outliers on the basis of a robust estimator of the covariance function of the data. We select the constant factor in the functional boxplot to control the probability of correctly detecting no outliers. Finally, we apply the selected factor to the functional boxplot of the original data. As applications, the factor selection procedure and the adjusted functional boxplots are demonstrated on sea surface temperatures, spatio-temporal precipitation and general circulation model (GCM) data. The outlier detection performance is also compared before and after the factor adjustment. © 2011 John Wiley & Sons, Ltd.

The high cost of low-acuity ICU outliers.

Science.gov (United States)

Dahl, Deborah; Wojtal, Greg G; Breslow, Michael J; Holl, Randy; Huguez, Debra; Stone, David; Korpi, Gloria

2012-01-01

Direct variable costs were determined on each hospital day for all patients with an intensive care unit (ICU) stay in four Phoenix-area hospital ICUs. Average daily direct variable cost in the four ICUs ranged from $1,436 to $1,759 and represented 69.4 percent and 45.7 percent of total hospital stay cost for medical and surgical patients, respectively. Daily ICU cost and length of stay (LOS) were higher in patients with higher ICU admission acuity of illness as measured by the APACHE risk prediction methodology; 16.2 percent of patients had an ICU stay in excess of six days, and these LOS outliers accounted for 56.7 percent of total ICU cost. While higher-acuity patients were more likely to be ICU LOS outliers, 11.1 percent of low-risk patients were outliers. The low-risk group included 69.4 percent of the ICU population and accounted for 47 percent of all LOS outliers. Low-risk LOS outliers accounted for 25.3 percent of ICU cost and incurred fivefold higher hospital stay costs and mortality rates. These data suggest that severity of illness is an important determinant of daily resource consumption and LOS, regardless of whether the patient arrives in the ICU with high acuity or develops complications that increase acuity. The finding that a substantial number of long-stay patients come into the ICU with low acuity and deteriorate after ICU admission is not widely recognized and represents an important opportunity to improve patient outcomes and lower costs. ICUs should consider adding low-risk LOS data to their quality and financial performance reports.

Evaluating Outlier Identification Tests: Mahalanobis "D" Squared and Comrey "Dk."

Science.gov (United States)

Rasmussen, Jeffrey Lee

1988-01-01

A Monte Carlo simulation was used to compare the Mahalanobis "D" Squared and the Comrey "Dk" methods of detecting outliers in data sets. Under the conditions investigated, the "D" Squared technique was preferable as an outlier removal statistic. (SLD)

Outlier Detection with Space Transformation and Spectral Analysis

DEFF Research Database (Denmark)

Dang, Xuan-Hong; Micenková, Barbora; Assent, Ira

2013-01-01

which rely on notions of distances or densities, this approach introduces a novel concept based on local quadratic entropy for evaluating the similarity of a data object with its neighbors. This information theoretic quantity is used to regularize the closeness amongst data instances and subsequently......Detecting a small number of outliers from a set of data observations is always challenging. In this paper, we present an approach that exploits space transformation and uses spectral analysis in the newly transformed space for outlier detection. Unlike most existing techniques in the literature...... benefits the process of mapping data into a usually lower dimensional space. Outliers are then identified by spectral analysis of the eigenspace spanned by the set of leading eigenvectors derived from the mapping procedure. The proposed technique is purely data-driven and imposes no assumptions regarding...

Detecting isotopic ratio outliers

International Nuclear Information System (INIS)

Bayne, C.K.; Smith, D.H.

1985-01-01

An alternative method is proposed for improving isotopic ratio estimates. This method mathematically models pulse-count data and uses iterative reweighted Poisson regression to estimate model parameters to calculate the isotopic ratios. This computer-oriented approach provides theoretically better methods than conventional techniques to establish error limits and to identify outliers. 6 refs., 3 figs., 3 tabs

Detection of outliers in a gas centrifuge experimental data

Directory of Open Access Journals (Sweden)

M. C. V. Andrade

2005-09-01

Full Text Available Isotope separation with a gas centrifuge is a very complex process. Development and optimization of a gas centrifuge requires experimentation. These data contain experimental errors, and like other experimental data, there may be some gross errors, also known as outliers. The detection of outliers in gas centrifuge experimental data is quite complicated because there is not enough repetition for precise statistical determination and the physical equations may be applied only to control of the mass flow. Moreover, the concentrations are poorly predicted by phenomenological models. This paper presents the application of a three-layer feed-forward neural network to the detection of outliers in analysis of performed on a very extensive experiment.

Global irradiation on horizontal surface at Hyderabad, Pakistan

International Nuclear Information System (INIS)

Kalhoro, A.N.

2005-01-01

The measurement of global irradiation on horizontal surface at PCSIR (Pakistan Council of Scientific and Industrial Research) Laboratories, Hyderabad, Pakistan, for the period of January-June, 2003 is presented in this paper. During six months the total global irradiation received on horizontal surface at Hyderabad Laboratories is 1.80238 MW-h-m2. The daily irradiation data (Watt-h/Sq.m) has been collected on continuous basis by means of EPLAB Pyranometer and EPLAB Electronic Integrator provided with DIGITEC printer system. HPX- Y recorder (potentiometer) is also connected for continuous data recording of solar intensity (m V). The weather effect over the radiation income was observed regularly and proportion of sunny, cloudy, partly cloudy and dusty days is plotted. Monthly mean daily irradiation bifurcated for sunny and cloudy days are also shown separately. To give an overview of sky conditions, the monthly clearness index is calculated. The highest value of average irradiation per day was recorded in June (7.15 kW/m/sup 2/) and minimum recorded in January (4.11 kW/m/sup 2/). The summer season, although rich in radiation with long sunshine duration, brings dust storms along with many partly cloudy or cloudy days, mostly in the month of May and likely in June as well. This could be an additional barrier for solar energy applications especially in desert areas; therefore the study was made for evaluating the effect of dust on the radiation flux. The purpose of the study is the development of rural life in Pakistan such that the inhabitants of rural areas may need not to wait for the connection to national grid. This study will help in improving the efficiency of solar thermal devices, (currently fabricated on theoretical basis at the laboratories), according to experimental data. (author)

The masking breakdown point of multivariate outlier identification rules

OpenAIRE

Becker, Claudia; Gather, Ursula

1997-01-01

In this paper, we consider one-step outlier identifiation rules for multivariate data, generalizing the concept of so-called alpha outlier identifiers, as presented in Davies and Gather (1993) for the case of univariate samples. We investigate, how the finite-sample breakdown points of estimators used in these identification rules influence the masking behaviour of the rules.

Development of a methodology for the detection of hospital financial outliers using information systems.

Science.gov (United States)

Okada, Sachiko; Nagase, Keisuke; Ito, Ayako; Ando, Fumihiko; Nakagawa, Yoshiaki; Okamoto, Kazuya; Kume, Naoto; Takemura, Tadamasa; Kuroda, Tomohiro; Yoshihara, Hiroyuki

2014-01-01

Comparison of financial indices helps to illustrate differences in operations and efficiency among similar hospitals. Outlier data tend to influence statistical indices, and so detection of outliers is desirable. Development of a methodology for financial outlier detection using information systems will help to reduce the time and effort required, eliminate the subjective elements in detection of outlier data, and improve the efficiency and quality of analysis. The purpose of this research was to develop such a methodology. Financial outliers were defined based on a case model. An outlier-detection method using the distances between cases in multi-dimensional space is proposed. Experiments using three diagnosis groups indicated successful detection of cases for which the profitability and income structure differed from other cases. Therefore, the method proposed here can be used to detect outliers. Copyright © 2013 John Wiley & Sons, Ltd.

Solid waste management and recycling : actors, partnerships and policies in Hyderabad, India and Nairobi, Kenya

NARCIS (Netherlands)

Post, J.; Baud, I.S.A.; Furedy, C.

2004-01-01

Solid waste management and recycling : actors, partnerships and policies in Hyderabad, India and Nairobi, Kenya / ed. by Isa Baud, Johan Post and Christine Furedy Author: Isabelle Suzanne Antoinette Baud; Johan Post Year: cop. 2004 Publisher: Dordrecht [etc.] : Kluwer Academic Publishers Series: The

The variance of length of stay and the optimal DRG outlier payments.

Science.gov (United States)

Felder, Stefan

2009-09-01

Prospective payment schemes in health care often include supply-side insurance for cost outliers. In hospital reimbursement, prospective payments for patient discharges, based on their classification into diagnosis related group (DRGs), are complemented by outlier payments for long stay patients. The outlier scheme fixes the length of stay (LOS) threshold, constraining the profit risk of the hospitals. In most DRG systems, this threshold increases with the standard deviation of the LOS distribution. The present paper addresses the adequacy of this DRG outlier threshold rule for risk-averse hospitals with preferences depending on the expected value and the variance of profits. It first shows that the optimal threshold solves the hospital's tradeoff between higher profit risk and lower premium loading payments. It then demonstrates for normally distributed truncated LOS that the optimal outlier threshold indeed decreases with an increase in the standard deviation.

An Unbiased Distance-based Outlier Detection Approach for High-dimensional Data

DEFF Research Database (Denmark)

Nguyen, Hoang Vu; Gopalkrishnan, Vivekanand; Assent, Ira

2011-01-01

than a global property. Different from existing approaches, it is not grid-based and dimensionality unbiased. Thus, its performance is impervious to grid resolution as well as the curse of dimensionality. In addition, our approach ranks the outliers, allowing users to select the number of desired...... outliers, thus mitigating the issue of high false alarm rate. Extensive empirical studies on real datasets show that our approach efficiently and effectively detects outliers, even in high-dimensional spaces....

Traffic noise in Hyderabad city. part I: road traffic noise

International Nuclear Information System (INIS)

Shaikh, G.H.; Shaikh, Q.

2000-01-01

Traffic noise survey was conducted at 20 sites in different areas and localities in Hyderabad city and each site noise data was collected continuously from 0800 to 2000 h. The data was analyzed for L/sub A99/, L/sub A90/, L/sub A50/, L/sub 10/ and L/sub A1/, and approximate values of L/sub Aeq12h/ were evaluated for each site. The results are discussed with reference to some criteria for community annoyance and means and ways to limit high-level traffic noise are suggested. (author)

Outlier-resilient complexity analysis of heartbeat dynamics

Science.gov (United States)

Lo, Men-Tzung; Chang, Yi-Chung; Lin, Chen; Young, Hsu-Wen Vincent; Lin, Yen-Hung; Ho, Yi-Lwun; Peng, Chung-Kang; Hu, Kun

2015-03-01

Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings.

Identificación de outliers en muestras multivariantes

OpenAIRE

Pérez Díez de los Ríos, José Luis

1987-01-01

En esta memoria se analiza la problemática de las observaciones Outliers en nuestras Multivariantes describiéndose las distintas técnicas que existen en la actualidad para la identificación de Outliers en nuestras multidimensionales y poniéndose de manifiesto que la mayoría de ellas son generalizaciones de ideas desarrolladas para el caso univariante o técnicas basadas en representaciones graficas. Se aborda a continuación el denominado efecto de enmascaramiento que se puede presentar cuando...

Evaluation of food hygiene in commercial food service establishments in Hyderabad

OpenAIRE

Kauser, Naazia; N., Santoshi Lakshmi

2015-01-01

Food handlers have a prime role to play in food businesses, and that is to guarantee the meals served are hygienic for consumption. The unhygienic working practices and attitude of the food handlers often play a major role in the food contamination process.The purpose of this study is to evaluate the level of knowledge, attitude and Food hygiene practices among food handlers in commercial food service outlets in Hyderabad. Two hundred food handlers from 20 food service outlets in the vicinity...

Microbiological Quality of Salads Served along with Street Foods of Hyderabad, India

Directory of Open Access Journals (Sweden)

Alekhya Sabbithi

2014-01-01

Full Text Available A study has been done to analyse the microbiological quality of salads served along with street foods of Hyderabad. A total of 163 salad samples, 53 of carrot and 110 of onion samples, were collected from four different zones of Hyderabad. About 74% and 56% had Staphylococcus aureus in carrots and onions, respectively. Fifty-eight percent of carrots and forty-five percent of onions samples contained Salmonella, 68% of carrots and 24% of onions had Yersinia. HACCP study was carried out with 6 street food vendors to identify the source of Salmonella contamination in salads. Food handlers were found to be responsible for Salmonella contamination in salads. The present study revealed the potential hazards of street vended salad vegetables, considering the handling practice usually carried out by vendors. Ninety-eight percent of the vendors did not wash the vegetables before processing and serving while about 56.6% of the vendors did not peel the vegetables. Majority of street vendors’ nails were uncut. A significant difference (P<0.01 was observed in Yersinia spp. and Salmonella spp. in wet-dirty chopping board when compared to clean-dry chopping board. A significant difference (P<0.05 of Staphylococcus spp. was observed when the status of cleaning cloth was neat/untidy.

IVS Combination Center at BKG - Robust Outlier Detection and Weighting Strategies

Science.gov (United States)

Bachmann, S.; Lösler, M.

2012-12-01

Outlier detection plays an important role within the IVS combination. Even if the original data is the same for all contributing Analysis Centers (AC), the analyzed data shows differences due to analysis software characteristics. The treatment of outliers is thus a fine line between keeping data heterogeneity and elimination of real outliers. Robust outlier detection based on the Least Median Square (LMS) is used within the IVS combination. This method allows reliable outlier detection with a small number of input parameters. A similar problem arises for the weighting of the individual solutions within the combination process. The variance component estimation (VCE) is used to control the weighting factor for each AC. The Operator-Software-Impact (OSI) method takes into account that the analyzed data is strongly influenced by the software and the responsible operator. It allows to make the VCE more sensitive to the diverse input data. This method has already been set up within GNSS data analysis as well as the analysis of troposphere data. The benefit of an OSI realization within the VLBI combination and its potential in weighting factor determination has not been investigated before.

A New Outlier Detection Method for Multidimensional Datasets

KAUST Repository

Abdel Messih, Mario A.

2012-07-01

This study develops a novel hybrid method for outlier detection (HMOD) that combines the idea of distance based and density based methods. The proposed method has two main advantages over most of the other outlier detection methods. The first advantage is that it works well on both dense and sparse datasets. The second advantage is that, unlike most other outlier detection methods that require careful parameter setting and prior knowledge of the data, HMOD is not very sensitive to small changes in parameter values within certain parameter ranges. The only required parameter to set is the number of nearest neighbors. In addition, we made a fully parallelized implementation of HMOD that made it very efficient in applications. Moreover, we proposed a new way of using the outlier detection for redundancy reduction in datasets where the confidence level that evaluates how accurate the less redundant dataset can be used to represent the original dataset can be specified by users. HMOD is evaluated on synthetic datasets (dense and mixed “dense and sparse”) and a bioinformatics problem of redundancy reduction of dataset of position weight matrices (PWMs) of transcription factor binding sites. In addition, in the process of assessing the performance of our redundancy reduction method, we developed a simple tool that can be used to evaluate the confidence level of reduced dataset representing the original dataset. The evaluation of the results shows that our method can be used in a wide range of problems.

Robust volcano plot: identification of differential metabolites in the presence of outliers.

Science.gov (United States)

Kumar, Nishith; Hoque, Md Aminul; Sugimoto, Masahiro

2018-04-11

The identification of differential metabolites in metabolomics is still a big challenge and plays a prominent role in metabolomics data analyses. Metabolomics datasets often contain outliers because of analytical, experimental, and biological ambiguity, but the currently available differential metabolite identification techniques are sensitive to outliers. We propose a kernel weight based outlier-robust volcano plot for identifying differential metabolites from noisy metabolomics datasets. Two numerical experiments are used to evaluate the performance of the proposed technique against nine existing techniques, including the t-test and the Kruskal-Wallis test. Artificially generated data with outliers reveal that the proposed method results in a lower misclassification error rate and a greater area under the receiver operating characteristic curve compared with existing methods. An experimentally measured breast cancer dataset to which outliers were artificially added reveals that our proposed method produces only two non-overlapping differential metabolites whereas the other nine methods produced between seven and 57 non-overlapping differential metabolites. Our data analyses show that the performance of the proposed differential metabolite identification technique is better than that of existing methods. Thus, the proposed method can contribute to analysis of metabolomics data with outliers. The R package and user manual of the proposed method are available at https://github.com/nishithkumarpaul/Rvolcano .

Use of multi-objective air pollution monitoring sites and online air pollution monitoring system for total health risk assessment in Hyderabad, India.

Science.gov (United States)

Anjaneyulu, Y; Jayakumar, I; Hima Bindu, V; Sagareswar, G; Mukunda Rao, P V; Rambabu, N; Ramani, K V

2005-08-01

A consensus has been emerging among public health experts in developing countries that air pollution, even at current ambient levels, aggravates respiratory and cardiovascular diseases and leads to premature mortality. Recent studies have also presented well-founded theories concerning the biological mechanisms involved and the groups of people that are probably more susceptible to health effects caused or exacerbated by inhalation of ambient particulate matter (PM.). On the basis of prognostic studies carried out in Center for Environment, JNT University, Hyderabad "it has been estimated that in Hyderabad some 1,700 to 3,000 people per year die prematurely as a result of inhaling PM". These figures reflect only the effects of acute exposure to air pollution. If the long-term effects of chronic exposure are taken into account, 10,000-15,000 people a year could die prematurely in Hyderabad. This estimate of the chronic effects is based on other studies, which are not completely comparable with the Hyderabad situation. While the study designs and analyses in these other studies may indeed be different or irrelevant to Hyderabad, the fact they were carried out in other countries is irrelevant. Taking into account these considerations, a model for total health risk assessment for the city of Hyderabad, and its state of Andhra Pradesh in India has been developed using a multi-objective air pollution monitoring network and online and real time air pollution monitoring stations. For the model studies a number of potential monitoring sites were screened for general and site-specific criteria in a geographic information system (GIS) environment that may, on a local basis, affect the representativeness of the data collected. Local features that may affect either the chemical or meteorological parameters are evaluated to assure a minimum of interference. Finally, for monitoring air pollution, an online and real-time monitoring system was designed using advanced

A New Methodology Based on Imbalanced Classification for Predicting Outliers in Electricity Demand Time Series

Directory of Open Access Journals (Sweden)

Francisco Javier Duque-Pintor

2016-09-01

Full Text Available The occurrence of outliers in real-world phenomena is quite usual. If these anomalous data are not properly treated, unreliable models can be generated. Many approaches in the literature are focused on a posteriori detection of outliers. However, a new methodology to a priori predict the occurrence of such data is proposed here. Thus, the main goal of this work is to predict the occurrence of outliers in time series, by using, for the first time, imbalanced classification techniques. In this sense, the problem of forecasting outlying data has been transformed into a binary classification problem, in which the positive class represents the occurrence of outliers. Given that the number of outliers is much lower than the number of common values, the resultant classification problem is imbalanced. To create training and test sets, robust statistical methods have been used to detect outliers in both sets. Once the outliers have been detected, the instances of the dataset are labeled accordingly. Namely, if any of the samples composing the next instance are detected as an outlier, the label is set to one. As a study case, the methodology has been tested on electricity demand time series in the Spanish electricity market, in which most of the outliers were properly forecast.

REVALENCE OF BACKACHE AMONG SCHOOL GOING CHILDREN OF HYDERABAD SINDH

Directory of Open Access Journals (Sweden)

Shireen Khanzada

2016-02-01

Full Text Available Background: The prevalence of backache is increasing in children with heavy weighed school bags and abnormal sitting posture both, at home and school. The aim of this study was to determine the prevalence of this much avoided issue of back pain among school going children of Hyderabad, Sindh. Methodology: 240 pupils (range, 7-14 years old were recruited in their respective schools of Hyderabad city. Inclusions were all the present students on that particular day of data collecting and excluding those who were absent that day. A preformed questionnaire form was filled with all due consent, following which, examination was done to check the parameters of height, weight, BMI, weight of school bag, and posture analysis. Result: The prevalence of back pain was 46.7% among the total 240 subjects studied. Out of which 14.4% boys and 32.3% girls were affected. The majority of affected children were age group of 10-12 years old. In our study 61% children had school bags weighing around 5 kg, which is point to be considered by high officials of Primary Education System in Pakistan. Conclusion: The symptoms of backache were significantly visible in those students carrying heavy bags in proportion to their own weight and BMI. This was also closely related to the time duration, subjects were spending in front of computer/television. After analysis and all, it turned out that a significant number of students were affected by abnormal postures leading to backache-, which may be held equally responsible for further Alleviation of such symptoms later in life.

On the Evaluation of Outlier Detection: Measures, Datasets, and an Empirical Study Continued

DEFF Research Database (Denmark)

Campos, G. O.; Zimek, A.; Sander, J.

2016-01-01

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate...... are available online in the repository at: http://www.dbs.ifi.lmu.de/research/outlier-evaluation/...

Ensemble Learning Method for Outlier Detection and its Application to Astronomical Light Curves

Science.gov (United States)

Nun, Isadora; Protopapas, Pavlos; Sim, Brandon; Chen, Wesley

2016-09-01

Outlier detection is necessary for automated data analysis, with specific applications spanning almost every domain from financial markets to epidemiology to fraud detection. We introduce a novel mixture of the experts outlier detection model, which uses a dynamically trained, weighted network of five distinct outlier detection methods. After dimensionality reduction, individual outlier detection methods score each data point for “outlierness” in this new feature space. Our model then uses dynamically trained parameters to weigh the scores of each method, allowing for a finalized outlier score. We find that the mixture of experts model performs, on average, better than any single expert model in identifying both artificially and manually picked outliers. This mixture model is applied to a data set of astronomical light curves, after dimensionality reduction via time series feature extraction. Our model was tested using three fields from the MACHO catalog and generated a list of anomalous candidates. We confirm that the outliers detected using this method belong to rare classes, like Novae, He-burning, and red giant stars; other outlier light curves identified have no available information associated with them. To elucidate their nature, we created a website containing the light-curve data and information about these objects. Users can attempt to classify the light curves, give conjectures about their identities, and sign up for follow up messages about the progress made on identifying these objects. This user submitted data can be used further train of our mixture of experts model. Our code is publicly available to all who are interested.

Estimation of equilibrium factors of radon and its progeny using SSNTDs in the various dwellings of Hyderabad, Andhra Pradesh, India

International Nuclear Information System (INIS)

Yadagiri Reddy, P.; Rama Reddy, K.; Sreenath Reddy, M.

2013-01-01

In the estimation of effective dose in the indoor environment due to Radon and its progeny the equilibrium factor (F) plays a significant role. It is the radioactive equilibrium between radon and its short-lived decay products. Generally in the dose estimation is made taking the equilibrium factor 0.4 (UNSCEAR value) for the radon and its progeny. But in practice the concentration of radon and its progeny vary significantly with local environmental conditions and time, subsequently the equilibrium factor F also changes and hence affects the effective dose estimation of a particular dwelling. Therefore the UNSCEAR F value does not reflect the actual effective doses. Therefore, the present study is carried out to estimate the equilibrium factors in different types of dwellings in the urban Hyderabad using SSNTDs. It is found that, the equilibrium factors in the urban Hyderabad vary from 0.01 to 0.71 with an average 0.32 ± 0.23. The average F values of urban Hyderabad relatively lower than Indian average and global average. The reasons for the lower equilibrium factor values in the study area have been discussed in this paper. (author)

On the Evaluation of Outlier Detection and One-Class Classification Methods

DEFF Research Database (Denmark)

Swersky, Lorne; Marques, Henrique O.; Sander, Jörg

2016-01-01

It has been shown that unsupervised outlier detection methods can be adapted to the one-class classification problem. In this paper, we focus on the comparison of oneclass classification algorithms with such adapted unsupervised outlier detection methods, improving on previous comparison studies ...

Outlier identification in urban soils and its implications for identification of potential contaminated land

Science.gov (United States)

Zhang, Chaosheng

2010-05-01

Outliers in urban soil geochemical databases may imply potential contaminated land. Different methodologies which can be easily implemented for the identification of global and spatial outliers were applied for Pb concentrations in urban soils of Galway City in Ireland. Due to its strongly skewed probability feature, a Box-Cox transformation was performed prior to further analyses. The graphic methods of histogram and box-and-whisker plot were effective in identification of global outliers at the original scale of the dataset. Spatial outliers could be identified by a local indicator of spatial association of local Moran's I, cross-validation of kriging, and a geographically weighted regression. The spatial locations of outliers were visualised using a geographical information system. Different methods showed generally consistent results, but differences existed. It is suggested that outliers identified by statistical methods should be confirmed and justified using scientific knowledge before they are properly dealt with.

Stoicism, the physician, and care of medical outliers

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Papadimos Thomas J

2004-12-01

Full Text Available Abstract Background Medical outliers present a medical, psychological, social, and economic challenge to the physicians who care for them. The determinism of Stoic thought is explored as an intellectual basis for the pursuit of a correct mental attitude that will provide aid and comfort to physicians who care for medical outliers, thus fostering continued physician engagement in their care. Discussion The Stoic topics of good, the preferable, the morally indifferent, living consistently, and appropriate actions are reviewed. Furthermore, Zeno's cardinal virtues of Justice, Temperance, Bravery, and Wisdom are addressed, as are the Stoic passions of fear, lust, mental pain, and mental pleasure. These concepts must be understood by physicians if they are to comprehend and accept the Stoic view as it relates to having the proper attitude when caring for those with long-term and/or costly illnesses. Summary Practicing physicians, especially those that are hospital based, and most assuredly those practicing critical care medicine, will be emotionally challenged by the medical outlier. A Stoic approach to such a social and psychological burden may be of benefit.

Outlier Detection in GNSS Pseudo-Range/Doppler Measurements for Robust Localization

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Salim Zair

2016-04-01

Full Text Available In urban areas or space-constrained environments with obstacles, vehicle localization using Global Navigation Satellite System (GNSS data is hindered by Non-Line Of Sight (NLOS and multipath receptions. These phenomena induce faulty data that disrupt the precise localization of the GNSS receiver. In this study, we detect the outliers among the observations, Pseudo-Range (PR and/or Doppler measurements, and we evaluate how discarding them improves the localization. We specify a contrario modeling for GNSS raw data to derive an algorithm that partitions the dataset between inliers and outliers. Then, only the inlier data are considered in the localization process performed either through a classical Particle Filter (PF or a Rao-Blackwellization (RB approach. Both localization algorithms exclusively use GNSS data, but they differ by the way Doppler measurements are processed. An experiment has been performed with a GPS receiver aboard a vehicle. Results show that the proposed algorithms are able to detect the ‘outliers’ in the raw data while being robust to non-Gaussian noise and to intermittent satellite blockage. We compare the performance results achieved either estimating only PR outliers or estimating both PR and Doppler outliers. The best localization is achieved using the RB approach coupled with PR-Doppler outlier estimation.

Gender relations and the dowry system in India : the case of Hyderabad

OpenAIRE

Mota, Manuela; Casaca, Sara Falcão

2016-01-01

This article seeks to contribute to a more comprehensive understanding of the gender relations and the dowry system in India. It is based on a qualitative study that gave priority to the undertaking of interviews with women from different educational backgrounds living in the city of Hyderabad (South of India). The predominant perception of the interviewees is that education promotes economic and symbolic independence. The higher the educational level, the more critical accounts are found in ...

Environmental radiation levels around Nuclear Fuel Complex, Hyderabad during 1981-1988

International Nuclear Information System (INIS)

Mehta, Navnit; Lakshmanan, A.R.; Kathuria, S.P.; Nambi, K.S.V.

1989-01-01

This report presents environmental radiation monitoring results around Nuclear Ffuel Complex (NFC) at Hyderabad for the period, 1981-'88. During 1981-'83 only indoor radiations were monitored at 12 locations in the region of about 15 km. radius around NFC plant. However, during 1984-'88 both indoor and outdoor monitoring was done in a standardised manner at 8 locations. In this routine monitoring programme, environmental thermoluminescent dosimeters were used in quarterly integrating cycles. The average outdoor natural radiation level around NFC during 1984-'88 is found to be 227 ± 34 (σ) mR/y, which is the highest among the various sites in the country where DAE units are located. Such a high level of natural background radiation in and around Hyderabad is due to granitic terrains which normally have significant amounts of primordial radioactivity. The indoor to outdoor radiation ratio is found to be 1.35 ± 0.1 (σ). Application of this ratio on all the available indoor radiation monitoring results of 1981-'88 gives an estimate of 230 ± 26 mR/y as the average outdoor radiation level, and this is in very close agreement with the directly measured value mentioned earlier. The temporal variations seen in the quarterly results of each location have been tested for Normal and Log-Normal distributions and found to yield satisfactory correlations, although the plots reveal slight skewness; the latter however, could not be attributed to the NFC operations. (author). 7 refs., 4 tabs., 12 figs

Analyzing contentious relationships and outlier genes in phylogenomics.

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Walker, Joseph F; Brown, Joseph W; Smith, Stephen A

2018-06-08

Recent studies have demonstrated that conflict is common among gene trees in phylogenomic studies, and that less than one percent of genes may ultimately drive species tree inference in supermatrix analyses. Here, we examined two datasets where supermatrix and coalescent-based species trees conflict. We identified two highly influential "outlier" genes in each dataset. When removed from each dataset, the inferred supermatrix trees matched the topologies obtained from coalescent analyses. We also demonstrate that, while the outlier genes in the vertebrate dataset have been shown in a previous study to be the result of errors in orthology detection, the outlier genes from a plant dataset did not exhibit any obvious systematic error and therefore may be the result of some biological process yet to be determined. While topological comparisons among a small set of alternate topologies can be helpful in discovering outlier genes, they can be limited in several ways, such as assuming all genes share the same topology. Coalescent species tree methods relax this assumption but do not explicitly facilitate the examination of specific edges. Coalescent methods often also assume that conflict is the result of incomplete lineage sorting (ILS). Here we explored a framework that allows for quickly examining alternative edges and support for large phylogenomic datasets that does not assume a single topology for all genes. For both datasets, these analyses provided detailed results confirming the support for coalescent-based topologies. This framework suggests that we can improve our understanding of the underlying signal in phylogenomic datasets by asking more targeted edge-based questions.

Pathway-based outlier method reveals heterogeneous genomic structure of autism in blood transcriptome.

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Campbell, Malcolm G; Kohane, Isaac S; Kong, Sek Won

2013-09-24

Decades of research strongly suggest that the genetic etiology of autism spectrum disorders (ASDs) is heterogeneous. However, most published studies focus on group differences between cases and controls. In contrast, we hypothesized that the heterogeneity of the disorder could be characterized by identifying pathways for which individuals are outliers rather than pathways representative of shared group differences of the ASD diagnosis. Two previously published blood gene expression data sets--the Translational Genetics Research Institute (TGen) dataset (70 cases and 60 unrelated controls) and the Simons Simplex Consortium (Simons) dataset (221 probands and 191 unaffected family members)--were analyzed. All individuals of each dataset were projected to biological pathways, and each sample's Mahalanobis distance from a pooled centroid was calculated to compare the number of case and control outliers for each pathway. Analysis of a set of blood gene expression profiles from 70 ASD and 60 unrelated controls revealed three pathways whose outliers were significantly overrepresented in the ASD cases: neuron development including axonogenesis and neurite development (29% of ASD, 3% of control), nitric oxide signaling (29%, 3%), and skeletal development (27%, 3%). Overall, 50% of cases and 8% of controls were outliers in one of these three pathways, which could not be identified using group comparison or gene-level outlier methods. In an independently collected data set consisting of 221 ASD and 191 unaffected family members, outliers in the neurogenesis pathway were heavily biased towards cases (20.8% of ASD, 12.0% of control). Interestingly, neurogenesis outliers were more common among unaffected family members (Simons) than unrelated controls (TGen), but the statistical significance of this effect was marginal (Chi squared P < 0.09). Unlike group difference approaches, our analysis identified the samples within the case and control groups that manifested each expression

Sparsity-weighted outlier FLOODing (OFLOOD) method: Efficient rare event sampling method using sparsity of distribution.

Science.gov (United States)

Harada, Ryuhei; Nakamura, Tomotake; Shigeta, Yasuteru

2016-03-30

As an extension of the Outlier FLOODing (OFLOOD) method [Harada et al., J. Comput. Chem. 2015, 36, 763], the sparsity of the outliers defined by a hierarchical clustering algorithm, FlexDice, was considered to achieve an efficient conformational search as sparsity-weighted "OFLOOD." In OFLOOD, FlexDice detects areas of sparse distribution as outliers. The outliers are regarded as candidates that have high potential to promote conformational transitions and are employed as initial structures for conformational resampling by restarting molecular dynamics simulations. When detecting outliers, FlexDice defines a rank in the hierarchy for each outlier, which relates to sparsity in the distribution. In this study, we define a lower rank (first ranked), a medium rank (second ranked), and the highest rank (third ranked) outliers, respectively. For instance, the first-ranked outliers are located in a given conformational space away from the clusters (highly sparse distribution), whereas those with the third-ranked outliers are nearby the clusters (a moderately sparse distribution). To achieve the conformational search efficiently, resampling from the outliers with a given rank is performed. As demonstrations, this method was applied to several model systems: Alanine dipeptide, Met-enkephalin, Trp-cage, T4 lysozyme, and glutamine binding protein. In each demonstration, the present method successfully reproduced transitions among metastable states. In particular, the first-ranked OFLOOD highly accelerated the exploration of conformational space by expanding the edges. In contrast, the third-ranked OFLOOD reproduced local transitions among neighboring metastable states intensively. For quantitatively evaluations of sampled snapshots, free energy calculations were performed with a combination of umbrella samplings, providing rigorous landscapes of the biomolecules. © 2015 Wiley Periodicals, Inc.

Quality of Care at Hospitals Identified as Outliers in Publicly Reported Mortality Statistics for Percutaneous Coronary Intervention.

Science.gov (United States)

Waldo, Stephen W; McCabe, James M; Kennedy, Kevin F; Zigler, Corwin M; Pinto, Duane S; Yeh, Robert W

2017-05-16

Public reporting of percutaneous coronary intervention (PCI) outcomes may create disincentives for physicians to provide care for critically ill patients, particularly at institutions with worse clinical outcomes. We thus sought to evaluate the procedural management and in-hospital outcomes of patients treated for acute myocardial infarction before and after a hospital had been publicly identified as a negative outlier. Using state reports, we identified hospitals that were recognized as negative PCI outliers in 2 states (Massachusetts and New York) from 2002 to 2012. State hospitalization files were used to identify all patients with an acute myocardial infarction within these states. Procedural management and in-hospital outcomes were compared among patients treated at outlier hospitals before and after public report of outlier status. Patients at nonoutlier institutions were used to control for temporal trends. Among 86 hospitals, 31 were reported as outliers for excess mortality. Outlier facilities were larger, treating more patients with acute myocardial infarction and performing more PCIs than nonoutlier hospitals ( P fashion (interaction P =0.50) after public report of outlier status. The likelihood of in-hospital mortality decreased at outlier institutions (RR, 0.83; 95% CI, 0.81-0.85) after public report, and to a lesser degree at nonoutlier institutions (RR, 0.90; 95% CI, 0.87-0.92; interaction P <0.001). Among patients that underwent PCI, in-hospital mortality decreased at outlier institutions after public recognition of outlier status in comparison with prior (RR, 0.72; 9% CI, 0.66-0.79), a decline that exceeded the reduction at nonoutlier institutions (RR, 0.87; 95% CI, 0.80-0.96; interaction P <0.001). Large hospitals with higher clinical volume are more likely to be designated as negative outliers. The rates of percutaneous revascularization increased similarly at outlier and nonoutlier institutions after report of outlier status. After outlier

An Improved Semisupervised Outlier Detection Algorithm Based on Adaptive Feature Weighted Clustering

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Tingquan Deng

2016-01-01

Full Text Available There exist already various approaches to outlier detection, in which semisupervised methods achieve encouraging superiority due to the introduction of prior knowledge. In this paper, an adaptive feature weighted clustering-based semisupervised outlier detection strategy is proposed. This method maximizes the membership degree of a labeled normal object to the cluster it belongs to and minimizes the membership degrees of a labeled outlier to all clusters. In consideration of distinct significance of features or components in a dataset in determining an object being an inlier or outlier, each feature is adaptively assigned different weights according to the deviation degrees between this feature of all objects and that of a certain cluster prototype. A series of experiments on a synthetic dataset and several real-world datasets are implemented to verify the effectiveness and efficiency of the proposal.

Use of Multi-Objective Air Pollution Monitoring Sites and Online Air Pollution Monitoring System for Total Health Risk Assessment in Hyderabad, India

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K. V. Ramani

2005-08-01

Full Text Available A consensus has been emerging among public health experts in developing countries that air pollution, even at current ambient levels, aggravates respiratory and cardiovascular diseases and leads to premature mortality. Recent studies have also presented well-founded theories concerning the biological mechanisms involved and the groups of people that are probably more susceptible to health effects caused or exacerbated by inhalation of ambient particulate matter (PM.. On the basis of prognostic studies carried out in Center for Environment, JNT University, Hyderabad “it has been estimated that in Hyderabad some 1,700 to 3,000 people per year die prematurely as a result of inhaling PM”. These figures reflect only the effects of acute exposure to air pollution. If the long-term effects of chronic exposure are taken into account, 10,000–15,000 people a year could die prematurely in Hyderabad. This estimate of the chronic effects is based on other studies, which are not completely comparable with the Hyderabad situation. While the study designs and analyses in these other studies may indeed be different or irrelevant to Hyderabad, the fact they were carried out in other countries is irrelevant. Taking into account these considerations, a model for total health risk assessment for the city of Hyderabad, and its state of Andhra Pradesh in India has been developed using a multi-objective air pollution monitoring network and online and real time air pollution monitoring stations. For the model studies a number of potential monitoring sites were screened for general and site-specific criteria in a geographic information system (GIS environment that may, on a local basis, affect the representativeness of the data collected. Local features that may affect either the chemical or meteorological parameters are evaluated to assure a minimum of interference. Finally, for monitoring air pollution, an online and real

Outliers and Extremes: Dragon-Kings or Dragon-Fools?

Science.gov (United States)

Schertzer, D. J.; Tchiguirinskaia, I.; Lovejoy, S.

2012-12-01

Geophysics seems full of monsters like Victor Hugo's Court of Miracles and monstrous extremes have been statistically considered as outliers with respect to more normal events. However, a characteristic magnitude separating abnormal events from normal ones would be at odd with the generic scaling behaviour of nonlinear systems, contrary to "fat tailed" probability distributions and self-organized criticality. More precisely, it can be shown [1] how the apparent monsters could be mere manifestations of a singular measure mishandled as a regular measure. Monstrous fluctuations are the rule, not outliers and they are more frequent than usually thought up to the point that (theoretical) statistical moments can easily be infinite. The empirical estimates of the latter are erratic and diverge with sample size. The corresponding physics is that intense small scale events cannot be smoothed out by upscaling. However, based on a few examples, it has also been argued [2] that one should consider "genuine" outliers of fat tailed distributions so monstrous that they can be called "dragon-kings". We critically analyse these arguments, e.g. finite sample size and statistical estimates of the largest events, multifractal phase transition vs. more classical phase transition. We emphasize the fact that dragon-kings are not needed in order that the largest events become predictable. This is rather reminiscent of the Feast of Fools picturesquely described by Victor Hugo. [1] D. Schertzer, I. Tchiguirinskaia, S. Lovejoy et P. Hubert (2010): No monsters, no miracles: in nonlinear sciences hydrology is not an outlier! Hydrological Sciences Journal, 55 (6) 965 - 979. [2] D. Sornette (2009): Dragon-Kings, Black Swans and the Prediction of Crises. International Journal of Terraspace Science and Engineering 1(3), 1-17.

78 FR 66336 - U.S. Healthcare Education Mission to New Delhi, Hyderabad, and Ahmedabad, India, January 27...

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2013-11-05

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78 FR 68030 - U.S. Healthcare Education Mission to New Delhi, Hyderabad, and Ahmedabad, India, January 27...

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2013-11-13

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Multivariate Functional Data Visualization and Outlier Detection

KAUST Repository

Dai, Wenlin

2017-03-19

This article proposes a new graphical tool, the magnitude-shape (MS) plot, for visualizing both the magnitude and shape outlyingness of multivariate functional data. The proposed tool builds on the recent notion of functional directional outlyingness, which measures the centrality of functional data by simultaneously considering the level and the direction of their deviation from the central region. The MS-plot intuitively presents not only levels but also directions of magnitude outlyingness on the horizontal axis or plane, and demonstrates shape outlyingness on the vertical axis. A dividing curve or surface is provided to separate non-outlying data from the outliers. Both the simulated data and the practical examples confirm that the MS-plot is superior to existing tools for visualizing centrality and detecting outliers for functional data.

Multivariate Functional Data Visualization and Outlier Detection

KAUST Repository

Dai, Wenlin; Genton, Marc G.

2017-01-01

This article proposes a new graphical tool, the magnitude-shape (MS) plot, for visualizing both the magnitude and shape outlyingness of multivariate functional data. The proposed tool builds on the recent notion of functional directional outlyingness, which measures the centrality of functional data by simultaneously considering the level and the direction of their deviation from the central region. The MS-plot intuitively presents not only levels but also directions of magnitude outlyingness on the horizontal axis or plane, and demonstrates shape outlyingness on the vertical axis. A dividing curve or surface is provided to separate non-outlying data from the outliers. Both the simulated data and the practical examples confirm that the MS-plot is superior to existing tools for visualizing centrality and detecting outliers for functional data.

A Note on the Vogelsang Test for Additive Outliers

DEFF Research Database (Denmark)

Haldrup, Niels; Sansó, Andreu

The role of additive outliers in integrated time series has attractedsome attention recently and research shows that outlier detection shouldbe an integral part of unit root testing procedures. Recently, Vogelsang(1999) suggested an iterative procedure for the detection of multiple additiveoutliers...... in integrated time series. However, the procedure appearsto suffr from serious size distortions towards the finding of too manyoutliers as has been shown by Perron and Rodriguez (2003). In this notewe prove the inconsistency of the test in each step of the iterative procedureand hence alternative routes need...

Receptor model-based source apportionment of particulate pollution in Hyderabad, India.

Science.gov (United States)

Guttikunda, Sarath K; Kopakka, Ramani V; Dasari, Prasad; Gertler, Alan W

2013-07-01

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2 ± 24.6, 96.2 ± 12.1, and 64.3 ± 21.2 μg/m(3) of PM10, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m(3). In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM10 and PM2.5 size fractions for three seasons. The receptor modeling results indicated that the PM10 pollution is dominated by the direct vehicular exhaust and road dust (more than 60%). PM2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.

Why General Outlier Detection Techniques Do Not Suffice For Wireless Sensor Networks?

NARCIS (Netherlands)

Zhang, Y.; Meratnia, Nirvana; Havinga, Paul J.M.

2009-01-01

Raw data collected in wireless sensor networks are often unreliable and inaccurate due to noise, faulty sensors and harsh environmental effects. Sensor data that significantly deviate from normal pattern of sensed data are often called outliers. Outlier detection in wireless sensor networks aims at

PEMODELAN ARIMA DAN DETEKSI OUTLIER DATA CURAH HUJAN SEBAGAI EVALUASI SISTEM RADIO GELOMBANG MILIMETER

Directory of Open Access Journals (Sweden)

Achmad Mauludiyanto

2009-01-01

Full Text Available The purpose of this paper is to provide the results of Arima modeling and outlier detection in the rainfall data in Surabaya. This paper explained about the steps in the formation of rainfall models, especially Box-Jenkins procedure for Arima modeling and outlier detection. Early stages of modeling stasioneritas Arima is the identification of data, both in mean and variance. Stasioneritas evaluation data in the variance can be done with Box-Cox transformation. Meanwhile, in the mean stasioneritas can be done with the plot data and forms of ACF. Identification of ACF and PACF of the stationary data is used to determine the order of allegations Arima model. The next stage is to estimate the parameters and diagnostic checks to see the suitability model. Process diagnostics check conducted to evaluate whether the residual model is eligible berdistribusi white noise and normal. Ljung-Box Test is a test that can be used to validate the white noise condition, while the Kolmogorov-Smirnov Test is an evaluation test for normal distribution. Residual normality test results showed that the residual model of Arima not white noise, and indicates the existence of outlier in the data. Thus, the next step taken is outlier detection to eliminate outlier effects and increase the accuracy of predictions of the model Arima. Arima modeling implementation and outlier detection is done by using MINITAB package and MATLAB. The research shows that the modeling Arima and outlier detection can reduce the prediction error as measured by the criteria Mean Square Error (MSE. Quantitatively, the decline in the value of MSE by incorporating outlier detection is 23.7%, with an average decline 6.5%.

[Outlier sample discriminating methods for building calibration model in melons quality detecting using NIR spectra].

Science.gov (United States)

Tian, Hai-Qing; Wang, Chun-Guang; Zhang, Hai-Jun; Yu, Zhi-Hong; Li, Jian-Kang

2012-11-01

Outlier samples strongly influence the precision of the calibration model in soluble solids content measurement of melons using NIR Spectra. According to the possible sources of outlier samples, three methods (predicted concentration residual test; Chauvenet test; leverage and studentized residual test) were used to discriminate these outliers respectively. Nine suspicious outliers were detected from calibration set which including 85 fruit samples. Considering the 9 suspicious outlier samples maybe contain some no-outlier samples, they were reclaimed to the model one by one to see whether they influence the model and prediction precision or not. In this way, 5 samples which were helpful to the model joined in calibration set again, and a new model was developed with the correlation coefficient (r) 0. 889 and root mean square errors for calibration (RMSEC) 0.6010 Brix. For 35 unknown samples, the root mean square errors prediction (RMSEP) was 0.854 degrees Brix. The performance of this model was more better than that developed with non outlier was eliminated from calibration set (r = 0.797, RMSEC= 0.849 degrees Brix, RMSEP = 1.19 degrees Brix), and more representative and stable with all 9 samples were eliminated from calibration set (r = 0.892, RMSEC = 0.605 degrees Brix, RMSEP = 0.862 degrees).

Distance Based Method for Outlier Detection of Body Sensor Networks

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Haibin Zhang

2016-01-01

Full Text Available We propose a distance based method for the outlier detection of body sensor networks. Firstly, we use a Kernel Density Estimation (KDE to calculate the probability of the distance to k nearest neighbors for diagnosed data. If the probability is less than a threshold, and the distance of this data to its left and right neighbors is greater than a pre-defined value, the diagnosed data is decided as an outlier. Further, we formalize a sliding window based method to improve the outlier detection performance. Finally, to estimate the KDE by training sensor readings with errors, we introduce a Hidden Markov Model (HMM based method to estimate the most probable ground truth values which have the maximum probability to produce the training data. Simulation results show that the proposed method possesses a good detection accuracy with a low false alarm rate.

A Distributed Algorithm for the Cluster-Based Outlier Detection Using Unsupervised Extreme Learning Machines

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Xite Wang

2017-01-01

Full Text Available Outlier detection is an important data mining task, whose target is to find the abnormal or atypical objects from a given dataset. The techniques for detecting outliers have a lot of applications, such as credit card fraud detection and environment monitoring. Our previous work proposed the Cluster-Based (CB outlier and gave a centralized method using unsupervised extreme learning machines to compute CB outliers. In this paper, we propose a new distributed algorithm for the CB outlier detection (DACB. On the master node, we collect a small number of points from the slave nodes to obtain a threshold. On each slave node, we design a new filtering method that can use the threshold to efficiently speed up the computation. Furthermore, we also propose a ranking method to optimize the order of cluster scanning. At last, the effectiveness and efficiency of the proposed approaches are verified through a plenty of simulation experiments.

Comparative Study of Outlier Detection Algorithms via Fundamental Analysis Variables: An Application on Firms Listed in Borsa Istanbul

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Senol Emir

2016-04-01

Full Text Available In a data set, an outlier refers to a data point that is considerably different from the others. Detecting outliers provides useful application-specific insights and leads to choosing right prediction models. Outlier detection (also known as anomaly detection or novelty detection has been studied in statistics and machine learning for a long time. It is an essential preprocessing step of data mining process. In this study, outlier detection step in the data mining process is applied for identifying the top 20 outlier firms. Three outlier detection algorithms are utilized using fundamental analysis variables of firms listed in Borsa Istanbul for the 2011-2014 period. The results of each algorithm are presented and compared. Findings show that 15 different firms are identified by three different outlier detection methods. KCHOL and SAHOL have the greatest number of appearances with 12 observations among these firms. By investigating the results, it is concluded that each of three algorithms makes different outlier firm lists due to differences in their approaches for outlier detection.

Shape based kinetic outlier detection in real-time PCR

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D'Atri Mario

2010-04-01

Full Text Available Abstract Background Real-time PCR has recently become the technique of choice for absolute and relative nucleic acid quantification. The gold standard quantification method in real-time PCR assumes that the compared samples have similar PCR efficiency. However, many factors present in biological samples affect PCR kinetic, confounding quantification analysis. In this work we propose a new strategy to detect outlier samples, called SOD. Results Richards function was fitted on fluorescence readings to parameterize the amplification curves. There was not a significant correlation between calculated amplification parameters (plateau, slope and y-coordinate of the inflection point and the Log of input DNA demonstrating that this approach can be used to achieve a "fingerprint" for each amplification curve. To identify the outlier runs, the calculated parameters of each unknown sample were compared to those of the standard samples. When a significant underestimation of starting DNA molecules was found, due to the presence of biological inhibitors such as tannic acid, IgG or quercitin, SOD efficiently marked these amplification profiles as outliers. SOD was subsequently compared with KOD, the current approach based on PCR efficiency estimation. The data obtained showed that SOD was more sensitive than KOD, whereas SOD and KOD were equally specific. Conclusion Our results demonstrated, for the first time, that outlier detection can be based on amplification shape instead of PCR efficiency. SOD represents an improvement in real-time PCR analysis because it decreases the variance of data thus increasing the reliability of quantification.

42 CFR 484.240 - Methodology used for the calculation of the outlier payment.

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2010-10-01

... for each case-mix group. (b) The outlier threshold for each case-mix group is the episode payment... the same for all case-mix groups. (c) The outlier payment is a proportion of the amount of estimated...

ZODET: software for the identification, analysis and visualisation of outlier genes in microarray expression data.

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Daniel L Roden

Full Text Available Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET that enables identification and visualisation of gross abnormalities in gene expression (outliers in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI, using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and Java.The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis.

Environmental education and socioresponsive engineering. Report of an educational initiative in Hyderabad, India.

Science.gov (United States)

Ansari, Ali Uddin; Jafari, Ashfaque; Mirzana, Ishrat Meera; Imtiaz, Zulfia; Lukacs, Heather

2003-07-01

A recent initiative at Muffakham Jah College of Engineering and Technology, Hyderabad, India, has resulted in setting up a program called Centre for Environment Studies and Socioresponsive Engineering which seeks to involve undergraduate students in studying and solving environmental problems in and around the city of Hyderabad, India. Two pilot projects have been undertaken--one focusing on design and construction of an eco-friendly house, The Natural House, and another directed at improving environmental and general living conditions in a slum area. The paper describes our attempts and experience of motivating our students to take interest in such projects. In an interesting development we invited a member of a student-faculty team at Massachusetts Institute of Technology (M.I.T.) that is doing a project in Nepal on safe drinking water. We report in our paper how the presentation by the guest from M.I.T. served as a catalyst for generating interest among civil and mechanical engineering students in our own projects. The paper includes contributions from one of our students and the M.I.T. staff member, reporting on their experiences related to the slum development project. We also discuss the Natural House project and its international and educational significance as a means of inculcating sensitivity and interest in nature among engineering students. We propose a pledge for engineers similar to the Hippocratic Oath for medical professionals.

Proposed School of Earth And Space Sciences, Hyderabad, India

Science.gov (United States)

Aswathanarayana, U.

2004-05-01

The hallmarks of the proposed school in the University of Hyderabad, Hyderabad,India, would be synergy, inclusivity and globalism. The School will use the synergy between the earth (including oceanic and atmospheric realms), space and information sciences to bridge the digital divide, and promote knowledge-driven and job-led economic development of the country. It will endeavour to (i) provide the basic science underpinnings for Space and Information Technologies, (ii) develop new methodologies for the utilization of natural resources (water, soils, sediments, minerals, biota, etc.)in ecologically-sustainable, employment-generating and economically-viable ways, (iii) mitigate the adverse consequences of natural hazards through preparedness systems,etc. The School will undertake research in the inter-disciplinary areas of earth and space sciences (e.g. climate predictability, satellite remote sensing of soil moisture) and linking integrative science with the needs of the decision makers. It will offer a two-year M.Tech. (four semesters, devoted to Theory, Tools, Applications and Dissertation, respectively ) course in Earth and Space Sciences. The Applications will initially cover eight course clusters devoted to Water Resources Management, Agriculture, Ocean studies, Energy Resources, Urban studies, Environment, Natural Hazards and Mineral Resources Management. The School will also offer a number of highly focused short-term refresher courses / supplementary courses to enable cadres to update their knowledge and skills. The graduates of the School would be able to find employment in macro-projects, such as inter-basin water transfers, and Operational crop condition assessment over large areas, etc. as well as in micro-projects, such as rainwater harvesting, and marketing of remote sensing products to stake-holders (e.g. precision agricultural advice to the farmers, using the large bandwidth of thousands of kilometres of unlit optical fibres). As the School is highly

Outlier Removal and the Relation with Reporting Errors and Quality of Psychological Research

Science.gov (United States)

Bakker, Marjan; Wicherts, Jelte M.

2014-01-01

Background The removal of outliers to acquire a significant result is a questionable research practice that appears to be commonly used in psychology. In this study, we investigated whether the removal of outliers in psychology papers is related to weaker evidence (against the null hypothesis of no effect), a higher prevalence of reporting errors, and smaller sample sizes in these papers compared to papers in the same journals that did not report the exclusion of outliers from the analyses. Methods and Findings We retrieved a total of 2667 statistical results of null hypothesis significance tests from 153 articles in main psychology journals, and compared results from articles in which outliers were removed (N = 92) with results from articles that reported no exclusion of outliers (N = 61). We preregistered our hypotheses and methods and analyzed the data at the level of articles. Results show no significant difference between the two types of articles in median p value, sample sizes, or prevalence of all reporting errors, large reporting errors, and reporting errors that concerned the statistical significance. However, we did find a discrepancy between the reported degrees of freedom of t tests and the reported sample size in 41% of articles that did not report removal of any data values. This suggests common failure to report data exclusions (or missingness) in psychological articles. Conclusions We failed to find that the removal of outliers from the analysis in psychological articles was related to weaker evidence (against the null hypothesis of no effect), sample size, or the prevalence of errors. However, our control sample might be contaminated due to nondisclosure of excluded values in articles that did not report exclusion of outliers. Results therefore highlight the importance of more transparent reporting of statistical analyses. PMID:25072606

42 CFR 412.84 - Payment for extraordinarily high-cost cases (cost outliers).

Science.gov (United States)

2010-10-01

... obtains accurate data with which to calculate either an operating or capital cost-to-charge ratio (or both... outlier payments will be based on operating and capital cost-to-charge ratios calculated based on a ratio... outliers). 412.84 Section 412.84 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF...

A Case-control Study of Diphtheria in the High Incidence City of Hyderabad, India.

Science.gov (United States)

Allam, Ramesh Reddy; Uthappa, Chengappa Kechamada; Duerst, Rebecca; Sorley, Evan; Udaragudi, Prasada Rao; Kampa, Shankar; Dworkin, Mark S

2016-03-01

India accounts for approximately 72% of reported diphtheria cases globally, the majority of which occur in the state of Andhra Pradesh. The aim of this study is to better understand lack of knowledge on diphtheria vaccination and to determine factors associated with diphtheria and low knowledge and negative attitudes. We performed a 1:1 case-control study of hospitalized diphtheria cases in Hyderabad. Eligible case patients were 10 years of age or older, resided within the city of Hyderabad and were diagnosed with diphtheria per the case definition. Patients admitted to the hospital for nonrespiratory communicable diseases and residing in the same geographic region as that of cases were eligible for enrolment as controls : There were no statistical differences in disease outcome by gender, education, economic status and mean room per person sleeping in the house in case and control subjects. Not having heard of diphtheria (adjusted odds ratio: 3.56; 95% confidence intervals: 1.58-8.04] and not believing that vaccines can prevent people from getting diseases (adjusted odds ratio: 3.99; 95% confidence intervals: 1.18-13.45) remained significantly associated with diphtheria on multivariate analysis. To reduce the burden of diphtheria in India, further efforts to educate the public about diphtheria should be considered.

Slowing ash mortality: a potential strategy to slam emerald ash borer in outlier sites

Science.gov (United States)

Deborah G. McCullough; Nathan W. Siegert; John Bedford

2009-01-01

Several isolated outlier populations of emerald ash borer (Agrilus planipennis Fairmaire) were discovered in 2008 and additional outliers will likely be found as detection surveys and public outreach activities...

Algorithms for Speeding up Distance-Based Outlier Detection

Data.gov (United States)

National Aeronautics and Space Administration — The problem of distance-based outlier detection is difficult to solve efficiently in very large datasets because of potential quadratic time complexity. We address...

Patterns of Care for Biologic-Dosing Outliers and Nonoutliers in Biologic-Naive Patients with Rheumatoid Arthritis.

Science.gov (United States)

Delate, Thomas; Meyer, Roxanne; Jenkins, Daniel

2017-08-01

Although most biologic medications for patients with rheumatoid arthritis (RA) have recommended fixed dosing, actual biologic dosing may vary among real-world patients, since some patients can receive higher (high-dose outliers) or lower (low-dose outliers) doses than what is recommended in medication package inserts. To describe the patterns of care for biologic-dosing outliers and nonoutliers in biologic-naive patients with RA. This was a retrospective, longitudinal cohort study of patients with RA who were not pregnant and were aged ≥ 18 and 110% of the approved dose in the package insert at any time during the study period. Baseline patient profiles, treatment exposures, and outcomes were collected during the 180 days before and up to 2 years after biologic initiation and compared across index biologic outlier groups. Patients were followed for at least 1 year, with a subanalysis of those patients who remained as members for 2 years. This study included 434 RA patients with 1 year of follow-up and 372 RA patients with 2 years of follow-up. Overall, the vast majority of patients were female (≈75%) and had similar baseline characteristics. Approximately 10% of patients were outliers in both follow-up cohorts. ETN patients were least likely to become outliers, and ADA patients were most likely to become outliers. Of all outliers during the 1-year follow-up, patients were more likely to be a high-dose outlier (55%) than a low-dose outlier (45%). Median 1- and 2-year adjusted total biologic costs (based on wholesale acquisition costs) were higher for ADA and ETA nonoutliers than for IFX nonoutliers. Biologic persistence was highest for IFX patients. Charlson Comorbidity Index score, ETN and IFX index biologic, and treatment with a nonbiologic disease-modifying antirheumatic drug (DMARD) before biologic initiation were associated with becoming high- or low-dose outliers (c-statistic = 0.79). Approximately 1 in 10 study patients with RA was identified as a

Detection of Outliers in Panel Data of Intervention Effects Model Based on Variance of Remainder Disturbance

Directory of Open Access Journals (Sweden)

Yanfang Lyu

2015-01-01

Full Text Available The presence of outliers can result in seriously biased parameter estimates. In order to detect outliers in panel data models, this paper presents a modeling method to assess the intervention effects based on the variance of remainder disturbance using an arbitrary strictly positive twice continuously differentiable function. This paper also provides a Lagrange Multiplier (LM approach to detect and identify a general type of outlier. Furthermore, fixed effects models and random effects models are discussed to identify outliers and the corresponding LM test statistics are given. The LM test statistics for an individual-based model to detect outliers are given as a particular case. Finally, this paper performs an application using panel data and explains the advantages of the proposed method.

Supervised Outlier Detection in Large-Scale Mvs Point Clouds for 3d City Modeling Applications

Science.gov (United States)

Stucker, C.; Richard, A.; Wegner, J. D.; Schindler, K.

2018-05-01

We propose to use a discriminative classifier for outlier detection in large-scale point clouds of cities generated via multi-view stereo (MVS) from densely acquired images. What makes outlier removal hard are varying distributions of inliers and outliers across a scene. Heuristic outlier removal using a specific feature that encodes point distribution often delivers unsatisfying results. Although most outliers can be identified correctly (high recall), many inliers are erroneously removed (low precision), too. This aggravates object 3D reconstruction due to missing data. We thus propose to discriminatively learn class-specific distributions directly from the data to achieve high precision. We apply a standard Random Forest classifier that infers a binary label (inlier or outlier) for each 3D point in the raw, unfiltered point cloud and test two approaches for training. In the first, non-semantic approach, features are extracted without considering the semantic interpretation of the 3D points. The trained model approximates the average distribution of inliers and outliers across all semantic classes. Second, semantic interpretation is incorporated into the learning process, i.e. we train separate inlieroutlier classifiers per semantic class (building facades, roof, ground, vegetation, fields, and water). Performance of learned filtering is evaluated on several large SfM point clouds of cities. We find that results confirm our underlying assumption that discriminatively learning inlier-outlier distributions does improve precision over global heuristics by up to ≍ 12 percent points. Moreover, semantically informed filtering that models class-specific distributions further improves precision by up to ≍ 10 percent points, being able to remove very isolated building, roof, and water points while preserving inliers on building facades and vegetation.

Outlier identification procedures for contingency tables using maximum likelihood and $L_1$ estimates

NARCIS (Netherlands)

Kuhnt, S.

2004-01-01

Observed cell counts in contingency tables are perceived as outliers if they have low probability under an anticipated loglinear Poisson model. New procedures for the identification of such outliers are derived using the classical maximum likelihood estimator and an estimator based on the L1 norm.

How do children travel to school in urban India? A cross-sectional study of 5,842 children in Hyderabad.

Science.gov (United States)

Tetali, Shailaja; Edwards, P; Roberts, G V S Murthy I

2016-10-19

Millions of children travel to school every day in India, yet little is known about this journey. We examined the distribution and determinants of school travel in Hyderabad, India. We conducted a cross-sectional survey using a two-stage stratified cluster sampling design. School travel questionnaires were used to collect data from children aged 11-14 years, attending private, semi-private and government funded schools in Hyderabad. We used Google Earth to estimate the distance from home to school for each child and modelled the relationship between distance to school and mode of travel, adjusting for confounders. Forty five of the 48 eligible schools that were selected agreed to participate, providing a total sample of 5842 children. The response rate was 99 %. Most children walked (57 %) or cycled (6 %) to school but 36 % used motorised transport (mostly bus). The proportion using motorised transport was higher in children attending private schools (41 %) than in those attending government schools (24 %). Most (90 %) children lived within 5km of school and 36 % lived within 1km. Greater distance to school was strongly associated with the use of motorised transport. Children living close to school were much more likely to walk or cycle. Most children in Hyderabad walk (57 %) or cycle (6 %) to school. If these levels are to be maintained, there is an urgent need to ensure that walking and cycling are safe and pleasant. Social policies that decrease distances to school could have a large impact on road traffic injuries, air pollution, and physical activity levels.

How do children travel to school in urban India? A cross-sectional study of 5,842 children in Hyderabad

Directory of Open Access Journals (Sweden)

Shailaja Tetali

2016-10-01

Full Text Available Abstract Background Millions of children travel to school every day in India, yet little is known about this journey. We examined the distribution and determinants of school travel in Hyderabad, India. Methods We conducted a cross-sectional survey using a two-stage stratified cluster sampling design. School travel questionnaires were used to collect data from children aged 11–14 years, attending private, semi-private and government funded schools in Hyderabad. We used Google Earth to estimate the distance from home to school for each child and modelled the relationship between distance to school and mode of travel, adjusting for confounders. Results Forty five of the 48 eligible schools that were selected agreed to participate, providing a total sample of 5842 children. The response rate was 99 %. Most children walked (57 % or cycled (6 % to school but 36 % used motorised transport (mostly bus. The proportion using motorised transport was higher in children attending private schools (41 % than in those attending government schools (24 %. Most (90 % children lived within 5km of school and 36 % lived within 1km. Greater distance to school was strongly associated with the use of motorised transport. Children living close to school were much more likely to walk or cycle. Conclusions Most children in Hyderabad walk (57 % or cycle (6 % to school. If these levels are to be maintained, there is an urgent need to ensure that walking and cycling are safe and pleasant. Social policies that decrease distances to school could have a large impact on road traffic injuries, air pollution, and physical activity levels.

Modeling of activation data in the BrainMapTM database: Detection of outliers

DEFF Research Database (Denmark)

Nielsen, Finn Årup; Hansen, Lars Kai

2002-01-01

models is identification of novelty, i.e., low probability database events. We rank the novelty of the outliers and investigate the cause for 21 of the most novel, finding several outliers that are entry and transcription errors or infrequent or non-conforming terminology. We briefly discuss the use...

The stability of soil aggregates in tilled fallow areas in Hyderabad district, Pakistan

Directory of Open Access Journals (Sweden)

Tagar Ahmed

2015-12-01

Full Text Available Arid areas are particularly susceptible to soil erosion due to long dry periods and sudden heavy downpours. This study investigates the aggregate size distribution and aggregate stability of twelve tilled fallow areas of Hyderabad district, Sindh, Pakistan. This study determined aggregate size distribution by dry sieving to evaluate the seedbed condition and aggregate stability using wet sieving to assess the susceptibility of tilled fallow areas to soil erosion. The aggregate size distribution of the soils of the selected areas was highly variable. Gulistan-e-Sarmast had the largest number of clods (51.0% followed by Kohsar (49.0%, Latifabad # 10 (41.10% and Daman-e-Kohsar (39.0%. Fazal Sun City, the left side of the Indus River, the Village Nooral Detha and the left side of the Abdullah Sports city had a greater number of large (>8.0 mm and small aggregates (<0.5 mm. The optimum aggregate size distribution was found in the left side of the channel, which had the largest number of aggregates (50.50% in the 0.5–8.0 mm sieve size range. Maximum aggregate stability (AS was found in Gulistan-e-Sarmast (46%, Kohsar (42% and Latifabad # 10 (34%, while all other soils had minimum aggregate stability (<14%. The minimum aggregate stabilities demonstrate that the tilled fallow areas of Hyderabad district are highly susceptible to erosion. Therefore, the present study suggests investigating potential ways to enhance the aggregate stabilities of soils.

GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets.

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John Patrick Mpindi

Full Text Available BACKGROUND: Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type ('outlier genes', a hallmark of potential oncogenes. METHODOLOGY: A new statistical method (the gene tissue index, GTI was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29 of these genes, and 17 of these 19 genes (90% showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target. CONCLUSIONS/SIGNIFICANCE: Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is

The outlier sample effects on multivariate statistical data processing geochemical stream sediment survey (Moghangegh region, North West of Iran)

International Nuclear Information System (INIS)

Ghanbari, Y.; Habibnia, A.; Memar, A.

2009-01-01

In geochemical stream sediment surveys in Moghangegh Region in north west of Iran, sheet 1:50,000, 152 samples were collected and after the analyze and processing of data, it revealed that Yb, Sc, Ni, Li, Eu, Cd, Co, as contents in one sample is far higher than other samples. After detecting this sample as an outlier sample, the effect of this sample on multivariate statistical data processing for destructive effects of outlier sample in geochemical exploration was investigated. Pearson and Spear man correlation coefficient methods and cluster analysis were used for multivariate studies and the scatter plot of some elements together the regression profiles are given in case of 152 and 151 samples and the results are compared. After investigation of multivariate statistical data processing results, it was realized that results of existence of outlier samples may appear as the following relations between elements: - true relation between two elements, which have no outlier frequency in the outlier sample. - false relation between two elements which one of them has outlier frequency in the outlier sample. - complete false relation between two elements which both have outlier frequency in the outlier sample

Co-circulation and co-infections of all dengue virus serotypes in Hyderabad, India 2014.

Science.gov (United States)

Vaddadi, K; Gandikota, C; Jain, P K; Prasad, V S V; Venkataramana, M

2017-09-01

The burden of dengue virus infections increased globally during recent years. Though India is considered as dengue hyper-endemic country, limited data are available on disease epidemiology. The present study includes molecular characterization of dengue virus strains occurred in Hyderabad, India, during the year 2014. A total of 120 febrile cases were recruited for this study, which includes only children and 41 were serologically confirmed for dengue positive infections using non-structural (NS1) and/or IgG/IgM ELISA tests. RT-PCR, nucleotide sequencing and evolutionary analyses were carried out to identify the circulating serotypes/genotypes. The data indicated a high percent of severe dengue (63%) in primary infections. Simultaneous circulation of all four serotypes and co-infections were observed for the first time in Hyderabad, India. In total, 15 patients were co-infected with more than one dengue serotype and 12 (80%) of them had severe dengue. One of the striking findings of the present study is the identification of serotype Den-1 as the first report from this region and this strain showed close relatedness to the Thailand 1980 strains but not to any of the strains reported from India until now. Phylogenetically, all four strains of the present study showed close relatedness to the strains, which are reported to be high virulent.

GHG and Air Pollution Co-benefits Analysis to Support Decision Making in Hyderabad, India

Science.gov (United States)

Guttikunda, S.; Shah, M.

2008-12-01

The increasing energy demand in the transport and industrial sectors accounts for a high carbon footprint in Hyderabad, India, and consequently to increasing air pollution. Integrated Environmental Strategies program under US EPA supported the analysis of Andhra Pradesh Pollution Control Board (PCB), to identify the major sources of pollution (local and global) and prioritize a series of strategies to better address mitigation in a cost effective manner. In Hyderabad, under the current trends, PM10 and CO2 emissions in 2020 are estimated to increase ~50 percent, compared to 2006 levels to ~43.5 ktons and ~10.3 million tons respectively. A co-benefits framework was implemented in analyzing the future control scenarios for human health benefits and carbon savings. Overall, implementing a series of interventions ranging from urban planning including better transport planning with bus rapid transport and metro rail, relocation of industries, and waste management, are expected to reduce the local and global emissions below the 2006 levels and yield an estimated ~US 196 million and ~US 492 million, in 2010 and 2020 respectively, in combined benefits of health and carbon savings. The PCB is coordinating the efforts for planning and implementation of these strategies. This paper will focus on presenting the methodology utilized for estimating emissions, pollutant dispersion, and impact on local and global environments, evaluated against the business as usual scenarios.

Electricity Price Forecasting Based on AOSVR and Outlier Detection

Institute of Scientific and Technical Information of China (English)

Zhou Dianmin; Gao Lin; Gao Feng

2005-01-01

Electricity price is of the first consideration for all the participants in electric power market and its characteristics are related to both market mechanism and variation in the behaviors of market participants. It is necessary to build a real-time price forecasting model with adaptive capability; and because there are outliers in the price data, they should be detected and filtrated in training the forecasting model by regression method. In view of these points, this paper presents an electricity price forecasting method based on accurate on-line support vector regression (AOSVR) and outlier detection. Numerical testing results show that the method is effective in forecasting the electricity prices in electric power market.

On the identification of Dragon Kings among extreme-valued outliers

Science.gov (United States)

Riva, M.; Neuman, S. P.; Guadagnini, A.

2013-07-01

Extreme values of earth, environmental, ecological, physical, biological, financial and other variables often form outliers to heavy tails of empirical frequency distributions. Quite commonly such tails are approximated by stretched exponential, log-normal or power functions. Recently there has been an interest in distinguishing between extreme-valued outliers that belong to the parent population of most data in a sample and those that do not. The first type, called Gray Swans by Nassim Nicholas Taleb (often confused in the literature with Taleb's totally unknowable Black Swans), is drawn from a known distribution of the tails which can thus be extrapolated beyond the range of sampled values. However, the magnitudes and/or space-time locations of unsampled Gray Swans cannot be foretold. The second type of extreme-valued outliers, termed Dragon Kings by Didier Sornette, may in his view be sometimes predicted based on how other data in the sample behave. This intriguing prospect has recently motivated some authors to propose statistical tests capable of identifying Dragon Kings in a given random sample. Here we apply three such tests to log air permeability data measured on the faces of a Berea sandstone block and to synthetic data generated in a manner statistically consistent with these measurements. We interpret the measurements to be, and generate synthetic data that are, samples from α-stable sub-Gaussian random fields subordinated to truncated fractional Gaussian noise (tfGn). All these data have frequency distributions characterized by power-law tails with extreme-valued outliers about the tail edges.

On the identification of Dragon Kings among extreme-valued outliers

Directory of Open Access Journals (Sweden)

M. Riva

2013-07-01

Full Text Available Extreme values of earth, environmental, ecological, physical, biological, financial and other variables often form outliers to heavy tails of empirical frequency distributions. Quite commonly such tails are approximated by stretched exponential, log-normal or power functions. Recently there has been an interest in distinguishing between extreme-valued outliers that belong to the parent population of most data in a sample and those that do not. The first type, called Gray Swans by Nassim Nicholas Taleb (often confused in the literature with Taleb's totally unknowable Black Swans, is drawn from a known distribution of the tails which can thus be extrapolated beyond the range of sampled values. However, the magnitudes and/or space–time locations of unsampled Gray Swans cannot be foretold. The second type of extreme-valued outliers, termed Dragon Kings by Didier Sornette, may in his view be sometimes predicted based on how other data in the sample behave. This intriguing prospect has recently motivated some authors to propose statistical tests capable of identifying Dragon Kings in a given random sample. Here we apply three such tests to log air permeability data measured on the faces of a Berea sandstone block and to synthetic data generated in a manner statistically consistent with these measurements. We interpret the measurements to be, and generate synthetic data that are, samples from α-stable sub-Gaussian random fields subordinated to truncated fractional Gaussian noise (tfGn. All these data have frequency distributions characterized by power-law tails with extreme-valued outliers about the tail edges.

Factor-based forecasting in the presence of outliers

DEFF Research Database (Denmark)

Kristensen, Johannes Tang

2014-01-01

Macroeconomic forecasting using factor models estimated by principal components has become a popular research topic with many both theoretical and applied contributions in the literature. In this paper we attempt to address an often neglected issue in these models: The problem of outliers...... in the data. Most papers take an ad-hoc approach to this problem and simply screen datasets prior to estimation and remove anomalous observations. We investigate whether forecasting performance can be improved by using the original unscreened dataset and replacing principal components with a robust...... apply the estimator in a simulated real-time forecasting exercise to test its merits. We use a newly compiled dataset of US macroeconomic series spanning the period 1971:2–2012:10. Our findings suggest that the chosen treatment of outliers does affect forecasting performance and that in many cases...

Rethinking urban space in cities - A study of parks in Hyderabad, India

Science.gov (United States)

Shrinagesh, B.; Markandey, Kalpana

2016-06-01

Urban areas being economically diversified attract large streams of migrants making for a burgeoning population. This is more prevalent in the developing countries. The concomitants of this are high density, heavy traffic movement and increased pollution levels. To reduce the stressful life of city dwellers it is important to have open spaces, where one can pursue leisure time activities a few removes from clutter. A public space is a space that is generally open and accessible to people. Roads, public parks, libraries etc, are typically considered public space. The term ‘public space’ is also often misconstrued to mean other things such as ‘gathering place’, which is an element of the larger concept of social space. Hyderabad, the historical city is the capital of Telangana, India and extends from longitude 78o23’ to 78o33’E and latitude of 17o17’ to 17o31’N. It is the second largest city in terms of area and fifth largest in terms of population. It is one of the fastest growing cities in India. There is a huge influx of people from other states in search of better opportunities. The main objectives of the study are; to study the sprawl and changing demographic structure of the city of Hyderabad, to study the accessibility of parks, to study the need for the emergence of a local public sphere. The data base will be mainly on secondary data collected from various government sources. A primary survey will be conducted based on a structured questionnaire. GIS and other mapping techniques will be applied to analyse the data.

Outlier identification in colorectal surgery should separate elective and nonelective service components.

Science.gov (United States)

Byrne, Ben E; Mamidanna, Ravikrishna; Vincent, Charles A; Faiz, Omar D

2014-09-01

The identification of health care institutions with outlying outcomes is of great importance for reporting health care results and for quality improvement. Historically, elective surgical outcomes have received greater attention than nonelective results, although some studies have examined both. Differences in outlier identification between these patient groups have not been adequately explored. The aim of this study was to compare the identification of institutional outliers for mortality after elective and nonelective colorectal resection in England. This was a cohort study using routine administrative data. Ninety-day mortality was determined by using statutory records of death. Adjusted Trust-level mortality rates were calculated by using multiple logistic regression. High and low mortality outliers were identified and compared across funnel plots for elective and nonelective surgery. All English National Health Service Trusts providing colorectal surgery to an unrestricted patient population were studied. Adults admitted for colorectal surgery between April 2006 and March 2012 were included. Segmental colonic or rectal resection was performed. The primary outcome measured was 90-day mortality. Included were 195,118 patients, treated at 147 Trusts. Ninety-day mortality rates after elective and nonelective surgery were 4% and 18%. No unit with high outlying mortality for elective surgery was a high outlier for nonelective mortality and vice versa. Trust level, observed-to-expected mortality for elective and nonelective surgery, was moderately correlated (Spearman ρ = 0.50, pinstitutional mortality outlier after elective and nonelective colorectal surgery was not closely related. Therefore, mortality rates should be reported for both patient cohorts separately. This would provide a broad picture of the state of colorectal services and help direct research and quality improvement activities.

Outlier identification and visualization for Pb concentrations in urban soils and its implications for identification of potential contaminated land

International Nuclear Information System (INIS)

Zhang Chaosheng; Tang Ya; Luo Lin; Xu Weilin

2009-01-01

Outliers in urban soil geochemical databases may imply potential contaminated land. Different methodologies which can be easily implemented for the identification of global and spatial outliers were applied for Pb concentrations in urban soils of Galway City in Ireland. Due to its strongly skewed probability feature, a Box-Cox transformation was performed prior to further analyses. The graphic methods of histogram and box-and-whisker plot were effective in identification of global outliers at the original scale of the dataset. Spatial outliers could be identified by a local indicator of spatial association of local Moran's I, cross-validation of kriging, and a geographically weighted regression. The spatial locations of outliers were visualised using a geographical information system. Different methods showed generally consistent results, but differences existed. It is suggested that outliers identified by statistical methods should be confirmed and justified using scientific knowledge before they are properly dealt with. - Outliers in urban geochemical databases can be detected to provide guidance for identification of potential contaminated land.

Genotoxicity of the Musi River (Hyderabad, India) investigated with the VITOTOX test.

Science.gov (United States)

Vijayashree, B; Ahuja, Y R; Regniers, L; Rao, V; Verschaeve, L

2005-01-01

The bacterial VITOTOX genotoxicity test was used to screen water samples collected from three different stations along the banks of the river Musi, in Hyderabad, India. Water was collected at three stations that differed from each other in the nature of the surrounding industrial and other activities. A number of different pollutants were also measured in water, soil and air samples. The three stations were found highly polluted and different with regard to the genotoxicity and toxicity of their samples. These results demonstrate the need for further biological studies in this area to generate valuable data on genomic instability, risk assessment of cancer, and to provide avenues for risk management.

Outlier robustness for wind turbine extrapolated extreme loads

DEFF Research Database (Denmark)

Natarajan, Anand; Verelst, David Robert

2012-01-01

. Stochastic identification of numerical artifacts in simulated loads is demonstrated using the method of principal component analysis. The extrapolation methodology is made robust to outliers through a weighted loads approach, whereby the eigenvalues of the correlation matrix obtained using the loads with its...

Fuzzy Treatment of Candidate Outliers in Measurements

Directory of Open Access Journals (Sweden)

Giampaolo E. D'Errico

2012-01-01

Full Text Available Robustness against the possible occurrence of outlying observations is critical to the performance of a measurement process. Open questions relevant to statistical testing for candidate outliers are reviewed. A novel fuzzy logic approach is developed and exemplified in a metrology context. A simulation procedure is presented and discussed by comparing fuzzy versus probabilistic models.

The comparison between several robust ridge regression estimators in the presence of multicollinearity and multiple outliers

Science.gov (United States)

Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said

2014-09-01

In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.

Outlier Detection in Urban Air Quality Sensor Networks

NARCIS (Netherlands)

van Zoest, V.M.; Stein, A.; Hoek, Gerard

2018-01-01

Low-cost urban air quality sensor networks are increasingly used to study the spatio-temporal variability in air pollutant concentrations. Recently installed low-cost urban sensors, however, are more prone to result in erroneous data than conventional monitors, e.g., leading to outliers. Commonly

Outlier identification and visualization for Pb concentrations in urban soils and its implications for identification of potential contaminated land

Energy Technology Data Exchange (ETDEWEB)

Zhang Chaosheng, E-mail: chaosheng.zhang@nuigalway.i [School of Geography and Archaeology, National University of Ireland, Galway (Ireland); Tang Ya [Department of Environmental Sciences, Sichuan University, Chengdu, Sichuan 610065 (China); Luo Lin; Xu Weilin [State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, Sichuan 610065 (China)

2009-11-15

Outliers in urban soil geochemical databases may imply potential contaminated land. Different methodologies which can be easily implemented for the identification of global and spatial outliers were applied for Pb concentrations in urban soils of Galway City in Ireland. Due to its strongly skewed probability feature, a Box-Cox transformation was performed prior to further analyses. The graphic methods of histogram and box-and-whisker plot were effective in identification of global outliers at the original scale of the dataset. Spatial outliers could be identified by a local indicator of spatial association of local Moran's I, cross-validation of kriging, and a geographically weighted regression. The spatial locations of outliers were visualised using a geographical information system. Different methods showed generally consistent results, but differences existed. It is suggested that outliers identified by statistical methods should be confirmed and justified using scientific knowledge before they are properly dealt with. - Outliers in urban geochemical databases can be detected to provide guidance for identification of potential contaminated land.

System and Method for Outlier Detection via Estimating Clusters

Science.gov (United States)

Iverson, David J. (Inventor)

2016-01-01

An efficient method and system for real-time or offline analysis of multivariate sensor data for use in anomaly detection, fault detection, and system health monitoring is provided. Models automatically derived from training data, typically nominal system data acquired from sensors in normally operating conditions or from detailed simulations, are used to identify unusual, out of family data samples (outliers) that indicate possible system failure or degradation. Outliers are determined through analyzing a degree of deviation of current system behavior from the models formed from the nominal system data. The deviation of current system behavior is presented as an easy to interpret numerical score along with a measure of the relative contribution of each system parameter to any off-nominal deviation. The techniques described herein may also be used to "clean" the training data.

A study of outliers in statistical distributions of mechanical properties of structural steels

International Nuclear Information System (INIS)

Oefverbeck, P.; Oestberg, G.

1977-01-01

The safety against failure of pressure vessels can be assessed by statistical methods, so-called probabilistic fracture mechanics. The data base for such estimations is admittedly rather meagre, making it necessary to assume certain conventional statistical distributions. Since the failure rates arrived at are low, for nuclear vessels of the order of 10 - to 10 - per year, the extremes of the variables involved, among other things the mechanical properties of the steel used, are of particular interest. A question sometimes raised is whether outliers, or values exceeding the extremes in the assumed distributions, might occur. In order to explore this possibility a study has been made of strength values of three qualities of structural steels, available in samples of up to about 12,000. Statistical evaluation of these samples with respect to outliers, using standard methods for this purpose, revealed the presence of such outliers in most cases, with a frequency of occurrence of, typically, a few values per thousand, estimated by the methods described. Obviously, statistical analysis alone cannot be expected to shed any light on the causes of outliers. Thus, the interpretation of these results with respect to their implication for the probabilistic estimation of the integrety of pressure vessels must await further studies of a similar nature in which the test specimens corresponding to outliers can be recovered and examined metallographically. For the moment the results should be regarded only as a factor to be considered in discussions of the safety of pressure vessels. (author)

Cancer Outlier Analysis Based on Mixture Modeling of Gene Expression Data

Directory of Open Access Journals (Sweden)

Keita Mori

2013-01-01

Full Text Available Molecular heterogeneity of cancer, partially caused by various chromosomal aberrations or gene mutations, can yield substantial heterogeneity in gene expression profile in cancer samples. To detect cancer-related genes which are active only in a subset of cancer samples or cancer outliers, several methods have been proposed in the context of multiple testing. Such cancer outlier analyses will generally suffer from a serious lack of power, compared with the standard multiple testing setting where common activation of genes across all cancer samples is supposed. In this paper, we consider information sharing across genes and cancer samples, via a parametric normal mixture modeling of gene expression levels of cancer samples across genes after a standardization using the reference, normal sample data. A gene-based statistic for gene selection is developed on the basis of a posterior probability of cancer outlier for each cancer sample. Some efficiency improvement by using our method was demonstrated, even under settings with misspecified, heavy-tailed t-distributions. An application to a real dataset from hematologic malignancies is provided.

Impact of Training on General Practitioner?s Knowledge, Attitude and Practices Regarding Emergency Contraception in Hyderabad

OpenAIRE

Bibi, Seema; Mustafa Abbasi, Razia; Awan, Shazia; Ara Qazi, Roshan; Ashfaque, Sanober

2013-01-01

Objectives: To elaborate the impact of family planning training on general practitioners? knowledge, attitude and practices regarding emergency contraception. Methods: A cross sectional survey involving 270 general practitioners was conducted in Hyderabad from 1st Oct to 31st Dec 2010. Participants were divided into two groups on the basis of attending family planning training course after graduation and were interviewed face to face. Data was noted on questionnaire asking their knowledge, at...

Improving Electronic Sensor Reliability by Robust Outlier Screening

Directory of Open Access Journals (Sweden)

Federico Cuesta

2013-10-01

Full Text Available Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount. Outlier detection algorithms are a key component in screening latent defects and decreasing the number of customer quality incidents (CQIs. This paper focuses on new spatial algorithms (Good Die in a Bad Cluster with Statistical Bins (GDBC SB and Bad Bin in a Bad Cluster (BBBC and an advanced outlier screening method, called Robust Dynamic Part Averaging Testing (RDPAT, as well as two practical improvements, which significantly enhance existing algorithms. Those methods have been used in production in Freescale® Semiconductor probe factories around the world for several years. Moreover, a study was conducted with production data of 289,080 dice with 26 CQIs to determine and compare the efficiency and effectiveness of all these algorithms in identifying CQIs.

Prospective casemix-based funding, analysis and financial impact of cost outliers in all-patient refined diagnosis related groups in three Belgian general hospitals.

Science.gov (United States)

Pirson, Magali; Martins, Dimitri; Jackson, Terri; Dramaix, Michèle; Leclercq, Pol

2006-03-01

This study examined the impact of cost outliers in term of hospital resources consumption, the financial impact of the outliers under the Belgium casemix-based system, and the validity of two "proxies" for costs: length of stay and charges. The cost of all hospital stays at three Belgian general hospitals were calculated for the year 2001. High resource use outliers were selected according to the following rule: 75th percentile +1.5 xinter-quartile range. The frequency of cost outliers varied from 7% to 8% across hospitals. Explanatory factors were: major or extreme severity of illness, longer length of stay, and intensive care unit stay. Cost outliers account for 22-30% of hospital costs. One-third of length-of-stay outliers are not cost outliers, and nearly one-quarter of charges outliers are not cost outliers. The current funding system in Belgium does not penalize hospitals having a high percentage of outliers. The billing generated by these patients largely compensates for costs generated. Length of stay and charges are not a good approximation to select cost outliers.

A Near-linear Time Approximation Algorithm for Angle-based Outlier Detection in High-dimensional Data

DEFF Research Database (Denmark)

Pham, Ninh Dang; Pagh, Rasmus

2012-01-01

projection-based technique that is able to estimate the angle-based outlier factor for all data points in time near-linear in the size of the data. Also, our approach is suitable to be performed in parallel environment to achieve a parallel speedup. We introduce a theoretical analysis of the quality...... neighbor are deteriorated in high-dimensional data. Following up on the work of Kriegel et al. (KDD '08), we investigate the use of angle-based outlier factor in mining high-dimensional outliers. While their algorithm runs in cubic time (with a quadratic time heuristic), we propose a novel random......Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional domains. A bottleneck of existing approaches is that implicit or explicit assessments on concepts of distance or nearest...

Detection of Outliers and Imputing of Missing Values for Water Quality UV-VIS Absorbance Time Series

OpenAIRE

Plazas-Nossa, Leonardo; Ávila Angulo, Miguel Antonio; Torres, Andrés

2017-01-01

Context:The UV-Vis absorbance collection using online optical captors for water quality detection may yield outliers and/or missing values. Therefore, pre-processing to correct these anomalies is required to improve the analysis of monitoring data. The aim of this study is to propose a method to detect outliers as well as to fill-in the gaps in time series. Method:Outliers are detected using Winsorising procedure and the application of the Discrete Fourier Transform (DFT) and the Inverse of F...

A tandem regression-outlier analysis of a ligand cellular system for key structural modifications around ligand binding.

Science.gov (United States)

Lin, Ying-Ting

2013-04-30

A tandem technique of hard equipment is often used for the chemical analysis of a single cell to first isolate and then detect the wanted identities. The first part is the separation of wanted chemicals from the bulk of a cell; the second part is the actual detection of the important identities. To identify the key structural modifications around ligand binding, the present study aims to develop a counterpart of tandem technique for cheminformatics. A statistical regression and its outliers act as a computational technique for separation. A PPARγ (peroxisome proliferator-activated receptor gamma) agonist cellular system was subjected to such an investigation. Results show that this tandem regression-outlier analysis, or the prioritization of the context equations tagged with features of the outliers, is an effective regression technique of cheminformatics to detect key structural modifications, as well as their tendency of impact to ligand binding. The key structural modifications around ligand binding are effectively extracted or characterized out of cellular reactions. This is because molecular binding is the paramount factor in such ligand cellular system and key structural modifications around ligand binding are expected to create outliers. Therefore, such outliers can be captured by this tandem regression-outlier analysis.

Post thyroidectomy complications: the Hyderabad experience

International Nuclear Information System (INIS)

Khanzada, T.W.; Samad, A.; Memonb, W.; Kumar, B.

2010-01-01

Objective: Thyroidectomy is a very common surgical procedure worldwide and is performed by surgeons with varied training. The outcome and complication rates are largely dependent on surgeon's skill and experience, the extent of surgery, indication of surgery and number of thyroid surgeries performed at that particular centre. The objective of this study was to determine the frequency of postoperative complications after thyroid surgery in Hyderabad, Pakistan. Study Design: It was a descriptive study and was carried out at 2 private hospitals including a teaching University Hospital over a period of 3 years from April 2005 to March 2008. Patients and Methods: All patients with goitre, who underwent any sort of thyroid surgery, were included in this study. Patients' bio-data including name, age sex, clinical status of thyroid, thyroid function tests, ultrasound, fine needle aspiration cytology and operative procedure, findings, post operative complications and histopathology reports were recorded. Data were analysed using SPSS 16.0. Results: The overall postoperative complication rate was 10.7%. Postoperative hypocalcaemia was the most frequent complication observed in 3.5% of all patients followed by recurrent laryngeal nerve (RLN) injury noted in 2.8% patients. The less common complications were bleeding, seroma formation and wound infection. Majority of these complications were associated with total thyroidectomy, male gender, and in patients with age more than 30 years. Conclusion: The commonest post thyroidectomy complication was hypocalcaemia. Male gender, old age, and extensive thyroid surgery were associated with increased complication rate. (author)

Outlier detection by robust Mahalanobis distance in geological data obtained by INAA to provenance studies

Energy Technology Data Exchange (ETDEWEB)

Santos, Jose O. dos, E-mail: osmansantos@ig.com.br [Instituto Federal de Educacao, Ciencia e Tecnologia de Sergipe (IFS), Lagarto, SE (Brazil); Munita, Casimiro S., E-mail: camunita@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Soares, Emilio A.A., E-mail: easoares@ufan.edu.br [Universidade Federal do Amazonas (UFAM), Manaus, AM (Brazil). Dept. de Geociencias

2013-07-01

The detection of outlier in geochemical studies is one of the main difficulties in the interpretation of dataset because they can disturb the statistical method. The search for outliers in geochemical studies is usually based in the Mahalanobis distance (MD), since points in multivariate space that are a distance larger the some predetermined values from center of the data are considered outliers. However, the MD is very sensitive to the presence of discrepant samples. Many robust estimators for location and covariance have been introduced in the literature, such as Minimum Covariance Determinant (MCD) estimator. When MCD estimators are used to calculate the MD leads to the so-called Robust Mahalanobis Distance (RD). In this context, in this work RD was used to detect outliers in geological study of samples collected from confluence of Negro and Solimoes rivers. The purpose of this study was to study the contributions of the sediments deposited by the Solimoes and Negro rivers in the filling of the tectonic depressions at Parana do Ariau. For that 113 samples were analyzed by Instrumental Neutron Activation Analysis (INAA) in which were determined the concentration of As, Ba, Ce, Co, Cr, Cs, Eu, Fe, Hf, K, La, Lu, Na, Nd, Rb, Sb, Sc, Sm, U, Yb, Ta, Tb, Th and Zn. In the dataset was possible to construct the ellipse corresponding to robust Mahalanobis distance for each group of samples. The samples found outside of the tolerance ellipse were considered an outlier. The results showed that Robust Mahalanobis Distance was more appropriate for the identification of the outliers, once it is a more restrictive method. (author)

Outlier detection by robust Mahalanobis distance in geological data obtained by INAA to provenance studies

International Nuclear Information System (INIS)

Santos, Jose O. dos; Munita, Casimiro S.; Soares, Emilio A.A.

2013-01-01

The detection of outlier in geochemical studies is one of the main difficulties in the interpretation of dataset because they can disturb the statistical method. The search for outliers in geochemical studies is usually based in the Mahalanobis distance (MD), since points in multivariate space that are a distance larger the some predetermined values from center of the data are considered outliers. However, the MD is very sensitive to the presence of discrepant samples. Many robust estimators for location and covariance have been introduced in the literature, such as Minimum Covariance Determinant (MCD) estimator. When MCD estimators are used to calculate the MD leads to the so-called Robust Mahalanobis Distance (RD). In this context, in this work RD was used to detect outliers in geological study of samples collected from confluence of Negro and Solimoes rivers. The purpose of this study was to study the contributions of the sediments deposited by the Solimoes and Negro rivers in the filling of the tectonic depressions at Parana do Ariau. For that 113 samples were analyzed by Instrumental Neutron Activation Analysis (INAA) in which were determined the concentration of As, Ba, Ce, Co, Cr, Cs, Eu, Fe, Hf, K, La, Lu, Na, Nd, Rb, Sb, Sc, Sm, U, Yb, Ta, Tb, Th and Zn. In the dataset was possible to construct the ellipse corresponding to robust Mahalanobis distance for each group of samples. The samples found outside of the tolerance ellipse were considered an outlier. The results showed that Robust Mahalanobis Distance was more appropriate for the identification of the outliers, once it is a more restrictive method. (author)

Reduction of ZTD outliers through improved GNSS data processing and screening strategies

Science.gov (United States)

Stepniak, Katarzyna; Bock, Olivier; Wielgosz, Pawel

2018-03-01

Though Global Navigation Satellite System (GNSS) data processing has been significantly improved over the years, it is still commonly observed that zenith tropospheric delay (ZTD) estimates contain many outliers which are detrimental to meteorological and climatological applications. In this paper, we show that ZTD outliers in double-difference processing are mostly caused by sub-daily data gaps at reference stations, which cause disconnections of clusters of stations from the reference network and common mode biases due to the strong correlation between stations in short baselines. They can reach a few centimetres in ZTD and usually coincide with a jump in formal errors. The magnitude and sign of these biases are impossible to predict because they depend on different errors in the observations and on the geometry of the baselines. We elaborate and test a new baseline strategy which solves this problem and significantly reduces the number of outliers compared to the standard strategy commonly used for positioning (e.g. determination of national reference frame) in which the pre-defined network is composed of a skeleton of reference stations to which secondary stations are connected in a star-like structure. The new strategy is also shown to perform better than the widely used strategy maximizing the number of observations available in many GNSS programs. The reason is that observations are maximized before processing, whereas the final number of used observations can be dramatically lower because of data rejection (screening) during the processing. The study relies on the analysis of 1 year of GPS (Global Positioning System) data from a regional network of 136 GNSS stations processed using Bernese GNSS Software v.5.2. A post-processing screening procedure is also proposed to detect and remove a few outliers which may still remain due to short data gaps. It is based on a combination of range checks and outlier checks of ZTD and formal errors. The accuracy of the

Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO)

Science.gov (United States)

Saleh Ahmar, Ansari; Guritno, Suryo; Abdurakhman; Rahman, Abdul; Awi; Alimuddin; Minggi, Ilham; Arif Tiro, M.; Kasim Aidid, M.; Annas, Suwardi; Utami Sutiksno, Dian; Ahmar, Dewi S.; Ahmar, Kurniawan H.; Abqary Ahmar, A.; Zaki, Ahmad; Abdullah, Dahlan; Rahim, Robbi; Nurdiyanto, Heri; Hidayat, Rahmat; Napitupulu, Darmawan; Simarmata, Janner; Kurniasih, Nuning; Andretti Abdillah, Leon; Pranolo, Andri; Haviluddin; Albra, Wahyudin; Arifin, A. Nurani M.

2018-01-01

The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. In the simulation data is obtained that the data contained AO initial models are ARIMA (2,0,0) with MSE = 36,780, after the detection and correction of data obtained by the iteration of the model ARIMA (2,0,0) with the coefficients obtained from the regression Zt = 0,106+0,204Z t-1+0,401Z t-2-329X 1(t)+115X 2(t)+35,9X 3(t) and MSE = 19,365. This shows that there is an improvement of forecasting error rate data.

A computational study on outliers in world music.

Science.gov (United States)

Panteli, Maria; Benetos, Emmanouil; Dixon, Simon

2017-01-01

The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as 'outliers'. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the 'uniqueness' of the music of each country.

An application of robust ridge regression model in the presence of outliers to real data problem

Science.gov (United States)

Shariff, N. S. Md.; Ferdaos, N. A.

2017-09-01

Multicollinearity and outliers are often leads to inconsistent and unreliable parameter estimates in regression analysis. The well-known procedure that is robust to multicollinearity problem is the ridge regression method. This method however is believed are affected by the presence of outlier. The combination of GM-estimation and ridge parameter that is robust towards both problems is on interest in this study. As such, both techniques are employed to investigate the relationship between stock market price and macroeconomic variables in Malaysia due to curiosity of involving the multicollinearity and outlier problem in the data set. There are four macroeconomic factors selected for this study which are Consumer Price Index (CPI), Gross Domestic Product (GDP), Base Lending Rate (BLR) and Money Supply (M1). The results demonstrate that the proposed procedure is able to produce reliable results towards the presence of multicollinearity and outliers in the real data.

Poland’s Trade with East Asia: An Outlier Approach

Directory of Open Access Journals (Sweden)

Tseng Shoiw-Mei

2015-12-01

Full Text Available Poland achieved an excellent reputation for economic transformation during the recent global recession. The European debt crisis, however, quickly forced the reorientation of Poland’s trade outside of the European Union (EU, especially toward the dynamic region of East Asia. This study analyzes time series data from 1999 to 2013 to detect outliers in order to determine the bilateral trade paths between Poland and each East Asian country during the events of Poland’s accession to the EU in 2004, the global financial crisis from 2008 to 2009, and the European debt crisis from 2010 to 2013. From the Polish standpoint, the results showed significantly clustering outliers in the above periods and in the general trade paths from dependence through distancing and improvement to the chance of approaching East Asian partners. This study also shows that not only China but also several other countries present an excellent opportunity for boosting bilateral trade, especially with regard to Poland’s exports.

Measurement of naturally occurring radioactive materials in commonly used building materials in Hyderabad, India

International Nuclear Information System (INIS)

Balbudhe, A.Y.; Vishwa Prasad, K.; Vidya Sagar, D.; Jha, S.K.; Tripathi, R.M.

2018-01-01

Building materials can cause significant gamma dose indoors, due to their natural radioactivity content. The knowledge of the natural radioactivity level of building materials is important for determination of population exposure, as most people spend 80-90% of their time indoors furthermore, it is useful in setting the standards and national guidelines for the use and management of these materials. The concentrations of natural radionuclides in building materials vary depending on the local geological and geographical conditions as well as geochemical characteristics of those materials. The aim of the study is to determine levels of natural radionuclide in the commonly used building materials in Hyderabad, India

Técnica de aprendizado semissupervisionado para detecção de outliers

OpenAIRE

Fabio Willian Zamoner

2014-01-01

Detecção de outliers desempenha um importante papel para descoberta de conhecimento em grandes bases de dados. O estudo é motivado por inúmeras aplicações reais como fraudes de cartões de crédito, detecção de falhas em componentes industriais, intrusão em redes de computadores, aprovação de empréstimos e monitoramento de condições médicas. Um outlier é definido como uma observação que desvia das outras observações em relação a uma medida e exerce considerável influência na análise de dados...

Identification of outliers and positive deviants for healthcare improvement: looking for high performers in hypoglycemia safety in patients with diabetes

Directory of Open Access Journals (Sweden)

Brigid Wilson

2017-11-01

Full Text Available Abstract Background The study objectives were to determine: (1 how statistical outliers exhibiting low rates of diabetes overtreatment performed on a reciprocal measure – rates of diabetes undertreatment; and (2 the impact of different criteria on high performing outlier status. Methods The design was serial cross-sectional, using yearly Veterans Health Administration (VHA administrative data (2009–2013. Our primary outcome measure was facility rate of HbA1c overtreatment of diabetes in patients at risk for hypoglycemia. Outlier status was assessed by using two approaches: calculating a facility outlier value within year, comparator group, and A1c threshold while incorporating at risk population sizes; and examining standardized model residuals across year and A1c threshold. Facilities with outlier values in the lowest decile for all years of data using more than one threshold and comparator or with time-averaged model residuals in the lowest decile for all A1c thresholds were considered high performing outliers. Results Using outlier values, three of the 27 high performers from 2009 were also identified in 2010–2013 and considered outliers. There was only modest overlap between facilities identified as top performers based on three thresholds: A1c  9% than VA average in the population of patients at high risk for hypoglycemia. Conclusions Statistical identification of positive deviants for diabetes overtreatment was dependent upon the specific measures and approaches used. Moreover, because two facilities may arrive at the same results via very different pathways, it is important to consider that a “best” practice may actually reflect a separate “worst” practice.

Adjusted functional boxplots for spatio-temporal data visualization and outlier detection

KAUST Repository

Sun, Ying; Genton, Marc G.

2011-01-01

This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio

Impact of outlier status on critical care patient outcomes: Does boarding medical intensive care unit patients make a difference?

Science.gov (United States)

Ahmad, Danish; Moeller, Katherine; Chowdhury, Jared; Patel, Vishal; Yoo, Erika J

2018-04-01

To evaluate the impact of outlier status, or the practice of boarding ICU patients in distant critical care units, on clinical and utilization outcomes. Retrospective observational study of all consecutive admissions to the MICU service between April 1, 2014-January 3, 2016, at an urban university hospital. Of 1931 patients, 117 were outliers (6.1%) for the entire duration of their ICU stay. In adjusted analyses, there was no association between outlier status and hospital (OR 1.21, 95% CI 0.72-2.05, p=0.47) or ICU mortality (OR 1.20, 95% CI 0.64-2.25, p=0.57). Outliers had shorter hospital and ICU lengths of stay (LOS) in addition to fewer ventilator days. Crossover patients who had variable outlier exposure also had no increase in hospital (OR 1.61; 95% CI 0.80-3.23; p=0.18) or ICU mortality (OR 1.05; 95% CI 0.43-2.54; p=0.92) after risk-adjustment. Boarding of MICU patients in distant units during times of bed nonavailability does not negatively influence patient mortality or LOS. Increased hospital and ventilator utilization observed among non-outliers in the home unit may be attributable, at least in part, to differences in patient characteristics. Prospective investigation into the practice of ICU boarding will provide further confirmation of its safety. Copyright © 2017 Elsevier Inc. All rights reserved.

Robust Regression Procedures for Predictor Variable Outliers.

Science.gov (United States)

1982-03-01

space of probability dis- tributions. Then the influence function of the estimator is defined to be the derivative of the functional evaluated at the...measure of the impact of an outlier x0 on the estimator . . . . . .0 10 T(F) is the " influence function " which is defined to be T(F) - lirT(F")-T(F...positive and negative directions. An em- pirical influence function can be defined in a similar fashion simply by replacing F with F in eqn. (3.4).n

pH prediction by artificial neural networks for the drinking water of the distribution system of Hyderabad city

International Nuclear Information System (INIS)

Memon, N.A.; Unar, M.A.; Ansari, A.K.

2012-01-01

In this research, feed forward ANN (Artificial Neural Network) model is developed and validated for predicting the pH at 10 different locations of the distribution system of drinking water of Hyderabad city. The developed model is MLP (Multilayer Perceptron) with back propagation algorithm. The data for the training and testing of the model are collected through an experimental analysis on weekly basis in a routine examination for maintaining the quality of drinking water in the city. 17 parameters are taken into consideration including pH. These all parameters are taken as input variables for the model and then pH is predicted for 03 phases;raw water of river Indus,treated water in the treatment plants and then treated water in the distribution system of drinking water. The training and testing results of this model reveal that MLP neural networks are exceedingly extrapolative for predicting the pH of river water, untreated and treated water at all locations of the distribution system of drinking water of Hyderabad city. The optimum input and output weights are generated with minimum MSE (Mean Square Error) < 5%. Experimental, predicted and tested values of pH are plotted and the effectiveness of the model is determined by calculating the coefficient of correlation (R2=0.999) of trained and tested results. (author)

Music Outlier Detection Using Multiple Sequence Alignment and Independent Ensembles

NARCIS (Netherlands)

Bountouridis, D.; Koops, Hendrik Vincent; Wiering, F.; Veltkamp, R.C.

2016-01-01

The automated retrieval of related music documents, such as cover songs or folk melodies belonging to the same tune, has been an important task in the field of Music Information Retrieval (MIR). Yet outlier detection, the process of identifying those documents that deviate significantly from the

The influence of outliers on a model for the estimation of ...

African Journals Online (AJOL)

Veekunde

problems that violate these assumptions is the problem of outliers. .... A normal probability plot of the ordered residuals on the normal order statistics, which are the ... observations from the normal distribution with zero mean and unit variance.

Outliers, Cheese, and Rhizomes: Variations on a Theme of Limitation

Science.gov (United States)

Stone, Lynda

2011-01-01

All research has limitations, for example, from paradigm, concept, theory, tradition, and discipline. In this article Lynda Stone describes three exemplars that are variations on limitation and are "extraordinary" in that they change what constitutes future research in each domain. Malcolm Gladwell's present day study of outliers makes a…

Adaptive Outlier-tolerant Exponential Smoothing Prediction Algorithms with Applications to Predict the Temperature in Spacecraft

OpenAIRE

Hu Shaolin; Zhang Wei; Li Ye; Fan Shunxi

2011-01-01

The exponential smoothing prediction algorithm is widely used in spaceflight control and in process monitoring as well as in economical prediction. There are two key conundrums which are open: one is about the selective rule of the parameter in the exponential smoothing prediction, and the other is how to improve the bad influence of outliers on prediction. In this paper a new practical outlier-tolerant algorithm is built to select adaptively proper parameter, and the exponential smoothing pr...

Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis.

Science.gov (United States)

Westerholt, Rene; Steiger, Enrico; Resch, Bernd; Zipf, Alexander

2016-01-01

Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially.

Assessment of an Integrated Nutrition Communication Approach to Educate the School-Going Adolescent Girls Living in Urban Slums of Hyderabad, Telangana State, India

Science.gov (United States)

Rao, D. Raghunatha; Vijayapushpam, T.; Rao, N. Amulya; Dube, Anilkumar; Venkaiah, K.

2016-01-01

Purpose: Consumption of right diet during the adolescent phase is a critical issue among the adolescent population as their eating behavior is significantly influenced by the peers. Therefore, a study was carried out to educate the school-going adolescent girls living in urban slums of Hyderabad, Telangana, India on right nutrition. Methods: The…

Impact of Urban Growth and Urbanization on the Environmental Degradation of Lakes in Hyderabad City, India

Science.gov (United States)

Nandan, M. J.; Sen, M. K.; Harini, P.; Sekhar, B. M.; Balaji, T.

2013-12-01

Lakes are a vital part of urban ecosystems which perform important ecological and environmental functions to safeguard local climate, groundwater and habitat. The incessant population growth coupled with low urban planning is causing severe damage to urban ecosystems throughout the world. Hyderabad is one of the largest growing metropolitan cities of India covering an area of 65000 ha situated on the banks of Musi River in the northern part of the Deccan Plateau. The city had a population of 1.25 million in 1961 which increased to 6.8 million in 2011 with a metropolitan population of 7.75 million, making it India's fourth most populous city and sixth most populous urban agglomeration. Hyderabad is popularly known as 'City of Lakes' which occupies the top position in India in terms of Urban Lakes. In 20th century, the number of lakes were around 925 which are now reduced to 521 and most of these lakes are facing extinction. The water spread area of these lakes has been considerably reduced due to steady urban growth and the carrying capacity and ecological status of these urban lakes are in real danger. Many of these lakes have shrunk in size while the waters of several lakes got polluted with the discharge of untreated domestic and industrial effluents. Taking into consideration the environmental degradation of urban lakes, an attempt was made to study the current status, loss of water bodies and water spread using remote sensing and GIS techniques. Time-series satellite images of MSS, IRS and RESOURCESAT and Survey of India maps of 1:50,000 and 1:25,000 were used for this study. Analysis of these together with other data sets was accomplished through integrated use of ERDAS Imagine Arc view and ArcGIS software packages. It is estimated that there were 925 lakes in 1982 in erstwhile Hyderabad Urban Development Authority (HUDA) area which came down to 521 in 2012. A total number of 404 lakes disappeared during the last 30 years period. Consequently the water spread

What 'outliers' tell us about missed opportunities for tuberculosis control: a cross-sectional study of patients in Mumbai, India

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Porter John DH

2010-05-01

Full Text Available Abstract Background India's Revised National Tuberculosis Control Programme (RNTCP is deemed highly successful in terms of detection and cure rates. However, some patients experience delays in accessing diagnosis and treatment. Patients falling between the 96th and 100th percentiles for these access indicators are often ignored as atypical 'outliers' when assessing programme performance. They may, however, provide clues to understanding why some patients never reach the programme. This paper examines the underlying vulnerabilities of patients with extreme values for delays in accessing the RNTCP in Mumbai city, India. Methods We conducted a cross-sectional study with 266 new sputum positive patients registered with the RNTCP in Mumbai. Patients were classified as 'outliers' if patient, provider and system delays were beyond the 95th percentile for the respective variable. Case profiles of 'outliers' for patient, provider and system delays were examined and compared with the rest of the sample to identify key factors responsible for delays. Results Forty-two patients were 'outliers' on one or more of the delay variables. All 'outliers' had a significantly lower per capita income than the remaining sample. The lack of economic resources was compounded by social, structural and environmental vulnerabilities. Longer patient delays were related to patients' perception of symptoms as non-serious. Provider delays were incurred as a result of private providers' failure to respond to tuberculosis in a timely manner. Diagnostic and treatment delays were minimal, however, analysis of the 'outliers' revealed the importance of social support in enabling access to the programme. Conclusion A proxy for those who fail to reach the programme, these case profiles highlight unique vulnerabilities that need innovative approaches by the RNTCP. The focus on 'outliers' provides a less resource- and time-intensive alternative to community-based studies for

Time Series Outlier Detection Based on Sliding Window Prediction

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Yufeng Yu

2014-01-01

Full Text Available In order to detect outliers in hydrological time series data for improving data quality and decision-making quality related to design, operation, and management of water resources, this research develops a time series outlier detection method for hydrologic data that can be used to identify data that deviate from historical patterns. The method first built a forecasting model on the history data and then used it to predict future values. Anomalies are assumed to take place if the observed values fall outside a given prediction confidence interval (PCI, which can be calculated by the predicted value and confidence coefficient. The use of PCI as threshold is mainly on the fact that it considers the uncertainty in the data series parameters in the forecasting model to address the suitable threshold selection problem. The method performs fast, incremental evaluation of data as it becomes available, scales to large quantities of data, and requires no preclassification of anomalies. Experiments with different hydrologic real-world time series showed that the proposed methods are fast and correctly identify abnormal data and can be used for hydrologic time series analysis.

Latent Clustering Models for Outlier Identification in Telecom Data

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Ye Ouyang

2016-01-01

Full Text Available Collected telecom data traffic has boomed in recent years, due to the development of 4G mobile devices and other similar high-speed machines. The ability to quickly identify unexpected traffic data in this stream is critical for mobile carriers, as it can be caused by either fraudulent intrusion or technical problems. Clustering models can help to identify issues by showing patterns in network data, which can quickly catch anomalies and highlight previously unseen outliers. In this article, we develop and compare clustering models for telecom data, focusing on those that include time-stamp information management. Two main models are introduced, solved in detail, and analyzed: Gaussian Probabilistic Latent Semantic Analysis (GPLSA and time-dependent Gaussian Mixture Models (time-GMM. These models are then compared with other different clustering models, such as Gaussian model and GMM (which do not contain time-stamp information. We perform computation on both sample and telecom traffic data to show that the efficiency and robustness of GPLSA make it the superior method to detect outliers and provide results automatically with low tuning parameters or expertise requirement.

Prevalence of vitamin D deficiency and its associated factors among the urban elderly population in Hyderabad metropolitan city, South India.

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Suryanarayana, Palla; Arlappa, Nimmathota; Sai Santhosh, Vadakattu; Balakrishna, Nagalla; Lakshmi Rajkumar, Pondey; Prasad, Undrajavarapu; Raju, Banavath Bhoja; Shivakeseva, Kommula; Divya Shoshanni, Kondru; Seshacharyulu, Madabushi; Geddam, Jagjeevan Babu; Prasanthi, Prabhakaran Sobhana; Ananthan, Rajendran

2018-03-01

Deficiency of vitamin D has been associated with various health conditions. However, vitamin D deficiency (VDD) and factors associated with VDD are not well studied, especially among the urban elderly population of India. To assess the prevalence of VDD and its associated factors among the urban free-living elderly population in Hyderabad. A community-based cross-sectional study was conducted among 298 urban elderly (≥60 years) by adapting a random sampling procedure. Demographic particulars were collected. Blood pressure and anthropometric measurements were recorded using standard equipment. Fasting glucose, lipid profile and 25-hydroxy vitamin D [25(OH) D] were estimated in plasma samples. The mean ± SE plasma vitamin D and the prevalence of VDD among the urban elderly population were 19.3 ± 0.54 (ng/ml) and 56.3%, respectively. The prevalence of VDD was significantly associated with education, high body mass index (BMI), hypertension (HT) and metabolic syndrome (MS). Multiple logistic regression analysis revealed HT as a significant predictor of vitamin D deficiency and the risk of VDD was double among the elderly with hypertension. The prevalence of VDD was high among the urban elderly population in the south Indian city of Hyderabad. High BMI, MS, HT and education are significant associated factors of VDD.

The obligation of physicians to medical outliers: a Kantian and Hegelian synthesis.

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Papadimos, Thomas J; Marco, Alan P

2004-06-03

Patients who present to medical practices without health insurance or with serious co-morbidities can become fiscal disasters to those who care for them. Their consumption of scarce resources has caused consternation among providers and institutions, especially as it concerns the amount and type of care they should receive. In fact, some providers may try to avoid caring for them altogether, or at least try to limit their institutional or practice exposure to them. We present a philosophical discourse, with emphasis on the writings of Immanuel Kant and G.F.W. Hegel, as to why physicians have the moral imperative to give such "outliers" considerate and thoughtful care. Outliers are defined and the ideals of morality, responsibility, good will, duty, and principle are applied to the care of patients whose financial means are meager and to those whose care is physiologically futile. Actions of moral worth, unconditional good will, and doing what is right are examined. Outliers are a legitimate economic concern to individual practitioners and institutions, however this should not lead to an evasion of care. These patients should be identified early in their course of care, but such identification should be preceded by a well-planned recognition of this burden and appropriate staffing and funding should be secured. A thoughtful team approach by medical practices and their institutions, involving both clinicians and non-clinicians, should be pursued.

A Student’s t Mixture Probability Hypothesis Density Filter for Multi-Target Tracking with Outliers

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Liu, Zhuowei; Chen, Shuxin; Wu, Hao; He, Renke; Hao, Lin

2018-01-01

In multi-target tracking, the outliers-corrupted process and measurement noises can reduce the performance of the probability hypothesis density (PHD) filter severely. To solve the problem, this paper proposed a novel PHD filter, called Student’s t mixture PHD (STM-PHD) filter. The proposed filter models the heavy-tailed process noise and measurement noise as a Student’s t distribution as well as approximates the multi-target intensity as a mixture of Student’s t components to be propagated in time. Then, a closed PHD recursion is obtained based on Student’s t approximation. Our approach can make full use of the heavy-tailed characteristic of a Student’s t distribution to handle the situations with heavy-tailed process and the measurement noises. The simulation results verify that the proposed filter can overcome the negative effect generated by outliers and maintain a good tracking accuracy in the simultaneous presence of process and measurement outliers. PMID:29617348

Vulnerability to HIV/AIDS among women of reproductive age in the slums of Delhi and Hyderabad, India.

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Ghosh, Jayati; Wadhwa, Vandana; Kalipeni, Ezekiel

2009-02-01

This report explores how vulnerability to HIV/AIDS applies to women in the reproductive age range living in the slum areas of Delhi and Hyderabad. The paper is based on a qualitative study of AIDS awareness levels conducted during the summer of 2006. It offers insightful narratives from a sample of 32 women, providing an in depth view of their vulnerability to HIV/AIDS due to their precarious socioeconomic conditions and low AIDS awareness. The women cited lack of education, low empowerment in expressing and accessing information related to sexual matters, and poverty as key factors to vulnerability.

Methods of Detecting Outliers in A Regression Analysis Model. | Ogu ...

African Journals Online (AJOL)

A Boilers data with dependent variable Y (man-Hour) and four independent variables X1 (Boiler Capacity), X2 (Design Pressure), X3 (Boiler Type), X4 (Drum Type) were used. The analysis of the Boilers data reviewed an unexpected group of Outliers. The results from the findings showed that an observation can be outlying ...

A robust ridge regression approach in the presence of both multicollinearity and outliers in the data

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Shariff, Nurul Sima Mohamad; Ferdaos, Nur Aqilah

2017-08-01

Multicollinearity often leads to inconsistent and unreliable parameter estimates in regression analysis. This situation will be more severe in the presence of outliers it will cause fatter tails in the error distributions than the normal distributions. The well-known procedure that is robust to multicollinearity problem is the ridge regression method. This method however is expected to be affected by the presence of outliers due to some assumptions imposed in the modeling procedure. Thus, the robust version of existing ridge method with some modification in the inverse matrix and the estimated response value is introduced. The performance of the proposed method is discussed and comparisons are made with several existing estimators namely, Ordinary Least Squares (OLS), ridge regression and robust ridge regression based on GM-estimates. The finding of this study is able to produce reliable parameter estimates in the presence of both multicollinearity and outliers in the data.

Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers

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Hachey Mark

2009-10-01

Full Text Available Abstract Background The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier detection has not been thoroughly investigated. Methods We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*pop; and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. Results For simulated data with outlier patterns, Tango's MEET, Moran's I and I*pop had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*pop (with 50% of total population as the maximum search window had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. Conclusion SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*pop perform best in global clustering scenarios among the selected methods. The use of SaTScan for

Tailor-made Surgical Guide Reduces Incidence of Outliers of Cup Placement.

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Hananouchi, Takehito; Saito, Masanobu; Koyama, Tsuyoshi; Sugano, Nobuhiko; Yoshikawa, Hideki

2010-04-01

Malalignment of the cup in total hip arthroplasty (THA) increases the risks of postoperative complications such as neck cup impingement, dislocation, and wear. We asked whether a tailor-made surgical guide based on CT images would reduce the incidence of outliers beyond 10 degrees from preoperatively planned alignment of the cup compared with those without the surgical guide. We prospectively followed 38 patients (38 hips, Group 1) having primary THA with the conventional technique and 31 patients (31 hips, Group 2) using the surgical guide. We designed the guide for Group 2 based on CT images and fixed it to the acetabular edge with a Kirschner wire to indicate the planned cup direction. Postoperative CT images showed the guide reduced the number of outliers compared with the conventional method (Group 1, 23.7%; Group 2, 0%). The surgical guide provided more reliable cup insertion compared with conventional techniques. Level II, therapeutic study. See the Guidelines for Authors for a complete description of levels of evidence.

The obligation of physicians to medical outliers: a Kantian and Hegelian synthesis

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Marco Alan P

2004-06-01

Full Text Available Abstract Background Patients who present to medical practices without health insurance or with serious co-morbidities can become fiscal disasters to those who care for them. Their consumption of scarce resources has caused consternation among providers and institutions, especially as it concerns the amount and type of care they should receive. In fact, some providers may try to avoid caring for them altogether, or at least try to limit their institutional or practice exposure to them. Discussion We present a philosophical discourse, with emphasis on the writings of Immanuel Kant and G.F.W. Hegel, as to why physicians have the moral imperative to give such "outliers" considerate and thoughtful care. Outliers are defined and the ideals of morality, responsibility, good will, duty, and principle are applied to the care of patients whose financial means are meager and to those whose care is physiologically futile. Actions of moral worth, unconditional good will, and doing what is right are examined. Summary Outliers are a legitimate economic concern to individual practitioners and institutions, however this should not lead to an evasion of care. These patients should be identified early in their course of care, but such identification should be preceded by a well-planned recognition of this burden and appropriate staffing and funding should be secured. A thoughtful team approach by medical practices and their institutions, involving both clinicians and non-clinicians, should be pursued.

Efficient estimation of dynamic density functions with an application to outlier detection

KAUST Repository

Qahtan, Abdulhakim Ali Ali; Zhang, Xiangliang; Wang, Suojin

2012-01-01

In this paper, we propose a new method to estimate the dynamic density over data streams, named KDE-Track as it is based on a conventional and widely used Kernel Density Estimation (KDE) method. KDE-Track can efficiently estimate the density with linear complexity by using interpolation on a kernel model, which is incrementally updated upon the arrival of streaming data. Both theoretical analysis and experimental validation show that KDE-Track outperforms traditional KDE and a baseline method Cluster-Kernels on estimation accuracy of the complex density structures in data streams, computing time and memory usage. KDE-Track is also demonstrated on timely catching the dynamic density of synthetic and real-world data. In addition, KDE-Track is used to accurately detect outliers in sensor data and compared with two existing methods developed for detecting outliers and cleaning sensor data. © 2012 ACM.

Optimum outlier model for potential improvement of environmental cleaning and disinfection.

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Rupp, Mark E; Huerta, Tomas; Cavalieri, R J; Lyden, Elizabeth; Van Schooneveld, Trevor; Carling, Philip; Smith, Philip W

2014-06-01

The effectiveness and efficiency of 17 housekeepers in terminal cleaning 292 hospital rooms was evaluated through adenosine triphosphate detection. A subgroup of housekeepers was identified who were significantly more effective and efficient than their coworkers. These optimum outliers may be used in performance improvement to optimize environmental cleaning.

Outlier removal, sum scores, and the inflation of the Type I error rate in independent samples t tests: the power of alternatives and recommendations.

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Bakker, Marjan; Wicherts, Jelte M

2014-09-01

In psychology, outliers are often excluded before running an independent samples t test, and data are often nonnormal because of the use of sum scores based on tests and questionnaires. This article concerns the handling of outliers in the context of independent samples t tests applied to nonnormal sum scores. After reviewing common practice, we present results of simulations of artificial and actual psychological data, which show that the removal of outliers based on commonly used Z value thresholds severely increases the Type I error rate. We found Type I error rates of above 20% after removing outliers with a threshold value of Z = 2 in a short and difficult test. Inflations of Type I error rates are particularly severe when researchers are given the freedom to alter threshold values of Z after having seen the effects thereof on outcomes. We recommend the use of nonparametric Mann-Whitney-Wilcoxon tests or robust Yuen-Welch tests without removing outliers. These alternatives to independent samples t tests are found to have nominal Type I error rates with a minimal loss of power when no outliers are present in the data and to have nominal Type I error rates and good power when outliers are present. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Utilization of maternal health services by the migrant population living in the non-notified slums of Hyderabad city, India

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Jagjivan Babu Geddam

2017-03-01

Full Text Available Background: Despite increase in accessibility and utilization of maternal health services in the state of Telangana, penetration of these services in vulnerable communities is inadequate. Aims & Objectives: To understand the determinants of utilization of reproductive health services by migrant population living in non-notified slums of Hyderabad city in the Indian state of Telangana. Material & Methods: It is a community based cross sectional study of 761 rural to urban internal migrant mothers with a child of less than 2 years of age residing for a period minimum of 30 days and not more than 10 years. Information was collected for socio demographic details, antenatal care and child delivery. Results: Mothers receiving at least 4 antenatal care visits and institutional deliveries in migrants was 69.6% and 69% respectively, compared to 85.8% and 97% in general population of Hyderabad city. The likelihood of mothers receiving adequate care is 6.7 times higher in mothers with secondary education compared to formal education. The likelihood of institutional delivery is 7.8 times higher in mothers availing adequate antenatal care versus inadequate care and 2.2 times higher in mothers with secondary education versus formal education. Conclusion: Utilization of antenatal care services and promotion of institutional deliveries can be improved by acting on the supply side barriers such as health care infrastructure and demand side barriers such as indirect consumer costs, financial constraints and community engagement

Adaptive distributed outlier detection for WSNs.

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De Paola, Alessandra; Gaglio, Salvatore; Lo Re, Giuseppe; Milazzo, Fabrizio; Ortolani, Marco

2015-05-01

The paradigm of pervasive computing is gaining more and more attention nowadays, thanks to the possibility of obtaining precise and continuous monitoring. Ease of deployment and adaptivity are typically implemented by adopting autonomous and cooperative sensory devices; however, for such systems to be of any practical use, reliability and fault tolerance must be guaranteed, for instance by detecting corrupted readings amidst the huge amount of gathered sensory data. This paper proposes an adaptive distributed Bayesian approach for detecting outliers in data collected by a wireless sensor network; our algorithm aims at optimizing classification accuracy, time complexity and communication complexity, and also considering externally imposed constraints on such conflicting goals. The performed experimental evaluation showed that our approach is able to improve the considered metrics for latency and energy consumption, with limited impact on classification accuracy.

The effects of additive outliers on tests for unit roots and cointegration

NARCIS (Netherlands)

Ph.H.B.F. Franses (Philip Hans); N. Haldrup (Niels)

1994-01-01

textabstractThe properties of the univariate Dickey-Fuller test and the Johansen test for the cointegrating rank when there exist additive outlying observations in the time series are examined. The analysis provides analytical as well as numerical evidence that additive outliers may produce spurious

Identifying multiple outliers in linear regression: robust fit and clustering approach

International Nuclear Information System (INIS)

Robiah Adnan; Mohd Nor Mohamad; Halim Setan

2001-01-01

This research provides a clustering based approach for determining potential candidates for outliers. This is modification of the method proposed by Serbert et. al (1988). It is based on using the single linkage clustering algorithm to group the standardized predicted and residual values of data set fit by least trimmed of squares (LTS). (Author)

Detection of Outliers and Imputing of Missing Values for Water Quality UV-VIS Absorbance Time Series

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Leonardo Plazas-Nossa

2017-01-01

Full Text Available Context: The UV-Vis absorbance collection using online optical captors for water quality detection may yield outliers and/or missing values. Therefore, data pre-processing is a necessary pre-requisite to monitoring data processing. Thus, the aim of this study is to propose a method that detects and removes outliers as well as fills gaps in time series. Method: Outliers are detected using Winsorising procedure and the application of the Discrete Fourier Transform (DFT and the Inverse of Fast Fourier Transform (IFFT to complete the time series. Together, these tools were used to analyse a case study comprising three sites in Colombia ((i Bogotá D.C. Salitre-WWTP (Waste Water Treatment Plant, influent; (ii Bogotá D.C. Gibraltar Pumping Station (GPS; and, (iii Itagüí, San Fernando-WWTP, influent (Medellín metropolitan area analysed via UV-Vis (Ultraviolet and Visible spectra. Results: Outlier detection with the proposed method obtained promising results when window parameter values are small and self-similar, despite that the three time series exhibited different sizes and behaviours. The DFT allowed to process different length gaps having missing values. To assess the validity of the proposed method, continuous subsets (a section of the absorbance time series without outlier or missing values were removed from the original time series obtaining an average 12% error rate in the three testing time series. Conclusions: The application of the DFT and the IFFT, using the 10% most important harmonics of useful values, can be useful for its later use in different applications, specifically for time series of water quality and quantity in urban sewer systems. One potential application would be the analysis of dry weather interesting to rain events, a feat achieved by detecting values that correspond to unusual behaviour in a time series. Additionally, the result hints at the potential of the method in correcting other hydrologic time series.

Outlier Loci and Selection Signatures of Simple Sequence Repeats (SSRs) in Flax (Linum usitatissimum L.).

Science.gov (United States)

Soto-Cerda, Braulio J; Cloutier, Sylvie

2013-01-01

Genomic microsatellites (gSSRs) and expressed sequence tag-derived SSRs (EST-SSRs) have gained wide application for elucidating genetic diversity and population structure in plants. Both marker systems are assumed to be selectively neutral when making demographic inferences, but this assumption is rarely tested. In this study, three neutrality tests were assessed for identifying outlier loci among 150 SSRs (85 gSSRs and 65 EST-SSRs) that likely influence estimates of population structure in three differentiated flax sub-populations ( F ST  = 0.19). Moreover, the utility of gSSRs, EST-SSRs, and the combined sets of SSRs was also evaluated in assessing genetic diversity and population structure in flax. Six outlier loci were identified by at least two neutrality tests showing footprints of balancing selection. After removing the outlier loci, the STRUCTURE analysis and the dendrogram topology of EST-SSRs improved. Conversely, gSSRs and combined SSRs results did not change significantly, possibly as a consequence of the higher number of neutral loci assessed. Taken together, the genetic structure analyses established the superiority of gSSRs to determine the genetic relationships among flax accessions, although the combined SSRs produced the best results. Genetic diversity parameters did not differ statistically ( P  > 0.05) between gSSRs and EST-SSRs, an observation partially explained by the similar number of repeat motifs. Our study provides new insights into the ability of gSSRs and EST-SSRs to measure genetic diversity and structure in flax and confirms the importance of testing for the occurrence of outlier loci to properly assess natural and breeding populations, particularly in studies considering only few loci.

Robust Wavelet Estimation to Eliminate Simultaneously the Effects of Boundary Problems, Outliers, and Correlated Noise

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Alsaidi M. Altaher

2012-01-01

Full Text Available Classical wavelet thresholding methods suffer from boundary problems caused by the application of the wavelet transformations to a finite signal. As a result, large bias at the edges and artificial wiggles occur when the classical boundary assumptions are not satisfied. Although polynomial wavelet regression and local polynomial wavelet regression effectively reduce the risk of this problem, the estimates from these two methods can be easily affected by the presence of correlated noise and outliers, giving inaccurate estimates. This paper introduces two robust methods in which the effects of boundary problems, outliers, and correlated noise are simultaneously taken into account. The proposed methods combine thresholding estimator with either a local polynomial model or a polynomial model using the generalized least squares method instead of the ordinary one. A primary step that involves removing the outlying observations through a statistical function is considered as well. The practical performance of the proposed methods has been evaluated through simulation experiments and real data examples. The results are strong evidence that the proposed method is extremely effective in terms of correcting the boundary bias and eliminating the effects of outliers and correlated noise.

Open-Source Radiation Exposure Extraction Engine (RE3) with Patient-Specific Outlier Detection.

Science.gov (United States)

Weisenthal, Samuel J; Folio, Les; Kovacs, William; Seff, Ari; Derderian, Vana; Summers, Ronald M; Yao, Jianhua

2016-08-01

We present an open-source, picture archiving and communication system (PACS)-integrated radiation exposure extraction engine (RE3) that provides study-, series-, and slice-specific data for automated monitoring of computed tomography (CT) radiation exposure. RE3 was built using open-source components and seamlessly integrates with the PACS. RE3 calculations of dose length product (DLP) from the Digital imaging and communications in medicine (DICOM) headers showed high agreement (R (2) = 0.99) with the vendor dose pages. For study-specific outlier detection, RE3 constructs robust, automatically updating multivariable regression models to predict DLP in the context of patient gender and age, scan length, water-equivalent diameter (D w), and scanned body volume (SBV). As proof of concept, the model was trained on 811 CT chest, abdomen + pelvis (CAP) exams and 29 outliers were detected. The continuous variables used in the outlier detection model were scan length (R (2)  = 0.45), D w (R (2) = 0.70), SBV (R (2) = 0.80), and age (R (2) = 0.01). The categorical variables were gender (male average 1182.7 ± 26.3 and female 1047.1 ± 26.9 mGy cm) and pediatric status (pediatric average 710.7 ± 73.6 mGy cm and adult 1134.5 ± 19.3 mGy cm).

Traffic noise in Hyderabad city, part-II. vehicular contribution to road traffic noise

International Nuclear Information System (INIS)

Sheikh, G.H.

2001-01-01

The results of a road traffic noise survey carried out in Hyderabad city showed that the levels of traffic noise in the City are alarmingly high and much beyond the comfortable limits. There, in order to investigate the level of the noise emitted by different types of vehicles plying on the city roads and to assess their individual contribution to high level traffic noise, studies have been carried out on the measurement of noise emitted by motorcycles, buses, auto-rickshaws, and motor vehicle horns as they normally move on the city roads. The data collected has been analyzed for L/sub v99/, L/sub v90/, L/sub v50/, L/sub v10/ and L/sub v1/ and results are discussed with reference to the existing motor vehicle rules in Pakistan and motor vehicle noise emission limits set by the EEC and other developed countries. Some suggestion have also been made to limit high level traffic noise. (author)

Ethical issues in recruitment of "healthy volunteers": study of a clinical research organisation in Hyderabad.

Science.gov (United States)

Krishna, Shilpa; Prasad, N Purendra

2014-01-01

This paper raises some of the ethical issues involved in the recruitment of healthy volunteers (HVs) by clinical research organizations (CROs) for bioavailability and bioequivalent (BA/BE) studies. It also explores the underlying reasons for the participation of the HVs and their interaction with the CROs. The findings are based on the data collected from 50 HVs participating in a BA/BE study conducted by a CRO in Hyderabad and from the key officials involved in it. The findings indicate the existence of various complex networks, throw some light on the role of middlemen ("Anna") and the negotiation process, and give us an insight into the social norms and values that compelled the HVs to participate in the study. The paper offers a critical analysis of a few ethical concerns.

Prevalence of Gastro-Intestinal Nematodes in Goats in Hyderabad and Adjoining Areas

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Nasreen Akhter*, A. G. Arijo, M. S. Phulan, Zafar Iqbal1 and K. B. Mirbahar

2011-10-01

Full Text Available The study was conducted to determine the prevalence of gastrointestinal nematodes of goats (n=1065 in and around Hyderabad using qualitative and quantitative coprological examinations. Results revealed that 43.10% (459 goats were infected with different species of nematodes including Haemonchus contortus (14.65%, Trichuris ovis (8.17%, Trichostrongylus axei (7.61%, Trichostrongylus colubriformis (6.76%, Oesphagostomum columbianum (5.35%, Ostertagia circumcincta (5.35%, Chabertia ovina (4.79% and Strongyloides papillosus (4.51%. Infections with mixed species of nematodes were recorded in 6.54% (n=30/459; T. ovis + H. contortus, 5.23% (n=24/459; C. ovina + H. contortus, 5.88% (n=27/459; S. papillosus + C. ovina, and 12.42% (n=57/459; O. circumcincta + T. ovis goats. Of the total infected (n=459; 51.4, 38.3 and 10.2% goats had light, moderate and heavy infections, respectively. The prevalence, nature and intensity of the helminthiasis in goats warrant an immediate attention to devise strategies for its control to reduce the production losses.

Nonlinear Optimization-Based Device-Free Localization with Outlier Link Rejection

Directory of Open Access Journals (Sweden)

Wendong Xiao

2015-04-01

Full Text Available Device-free localization (DFL is an emerging wireless technique for estimating the location of target that does not have any attached electronic device. It has found extensive use in Smart City applications such as healthcare at home and hospitals, location-based services at smart spaces, city emergency response and infrastructure security. In DFL, wireless devices are used as sensors that can sense the target by transmitting and receiving wireless signals collaboratively. Many DFL systems are implemented based on received signal strength (RSS measurements and the location of the target is estimated by detecting the changes of the RSS measurements of the wireless links. Due to the uncertainty of the wireless channel, certain links may be seriously polluted and result in erroneous detection. In this paper, we propose a novel nonlinear optimization approach with outlier link rejection (NOOLR for RSS-based DFL. It consists of three key strategies, including: (1 affected link identification by differential RSS detection; (2 outlier link rejection via geometrical positional relationship among links; (3 target location estimation by formulating and solving a nonlinear optimization problem. Experimental results demonstrate that NOOLR is robust to the fluctuation of the wireless signals with superior localization accuracy compared with the existing Radio Tomographic Imaging (RTI approach.

International Conference on Analytic and Algebraic Geometry held at the Tata Institute of Fundamental Research and the University of Hyderabad

CERN Document Server

Biswas, Indranil; Morye, Archana; Parameswaran, A

2017-01-01

This volume is an outcome of the International conference held in Tata Institute of Fundamental Research and the University of Hyderabad. There are fifteen articles in this volume. The main purpose of the articles is to introduce recent and advanced techniques in the area of analytic and algebraic geometry. This volume attempts to give recent developments in the area to target mainly young researchers who are new to this area. Also, some research articles have been added to give examples of how to use these techniques to prove new results.

Combined CT-based and image-free navigation systems in TKA reduces postoperative outliers of rotational alignment of the tibial component.

Science.gov (United States)

Mitsuhashi, Shota; Akamatsu, Yasushi; Kobayashi, Hideo; Kusayama, Yoshihiro; Kumagai, Ken; Saito, Tomoyuki

2018-02-01

Rotational malpositioning of the tibial component can lead to poor functional outcome in TKA. Although various surgical techniques have been proposed, precise rotational placement of the tibial component was difficult to accomplish even with the use of a navigation system. The purpose of this study is to assess whether combined CT-based and image-free navigation systems replicate accurately the rotational alignment of tibial component that was preoperatively planned on CT, compared with the conventional method. We compared the number of outliers for rotational alignment of the tibial component using combined CT-based and image-free navigation systems (navigated group) with those of conventional method (conventional group). Seventy-two TKAs were performed between May 2012 and December 2014. In the navigated group, the anteroposterior axis was prepared using CT-based navigation system and the tibial component was positioned under control of the navigation. In the conventional group, the tibial component was placed with reference to the Akagi line that was determined visually. Fisher's exact probability test was performed to evaluate the results. There was a significant difference between the two groups with regard to the number of outliers: 3 outliers in the navigated group compared with 12 outliers in the conventional group (P image-free navigation systems decreased the number of rotational outliers of tibial component, and was helpful for the replication of the accurate rotational alignment of the tibial component that was preoperatively planned.

Detecting outliers and/or leverage points: a robust two-stage procedure with bootstrap cut-off points

Directory of Open Access Journals (Sweden)

Ettore Marubini

2014-01-01

Full Text Available This paper presents a robust two-stage procedure for identification of outlying observations in regression analysis. The exploratory stage identifies leverage points and vertical outliers through a robust distance estimator based on Minimum Covariance Determinant (MCD. After deletion of these points, the confirmatory stage carries out an Ordinary Least Squares (OLS analysis on the remaining subset of data and investigates the effect of adding back in the previously deleted observations. Cut-off points pertinent to different diagnostics are generated by bootstrapping and the cases are definitely labelled as good-leverage, bad-leverage, vertical outliers and typical cases. The procedure is applied to four examples.

Health and Safety of Hyderabad Industries’ Labor. Causes and Awareness

Directory of Open Access Journals (Sweden)

A. R. Khoso

2017-12-01

Full Text Available Labor’s health and safety (H&S is a matter of concern for all industries. Occurrence of accidents in industries is becoming a common issue. Both white collar and blue-collar workers are not shielded from materials that damage their health. This study identifies the critical factors affecting labor’s H&S in Hyderabad, Pakistan industries. The awareness of labor regarding prevention and consequences that affect workers’ H&S is also a matter of interest of this research. The severity of factors was determined through questionnaire survey from experts, H&S supervisors and managerial staff of industries. For the descriptive analysis the software SPPS 24.0 was used. This research also includes interviews form industry laborers about awareness regarding H&S critical factors. The results show that, Improper PPE use, operating machines that are poorly maintained, long term exposure to high intensity noise, working extended and irregular hours and lack of knowledge of working instruments are the critical causes of accidents. Also 60.9%, 73.9%, 69.6%, 78.3% and 89% of workers are not aware about these causes and their consequences. Thus, this research is a road map for industrial employers, law makers, local, provisional and federal Government of Pakistan in order to help minimizing the workplace accidents and the providing of safe and secure working environment for laborers.

A method for separating seismo-ionospheric TEC outliers from heliogeomagnetic disturbances by using nu-SVR

Energy Technology Data Exchange (ETDEWEB)

Pattisahusiwa, Asis [Bandung Institute of Technology (Indonesia); Liong, The Houw; Purqon, Acep [Earth physics and complex systems research group, Bandung Institute of Technology (Indonesia)

2015-09-30

Seismo-Ionospheric is a study of ionosphere disturbances associated with seismic activities. In many previous researches, heliogeomagnetic or strong earthquake activities can caused the disturbances in the ionosphere. However, it is difficult to separate these disturbances based on related sources. In this research, we proposed a method to separate these disturbances/outliers by using nu-SVR with the world-wide GPS data. TEC data related to the 26th December 2004 Sumatra and the 11th March 2011 Honshu earthquakes had been analyzed. After analyzed TEC data in several location around the earthquake epicenter and compared with geomagnetic data, the method shows a good result in the average to detect the source of these outliers. This method is promising to use in the future research.

The Super‑efficiency Model and its Use for Ranking and Identification of Outliers

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Kristína Kočišová

2017-01-01

Full Text Available This paper employs non‑radial and non‑oriented super‑efficiency SBM model under the assumption of a variable return to scale to analyse performance of twenty‑two Czech and Slovak domestic commercial banks in 2015. The banks were ranked according to asset‑oriented and profit‑oriented intermediation approach. We pooled the cross‑country data and used them to define a common best‑practice efficiency frontier. This allowed us to focus on determining relative differences in efficiency across banks. The average efficiency was evaluated separately on the “national” and “international” level. Based on the results of analysis can be seen that in Slovak banking sector the level of super‑efficiency was lower compared to Czech banks. Also, the number of super‑efficient banks was lower in a case of Slovakia under both approaches. The boxplot analysis was used to determine the outliers in the dataset. The results suggest that the exclusion of outliers led to the better statistical characteristic of estimated efficiency.

Outlier Detection in Structural Time Series Models

DEFF Research Database (Denmark)

Marczak, Martyna; Proietti, Tommaso

investigate via Monte Carlo simulations how this approach performs for detecting additive outliers and level shifts in the analysis of nonstationary seasonal time series. The reference model is the basic structural model, featuring a local linear trend, possibly integrated of order two, stochastic seasonality......Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has attracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The general......–to–specific approach to the detection of structural change, currently implemented in Autometrics via indicator saturation, has proven to be both practical and effective in the context of stationary dynamic regression models and unit–root autoregressions. By focusing on impulse– and step–indicator saturation, we...

Effect of stress on serum cholestrol levels in nurses and housewives of Hyderabad - Pakistan

International Nuclear Information System (INIS)

Watto, F.H.; Memon, M.S.; Memon, A.N.; Ghanghro, A.B.; Yaquib, M.; Watto, M.H.S.; Tirmizi, S.A.

2010-01-01

A cohort type study was designed to evaluate environmental, psychological and physiological stresses in nurses and housewives and to correlate with their serum total cholesterol, HDL cholesterol, LDL cholesterol and triglyceride levels. Total 160 females from middle socioeconomic groups (nurses, n=80 and housewives, n=80) aged between 25-45 years participated in this study and subjects were selected from Hyderabad and its adjoining areas. Environmental, psychological and physiological stress levels were measured with likert scale. Total cholesterol, LDL cholesterol and HDL cholesterol were measured by CHOD-PAP method and triglyceride levels were measured by GPO method. Housewives were found to have high levels of total cholesterol, LDL cholesterol and triglycerides. The HDL cholesterol were lower. Environmental, psychological and physiological stresses were significantly higher in housewives as compared to the nurses. Highest level of environmental stress was observed in nonworking group i.e. housewives. A significant relation between serum cholesterol levels and three types of stresses was observed. (author)

Expansion of urban area and wastewater irrigated rice area in Hyderabad, India

Science.gov (United States)

Gumma, K.M.; van, Rooijen D.; Nelson, A.; Thenkabail, P.S.; Aakuraju, Radha V.; Amerasinghe, P.

2011-01-01

The goal of this study was to investigate land use changes in urban and peri-urban Hyderabad and their influence on wastewater irrigated rice using Landsat ETM + data and spectral matching techniques. The main source of irrigation water is the Musi River, which collects a large volume of wastewater and stormwater while running through the city. From 1989 to 2002, the wastewater irrigated area along the Musi River increased from 5,213 to 8,939 ha with concurrent expansion of the city boundaries from 22,690 to 42,813 ha and also decreased barren lands and range lands from 86,899 to 66,616 ha. Opportunistic shifts in land use, especially related to wastewater irrigated agriculture, were seen as a response to the demand for fresh vegetables and easy access to markets, exploited mainly by migrant populations. While wastewater irrigated agriculture contributes to income security of marginal groups, it also supplements the food basket of many city dwellers. Landsat ETM + data and advanced methods such as spectral matching techniques are ideal for quantifying urban expansion and associated land use changes, and are useful for urban planners and decision makers alike. ?? 2011 Springer Science+Business Media B.V.

A Global Photoionization Response to Prompt Emission and Outliers: Different Origin of Long Gamma-ray Bursts?

Science.gov (United States)

Wang, J.; Xin, L. P.; Qiu, Y. L.; Xu, D. W.; Wei, J. Y.

2018-03-01

By using the line ratio C IV λ1549/C II λ1335 as a tracer of the ionization ratio of the interstellar medium (ISM) illuminated by a long gamma-ray burst (LGRB), we identify a global photoionization response of the ionization ratio to the photon luminosity of the prompt emission assessed by either L iso/E peak or {L}iso}/{E}peak}2. The ionization ratio increases with both L iso/E peak and L iso/E 2 peak for a majority of the LGRBs in our sample, although there are a few outliers. The identified dependence of C IV/C II on {L}iso}/{E}peak}2 suggests that the scatter of the widely accepted Amati relation is related to the ionization ratio in the ISM. The outliers tend to have relatively high C IV/C II values as well as relatively high C IV λ1549/Si IV λ1403 ratios, which suggests an existence of Wolf–Rayet stars in the environment of these LGRBs. We finally argue that the outliers and the LGRBs following the identified C IV/C II‑L iso/E peak ({L}iso}/{E}peak}2) correlation might come from different progenitors with different local environments.

Probabilistic Neural Networks for Chemical Sensor Array Pattern Recognition: Comparison Studies, Improvements and Automated Outlier Rejection

National Research Council Canada - National Science Library

Shaffer, Ronald E

1998-01-01

For application to chemical sensor arrays, the ideal pattern recognition is accurate, fast, simple to train, robust to outliers, has low memory requirements, and has the ability to produce a measure...

Outlier Detection in Regression Using an Iterated One-Step Approximation to the Huber-Skip Estimator

DEFF Research Database (Denmark)

Johansen, Søren; Nielsen, Bent

2013-01-01

In regression we can delete outliers based upon a preliminary estimator and reestimate the parameters by least squares based upon the retained observations. We study the properties of an iteratively defined sequence of estimators based on this idea. We relate the sequence to the Huber-skip estima......In regression we can delete outliers based upon a preliminary estimator and reestimate the parameters by least squares based upon the retained observations. We study the properties of an iteratively defined sequence of estimators based on this idea. We relate the sequence to the Huber...... that the normalized estimation errors are tight and are close to a linear function of the kernel, thus providing a stochastic expansion of the estimators, which is the same as for the Huber-skip. This implies that the iterated estimator is a close approximation of the Huber-skip...

Chemical analysis of sewage sludge of southern sewerage treatment plant (SSTP) Hyderabad for achieving sustainable development in sector of agriculture

International Nuclear Information System (INIS)

Qureshi, K.; Shaikh, N.; Ahmed, R.S.; Nawaz, Z.

2003-01-01

A study on the chemical analysis of sewage sludge of southern sewerage treatment plant (SSPP) Hyderabad was studied. Chemical analysis on sludge samples collected form the waste stabilization for different micro-nutrients (essential manures, nitrogen, phosphorus, potassium, calcium and magnesium) were conducted in year 1999-2000. These nutrients and metal were detected by reliable analytical method i.e. Kjeldahls method and Atomic Absorption Spectrophotometer. The analysis showed that sewage sludge contained sufficient quantity of primary and secondary nutrients, hence sewage sludge could be utilized as a natural fertilizer. This will not only solve the disposal problem but it would also be environmentally safer way of providing regulators to the plants. (author)

The Space-Time Variation of Global Crop Yields, Detecting Simultaneous Outliers and Identifying the Teleconnections with Climatic Patterns

Science.gov (United States)

Najafi, E.; Devineni, N.; Pal, I.; Khanbilvardi, R.

2017-12-01

An understanding of the climate factors that influence the space-time variability of crop yields is important for food security purposes and can help us predict global food availability. In this study, we address how the crop yield trends of countries globally were related to each other during the last several decades and the main climatic variables that triggered high/low crop yields simultaneously across the world. Robust Principal Component Analysis (rPCA) is used to identify the primary modes of variation in wheat, maize, sorghum, rice, soybeans, and barley yields. Relations between these modes of variability and important climatic variables, especially anomalous sea surface temperature (SSTa), are examined from 1964 to 2010. rPCA is also used to identify simultaneous outliers in each year, i.e. systematic high/low crop yields across the globe. The results demonstrated spatiotemporal patterns of these crop yields and the climate-related events that caused them as well as the connection of outliers with weather extremes. We find that among climatic variables, SST has had the most impact on creating simultaneous crop yields variability and yield outliers in many countries. An understanding of this phenomenon can benefit global crop trade networks.

Natural treatment system models for wastewater management: a study from Hyderabad, India.

Science.gov (United States)

Sonkamble, Sahebrao; Wajihuddin, Md; Jampani, Mahesh; Sarah, S; Somvanshi, V K; Ahmed, Shakeel; Amerasinghe, Priyanie; Boisson, Alexandre

2018-01-01

Wastewater generated on a global scale has become a significant source of water resources which necessitates appropriate management strategies. However, the complexities associated with wastewater are lack of economically viable treatment systems, especially in low- and middle-income countries. While many types of treatment systems are needed to serve the various local issues, we propose natural treatment systems (NTS) such as natural wetlands that are eco-friendly, cost-effective, and can be jointly driven by public bodies and communities. In order for it to be part of wastewater management, this study explores the NTS potential for removal of pollutants, cost-effectiveness, and reuse options for the 1.20 million m 3 /day of wastewater generated in Hyderabad, India. The pilot study includes hydro-geophysical characterization of natural wetland to determine pollutant removal efficiency and its effective utilization for treated wastewater in the peri-urban habitat. The results show the removal of organic content (76-78%), nutrients (77-97%), and microbes (99.5-99.9%) from the wetland-treated wastewater and its suitability for agriculture applications. Furthermore, the wetland efficiency integrated with engineered interventions led to the development of NTS models with different application scenarios: (i) constructed wetlands, (ii) minimized community wetlands, and (iii) single outlet system, suitable for urban, peri-urban and rural areas, respectively.

A Positive Deviance Approach to Early Childhood Obesity: Cross-Sectional Characterization of Positive Outliers

OpenAIRE

Foster, Byron Alexander; Farragher, Jill; Parker, Paige; Hale, Daniel E.

2015-01-01

Objective: Positive deviance methodology has been applied in the developing world to address childhood malnutrition and has potential for application to childhood obesity in the United States. We hypothesized that among children at high-risk for obesity, evaluating normal weight children will enable identification of positive outlier behaviors and practices.

Characterization and aerobic biological treatment of msw: a case study of hyderabad city

International Nuclear Information System (INIS)

Korai, M.S.; Mahar, R.B.

2014-01-01

This study was conducted to assess the MSW (Municipal Solid Waste) generated in Hyderabad city for its suitability to make compost product through AB (Aerobic Biological) treatment. Assessment of MSW regarding its generation rate, quantification and characterization decides its suitability for composting process. Three AB treatment reactors R1 (natural air circulation and manually mixed reactor), R2 (compressed air circulation and manually mixed reactor) and R3 (compressed air circulation and mechanically mixed reactor) were designed and fabricated. AB treatment of the segregated food and yard waste reveals that there is no any significant change occurs in the moisture content of the compost product in all the reactors but, significant loss of VS (Volatile Solids) and gain of ash content was observed for reactor R2. Thus, the reactor R2 is the most efficient reactor in comparison to other reactors. Moreover, the mechanical mixing in AB treatment does not significantly increase VS loss. Further the reactor R1 does not consumes electricity and thus can be employed as the solution for converting segregated food and yard waste from MSW into a compost product. (author)

Characterization and Aerobic Biological Treatment of MSW: A Case Study of Hyderabad City

Directory of Open Access Journals (Sweden)

Muhammad Safar Korai

2014-07-01

Full Text Available This study was conducted to assess the MSW (Municipal Solid Waste generated in Hyderabad city for its suitability to make compost product through AB (Aerobic Biological treatment. Assessment of MSW regarding its generation rate, quantification and characterization decides its suitability for composting process. Three AB treatment reactors R1 (natural air circulation and manually mixed reactor, R2 (compressed air circulation and manually mixed reactor and R3 (compressed air circulation and mechanically mixed reactor were designed and fabricated. AB treatment of the segregated food and yard waste reveals that there is no any significant change occurs in the moisture content of the compost product in all the reactors but, significant loss of VS (Volatile Solids and gain of ash content was observed for reactor R2. Thus, the reactor R2 is the most efficient reactor in comparison to other reactors. Moreover, the mechanical mixing in AB treatment does not significantly increase VS loss. Further the reactor R1 does not consumes electricity and thus can be employed as the solution for converting segregated food and yard waste from MSW into a compost product

Hypothyroid associated megaesophagus in dogs: four years (2009-2013 study in Hyderabad, India

Directory of Open Access Journals (Sweden)

Karlapudi Satish Kumar

2015-06-01

Full Text Available Megaoesophagus is uncommon but an important consideration for chronic regurgitation in dogs. Five dogs of various breeds were presented to the Teaching Veterinary Clinical Complex (TVCC at College of Veterinary Science, Hyderabad with signs of chronic regurgitation, loss of weight, lethargy, weakness, dehydration and abnormalities of skin, and hair coat were diagnosed for megaesophagus on barium meal contrast radiography. At the TVCC, radiography and gastroscopy were performed, and the condition was confirmed as megaesophagus. Ancillary hemato-biochemical evaluations revealed normocytic normochromic anemia and mild leukocytosis with normal enzymatic activity in liver and kidneys. The thyroid profile in 80% (n=4/5 dogs showed decreased T3 and T4, and elevated thyroid stimulating hormone (TSH levels confirming hypothyroidism. Ultrasonography of abdomen eliminated obstructions in the gastro-intestinal tract and other systemic conditions. Echocardiographic observations were normal in all the dogs. Treatment with metoclopramide (dosed at 5 mg/kg bwt and levothyroxine (dosed at 20 μg/kg bwt and modified management practices involving feeding and diets were successful in controlling the regurgitation in dogs and resulted in good clinical recovery within 20-30 days of post-treatment.

Outlier treatment for improving parameter estimation of group contribution based models for upper flammability limit

DEFF Research Database (Denmark)

Frutiger, Jerome; Abildskov, Jens; Sin, Gürkan

2015-01-01

Flammability data is needed to assess the risk of fire and explosions. This study presents a new group contribution (GC) model to predict the upper flammability limit UFL oforganic chemicals. Furthermore, it provides a systematic method for outlier treatment inorder to improve the parameter...

Detection of outliers by neural network on the gas centrifuge experimental data of isotopic separation process

International Nuclear Information System (INIS)

Andrade, Monica de Carvalho Vasconcelos

2004-01-01

This work presents and discusses the neural network technique aiming at the detection of outliers on a set of gas centrifuge isotope separation experimental data. In order to evaluate the application of this new technique, the result obtained of the detection is compared to the result of the statistical analysis combined with the cluster analysis. This method for the detection of outliers presents a considerable potential in the field of data analysis and it is at the same time easier and faster to use and requests very less knowledge of the physics involved in the process. This work established a procedure for detecting experiments which are suspect to contain gross errors inside a data set where the usual techniques for identification of these errors cannot be applied or its use/demands an excessively long work. (author)

A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series

Science.gov (United States)

Cohn, T.A.; England, J.F.; Berenbrock, C.E.; Mason, R.R.; Stedinger, J.R.; Lamontagne, J.R.

2013-01-01

he Grubbs-Beck test is recommended by the federal guidelines for detection of low outliers in flood flow frequency computation in the United States. This paper presents a generalization of the Grubbs-Beck test for normal data (similar to the Rosner (1983) test; see also Spencer and McCuen (1996)) that can provide a consistent standard for identifying multiple potentially influential low flows. In cases where low outliers have been identified, they can be represented as “less-than” values, and a frequency distribution can be developed using censored-data statistical techniques, such as the Expected Moments Algorithm. This approach can improve the fit of the right-hand tail of a frequency distribution and provide protection from lack-of-fit due to unimportant but potentially influential low flows (PILFs) in a flood series, thus making the flood frequency analysis procedure more robust.

Robust PLS approach for KPI-related prediction and diagnosis against outliers and missing data

Science.gov (United States)

Yin, Shen; Wang, Guang; Yang, Xu

2014-07-01

In practical industrial applications, the key performance indicator (KPI)-related prediction and diagnosis are quite important for the product quality and economic benefits. To meet these requirements, many advanced prediction and monitoring approaches have been developed which can be classified into model-based or data-driven techniques. Among these approaches, partial least squares (PLS) is one of the most popular data-driven methods due to its simplicity and easy implementation in large-scale industrial process. As PLS is totally based on the measured process data, the characteristics of the process data are critical for the success of PLS. Outliers and missing values are two common characteristics of the measured data which can severely affect the effectiveness of PLS. To ensure the applicability of PLS in practical industrial applications, this paper introduces a robust version of PLS to deal with outliers and missing values, simultaneously. The effectiveness of the proposed method is finally demonstrated by the application results of the KPI-related prediction and diagnosis on an industrial benchmark of Tennessee Eastman process.

Analysis of Drinking Water Supply System Encompassing The Catchment, The Reservoir and The Treatment Facility (A Case Study of Osman Sagar Drinking Water Supply System, Hyderabad, India)

OpenAIRE

Balijepalli, Valli Priya

2009-01-01

Unregulated urban growth and unscientific approach towards source protection led to the degradation and loss of fresh water lakes in Hyderabad. Osman Sagar is one of the few lakes that still retains its fresh water status. In recent times it witnessed drastic fluctuations in its inflows resulting in reduced drinking water supply. The study emphasizes the need to improve the overall water management based on the integration of scientific assessment and appropriate management strategies.

SPATIAL CLUSTER AND OUTLIER IDENTIFICATION OF GEOCHEMICAL ASSOCIATION OF ELEMENTS: A CASE STUDY IN JUIRUI COPPER MINING AREA

Directory of Open Access Journals (Sweden)

Tien Thanh NGUYEN

2016-12-01

Full Text Available Spatial clusters and spatial outliers play an important role in the study of the spatial distribution patterns of geochemical data. They characterize the fundamental properties of mineralization processes, the spatial distribution of mineral deposits, and ore element concentrations in mineral districts. In this study, a new method for the study of spatial distribution patterns of multivariate data is proposed based on a combination of robust Mahalanobis distance and local Moran’s Ii. In order to construct the spatial matrix, the Moran's I spatial correlogram was first used to determine the range. The robust Mahalanobis distances were then computed for an association of elements. Finally, local Moran’s Ii statistics was used to measure the degree of spatial association and discover the spatial distribution patterns of associations of Cu, Au, Mo, Ag, Pb, Zn, As, and Sb elements including spatial clusters and spatial outliers. Spatial patterns were analyzed at six different spatial scales (2km, 4 km, 6 km, 8 km, 10 km and 12 km for both the raw data and Box-Cox transformed data. The results show that identified spatial cluster and spatial outlier areas using local Moran’s Ii and the robust Mahalanobis accord the objective reality and have a good conformity with known deposits in the study area.

An SPSS implementation of the nonrecursive outlier deletion procedure with shifting z score criterion (Van Selst & Jolicoeur, 1994).

Science.gov (United States)

Thompson, Glenn L

2006-05-01

Sophisticated univariate outlier screening procedures are not yet available in widely used statistical packages such as SPSS. However, SPSS can accept user-supplied programs for executing these procedures. Failing this, researchers tend to rely on simplistic alternatives that can distort data because they do not adjust to cell-specific characteristics. Despite their popularity, these simple procedures may be especially ill suited for some applications (e.g., data from reaction time experiments). A user friendly SPSS Production Facility implementation of the shifting z score criterion procedure (Van Selst & Jolicoeur, 1994) is presented in an attempt to make it easier to use. In addition to outlier screening, optional syntax modules can be added that will perform tedious database management tasks (e.g., restructuring or computing means).

Preconditions for market solution to urban water scarcity: Empirical results from Hyderabad City, India

Science.gov (United States)

Saleth, R. Maria; Dinar, Ariel

2001-01-01

Utilizing both primary and secondary information pertaining to the water sector of Hyderabad City, India, this paper (1) evaluates the economics of various technically feasible supply augmentations options; (2) estimates the group-specific water demand and consumption response functions under alternative pricing behaviors; (3) calculates the net willingness to pay (NWTP, considered to be the value of raw water at source) of different user groups as derived from their respective price elasticities; (4) shows how inadequate the NWTP is to justify most supply augmentation options including intersectoral water transfers under the existing water rate structure; (5) argues that the economic and institutional conditions internal to urban water sector cannot justify an externally imposed water transfers, whether market-based or otherwise, as long as the water rate structure is inefficient and regressive; and (6) concludes by underlining the central role that the pricing option, both the level and structure, plays not only in activating a number of nonprice options but also in generating incentives for the emergence of new and the consolidation of existing institutional conditions needed to support economically rooted water transfers and conservation initiatives.

New approach for the identification of implausible values and outliers in longitudinal childhood anthropometric data.

Science.gov (United States)

Shi, Joy; Korsiak, Jill; Roth, Daniel E

2018-03-01

We aimed to demonstrate the use of jackknife residuals to take advantage of the longitudinal nature of available growth data in assessing potential biologically implausible values and outliers. Artificial errors were induced in 5% of length, weight, and head circumference measurements, measured on 1211 participants from the Maternal Vitamin D for Infant Growth (MDIG) trial from birth to 24 months of age. Each child's sex- and age-standardized z-score or raw measurements were regressed as a function of age in child-specific models. Each error responsible for a biologically implausible decrease between a consecutive pair of measurements was identified based on the higher of the two absolute values of jackknife residuals in each pair. In further analyses, outliers were identified as those values beyond fixed cutoffs of the jackknife residuals (e.g., greater than +5 or less than -5 in primary analyses). Kappa, sensitivity, and specificity were calculated over 1000 simulations to assess the ability of the jackknife residual method to detect induced errors and to compare these methods with the use of conditional growth percentiles and conventional cross-sectional methods. Among the induced errors that resulted in a biologically implausible decrease in measurement between two consecutive values, the jackknife residual method identified the correct value in 84.3%-91.5% of these instances when applied to the sex- and age-standardized z-scores, with kappa values ranging from 0.685 to 0.795. Sensitivity and specificity of the jackknife method were higher than those of the conditional growth percentile method, but specificity was lower than for conventional cross-sectional methods. Using jackknife residuals provides a simple method to identify biologically implausible values and outliers in longitudinal child growth data sets in which each child contributes at least 4 serial measurements. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

An Efficient Method for Detection of Outliers in Tracer Curves Derived from Dynamic Contrast-Enhanced Imaging

Directory of Open Access Journals (Sweden)

Linning Ye

2018-01-01

Full Text Available Presence of outliers in tracer concentration-time curves derived from dynamic contrast-enhanced imaging can adversely affect the analysis of the tracer curves by model-fitting. A computationally efficient method for detecting outliers in tracer concentration-time curves is presented in this study. The proposed method is based on a piecewise linear model and implemented using a robust clustering algorithm. The method is noniterative and all the parameters are automatically estimated. To compare the proposed method with existing Gaussian model based and robust regression-based methods, simulation studies were performed by simulating tracer concentration-time curves using the generalized Tofts model and kinetic parameters derived from different tissue types. Results show that the proposed method and the robust regression-based method achieve better detection performance than the Gaussian model based method. Compared with the robust regression-based method, the proposed method can achieve similar detection performance with much faster computation speed.

Quartile and Outlier Detection on Heterogeneous Clusters Using Distributed Radix Sort

International Nuclear Information System (INIS)

Meredith, Jeremy S.; Vetter, Jeffrey S.

2011-01-01

In the past few years, performance improvements in CPUs and memory technologies have outpaced those of storage systems. When extrapolated to the exascale, this trend places strict limits on the amount of data that can be written to disk for full analysis, resulting in an increased reliance on characterizing in-memory data. Many of these characterizations are simple, but require sorted data. This paper explores an example of this type of characterization - the identification of quartiles and statistical outliers - and presents a performance analysis of a distributed heterogeneous radix sort as well as an assessment of current architectural bottlenecks.

Health & nutritional status of HIV infected children in Hyderabad, India.

Science.gov (United States)

Swetha, G Krishna; Hemalatha, R; Prasad, U V; Murali, Vasudev; Damayanti, K; Bhaskar, V

2015-01-01

Information on nutritional status of HIV infected children from India is lacking and is required before taking up nutritional supplementation trials. Thus, the aim of the present study was to assess the growth and morbidity status of HIV infected children over a period of one year in a city in southern India. This was an observational study carried out between July 2009 and February 2011, at two orphanages in Hyderabad, India. Seventy seven HIV-positive children aged between 1 and half and 15 years, both on and not on antiretroviral therapy (ART) were included. Nutritional status was assessed longitudinally for one year by weight gain, linear growth and body composition. Serum samples were analyzed for haemoglobin, micronutrients, CD4 and CD8 counts. Dietary intakes were assessed by institutional diet survey and morbidity data were recorded every day for 12 months. Mean energy intakes were less than recommended dietary allowance (RDA) in all age groups. Iron and folate intakes were less than 50 per cent of RDA; 46 (59.7%) children were stunted, 36 (46.8%) were underweight and 15 (19.5%) had low BMI for age. Anaemia was observed in 35 (45.5%) children. Micronutrient deficiencies such as vitamin D (40/77; 51.9%), vitamin A (11/77; 14.3%), folate (37/77; 48.1%), iron (38/77; 49.3%) were widely prevalent. HIV viral load was higher in children not on ART and those with morbidity. Respiratory (36.6%) and dermatological illnesses (18.8%) were the commonest presentations. Acute, chronic malnutrition and micronutrient deficiencies were common in HIV infected children, especially in those not on ART and having morbidity. With severe malnutrition being an alarming consequence of HIV, prophylactic nutritive care should be considered for integration into HIV care strategies besides initiation of ART to improve the nutritional status and quality of life of these children.

Identification of Outlier Loci Responding to Anthropogenic and Natural Selection Pressure in Stream Insects Based on a Self-Organizing Map

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Bin Li

2016-05-01

Full Text Available Water quality maintenance should be considered from an ecological perspective since water is a substrate ingredient in the biogeochemical cycle and is closely linked with ecosystem functioning and services. Addressing the status of live organisms in aquatic ecosystems is a critical issue for appropriate prediction and water quality management. Recently, genetic changes in biological organisms have garnered more attention due to their in-depth expression of environmental stress on aquatic ecosystems in an integrative manner. We demonstrate that genetic diversity would adaptively respond to environmental constraints in this study. We applied a self-organizing map (SOM to characterize complex Amplified Fragment Length Polymorphisms (AFLP of aquatic insects in six streams in Japan with natural and anthropogenic variability. After SOM training, the loci compositions of aquatic insects effectively responded to environmental selection pressure. To measure how important the role of loci compositions was in the population division, we altered the AFLP data by flipping the existence of given loci individual by individual. Subsequently we recognized the cluster change of the individuals with altered data using the trained SOM. Based on SOM recognition of these altered data, we determined the outlier loci (over 90th percentile that showed drastic changes in their belonging clusters (D. Subsequently environmental responsiveness (Ek’ was also calculated to address relationships with outliers in different species. Outlier loci were sensitive to slightly polluted conditions including Chl-a, NH4-N, NOX-N, PO4-P, and SS, and the food material, epilithon. Natural environmental factors such as altitude and sediment additionally showed relationships with outliers in somewhat lower levels. Poly-loci like responsiveness was detected in adapting to environmental constraints. SOM training followed by recognition shed light on developing algorithms de novo to

Spatio-temporal variability of CO and O3 in Hyderabad (17°N, 78°E, central India, based on MOZAIC and TES observations and WRF-Chem and MOZART-4 models

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Varun Sheel

2016-05-01

Full Text Available This article is based on the study of the seasonal and interannual variability of carbon monoxide (CO and ozone (O3 at different altitudes of the troposphere over Hyderabad, India, during 2006–2010 using Measurement of OZone and water vapour by Airbus In-Service Aircraft (MOZAIC and observation from Tropospheric Emission Spectrometer (TES aboard NASA's Aura satellite. The MOZAIC observations show maximum seasonal variability in both CO and O3 during winter and pre-monsoon season, with CO in the range (100–200±13 ppbv and O3 in the range (50–70±9 ppbv. The time-series of MOZAIC data shows a significant increase of 4.2±1.3 % in the surface CO and 6.7±1.3 % in the surface O3 during 2006–2010 in Hyderabad. From MOZAIC observations, we identify CO and O3 profiles that are anomalous with respect to the monthly mean and compare those with Weather Research Forecast model coupled with Chemistry (WRF-Chem and Model for OZone and Related Tracers, version 4 profiles for the same day. The anomalous profiles of WRF-Chem are simulated using three convection schemes. The goodness of comparison depends on the convection scheme and the altitude region of the troposphere.

Design of Laser Based Monitoring Systems for Compliance Management of Odorous and Hazardous Air Pollutants in Selected Chemical Industrial Estates at Hyderabad, India

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Sudhakar, P.; Kalavathi, P.; Ramakrishna Rao, D.; Satyanarayna, M.

2014-12-01

Industrialization can no longer sustain without internalization of the concerns of the receiving environment and land-use. Increased awareness and public pressure, coupled with regulatory instruments and bodies exert constant pressure on industries to control their emissions to a level acceptable to the receiving environment. However, when a group of industries come-up together as an industrial estate, the cumulative impacts of all the industries together often challenges the expected/desired quality of receiving environment, requiring stringent pollution control and monitoring measures. Laser remote sensing techniques provide powerful tools for environmental monitoring. These methods provide range resolved measurements of concentrations of various gaseous pollutants and suspended particulate matter (SPM) not only in the path of the beam but over the entire area. A three dimensional mapping of the pollutants and their dispersal can be estimated using the laser remote sensing methods on a continuous basis. Laser Radar (Lidar) systems are the measurements technology used in the laser remote sensing methods. Differential absorption lidar (DIAL) and Raman Lidar technologies have proved to be very useful for remote sensing of air pollutants. DIAL and Raman lidar systems can be applied for range resolved measurements of molecules like SO2, NO2, O3 Hg, CO, C2H4, H2O, CH4, hydrocarbons etc. in real time on a continuous basis. This paper describes the design details of the DAIL and Raman lidar techniques for measurement of various hazardous air pollutants which are being released into the atmosphere by the chemical industries operating in the Bachupally industrial Estate area at Hyderabad, India. The relative merits of the two techniques have been studied and the minimum concentration of pollutants that can be measured using these systems are presented. A dispersion model of the air pollutants in the selected chemical industrial estates at Hyderabad has been developed.

Association of IRS1, CAPN10, and PPARG gene polymorphisms with type 2 diabetes mellitus in the high-risk population of Hyderabad, India.

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Kommoju, Uma Jyothi; Maruda, Jayaraj; Kadarkarai Samy, Subburaj; Irgam, Kumuda; Kotla, Jaya Prasad; Reddy, Battini Mohan

2014-11-01

We attempted to validate earlier findings on the nature of the association of the IRS1, CAPN10, and PPARG genes with type 2 diabetes mellitus (T2DM) in the high-risk population of Hyderabad, India. A sample of 1379 subjects (758 T2DM patients, 621 controls) was genotyped for single nucleotide polymorphisms (SNPs) of the IRS1 (rs1801278), CAPN10 (rs3792267, rs5030952), and PPARG (rs1801282) genes. The allele and genotype frequencies of IRS1 (rs1801278) and CAPN10 (rs3792267) SNPs differed significantly between the patient and control groups. Logistic regression analysis suggested a significant association of these two SNPs (P ≤ 0.007) with T2DM and the strength of association did not alter when adjusted for age, gender, body mass index, and the waist : hip ratio as covariates. The same two SNPs showed significant association in multivariate logistic regression analyses, even after Bonferroni correction for multiple testing, suggesting an independent nature of the role of these genes in the manifestation of T2DM in our population. We replicated the significant association of rs1801278 and rs3792267 SNPs of the IRS1 and CAPN10 genes with T2DM in the population of Hyderabad. Despite the known biological significance of the PPARG gene and a sufficient statistical power of the present study, we could not replicate the association of PPARG with T2DM in our high-risk population. Given the vast ethnic, geographic, and genetic heterogeneity of the Indian population, many more studies are needed covering the ethnic and geographic heterogeneity of India to enable identification of an Indian-specific profile of genes associated with T2DM. © 2014 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd.

Inhalation dose due to indoor radon and thoron concentrations in the surrounding villages of Hyderabad, Andhra Pradesh, India

International Nuclear Information System (INIS)

Sreenath Reddy, M.; Sreenivasa Reddy, B.; Yadagiri Reddy, P.; Gopal Reddy, Ch.; Rama Reddy, K.

2006-01-01

Inhalation of radon, thoron and their decay products is the major contribution to the total radioactive dose received by the human population from the natural radiation. The indoor inhalation doses due to radon, thoron and their progenies in the surrounding villages of Hyderabad, India are evaluated. The average inhalation dose due to radon and its progeny is found to be 0.26 ± 0.21 mSv y -1 and due to thoron and its progeny is 0.35 ± 0.38 mSv y -1 . The inhalation dose is also analyzed based on the types of floor, roof and walls of the dwellings and it is found that the dwellings with mud type construction materials have higher inhalation dose. Generally, the contribution of thoron and its progeny to the total dose is neglected but in the present study area the fractional dose of thoron and its progeny is found to be comparable to that of radon and its progeny. (author)

A computational study on outliers in world music

Science.gov (United States)

Benetos, Emmanouil; Dixon, Simon

2017-01-01

The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as ‘outliers’. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the ‘uniqueness’ of the music of each country. PMID:29253027

Etiological pattern and early outcome of patients presenting with obstructive jaundice at isra university hospital, hyderabad, pakistan

International Nuclear Information System (INIS)

Bhanbhro, R.J.; Maheshwari, T.; Jarwar, M.

2017-01-01

Objective: To determine the etiological pattern and early outcome of patients presenting with obstructive jaundice. Methodology: This prospective case series was conducted on 82 patients through convenient sampling for one year from July 2010 to June 2011 at Isra University Hospital, Hyderabad, Pakistan. All patients with obstructive jaundice were included in this study. After making final diagnosis, depending upon the etiology and stage of disease, the patient was offered the appropriate treatment. SPSS version 16.0 was used to for data analysis. Results: Mean age of the participants was 54.16+-11.50. Males were predominant as compare to females, 57.3% and 42.7%. Gallstones were the most common cause; seen in 74 (90.2%) patients. Seventy (96.3%) were managed conservatively as compare to those patients in which surgery performed (1 case, 1.2%). 97.6% improved and were discharged where as 2(1.64%) did not improve. Conclusion: Gallstones were the predominant cause of obstructive jaundice in our setup. Most of the patients did not require surgical treatment, and outcome was very good with conservative treatment. (author)

Cross-visit tumor sub-segmentation and registration with outlier rejection for dynamic contrast-enhanced MRI time series data.

Science.gov (United States)

Buonaccorsi, G A; Rose, C J; O'Connor, J P B; Roberts, C; Watson, Y; Jackson, A; Jayson, G C; Parker, G J M

2010-01-01

Clinical trials of anti-angiogenic and vascular-disrupting agents often use biomarkers derived from DCE-MRI, typically reporting whole-tumor summary statistics and so overlooking spatial parameter variations caused by tissue heterogeneity. We present a data-driven segmentation method comprising tracer-kinetic model-driven registration for motion correction, conversion from MR signal intensity to contrast agent concentration for cross-visit normalization, iterative principal components analysis for imputation of missing data and dimensionality reduction, and statistical outlier detection using the minimum covariance determinant to obtain a robust Mahalanobis distance. After applying these techniques we cluster in the principal components space using k-means. We present results from a clinical trial of a VEGF inhibitor, using time-series data selected because of problems due to motion and outlier time series. We obtained spatially-contiguous clusters that map to regions with distinct microvascular characteristics. This methodology has the potential to uncover localized effects in trials using DCE-MRI-based biomarkers.

Prevalence of dental caries in people attending special schools in Hyderabad-Secunderabad, India

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Mahesh Kumar Duddu

2016-01-01

Full Text Available Aim: The present cross-sectional study was conducted to determine the decayed, missing, filled primary and permanent teeth (dmft-DMFT indices and its association with the type of disability in 856 disabled individuals attending special schools in twin cities of Hyderabad and Secunderabad, Andhra Pradesh State, India. Materials and Methods: Participants were grouped according to their disability such as: Mild, moderate, severe mental retardation, hearing and speech defect and others (39 (including Down′s syndrome [20], autism [9], hyperactive [4], microcephaly [2], border line cases [4]. Examination was carried out at their schools, with participants seated in ordinary chairs and examined under natural light with mouth mirror and probe. Subjects were of different age groups ranging from 1 to 55 years. Statistical Analysis Used: Analysis of variance with post-hoc Games-Howell test was used for statistical analysis. Results: Mean dmft; DMFT scores were as follows: 2-6 years: 1.58 ± 1.9; 2.18 ± 2.94, 7-12 years: 1.1 ± 2.4; 1.9 ± 2.13, 13-30 years: 2.38 ± 2.5, 30+ years: 2.13 ± 3.2. Overall only 23% of subjects were caries free. "dmft" was statistically higher among moderate mentally retarded group while DMFT was statistically higher in mild and moderate mentally retarded groups. Conclusions: These findings emphasize the need of educating parents and caregivers of disabled individuals in preventive dental procedures, especially those of the mild and moderate mentally challenged group.

Prevalence of multidrug resistance among retreatment pulmonary tuberculosis cases in a tertiary care hospital, Hyderabad, India

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Subhakar Kandi

2013-01-01

Full Text Available Background: India is one of the high tuberculosis (TB burden countries in the world. India ranks second in harboring multi drug resistant (MDR-TB cases. About 50,000 of MDR cases are recorded in retreatment pulmonary TB cases. This study was conducted in a tertiary care facility (Government General and Chest Hospital in Hyderabad, India. Objectives: Toassess: Proportion of the TB patients having MDR-TB at the initiation of retreatment regimen; the prevalence of isoniazid (INH resistance in this geographical area. Materials and Methods: An analytical, observational, prospective cohort study of patients attending the out-patient department from December 2010 to March 2011. Results: Sputum samples from 100 patients were subjected to acid fast bacilli (AFB culture and drug sensitivity testing. Of these, 28 (28% were MDR-TB, 42 (42% were non-MDR-TB and 39% being INH resistance. Conclusions: In conclusion, one third of the retreatment pulmonary TB cases attending a tertiary care institute for TB will be MDR-TB at the initiation of treatment and there is a need to include ethambutol in the continuation phase of new TB case treatment in view of high INH resistance.

Detecting outliers and learning complex structures with large spectroscopic surveys - a case study with APOGEE stars

Science.gov (United States)

Reis, Itamar; Poznanski, Dovi; Baron, Dalya; Zasowski, Gail; Shahaf, Sahar

2018-05-01

In this work, we apply and expand on a recently introduced outlier detection algorithm that is based on an unsupervised random forest. We use the algorithm to calculate a similarity measure for stellar spectra from the Apache Point Observatory Galactic Evolution Experiment (APOGEE). We show that the similarity measure traces non-trivial physical properties and contains information about complex structures in the data. We use it for visualization and clustering of the data set, and discuss its ability to find groups of highly similar objects, including spectroscopic twins. Using the similarity matrix to search the data set for objects allows us to find objects that are impossible to find using their best-fitting model parameters. This includes extreme objects for which the models fail, and rare objects that are outside the scope of the model. We use the similarity measure to detect outliers in the data set, and find a number of previously unknown Be-type stars, spectroscopic binaries, carbon rich stars, young stars, and a few that we cannot interpret. Our work further demonstrates the potential for scientific discovery when combining machine learning methods with modern survey data.

The Outlier Sectors: Areas of Non-Free Trade in the North American Free Trade Agreement

OpenAIRE

Eric T. Miller

2002-01-01

Since its entry into force, the North American Free Trade Agreement (NAFTA) has been enormously influential as a model for trade liberalization. While trade in goods among Canada, the United States and Mexico has been liberalized to a significant degree, this most famous of agreements nonetheless contains areas of recalcitrant protectionism. The first part of this paper identifies these "outlier sectors" and classifies them by primary source advocating protectionism, i.e., producer interests ...

Segmentation by Large Scale Hypothesis Testing - Segmentation as Outlier Detection

DEFF Research Database (Denmark)

Darkner, Sune; Dahl, Anders Lindbjerg; Larsen, Rasmus

2010-01-01

a microscope and we show how the method can handle transparent particles with significant glare point. The method generalizes to other problems. THis is illustrated by applying the method to camera calibration images and MRI of the midsagittal plane for gray and white matter separation and segmentation......We propose a novel and efficient way of performing local image segmentation. For many applications a threshold of pixel intensities is sufficient but determine the appropriate threshold value can be difficult. In cases with large global intensity variation the threshold value has to be adapted...... locally. We propose a method based on large scale hypothesis testing with a consistent method for selecting an appropriate threshold for the given data. By estimating the background distribution we characterize the segment of interest as a set of outliers with a certain probability based on the estimated...

Rapid eye movement sleep behavior disorder as an outlier detection problem

DEFF Research Database (Denmark)

Kempfner, Jacob; Sørensen, Gertrud Laura; Nikolic, M.

2014-01-01

OBJECTIVE: Idiopathic rapid eye movement (REM) sleep behavior disorder is a strong early marker of Parkinson's disease and is characterized by REM sleep without atonia and/or dream enactment. Because these measures are subject to individual interpretation, there is consequently need...... for quantitative methods to establish objective criteria. This study proposes a semiautomatic algorithm for the early detection of Parkinson's disease. This is achieved by distinguishing between normal REM sleep and REM sleep without atonia by considering muscle activity as an outlier detection problem. METHODS......: Sixteen healthy control subjects, 16 subjects with idiopathic REM sleep behavior disorder, and 16 subjects with periodic limb movement disorder were enrolled. Different combinations of five surface electromyographic channels, including the EOG, were tested. A muscle activity score was automatically...

Predictors of High Profit and High Deficit Outliers under SwissDRG of a Tertiary Care Center.

Science.gov (United States)

Mehra, Tarun; Müller, Christian Thomas Benedikt; Volbracht, Jörk; Seifert, Burkhardt; Moos, Rudolf

2015-01-01

Case weights of Diagnosis Related Groups (DRGs) are determined by the average cost of cases from a previous billing period. However, a significant amount of cases are largely over- or underfunded. We therefore decided to analyze earning outliers of our hospital as to search for predictors enabling a better grouping under SwissDRG. 28,893 inpatient cases without additional private insurance discharged from our hospital in 2012 were included in our analysis. Outliers were defined by the interquartile range method. Predictors for deficit and profit outliers were determined with logistic regressions. Predictors were shortlisted with the LASSO regularized logistic regression method and compared to results of Random forest analysis. 10 of these parameters were selected for quantile regression analysis as to quantify their impact on earnings. Psychiatric diagnosis and admission as an emergency case were significant predictors for higher deficit with negative regression coefficients for all analyzed quantiles (p<0.001). Admission from an external health care provider was a significant predictor for a higher deficit in all but the 90% quantile (p<0.001 for Q10, Q20, Q50, Q80 and p = 0.0017 for Q90). Burns predicted higher earnings for cases which were favorably remunerated (p<0.001 for the 90% quantile). Osteoporosis predicted a higher deficit in the most underfunded cases, but did not predict differences in earnings for balanced or profitable cases (Q10 and Q20: p<0.00, Q50: p = 0.10, Q80: p = 0.88 and Q90: p = 0.52). ICU stay, mechanical and patient clinical complexity level score (PCCL) predicted higher losses at the 10% quantile but also higher profits at the 90% quantile (p<0.001). We suggest considering psychiatric diagnosis, admission as an emergency case and admission from an external health care provider as DRG split criteria as they predict large, consistent and significant losses.

Predictors of High Profit and High Deficit Outliers under SwissDRG of a Tertiary Care Center.

Directory of Open Access Journals (Sweden)

Tarun Mehra

Full Text Available Case weights of Diagnosis Related Groups (DRGs are determined by the average cost of cases from a previous billing period. However, a significant amount of cases are largely over- or underfunded. We therefore decided to analyze earning outliers of our hospital as to search for predictors enabling a better grouping under SwissDRG.28,893 inpatient cases without additional private insurance discharged from our hospital in 2012 were included in our analysis. Outliers were defined by the interquartile range method. Predictors for deficit and profit outliers were determined with logistic regressions. Predictors were shortlisted with the LASSO regularized logistic regression method and compared to results of Random forest analysis. 10 of these parameters were selected for quantile regression analysis as to quantify their impact on earnings.Psychiatric diagnosis and admission as an emergency case were significant predictors for higher deficit with negative regression coefficients for all analyzed quantiles (p<0.001. Admission from an external health care provider was a significant predictor for a higher deficit in all but the 90% quantile (p<0.001 for Q10, Q20, Q50, Q80 and p = 0.0017 for Q90. Burns predicted higher earnings for cases which were favorably remunerated (p<0.001 for the 90% quantile. Osteoporosis predicted a higher deficit in the most underfunded cases, but did not predict differences in earnings for balanced or profitable cases (Q10 and Q20: p<0.00, Q50: p = 0.10, Q80: p = 0.88 and Q90: p = 0.52. ICU stay, mechanical and patient clinical complexity level score (PCCL predicted higher losses at the 10% quantile but also higher profits at the 90% quantile (p<0.001.We suggest considering psychiatric diagnosis, admission as an emergency case and admission from an external health care provider as DRG split criteria as they predict large, consistent and significant losses.

Outlier SNP markers reveal fine-scale genetic structuring across European hake populations (Merluccius merluccius)

DEFF Research Database (Denmark)

Milano, I.; Babbucci, M.; Cariani, A.

2014-01-01

fishery. Analysis of 850 individuals from 19 locations across the entire distribution range showed evidence for several outlier loci, with significantly higher resolving power. While 299 putatively neutral SNPs confirmed the genetic break between basins (FCT = 0.016) and weak differentiation within basins...... even when neutral markers provide genetic homogeneity across populations. Here, 381 SNPs located in transcribed regions were used to assess largeand fine-scale population structure in the European hake (Merluccius merluccius), a widely distributed demersal species of high priority for the European...

Villes indiennes sous tutelle ? Une réflexion sur les échelles de gouvernance à partir des cas de Mumbai et Hyderabad

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Loraine Kennedy

2011-11-01

Full Text Available De manière croissante, les décideurs politiques en Inde perçoivent le rôle crucial des villes dans l’économie nationale et les politiques actuelles menées par les États régionaux reflètent cette prise de conscience. Basée sur les cas proches, sans être entièrement comparables, d’Hyderabad et de Mumbai, cette recherche montre que les gouvernements des États ont adopté des stratégies de croissance centrée sur la ville, à l’instar des tendances internationales. Cela soulève la question du rééchelonnage des instances décisionnelles et de l’essor de l’émergence politique des régions métropolitaines. Après l'examen détaillé des stratégies de développement économique et urbain adoptées à Mumbai et à Hyderabad, cet article défend l’idée que les grandes villes indiennes n’ont pas une position suffisamment solide pour revendiquer un poids politique vis-à-vis de leur gouvernement régional et ne sont pas armées pour s'engager sérieusement dans la construction d’une action collective à l’échelle métropolitaine. Il convient de souligner cette déconnexion paroxystique entre les fonctions politiques et économiques, dans la mesure où cela marque une différence de degré avec l’expérience européenne récente. La subordination politique des collectivités locales urbaines en Inde est aggravée par le caractère traditionnellement centralisateur des institutions politiques, la faiblesse relative des institutions locales de gouvernance (en termes de mandat et de ressources fiscales, l'absence de maires puissants et la quasi-inexistence de statut politique de la plupart des régions métropolitaines. En outre, échafauder un plan stratégique qui tienne compte de la croissance économique, de la justice sociale et de l’environnement est une tâche herculéenne, particulièrement dans une société plurielle. Ainsi, dans les deux villes les processus en cours sont conflictuels et empreints de

Calculation of climatic reference values and its use for automatic outlier detection in meteorological datasets

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B. Téllez

2008-04-01

Full Text Available The climatic reference values for monthly and annual average air temperature and total precipitation in Catalonia – northeast of Spain – are calculated using a combination of statistical methods and geostatistical techniques of interpolation. In order to estimate the uncertainty of the method, the initial dataset is split into two parts that are, respectively, used for estimation and validation. The resulting maps are then used in the automatic outlier detection in meteorological datasets.

The source of prehistoric obsidian artefacts from the Polynesian outlier of Taumako in the Solomon Islands

Energy Technology Data Exchange (ETDEWEB)

Leach, Foss [Otago Univ., Dunedin (New Zealand). Dept. of Anthropology

1985-01-01

Six obsidian artefacts from the Polynesian outlier of Taumako in the Solomon Islands dating to between 500 and 1000 B.C. were analysed for trace elements by the PIXE-PIGME method. Four are shown to derive from Vanuatu, but the remaining two artefacts do not match any of the known 66 sources in the Pacific region. Continuing difficulties with the methodology of Pacific obsidian sourcing are discussed. 14 refs; 2 tables.

A new approach for assessing the state of environment using isometric log-ratio transformation and outlier detection for computation of mean PCDD/F patterns in biota.

Science.gov (United States)

Lehmann, René

2015-01-01

To assess the state of the environment, various compartments are examined as part of monitoring programs. Within monitoring, a special focus is on chemical pollution. One of the most toxic substances ever synthesized is the well-known dioxin 2,3,7,8-TCDD (2,3,7,8-tetra-chlor-dibenzo-dioxin). Other PCDD/F (polychlorinated-dibenzo-dioxin and furan) can act toxic too. They are ubiquitary and persistent in various environmental compartments. Assessing the state of environment requires knowledge of typical local patterns of PCDD/F for as many compartments as possible. For various species of wild animals and plants (so called biota), I present the mean local congenere profiles of ubiquitary PCDD/F contamination reflecting typical patterns and levels of environmental burden for various years. Trends in time series of means can indicate success or failure of a measure of PCDD/F reduction. For short time series of mean patterns, it can be hard to detect trends. A new approach regarding proportions of outliers in the corresponding annual cross-sectional data sets in parallel can help detect decreasing or increasing environmental burden and support analysis of time series. Further, in this article, the true structure of PCDD/F data in biota is revealed, that is, the compositional data structure. It prevents direct application of statistical standard procedures to the data rendering results of statistical analysis meaningless. Results indicate that the compositional data structure of PCDD/F in biota is of great interest and should be taken into account in future studies. Isometric log-ratio (ilr) transformation is used, providing data statistical standard procedures that can be applied too. Focusing on the identification of typical PCDD/F patterns in biota, outliers are removed from annual data since they represent an extraordinary situation in the environment. Identification of outliers yields two advantages. First, typical (mean) profiles and levels of PCDD/F contamination

Identification of Outliers in Grace Data for Indo-Gangetic Plain Using Various Methods (Z-Score, Modified Z-score and Adjusted Boxplot) and Its Removal

Science.gov (United States)

Srivastava, S.

2015-12-01

Gravity Recovery and Climate Experiment (GRACE) data are widely used for the hydrological studies for large scale basins (≥100,000 sq km). GRACE data (Stokes Coefficients or Equivalent Water Height) used for hydrological studies are not direct observations but result from high level processing of raw data from the GRACE mission. Different partner agencies like CSR, GFZ and JPL implement their own methodology and their processing methods are independent from each other. The primary source of errors in GRACE data are due to measurement and modeling errors and the processing strategy of these agencies. Because of different processing methods, the final data from all the partner agencies are inconsistent with each other at some epoch. GRACE data provide spatio-temporal variations in Earth's gravity which is mainly attributed to the seasonal fluctuations in water level on Earth surfaces and subsurface. During the quantification of error/uncertainties, several high positive and negative peaks were observed which do not correspond to any hydrological processes but may emanate from a combination of primary error sources, or some other geophysical processes (e.g. Earthquakes, landslide, etc.) resulting in redistribution of earth's mass. Such peaks can be considered as outliers for hydrological studies. In this work, an algorithm has been designed to extract outliers from the GRACE data for Indo-Gangetic plain, which considers the seasonal variations and the trend in data. Different outlier detection methods have been used such as Z-score, modified Z-score and adjusted boxplot. For verification, assimilated hydrological (GLDAS) and hydro-meteorological data are used as the reference. The results have shown that the consistency amongst all data sets improved significantly after the removal of outliers.

RE-EXAMINING HIGH ABUNDANCE SLOAN DIGITAL SKY SURVEY MASS-METALLICITY OUTLIERS: HIGH N/O, EVOLVED WOLF-RAYET GALAXIES?

International Nuclear Information System (INIS)

Berg, Danielle A.; Skillman, Evan D.; Marble, Andrew R.

2011-01-01

We present new MMT spectroscopic observations of four dwarf galaxies representative of a larger sample observed by the Sloan Digital Sky Survey and identified by Peeples et al. as low-mass, high oxygen abundance outliers from the mass-metallicity relation. Peeples showed that these four objects (with metallicity estimates of 8.5 ≤ 12 + log(O/H) ≤ 8.8) have oxygen abundance offsets of 0.4-0.6 dex from the M B luminosity-metallicity relation. Our new observations extend the wavelength coverage to include the [O II] λλ3726, 3729 doublet, which adds leverage in oxygen abundance estimates and allows measurements of N/O ratios. All four spectra are low excitation, with relatively high N/O ratios (N/O ∼> 0.10), each of which tend to bias estimates based on strong emission lines toward high oxygen abundances. These spectra all fall in a regime where the 'standard' strong-line methods for metallicity determinations are not well calibrated either empirically or by photoionization modeling. By comparing our spectra directly to photoionization models, we estimate oxygen abundances in the range of 7.9 ≤ 12 + log (O/H) ≤ 8.4, consistent with the scatter of the mass-metallicity relation. We discuss the physical nature of these galaxies that leads to their unusual spectra (and previous classification as outliers), finding their low excitation, elevated N/O, and strong Balmer absorption are consistent with the properties expected from galaxies evolving past the 'Wolf-Rayet galaxy' phase. We compare our results to the 'main' sample of Peeples and conclude that they are outliers primarily due to enrichment of nitrogen relative to oxygen and not due to unusually high oxygen abundances for their masses or luminosities.

Impact of social determinants on well-being of urban construction workers of Hyderabad.

Science.gov (United States)

Bala, Sudha; Valsangkar, Sameer; Lakshman Rao, Reshaboyina Lakshmi Narayana; Surya Prabha, Manem Lakshmi

2016-01-01

Hyderabad has witnessed one of the largest labor immigration in recent years and these construction workers are highly vulnerable in terms of health. Social determinants of health (SDH) arise from conditions in which they live and these factors interact with each other to produce direct impact on health. (1) To evaluate the sociodemographic and job characteristics of the construction workers. (2) To assess the impact of social determinants on well-being. A sample size of 135 construction workers working at three sites of HITEC city were interviewed using semi-structured questionnaire. Health perception and the impact on well-being was measured using the Healthy Days Module and Kessler's Psychological Distress Scale. SDH were measured on a 27-item questionnaire with responses on a Likert scale ranging from 0 to 4. Proportions, percentages, P values, and mean scores were obtained. The mean age of the sample was 35.4 ± 11.94 years. Seventeen (12.6%) of the workers reported a high risk score on the Kessler's Psychological Distress Scale. Binary logistic regression analysis was used to identify significant domains of social determinants independently associated with the well being of construction workers and significant among the nine domains of social determinants were addiction score domain with odds of 2.259 and a P value of 0.015 and the distress domain with odds of 1.108 and a P < 0.001. There is a significant impairment of physical and mental health due to various factors including SDH, such as addictive habits and psychological distress, which are amenable to prevention.

Using a cross-model loadings plot to identify protein spots causing 2-DE gels to become outliers in PCA

DEFF Research Database (Denmark)

Kristiansen, Luise Cederkvist; Jacobsen, Susanne; Jessen, Flemming

2010-01-01

The multivariate method PCA is an exploratory tool often used to get an overview of multivariate data, such as the quantified spot volumes of digitized 2-DE gels. PCA can reveal hidden structures present in the data, and thus enables identification of potential outliers and clustering. Based on PCA...

Antibiotic Prescribing Habits of Dental Surgeons in Hyderabad City, India, for Pulpal and Periapical Pathologies: A Survey

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K. Pavan Kumar

2013-01-01

Full Text Available Aim. To determine the antibiotic prescribing habits for pulpal and periapical pathology among dentists in Hyderabad city, India. Methodology. A total of 246 questionnaires were distributed to all the dentists registered with the local dental branch. Demographic details and questions regarding type and dosage of antibiotics prescribed for allergic and nonallergic patients were recorded. Inferential statistics were performed, and P<0.05 was considered statistically significant. Results. The response rate for the study was 87.8%. Around 148 (68.5% of respondents regularly prescribed antibiotics for endodontic management. The first antibiotic of choice for patients with no history of medical allergies was a combination of amoxicillin and metronidazole, followed by amoxicillin alone (29.1%. The first antibiotic of choice in case of allergy to penicillin was erythromycin. Necrotic pulp with acute apical periodontitis with swelling and moderate/severe preoperative symptom was the condition most commonly identified for antibiotic therapy (92.1%. Conclusion. The present study reveals that the overall antibiotic prescribing practices among this group of dentists were quite high, and there is a need for more educational initiatives to rationalize the use of antibiotics in dentistry.

Depression, anxiety, and stress among undergraduate dental students in Hyderabad City, Telangana, India: A cross-sectional study

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Ambati Sravani

2018-01-01

Full Text Available Introduction: Increased levels of psychological disturbances such as depression, anxiety, and stress (DAS among dental students affect the way these students take care of patients. Aim: The aim of this study is to assess DAS among undergraduate dental students in Hyderabad city, Telangana, India. Materials and Methods: A short version of depression, anxiety, and stress scale was distributed to undergraduate dental students in four dental colleges. Comparison among the variables was done using ANOVA and Independent t-test. Results: The study group comprised 200 (23.7% males and 645 (76.3% females. The overall mean DAS score and its dimensions were not significant based on gender. Married students showed significantly more DAS compared to unmarried (P < 0.05. When the year of study was considered for all colleges together, the overall mean DAS score and its individual dimensions score were significantly high among III year students followed by IV, I, and II years (P < 0.05. Conclusion: Clinical years were more stressful than the nonclinical years. This suggests a need for special attention to the structure of the clinical program, particularly at the point of transition from the preclinical to the clinical phase.

Environmental pollution with antimicrobial agents from bulk drug manufacturing industries in Hyderabad, South India, is associated with dissemination of extended-spectrum beta-lactamase and carbapenemase-producing pathogens.

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Lübbert, Christoph; Baars, Christian; Dayakar, Anil; Lippmann, Norman; Rodloff, Arne C; Kinzig, Martina; Sörgel, Fritz

2017-08-01

High antibiotic and antifungal concentrations in wastewater from anti-infective drug production may exert selection pressure for multidrug-resistant (MDR) pathogens. We investigated the environmental presence of active pharmaceutical ingredients and their association with MDR Gram-negative bacteria in Hyderabad, South India, a major production area for the global bulk drug market. From Nov 19 to 28, 2016, water samples were collected from the direct environment of bulk drug manufacturing facilities, the vicinity of two sewage treatment plants, the Musi River, and habitats in Hyderabad and nearby villages. Samples were analyzed for 25 anti-infective pharmaceuticals with liquid chromatography-tandem mass spectrometry and for MDR Gram-negative bacteria using chromogenic culture media. In addition, specimens were screened with PCR for bla VIM , bla KPC , bla NDM , bla IMP-1 , and bla OXA-48 resistance genes. All environmental specimens from 28 different sampling sites were contaminated with antimicrobials. High concentrations of moxifloxacin, voriconazole, and fluconazole (up to 694.1, 2500, and 236,950 µg/L, respectively) as well as increased concentrations of eight other antibiotics were found in sewers in the Patancheru-Bollaram industrial area. Corresponding microbiological analyses revealed an extensive presence of extended-spectrum beta-lactamase and carbapenemase-producing Enterobacteriaceae and non-fermenters (carrying mainly bla OXA-48 , bla NDM , and bla KPC ) in more than 95% of the samples. Insufficient wastewater management by bulk drug manufacturing facilities leads to unprecedented contamination of water resources with antimicrobial pharmaceuticals, which seems to be associated with the selection and dissemination of carbapenemase-producing pathogens. The development and global spread of antimicrobial resistance present a major challenge for pharmaceutical producers and regulatory agencies.

Frequency of the Occurence of Methicilin Resistant Staphylococcus aureus (MRSA Infections in Hyderabad, Pakistan

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Nazir Ahmed Brohi

2017-06-01

Full Text Available Staphylococcus aureus is a potential pathogen of hospital and community related infections. It secretes toxins or the enzymes as virulence factor of mild to severe infections and show resistance to beta-lactam antibiotic including penicillin, methicillin, oxacillin and now vancomycin that could alarm of equal risk factors of Methicillin Resistant Staphylococcus aureus (MRSA infections in the patients. The survey report of 381 patients of Hyderabad, Pakistan was collected from March 2013 to June 2014 in which 176 cases were reported for Staphylococcus aureus in both genders of different age groups of 3-15 y kids, 16-45 y adults and 45-70 y olds, which showed 208 and 132 specimens Staphylococcus infection and 16 and 4 cases of MRSA infections in male and female patients, respectively whereas other 31 cases showed no infection. The laboratory diagnosis of the 200 samples from various hospitalized patients revealed the highest percentage of Methicillin Resistant Staphylococcus aureus MRSA in pus and post-operative wounds (17% followed by skin swabs (10%, sputum (7% and blood (0%. The observations revealed greater prevalence of MRSA infection in elderly age 16-45 years males than the females and other age groups. Antibiotic susceptibility test of 26 antibiotics revealed resistance (R-53%, sensitive (S-39 and variable (V-7% sensitivity zones (mm. Amplification of mecA gene was done using PCR reaction that revealed mecA gene bands up to 150-200 base pairs by test resistant strains.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

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Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

Science.gov (United States)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Radiological and environmental safety aspects of uranium fuel fabrication plants at Nuclear Fuel Complex, Hyderabad

International Nuclear Information System (INIS)

Viswanathan, S.; Surya Rao, B.; Lakshmanan, A.R.; Krishna Rao, T.

1991-01-01

Nuclear Fuel Complex, Hyderabad manufactures uranium dioxide fuel assemblies for PHWRs and BWRs operating in India. Starting materials are magnesium diuranate received from UCIL, Jaduguda and imported UF. Both of these are converted to UO 2 pellets by identical chemical processes and mechanical compacting. Since the uranium handled here is free of daughter product activities, external radiation is not a problem. Inhalation of airborne U compounds is one of the main source of exposure. Engineered protective measures like enclosures around U bearing powder handling equipment and local exhausts reduce worker's exposure. Installation of pre-filters, wet rotoclones and electrostatic precipitators in the ventillation system reduces the release of U into the environment. The criticality hazard in handling slightly enriched uranium is very low due to the built-in control based on geometry and inventory. Where airborne uranium is significant, workers are provided with protective respirators. The workers are regularly monitored for external exposure and also for internal exposure. The environmental releases from the NFC facility is well controlled. Soil, water and air from the NFC environment are routinely collected and analysed for all the possible pollutants. The paper describes the Health Physics experience during the last five years on occupational exposures and on environmental surveillance which reveals the high quality of safety observed in our nuclear fuel fabricating installations. (author). 4 refs., 6 tabs

Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study.

Science.gov (United States)

Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P

2014-06-26

To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.

Engaging children in the development of obesity interventions: Exploring outcomes that matter most among obesity positive outliers.

Science.gov (United States)

Sharifi, Mona; Marshall, Gareth; Goldman, Roberta E; Cunningham, Courtney; Marshall, Richard; Taveras, Elsie M

2015-11-01

To explore outcomes and measures of success that matter most to 'positive outlier' children who improved their body mass index (BMI) despite living in obesogenic neighborhoods. We collected residential address and longitudinal height/weight data from electronic health records of 22,657 children ages 6-12 years in Massachusetts. We defined obesity "hotspots" as zip codes where >15% of children had a BMI ≥95th percentile. Using linear mixed effects models, we generated a BMI z-score slope for each child with a history of obesity. We recruited 10-12 year-olds with negative slopes living in hotspots for focus groups. We analyzed group transcripts and discussed emerging themes in iterative meetings using an immersion/crystallization approach. We reached thematic saturation after 4 focus groups with 21 children. Children identified bullying and negative peer comparisons related to physical appearance, clothing size, and athletic ability as motivating them to achieve a healthier weight, and they measured success as improvement in these domains. Positive relationships with friends and family facilitated both behavior change initiation and maintenance. The perspectives of positive outlier children can provide insight into children's motivations leading to successful obesity management. Child/family engagement should guide the development of patient-centered obesity interventions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Wastewater treatment and reuse in urban agriculture: exploring the food, energy, water, and health nexus in Hyderabad, India

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Miller-Robbie, Leslie; Ramaswami, Anu; Amerasinghe, Priyanie

2017-07-01

Nutrients and water found in domestic treated wastewater are valuable and can be reutilized in urban agriculture as a potential strategy to provide communities with access to fresh produce. In this paper, this proposition is examined by conducting a field study in the rapidly developing city of Hyderabad, India. Urban agriculture trade-offs in water use, energy use and GHG emissions, nutrient uptake, and crop pathogen quality are evaluated, and irrigation waters of varying qualities (treated wastewater, versus untreated water and groundwater) are compared. The results are counter-intuitive, and illustrate potential synergies and key constraints relating to the food-energy-water-health (FEW-health) nexus in developing cities. First, when the impact of GHG emissions from untreated wastewater diluted in surface streams is compared with the life cycle assessment of wastewater treatment with reuse in agriculture, the treatment-plus-reuse case yields a 33% reduction in life cycle system-wide GHG emissions. Second, despite water cycling benefits in urban agriculture, only contamination and farmer behavior and harvesting practices. The study uncovers key physical, environmental, and behavioral factors that constrain benefits achievable at the FEW-health nexus in urban areas.

Co-ordinated research programme on isotope-aided studies of the bioavailability of iron and zinc from human diets. Report of the second research co-ordination meeting, Hyderabad, India, 16-20 November 1992

International Nuclear Information System (INIS)

1994-01-01

The Co-ordinated Research Programme (CRP) on ''Isotope-Aided Studies on the Bioavailability of Iron and Zinc from Human Diets'' was initiated by the IAEA in 1990, and presently encompasses participating institutes in 11 countries. A summary of the discussions that took place during thr second Research Co-ordination Meeting held in Hyderabad, India, between 16-20 November 1992, is given in this report together with 12 working papers (progress reports) presented by individual participants. A separate abstract was prepared for each of these papers. Refs, figs and tabs

Client Satisfaction And Decision Making Amongst Females Visiting Family Planning Clinics In Hyderabad, Pakistan.

Science.gov (United States)

Memon, Arbia; Hamid, Saima; Kumar, Ramesh

2017-01-01

Family Planning is the basic right of the human being. It involves decision regarding the number of children and desired space between children by the couple themselves. Quality services involving multiple dimensions build the confidence of the clients and lack of quality is one of the constraints behind incomplete coverage of family planning. Objectives of the current study were to determine the client satisfaction, decision-making process and various influences on clients in adopting family planning methods. This cross-sectional study was conducted at Family Planning Centre of Liaquat University Hospital, Hyderabad in 2016. Quality of the family planning services and satisfaction with the services were assessed through responses obtained from women selected purposively and visiting family planning centre through exit interviews with structured pretested and reliable questionnaire after taking the written consent. Access to Family Planning Centre was not an issue in 92% cases but only 31% respondents were appropriately greeted, 77% faced blank expression and 13% received sufficient privacy. Health problems and socioeconomic conditions were inquired by 41% and18% providers respectively, while motivating force for service use was mother in law in most 35% cases. Health workers were successful in clarifying misinformation (86%) and explaining side effects (71%) but only 21% respondents were satisfied with services. Respondents are influenced by family and health care providers while making decision and type of influence was considered positive by 83% respondents. Training and monitoring system be strengthened at family planning centres to improve quality of services while important influencing relations be focused for family planning education to improve utilization of services.

Genomic outlier profile analysis: mixture models, null hypotheses, and nonparametric estimation.

Science.gov (United States)

Ghosh, Debashis; Chinnaiyan, Arul M

2009-01-01

In most analyses of large-scale genomic data sets, differential expression analysis is typically assessed by testing for differences in the mean of the distributions between 2 groups. A recent finding by Tomlins and others (2005) is of a different type of pattern of differential expression in which a fraction of samples in one group have overexpression relative to samples in the other group. In this work, we describe a general mixture model framework for the assessment of this type of expression, called outlier profile analysis. We start by considering the single-gene situation and establishing results on identifiability. We propose 2 nonparametric estimation procedures that have natural links to familiar multiple testing procedures. We then develop multivariate extensions of this methodology to handle genome-wide measurements. The proposed methodologies are compared using simulation studies as well as data from a prostate cancer gene expression study.

Stakeholder Views, Financing and Policy Implications for Reuse of Wastewater for Irrigation: A Case from Hyderabad, India

Directory of Open Access Journals (Sweden)

Markus Starkl

2015-01-01

Full Text Available When flowing through Hyderabad, the capital of Telangana, India, the Musi River picks up (partially treated and untreated sewage from the city. Downstream of the city, farmers use this water for the irrigation of rice and vegetables. Treatment of the river water before it is used for irrigation would address the resulting risks for health and the environment. To keep the costs and operational efforts low for the farmers, the use of constructed wetlands is viewed as a suitable option. Towards this end, the paper investigates the interests and perceptions of government stakeholders and famers on the treatment of wastewater for irrigation and further explores the consumer willingness to pay a higher price for cleaner produced vegetables. Full cost recovery from farmers and consumers cannot be expected, if mass scale treatment of irrigation water is implemented. Instead, both consumers and farmers would expect that the government supports treatment of irrigation water. Most stakeholders associated with the government weigh health and environment so high, that these criteria outweigh cost concerns. They also support the banning of irrigation with polluted water. However, fining farmers for using untreated river water would penalize them for pollution caused by others. Therefore public funding of irrigation water treatment is recommended.

Robust identification of transcriptional regulatory networks using a Gibbs sampler on outlier sum statistic.

Science.gov (United States)

Gu, Jinghua; Xuan, Jianhua; Riggins, Rebecca B; Chen, Li; Wang, Yue; Clarke, Robert

2012-08-01

Identification of transcriptional regulatory networks (TRNs) is of significant importance in computational biology for cancer research, providing a critical building block to unravel disease pathways. However, existing methods for TRN identification suffer from the inclusion of excessive 'noise' in microarray data and false-positives in binding data, especially when applied to human tumor-derived cell line studies. More robust methods that can counteract the imperfection of data sources are therefore needed for reliable identification of TRNs in this context. In this article, we propose to establish a link between the quality of one target gene to represent its regulator and the uncertainty of its expression to represent other target genes. Specifically, an outlier sum statistic was used to measure the aggregated evidence for regulation events between target genes and their corresponding transcription factors. A Gibbs sampling method was then developed to estimate the marginal distribution of the outlier sum statistic, hence, to uncover underlying regulatory relationships. To evaluate the effectiveness of our proposed method, we compared its performance with that of an existing sampling-based method using both simulation data and yeast cell cycle data. The experimental results show that our method consistently outperforms the competing method in different settings of signal-to-noise ratio and network topology, indicating its robustness for biological applications. Finally, we applied our method to breast cancer cell line data and demonstrated its ability to extract biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer. The Gibbs sampler MATLAB package is freely available at http://www.cbil.ece.vt.edu/software.htm. xuan@vt.edu Supplementary data are available at Bioinformatics online.

The internal structure of eclogite-facies ophiolite complexes: Implications from the Austroalpine outliers within the Zermatt-Saas Zone, Western Alps

Science.gov (United States)

Weber, Sebastian; Martinez, Raul

2016-04-01

The Western Alpine Penninic domain is a classical accretionary prism that formed after the closure of the Penninic oceans in the Paleogene. Continental and oceanic nappes were telescoped into the Western Alpine stack associated with continent-continent collision. Within the Western Alpine geologic framework, the ophiolite nappes of the Zermatt-Saas Zone and the Tsate Unit are the remnants of the southern branch of the Piemonte-Liguria ocean basin. In addition, a series of continental basement slices reported as lower Austroalpine outliers have preserved an eclogitic high-pressure imprint, and are tectonically sandwiched between these oceanic nappes. Since the outliers occur at an unusual intra-ophiolitic setting and show a polymetamorphic character, this group of continental slices is of special importance for understanding the tectono-metamorphic evolution of Western Alps. Recently, more geochronological data from the Austroalpine outliers have become available that make it possible to establish a more complete picture of their complex geological history. The Lu-Hf garnet-whole rock ages for prograde growth of garnet fall into the time interval of 52 to 62 Ma (Weber et al., 2015, Fassmer et al. 2015), but are consistently higher than the Lu-Hf garnet-whole rock ages from several other locations throughout the Zermatt-Saas zone that range from 52 to 38 Ma (Skora et al., 2015). This discrepancy suggests that the Austroalpine outliers may have been subducted earlier than the ophiolites of the Zermatt-Saas Zone and therefore have been tectonically emplaced into their present intra-ophiolite position. This points to the possibility that the Zermatt-Saas Zone consists of tectonic subunits, which reached their respective pressure peaks over a prolonged time period, approximately 10-20 Ma. The pressure-temperature estimates from several members of the Austroalpine outliers indicate a complex distribution of metamorphic peak conditions, without ultrahigh

Engaging children in the development of obesity interventions: exploring outcomes that matter most among obesity positive outliers

OpenAIRE

Sharifi, Mona; Marshall, Gareth; Goldman, Roberta E.; Cunningham, Courtney; Marshall, Richard; Taveras, Elsie M

2015-01-01

Objective To explore outcomes and measures of success that matter most to 'positive outlier' children who improved their body mass index (BMI) despite living in obesogenic neighborhoods. Methods We collected residential address and longitudinal height/weight data from electronic health records of 22,657 children ages 6–12 years in Massachusetts. We defined obesity “hotspots” as zip codes where >15% of children had a BMI ≥95th percentile. Using linear mixed effects models, we gener...

Analysis and detection of functional outliers in water quality parameters from different automated monitoring stations in the Nalón river basin (Northern Spain).

Science.gov (United States)

Piñeiro Di Blasi, J I; Martínez Torres, J; García Nieto, P J; Alonso Fernández, J R; Díaz Muñiz, C; Taboada, J

2015-01-01

The purposes and intent of the authorities in establishing water quality standards are to provide enhancement of water quality and prevention of pollution to protect the public health or welfare in accordance with the public interest for drinking water supplies, conservation of fish, wildlife and other beneficial aquatic life, and agricultural, industrial, recreational, and other reasonable and necessary uses as well as to maintain and improve the biological integrity of the waters. In this way, water quality controls involve a large number of variables and observations, often subject to some outliers. An outlier is an observation that is numerically distant from the rest of the data or that appears to deviate markedly from other members of the sample in which it occurs. An interesting analysis is to find those observations that produce measurements that are different from the pattern established in the sample. Therefore, identification of atypical observations is an important concern in water quality monitoring and a difficult task because of the multivariate nature of water quality data. Our study provides a new method for detecting outliers in water quality monitoring parameters, using turbidity, conductivity and ammonium ion as indicator variables. Until now, methods were based on considering the different parameters as a vector whose components were their concentration values. This innovative approach lies in considering water quality monitoring over time as continuous curves instead of discrete points, that is to say, the dataset of the problem are considered as a time-dependent function and not as a set of discrete values in different time instants. This new methodology, which is based on the concept of functional depth, was applied to the detection of outliers in water quality monitoring samples in the Nalón river basin with success. Results of this study were discussed here in terms of origin, causes, etc. Finally, the conclusions as well as advantages of

Estimating the number of components and detecting outliers using Angle Distribution of Loading Subspaces (ADLS) in PCA analysis.

Science.gov (United States)

Liu, Y J; Tran, T; Postma, G; Buydens, L M C; Jansen, J

2018-08-22

Principal Component Analysis (PCA) is widely used in analytical chemistry, to reduce the dimensionality of a multivariate data set in a few Principal Components (PCs) that summarize the predominant patterns in the data. An accurate estimate of the number of PCs is indispensable to provide meaningful interpretations and extract useful information. We show how existing estimates for the number of PCs may fall short for datasets with considerable coherence, noise or outlier presence. We present here how Angle Distribution of the Loading Subspaces (ADLS) can be used to estimate the number of PCs based on the variability of loading subspace across bootstrap resamples. Based on comprehensive comparisons with other well-known methods applied on simulated dataset, we show that ADLS (1) may quantify the stability of a PCA model with several numbers of PCs simultaneously; (2) better estimate the appropriate number of PCs when compared with the cross-validation and scree plot methods, specifically for coherent data, and (3) facilitate integrated outlier detection, which we introduce in this manuscript. We, in addition, demonstrate how the analysis of different types of real-life spectroscopic datasets may benefit from these advantages of ADLS. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach

Science.gov (United States)

Petersen, D.; Naveed, P.; Ragheb, A.; Niedieker, D.; El-Mashtoly, S. F.; Brechmann, T.; Kötting, C.; Schmiegel, W. H.; Freier, E.; Pox, C.; Gerwert, K.

2017-06-01

Endoscopy plays a major role in early recognition of cancer which is not externally accessible and therewith in increasing the survival rate. Raman spectroscopic fiber-optical approaches can help to decrease the impact on the patient, increase objectivity in tissue characterization, reduce expenses and provide a significant time advantage in endoscopy. In gastroenterology an early recognition of malign and precursor lesions is relevant. Instantaneous and precise differentiation between adenomas as precursor lesions for cancer and hyperplastic polyps on the one hand and between high and low-risk alterations on the other hand is important. Raman fiber-optical measurements of colon biopsy samples taken during colonoscopy were carried out during a clinical study, and samples of adenocarcinoma (22), tubular adenomas (141), hyperplastic polyps (79) and normal tissue (101) from 151 patients were analyzed. This allows us to focus on the bioinformatic analysis and to set stage for Raman endoscopic measurements. Since spectral differences between normal and cancerous biopsy samples are small, special care has to be taken in data analysis. Using a leave-one-patient-out cross-validation scheme, three different outlier identification methods were investigated to decrease the influence of systematic errors, like a residual risk in misplacement of the sample and spectral dilution of marker bands (esp. cancerous tissue) and therewith optimize the experimental design. Furthermore other validations methods like leave-one-sample-out and leave-one-spectrum-out cross-validation schemes were compared with leave-one-patient-out cross-validation. High-risk lesions were differentiated from low-risk lesions with a sensitivity of 79%, specificity of 74% and an accuracy of 77%, cancer and normal tissue with a sensitivity of 79%, specificity of 83% and an accuracy of 81%. Additionally applied outlier identification enabled us to improve the recognition of neoplastic biopsy samples.

Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach.

Science.gov (United States)

Petersen, D; Naveed, P; Ragheb, A; Niedieker, D; El-Mashtoly, S F; Brechmann, T; Kötting, C; Schmiegel, W H; Freier, E; Pox, C; Gerwert, K

2017-06-15

Endoscopy plays a major role in early recognition of cancer which is not externally accessible and therewith in increasing the survival rate. Raman spectroscopic fiber-optical approaches can help to decrease the impact on the patient, increase objectivity in tissue characterization, reduce expenses and provide a significant time advantage in endoscopy. In gastroenterology an early recognition of malign and precursor lesions is relevant. Instantaneous and precise differentiation between adenomas as precursor lesions for cancer and hyperplastic polyps on the one hand and between high and low-risk alterations on the other hand is important. Raman fiber-optical measurements of colon biopsy samples taken during colonoscopy were carried out during a clinical study, and samples of adenocarcinoma (22), tubular adenomas (141), hyperplastic polyps (79) and normal tissue (101) from 151 patients were analyzed. This allows us to focus on the bioinformatic analysis and to set stage for Raman endoscopic measurements. Since spectral differences between normal and cancerous biopsy samples are small, special care has to be taken in data analysis. Using a leave-one-patient-out cross-validation scheme, three different outlier identification methods were investigated to decrease the influence of systematic errors, like a residual risk in misplacement of the sample and spectral dilution of marker bands (esp. cancerous tissue) and therewith optimize the experimental design. Furthermore other validations methods like leave-one-sample-out and leave-one-spectrum-out cross-validation schemes were compared with leave-one-patient-out cross-validation. High-risk lesions were differentiated from low-risk lesions with a sensitivity of 79%, specificity of 74% and an accuracy of 77%, cancer and normal tissue with a sensitivity of 79%, specificity of 83% and an accuracy of 81%. Additionally applied outlier identification enabled us to improve the recognition of neoplastic biopsy samples. Copyright �

¿Se pueden predecir geográficamente los resultados electorales? Una aplicación del análisis de clusters y outliers espaciales

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Carlos J. Vilalta Perdomo

2008-01-01

Full Text Available Los resultados de este estudio demuestran que al aplicar la estadística espacial en la geografía electoral es posible predecir los resultados electorales. Se utilizan los conceptos geográficos de cluster y outlier espaciales, y como variable predictiva la segregación espacial socioeconómica. Las técnicas estadísticas que se emplean son los índices globales y locales de autocorrelación espacial de Moran y el análisis de regresión lineal. Sobre los datos analizados se encuentra: 1 que la Ciudad de México posee clusters espaciales de apoyo electoral y de marginación, 2 outliers espaciales de marginación, 3 que los partidos electorales se excluyen geográficamente, y 4 que sus resultados dependen significativamente de los niveles de segregación espacial en la ciudad.

Are tuberculosis patients in a tertiary care hospital in Hyderabad, India being managed according to national guidelines?

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Kiran Kumar Kondapaka

Full Text Available SETTING: A tertiary health care facility (Government General and Chest hospital in Hyderabad, India. OBJECTIVES: To assess a the extent of compliance of specialists to standardized national (RNTCP tuberculosis management guidelines and b if patients on discharge from hospital were being appropriately linked up with peripheral health facilities for continuation of anti-Tuberculosis (TB treatment. METHODS: A descriptive study using routine programme data and involving all TB patients admitted to inpatient care from 1(st January to 30(th June, 2010. RESULTS AND CONCLUSIONS: There were a total of 3120 patients admitted of whom, 1218 (39% required anti-TB treatment. Of these 1104 (98% were treated with one of the RNTCP recommended regimens, while 28 (2% were treated with non-RNTCP regimens. The latter included individually tailored MDR-TB treatment regimens for 19 patients and adhoc regimens for nine patients. A total of 957 (86% patients were eventually discharged from the hospital of whom 921 (96% had a referral form filled for continuing treatment at a peripheral health facility. Formal feedback from peripheral health facilities on continuation of TB treatment was received for 682 (74% patients. In a tertiary health facility with specialists the great majority of TB patients are managed in line with national guidelines. However a number of short-comings were revealed and measures to rectify these are discussed.

An optimized outlier detection algorithm for jury-based grading of engineering design projects

DEFF Research Database (Denmark)

Thompson, Mary Kathryn; Espensen, Christina; Clemmensen, Line Katrine Harder

2016-01-01

This work characterizes and optimizes an outlier detection algorithm to identify potentially invalid scores produced by jury members while grading engineering design projects. The paper describes the original algorithm and the associated adjudication process in detail. The impact of the various...... (the base rule and the three additional conditions) play a role in the algorithm's performance and should be included in the algorithm. Because there is significant interaction between the base rule and the additional conditions, many acceptable combinations that balance the FPR and FNR can be found......, but no true optimum seems to exist. The performance of the best optimizations and the original algorithm are similar. Therefore, it should be possible to choose new coefficient values for jury populations in other cultures and contexts logically and empirically without a full optimization as long...

Ranking Fragment Ions Based on Outlier Detection for Improved Label-Free Quantification in Data-Independent Acquisition LC-MS/MS

Science.gov (United States)

Bilbao, Aivett; Zhang, Ying; Varesio, Emmanuel; Luban, Jeremy; Strambio-De-Castillia, Caterina; Lisacek, Frédérique; Hopfgartner, Gérard

2016-01-01

Data-independent acquisition LC-MS/MS techniques complement supervised methods for peptide quantification. However, due to the wide precursor isolation windows, these techniques are prone to interference at the fragment ion level, which in turn is detrimental for accurate quantification. The “non-outlier fragment ion” (NOFI) ranking algorithm has been developed to assign low priority to fragment ions affected by interference. By using the optimal subset of high priority fragment ions these interfered fragment ions are effectively excluded from quantification. NOFI represents each fragment ion as a vector of four dimensions related to chromatographic and MS fragmentation attributes and applies multivariate outlier detection techniques. Benchmarking conducted on a well-defined quantitative dataset (i.e. the SWATH Gold Standard), indicates that NOFI on average is able to accurately quantify 11-25% more peptides than the commonly used Top-N library intensity ranking method. The sum of the area of the Top3-5 NOFIs produces similar coefficients of variation as compared to the library intensity method but with more accurate quantification results. On a biologically relevant human dendritic cell digest dataset, NOFI properly assigns low priority ranks to 85% of annotated interferences, resulting in sensitivity values between 0.92 and 0.80 against 0.76 for the Spectronaut interference detection algorithm. PMID:26412574

Epidemiology of road traffic injury patients presenting to a tertiary hospital in Hyderabad, India.

Science.gov (United States)

Howley, Isaac W; Gupta, Shivam; Tetali, Shailaja; Josyula, Lakshmi K; Wadhwaniya, Shirin; Gururaj, Gopalkrishna; Rao, Mohan; Hyder, Adnan A

2017-12-01

Road traffic injuries kill more people in India than in any other country in the world, and these numbers are rising with increasing population density and motorization. Official statistics regarding road traffic injuries are likely subject to underreporting. This study presents results of a surveillance program based at a public tertiary hospital in Hyderabad, India. All consenting patients who presented to the casualty ward after a road traffic injury over a 9-month period were enrolled. Interviews were performed and data abstracted from clinical records by trained research assistants. Data included demographics, injury characteristics, risk factors, safety behaviors, and outcomes. A total of 5,298 patients were enrolled; their mean age was 32.4 years (standard deviation 13.8) and 87.3% were men; 58.2% of patients were injured while riding a motorcycle or scooter, 22.5% were pedestrians, and 9.2% used motorized rickshaws. The most frequent collision type was skid or rollover (40.9%). Male victims were younger than female victims and were overrepresented among motorized 2-wheeler users. Patients were most frequently injured from 1600 to 2400. A total of 27.3% of patients were admitted. Hospital mortality was 5.3%, and 48.2% of deaths were among motorized 2-wheeler users. This is one of the few prospective, hospital-based studies of road traffic injury epidemiology in India. The patient population in this study was similar to prior hospital-based studies. When compared to government surveillance systems, this study showed motorized 2-wheeler users to be more frequently represented among the overall population and among fatalities. Further research should be done to develop interventions to decrease mortality associated with 2-wheeled vehicles in India. Copyright © 2017. Published by Elsevier Inc.

Utilization of over the counter medication among pregnant women; a cross-sectional study conducted at Isra University Hospital, Hyderabad.

Science.gov (United States)

Bohio, Rabail; Brohi, Zahida Perveen; Bohio, Farrukh

2016-01-01

To determine the frequency of use of over-the-counter medication among pregnant women, types of medicines, source of information and reason to opts for self-medication. The descriptive cross-sectional study was conducted at Isra University Hospital, Hyderabad, Pakistan, from April 14 to October 14, 2014, and comprised pregnant women who were interviewed face to face. Data was collected on a proforma comprising demographic data, practice of using over-the-counter medications before and during pregnancy, type of medicines, illnesses, knowledge about the medicines, source of recommendation and reason for practicing it. Data was analysed on SPSS 16. The mean age of 351 patients in the study was 26.19±4.82 years (range: 18-45 years).The mean gestational age was 26.28±10.42. Overall, 223(63.5%) patients were using over-the-counter drugs before pregnancy; 128(36.5%) had used them in previous pregnancy; and 133(37.9%) were using them during the current pregnancy. Most common medication used was acetaminophen 58(43.6%), headache was the most common illness 80(60.2%). A total of 103(77.4%) had no knowledge about the medicines. A significant number of pregnant women indulged in the practice of using over-the-counter medication.

Metallurgical structure modification of UO{sub 2} pellet during sintering - experience at NFC, Hyderabad, India

Energy Technology Data Exchange (ETDEWEB)

Santra, N.; Sinha, T.K.; Singh, A.K.; Sairam, S.; Sheela, S.; Saibaba, N., E-mail: santra@nfc.gov.in [Nuclear Fuel Complex, Dept. of Atomic Energy, Hyderabad (India)

2013-07-01

Nuclear Fuel Complex (NFC), Department of Atomic Energy (DAE) produces UO{sub 2} fuel pellets by powder compaction, high temperature sintering followed by centreless wet grinding method from the stabilized UO{sub 2} powder generated through ADU-route. Enhancement of fuel burn up of the Indian PHWRs becomes very important in order to effectively utilize the fuel to the maximum extent inside the reactor. Burn up is mainly limited by increased fission gas release from the fuel during reactor operation. Without introducing much change in the design, rate of release of fission gas can be reduced through enlargement of UO{sub 2} grain size. In Powder Metallurgical (PM) route of fuel fabrication, trials were taken by doping various oxide powder additives like TiO{sub 2}, Al{sub 2}O{sub 3}, SiO{sub 2}, Nb{sub 2}O{sub 5} and Cr{sub 2}O{sub 3}. The dopant normally goes into the solid solution of parent matrix during sintering at 1700 {sup o}C and thus enhance the rate of diffusion. Aliovalant dopant can alter the defect chemistry of the parent material either by creating vacancy or interstitial. It is apparently understood that the combination of above mechanisms are responsible for structural modification of UO{sub 2}. Hence selection of dopant remains largely empirical. It has been observed at NFC Hyderabad that the Cr{sub 2}O{sub 3} is the most suitable for achieving average UO{sub 2} grain size of about 70 micron and 98%TD of the sintered pellet. The paper discusses about the various experimental trials, sintered densities, metallographic examination, effect of different quantities, analysis and result obtained thereof. (author)

Association of TCF7L2 gene polymorphisms with T2DM in the population of Hyderabad, India.

Directory of Open Access Journals (Sweden)

Kommoju Uma Jyothi

Full Text Available We attempt to evaluate the nature of association of TCF7L2 gene variants with T2DM, for the first time in the population of Hyderabad, which is considered to be diabetic capital of India. It is a case-control study of the three SNPs of TCF7L2, rs7903146, rs12255372 and rs11196205, genotyped on Sequenom Massarray platform, in a sample of 758 patients and 621 controls. The risk allele frequency of the three SNPs was found to be significantly higher in the T2DM cases than controls, implicating susceptibility for diabetes (p<0.01. The greatest risk of developing the disease was conferred by rs7903146. Further, the logistic regression of genotypes of each SNP under log additive model, and the haplotypes constituted by at least one of the three risk alleles also show significantly greater risk of developing T2DM when compared to the wild type haplotype. Further, BMI and WHR emerge as significant covariates with confounding effects. The strong association of the TCF7L2 SNPs with T2DM is consistent with the findings among other Indian and Non-Indian populations, suggesting universal phenomena of its association across ethnic groups globally, both within and outside the Indian subcontinent, albeit the functional relevance of these SNPs needs yet to be established.

Organochlorine pesticide contamination of ground water in the city of Hyderabad.

Science.gov (United States)

Shukla, Gangesh; Kumar, Anoop; Bhanti, Mayank; Joseph, P E; Taneja, Ajay

2006-02-01

Organochlorine pesticides are ubiquitous and persistent organic pollutants used widely throughout the world. Due to the extensive use in agriculture, organic environmental contaminants such as HCH, DDT along with other organochlorine pesticides are distributed globally by transport through air and water. The main aim of present study is to determine contamination levels of organochlorine pesticides in the ground water of Hyderabad City. Water samples were collected from 28 domestic well supplies of the city. For this study, random sampling technique was applied, all the samples were collected in high purity glass bottles and refrigerated at 4 degrees C until analysis. Solid Phase Extraction (SPE) is used for the extraction of organochlorine pesticide residues in water sample. The collected water samples were pre-filtered through a 0.45 microg glass fiber filter (Wattman GF/F) to remove particulate matter and were acidified with hydrochloric acid (6N) to pH 2.5. Methanol modifier (BDH, for pesticide residue analysis, 10 mL) was added to water sample for better extraction. SPE using pre-packed reversed phase octadecyl (C-18 bonded silica) contained in cartridges was used for sample preparation. Prior to the extraction, the C-18 bonded phase, which contains 500 mg of bonded phase, was washed with 20 mL methanol. The sample was mixed well and allowed to percolate through the cartridges with flow rate of 10-15 mL/min under vacuum. After sample extraction, suction continued for 15 min to dry the packing material and pesticides trapped in the C-18 bonded phases were eluted by passing 10 mL hexane and fraction was evaporated in a gentle steam of Nitrogen. In all samples pesticide residues were analyzed by GC (Chemito-8510) with Ni63 ECD detector. Helium was used as carrier gas and nitrogen was used as make up gas. The injection technique was split/split less. All the samples analyzed were found to be contaminated with four pesticides i.e. DDT, beta-Endosulfan, alpha

Evaluation of the expected moments algorithm and a multiple low-outlier test for flood frequency analysis at streamgaging stations in Arizona

Science.gov (United States)

Paretti, Nicholas V.; Kennedy, Jeffrey R.; Cohn, Timothy A.

2014-01-01

Flooding is among the costliest natural disasters in terms of loss of life and property in Arizona, which is why the accurate estimation of flood frequency and magnitude is crucial for proper structural design and accurate floodplain mapping. Current guidelines for flood frequency analysis in the United States are described in Bulletin 17B (B17B), yet since B17B’s publication in 1982 (Interagency Advisory Committee on Water Data, 1982), several improvements have been proposed as updates for future guidelines. Two proposed updates are the Expected Moments Algorithm (EMA) to accommodate historical and censored data, and a generalized multiple Grubbs-Beck (MGB) low-outlier test. The current guidelines use a standard Grubbs-Beck (GB) method to identify low outliers, changing the determination of the moment estimators because B17B uses a conditional probability adjustment to handle low outliers while EMA censors the low outliers. B17B and EMA estimates are identical if no historical information or censored or low outliers are present in the peak-flow data. EMA with MGB (EMA-MGB) test was compared to the standard B17B (B17B-GB) method for flood frequency analysis at 328 streamgaging stations in Arizona. The methods were compared using the relative percent difference (RPD) between annual exceedance probabilities (AEPs), goodness-of-fit assessments, random resampling procedures, and Monte Carlo simulations. The AEPs were calculated and compared using both station skew and weighted skew. Streamgaging stations were classified by U.S. Geological Survey (USGS) National Water Information System (NWIS) qualification codes, used to denote historical and censored peak-flow data, to better understand the effect that nonstandard flood information has on the flood frequency analysis for each method. Streamgaging stations were also grouped according to geographic flood regions and analyzed separately to better understand regional differences caused by physiography and climate. The B

Studies on aerosol optical properties over urban and semi-urban environments of Hyderabad and Anantapur

International Nuclear Information System (INIS)

Lata, K.M.; Badarinath, K.V.S.; Rao, T.V. Ramakrishna; Reddy, R.R.; Ahammed, Y. Nazeer; Gopal, K. Rama; Azeem, P. Abdul

2003-01-01

Aerosols in the troposphere exert an important influence on global climate and the environment through scattering, transmission and absorption of radiation as well as acting as nuclei for cloud formation. Atmospheric aerosol particles influence the earth's radiation balance directly by scattering of infrared energy and indirectly by modifying the properties of clouds through microphysical processes. The present study addresses visibility, radiative forcing, size distribution and attenuation of aerosols over the period from January to May, 2001 for urban and semi-urban regions of Hyderabad and Anantapur. High aerosol loading has been observed over urban environment compared to semi-urban environment. Aerosol optical depth values increased from January to April and then decreased during May over both urban and semi-urban regions. Over urban region, visibility decreased from January to April and increased during May. Similar trend has been observed over semi-urban region with relatively higher values of visibility. Radiative forcing estimated using aerosol optical depth values increased from January to April and then decreased during the month of May over urban and semi-urban areas. High visibility and low radiative forcing has been noticed over semi-urban area due to less aerosol loading. Wavelength exponent and turbidity coefficient registered high values over urban environment compared to semi-urban environment. Attenuation coefficient showed high values over urban region compared to semi-urban region. It reveals that semi-urban environment receives high solar flux than urban environment. Using 10 channel quartz crystal microbalance, measurements of total mass concentration and mass size distribution of near surface aerosols has been made over semi-urban environment and compared with size distribution derived from inversion methods based on aerosol optical depth variation with wavelength. The sensitivity of constrained linear inversions for inferring columnar

Autoimmune hepatitis in a teenage boy: 'overlap' or 'outlier' syndrome--dilemma for internists.

Science.gov (United States)

Talukdar, Arunansu; Khanra, Dibbendhu; Mukherjee, Kabita; Saha, Manjari

2013-02-08

An 18-year-old boy presented with upper gastrointestinal bleeding and jaundice. Investigations revealed coarse hepatomegaly, splenomegaly and advanced oesophageal varices. Blood reports showed marked rise of alkaline phosphatase and more than twofold rise of transaminases and IgG. Liver histology was suggestive of piecemeal necrosis, interphase hepatitis and bile duct proliferation. Antinuclear antibody was positive in high titre along with positive antismooth muscle antibody and antimitochondrial antibody. The patient was positive for human leukocyte antigen DR3 type. Although an 'overlap' syndrome exists between autoimmune hepatitis (AIH) and primary biliary cirrhosis (PBC), a cholestatic variant of AIH, a rare 'outlier' syndrome could not be excluded in our case. Moreover, 'the chicken or the egg', AIH or PBC, the dilemma for the internists continued. The patient was put on steroid and ursodeoxycholic acid with unsatisfactory response. The existing international criteria for diagnosis of AIH are not generous enough to accommodate its variant forms.

Fermi–Dirac Statistics

Indian Academy of Sciences (India)

Subhash Chaturvedi1 Shyamal Biswas2. School of Physics University of Hyderabad C R Rao Road, Gachibowli Hyderabad 500 046, India. University of Hyderabad C R Rao Road, Gachibowli Hyderabad 500 046, India. Resonance – Journal of Science Education. Current Issue : Vol. 23, Issue 4 · Current Issue Volume 23 ...

Examination of pulsed eddy current for inspection of second layer aircraft wing lap-joint structures using outlier detection methods

Energy Technology Data Exchange (ETDEWEB)

Butt, D.M., E-mail: Dennis.Butt@forces.gc.ca [Royal Military College of Canada, Dept. of Chemistry and Chemical Engineering, Kingston, Ontario (Canada); Underhill, P.R.; Krause, T.W., E-mail: Thomas.Krause@rmc.ca [Royal Military College of Canada, Dept. of Physics, Kingston, Ontario (Canada)

2016-09-15

Ageing aircraft are susceptible to fatigue cracks at bolt hole locations in multi-layer aluminum wing lap-joints due to cyclic loading conditions experienced during typical aircraft operation, Current inspection techniques require removal of fasteners to permit inspection of the second layer from within the bolt hole. Inspection from the top layer without fastener removal is desirable in order to minimize aircraft downtime while reducing the risk of collateral damage. The ability to detect second layer cracks without fastener removal has been demonstrated using a pulsed eddy current (PEC) technique. The technique utilizes a breakdown of the measured signal response into its principal components, each of which is multiplied by a representative factor known as a score. The reduced data set of scores, which represent the measured signal, are examined for outliers using cluster analysis methods in order to detect the presence of defects. However, the cluster analysis methodology is limited by the fact that a number of representative signals, obtained from fasteners where defects are not present, are required in order to perform classification of the data. Alternatively, blind outlier detection can be achieved without having to obtain representative defect-free signals, by using a modified smallest half-volume (MSHV) approach. Results obtained using this approach suggest that self-calibrating blind detection of cyclic fatigue cracks in second layer wing structures in the presence of ferrous fasteners is possible without prior knowledge of the sample under test and without the use of costly calibration standards. (author)

Examination of pulsed eddy current for inspection of second layer aircraft wing lap-joint structures using outlier detection methods

International Nuclear Information System (INIS)

Butt, D.M.; Underhill, P.R.; Krause, T.W.

2016-01-01

Ageing aircraft are susceptible to fatigue cracks at bolt hole locations in multi-layer aluminum wing lap-joints due to cyclic loading conditions experienced during typical aircraft operation, Current inspection techniques require removal of fasteners to permit inspection of the second layer from within the bolt hole. Inspection from the top layer without fastener removal is desirable in order to minimize aircraft downtime while reducing the risk of collateral damage. The ability to detect second layer cracks without fastener removal has been demonstrated using a pulsed eddy current (PEC) technique. The technique utilizes a breakdown of the measured signal response into its principal components, each of which is multiplied by a representative factor known as a score. The reduced data set of scores, which represent the measured signal, are examined for outliers using cluster analysis methods in order to detect the presence of defects. However, the cluster analysis methodology is limited by the fact that a number of representative signals, obtained from fasteners where defects are not present, are required in order to perform classification of the data. Alternatively, blind outlier detection can be achieved without having to obtain representative defect-free signals, by using a modified smallest half-volume (MSHV) approach. Results obtained using this approach suggest that self-calibrating blind detection of cyclic fatigue cracks in second layer wing structures in the presence of ferrous fasteners is possible without prior knowledge of the sample under test and without the use of costly calibration standards. (author)

Robust motion correction and outlier rejection of in vivo functional MR images of the fetal brain and placenta during maternal hyperoxia

OpenAIRE

You, Wonsang; Serag, Ahmed; Evangelou, Iordanis E.; Andescavage, Nickie; Limperopoulos, Catherine

2017-01-01

Subject motion is a major challenge in functional magnetic resonance imaging studies (fMRI) of the fetal brain and placenta during maternal hyperoxia. We propose a motion correction and volume outlier rejection method for the correction of severe motion artifacts in both fetal brain and placenta. The method is optimized to the experimental design by processing different phases of acquisition separately. It also automatically excludes high-motion volumes and all the missing data are regressed ...

Robust motion correction and outlier rejection of in vivo functional MR images of the fetal brain and placenta during maternal hyperoxia

OpenAIRE

You, Wonsang; Serag, Ahmed; Evangelou, Iordanis E.; Andescavage, Nickie; Limperopoulos, Catherine

2015-01-01

Subject motion is a major challenge in functional magnetic resonance imaging studies (fMRI) of the fetal brain and placenta during maternal hyperoxia. We propose a motion correction and volume outlier rejection method for the correction of severe motion artifacts in both fetal brain and placenta. The method is optimized to the experimental design by processing different phases of acquisition separately. It also automatically excludes high-motion volumes and all the missing data are regressed ...

ACKNOWLEDGEMENTS

Indian Academy of Sciences (India)

covers1

. Dipankar Nandi, Bangalore. Vidyanand Nanjundiah, Bangalore. Sankar Narayanan, Hyderabad. Laxmi Charan Padhy, Mumbai. Gopal Pande, Hyderabad. H N Pandey, Nirjuli. Ashwani Pareek, New Delhi. Veena K Parnaik, Hyderabad.

Outlier Removal in Model-Based Missing Value Imputation for Medical Datasets

Directory of Open Access Journals (Sweden)

Min-Wei Huang

2018-01-01

Full Text Available Many real-world medical datasets contain some proportion of missing (attribute values. In general, missing value imputation can be performed to solve this problem, which is to provide estimations for the missing values by a reasoning process based on the (complete observed data. However, if the observed data contain some noisy information or outliers, the estimations of the missing values may not be reliable or may even be quite different from the real values. The aim of this paper is to examine whether a combination of instance selection from the observed data and missing value imputation offers better performance than performing missing value imputation alone. In particular, three instance selection algorithms, DROP3, GA, and IB3, and three imputation algorithms, KNNI, MLP, and SVM, are used in order to find out the best combination. The experimental results show that that performing instance selection can have a positive impact on missing value imputation over the numerical data type of medical datasets, and specific combinations of instance selection and imputation methods can improve the imputation results over the mixed data type of medical datasets. However, instance selection does not have a definitely positive impact on the imputation result for categorical medical datasets.

Evaluation of Impacts of Landuse Changes on Air Quality in Hyderabad Metropolis Using Remote Sensing and GIS - A Case Study from Indian Sub-Continent

Science.gov (United States)

Vuppala, P.; S. S, A.; Mareddy, A.

2004-12-01

Around the world cities in developing countries are rapidly growing as more and more people become urban dwellers resulting in increased level of air pollution caused by changes in transportation, energy production and industrial activities. Air quality is an issue of critical importance in view of the accumulating evidence showing the adverse effects of pollution on human health, agricultural crops, manmade environments and ecosystems. An integrated study for identification of appropriate sites for representative evaluation of air pollution, novel means of monitoring air quality, identifying the predominant sources of pollution, effective assessment of air quality and evaluation of different management strategies essential for the development of a healthy and livable region is carried out for Hyderabad metropolis in India using Remote sensing and Geographical Information System (GIS) based assessment tools. Correlation studies between the concentration level of pollutants in urban air and urban land use are also dealt with. Municipal Corporation of Hyderabad (MCH) is divided into eleven planning zones out of which the present study area i.e. Zone I & IIA comprises of industrial, highly commercial and densely populated areas, apart from medium and sparse residential areas making it environmentally sensitive. Sampling locations were identified based on the land use/ land cover of the region and air samples were collected from areas having varying land use patterns using a high volume air sampler. The samples were then analyzed for the presence of Sulphur oxides(SO--x), Oxides of Nitrogen(NO--x), Total Suspended Particulate Matter(TSPM) and Respirable Suspended Particulate Matter(RSPM) using standard protocols and maps showing spatial distribution of SOx, NO--x, TSPM & RSPM were prepared using curve fitting technique of Arc/Info & ArcView GIS software. Air Quality Index (AQI), indicating the overall quality of air and extent of pollution is also calculated, based on

On damage detection in wind turbine gearboxes using outlier analysis

Science.gov (United States)

Antoniadou, Ifigeneia; Manson, Graeme; Dervilis, Nikolaos; Staszewski, Wieslaw J.; Worden, Keith

2012-04-01

The proportion of worldwide installed wind power in power systems increases over the years as a result of the steadily growing interest in renewable energy sources. Still, the advantages offered by the use of wind power are overshadowed by the high operational and maintenance costs, resulting in the low competitiveness of wind power in the energy market. In order to reduce the costs of corrective maintenance, the application of condition monitoring to gearboxes becomes highly important, since gearboxes are among the wind turbine components with the most frequent failure observations. While condition monitoring of gearboxes in general is common practice, with various methods having been developed over the last few decades, wind turbine gearbox condition monitoring faces a major challenge: the detection of faults under the time-varying load conditions prevailing in wind turbine systems. Classical time and frequency domain methods fail to detect faults under variable load conditions, due to the temporary effect that these faults have on vibration signals. This paper uses the statistical discipline of outlier analysis for the damage detection of gearbox tooth faults. A simplified two-degree-of-freedom gearbox model considering nonlinear backlash, time-periodic mesh stiffness and static transmission error, simulates the vibration signals to be analysed. Local stiffness reduction is used for the simulation of tooth faults and statistical processes determine the existence of intermittencies. The lowest level of fault detection, the threshold value, is considered and the Mahalanobis squared-distance is calculated for the novelty detection problem.

{3+}$ substituted MgCuMn ferrites synthesized by microwave ...

Indian Academy of Sciences (India)

Author Affiliations. T RAMESH1 S R MURTHY2. Department of Physics, BVRIT Hyderabad College of Engineering for Women, Hyderabad 500 090, India; Department of Physics, Osmania University, Hyderabad 500 007, India ...

When the Plus Sign is a Negative: Challenging and Reinforcing Embodied Stigmas Through Outliers and Counter-Narratives.

Science.gov (United States)

Lippert, Alexandra

2017-11-30

When individuals become aware of their stigma, they attempt to manage their identity through discourses that both challenge and reinforce power. Identity management is fraught with tensions between the desire to fit normative social constructions and counter the same discourse. This essay explores identity management in the midst of the embodied stigmas concerning unplanned pregnancy during college and raising a biracial son. In doing so, this essay points to the difference between outlier narratives and counter-narratives. The author encourages health communication scholars to explore conditions under which storytelling moves beyond the personal to the political. Emancipatory intent does not guarantee emancipatory outcomes. Storytelling can function therapeutically for individuals while failing to redress forces that constrain human potential and agency.

Portraying the Expression Landscapes of B-CellLymphoma-Intuitive Detection of Outlier Samples and of Molecular Subtypes

Directory of Open Access Journals (Sweden)

Lydia Hopp

2013-12-01

Full Text Available We present an analytic framework based on Self-Organizing Map (SOM machine learning to study large scale patient data sets. The potency of the approach is demonstrated in a case study using gene expression data of more than 200 mature aggressive B-cell lymphoma patients. The method portrays each sample with individual resolution, characterizes the subtypes, disentangles the expression patterns into distinct modules, extracts their functional context using enrichment techniques and enables investigation of the similarity relations between the samples. The method also allows to detect and to correct outliers caused by contaminations. Based on our analysis, we propose a refined classification of B-cell Lymphoma into four molecular subtypes which are characterized by differential functional and clinical characteristics.

Prevalence of Pulmonary Tuberculosis among Household Contacts in Hyderabad, Sindh: Active Contact Tracing in Children with Tuberculosis

International Nuclear Information System (INIS)

Sheikh, M.A.; Shah, S.A.A.

2017-01-01

Background: Tuberculosis (TB) in children is clearly linked to TB in adults therefore active household contact tracing is an important method of early diagnosis and treatment particularly in high-TB-burden countries. Objectives: To estimate the prevalence of TB among household contacts of children suffering from tuberculosis using active contact tracing and linking them to TB program for treatment. Subjects and Methods: A total of 125 children suffering from active tuberculosis (index cases)aged 12 years or less were randomly selected from the outpatient department of a tertiary care hospital of Hyderabad. Using their home address, all house hold members of the index cases (sharing one kitchen) were identified. The households were visited by a team including a doctor and the supported staff and were screened for TB using history, physical examination, sputum for AFB and X-ray of chest. Clinical suspects were divided in to two populations, equal to or less than 12 years of age and greater than this age. All suspected cases were brought to outpatient's department of the hospital where children were examined and diagnosed by pediatrician and adults were examined by the pulmonologist. Results: There were 125 children and 1365 household members. Prevalence of active TB in adult household contacts was 8.1 percent and among children was 5.7 percent. Mother, father, grand parents or siblings were the source of disease spread in children. Family history of TB was present in 95 percent (pulmonary 78 percent, extra-pulmonary 22 percent). Conclusion: Tuberculosis in children is mostly spreading from household member hence deeply required to undertake active contact tracing in each new case that is diagnosed or being treated. Policy message: National and Provincial TB programs should advocate and undertake active screening of all household contacts of all TB cases. (author)

An approach to the analysis of SDSS spectroscopic outliers based on self-organizing maps. Designing the outlier analysis software package for the next Gaia survey

Science.gov (United States)

Fustes, D.; Manteiga, M.; Dafonte, C.; Arcay, B.; Ulla, A.; Smith, K.; Borrachero, R.; Sordo, R.

2013-11-01

Aims: A new method applied to the segmentation and further analysis of the outliers resulting from the classification of astronomical objects in large databases is discussed. The method is being used in the framework of the Gaia satellite Data Processing and Analysis Consortium (DPAC) activities to prepare automated software tools that will be used to derive basic astrophysical information that is to be included in final Gaia archive. Methods: Our algorithm has been tested by means of simulated Gaia spectrophotometry, which is based on SDSS observations and theoretical spectral libraries covering a wide sample of astronomical objects. Self-organizing maps networks are used to organize the information in clusters of objects, as homogeneously as possible according to their spectral energy distributions, and to project them onto a 2D grid where the data structure can be visualized. Results: We demonstrate the usefulness of the method by analyzing the spectra that were rejected by the SDSS spectroscopic classification pipeline and thus classified as "UNKNOWN". First, our method can help distinguish between astrophysical objects and instrumental artifacts. Additionally, the application of our algorithm to SDSS objects of unknown nature has allowed us to identify classes of objects with similar astrophysical natures. In addition, the method allows for the potential discovery of hundreds of new objects, such as white dwarfs and quasars. Therefore, the proposed method is shown to be very promising for data exploration and knowledge discovery in very large astronomical databases, such as the archive from the upcoming Gaia mission.

Self reported behavioral and emotional difficulties in relation to dentition status among school going children of Dilsukhnagar, Hyderabad, India.

Science.gov (United States)

Srilatha, Adepu; Doshi, Dolar; Reddy, Madupu Padma; Kulkarni, Suhas; Reddy, Bandari Srikanth

2016-01-01

Oral health has strong biological, psychological, and social projections, which influence the quality of life. Thus, developing a common vision and a comprehensive approach to address children's social, emotional, and behavioral health needs is an integral part of the child and adolescent's overall health. To assess and compare the behavior and emotional difficulties among 15-year-olds and to correlate it with their dentition status based on gender. Study Settings and Design: A cross-sectional questionnaire study among 15-year-old schoolgoing children in six private schools in Dilsukhnagar, Hyderabad, India. The behavior and emotional difficulties were assessed using self-reported Strengths and Difficulties Questionnaire (SDQ). The dentition status was recorded by the criteria given by the World Health Organization (WHO) in the Basic Oral Health Survey Assessment Form (1997). Independent Student's t-test was used for comparison among the variables. Correlation between scales of SDQ and dentition status was done using Karl Pearson's correlation coefficient method. Girls reported more emotional problems and good prosocial behavior and males had more conduct problems, hyperactivity, peer problems, and total difficulty problems. Total decayed-missing-filled teeth (DMFT) and decayed component were significantly and positively correlated with total difficulty, emotional symptom, and conduct problems scale while missing component was correlated with the hyperactivity scale and filled component with prosocial behavior. DMFT and its components showed an association with all scales of SDQ except for peer problem scale. Thus, the oral health of children was significantly influenced by behavioral and emotional difficulties; so, changes in the mental health status will affect the oral health of children.

Pramana – Journal of Physics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. Chandrasekher Mukku1 Swadesh M Mahajan2 Bindu A Bambah3. International Institute of Information Technology, Hyderabad 500 032, India; Institute of Fusion Studies, University of Texas, Austin, Texas 78712, USA; School of Physics, University of Hyderabad, Hyderabad 500 046, India ...

Mitochondrial DNA heritage of Cres Islanders--example of Croatian genetic outliers.

Science.gov (United States)

Jeran, Nina; Havas Augustin, Dubravka; Grahovac, Blaienka; Kapović, Miljenko; Metspalu, Ene; Villems, Richard; Rudan, Pavao

2009-12-01

Diversity of mitochondrial DNA (mtDNA) lineages of the Island of Cres was determined by high-resolution phylogenetic analysis on a sample of 119 adult unrelated individuals from eight settlements. The composition of mtDNA pool of this Island population is in contrast with other Croatian and European populations. The analysis revealed the highest frequency of haplogroup U (29.4%) with the predominance of one single lineage of subhaplogroup U2e (20.2%). Haplogroup H is the second most prevalent one with only 27.7%. Other very interesting features of contemporary Island population are extremely low frequency of haplogroup J (only 0.84%), and much higher frequency of haplogroup W (12.6%) comparing to other Croatian and European populations. Especially interesting finding is a strikingly higher frequency of haplogroup N1a (9.24%) presented with African/south Asian branch almost absent in Europeans, while its European sister-branch, proved to be highly prevalent among Neolithic farmers, is present in contemporary Europeans with only 0.2%. Haplotype analysis revealed that only five mtDNA lineages account for almost 50% of maternal genetic heritage of this island and they present supposed founder lineages. All presented findings confirm that genetic drift, especially founder effect, has played significant role in shaping genetic composition of the isolated population of the Island of Cres. Due to presented data contemporary population of Cres Island can be considered as genetic "outlier" among Croatian populations.

A quick method based on SIMPLISMA-KPLS for simultaneously selecting outlier samples and informative samples for model standardization in near infrared spectroscopy

Science.gov (United States)

Li, Li-Na; Ma, Chang-Ming; Chang, Ming; Zhang, Ren-Cheng

2017-12-01

A novel method based on SIMPLe-to-use Interactive Self-modeling Mixture Analysis (SIMPLISMA) and Kernel Partial Least Square (KPLS), named as SIMPLISMA-KPLS, is proposed in this paper for selection of outlier samples and informative samples simultaneously. It is a quick algorithm used to model standardization (or named as model transfer) in near infrared (NIR) spectroscopy. The NIR experiment data of the corn for analysis of the protein content is introduced to evaluate the proposed method. Piecewise direct standardization (PDS) is employed in model transfer. And the comparison of SIMPLISMA-PDS-KPLS and KS-PDS-KPLS is given in this research by discussion of the prediction accuracy of protein content and calculation speed of each algorithm. The conclusions include that SIMPLISMA-KPLS can be utilized as an alternative sample selection method for model transfer. Although it has similar accuracy to Kennard-Stone (KS), it is different from KS as it employs concentration information in selection program. This means that it ensures analyte information is involved in analysis, and the spectra (X) of the selected samples is interrelated with concentration (y). And it can be used for outlier sample elimination simultaneously by validation of calibration. According to the statistical data results of running time, it is clear that the sample selection process is more rapid when using KPLS. The quick algorithm of SIMPLISMA-KPLS is beneficial to improve the speed of online measurement using NIR spectroscopy.

Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

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Goovaerts Pierre

2004-07-01

Full Text Available Abstract Background Complete Spatial Randomness (CSR is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new

Assessment of Air Pollution and its Effects on Health of Workers of Steel Re-Rolling Mills in Hyderabad

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Altaf Alam Noonari

2016-04-01

Full Text Available The SRRMs (Steel Re-Rolling Mills are being releasing air pollutants in the environment. In order to evaluate their effect on the health of the workers, health and safety issues were analyzed by first measuring the concentrations of SO x (OIxides of Sulphur, NO x (Oxides of Nitrogen, CO (Carbon Monoxide and O2 (Oxygen produced in the three SRRMs located in SITE area Hyderabad. The mean concentration of SO x , NO x and CO were in the order of 0.35, 0.280, 6.333 ppm, respectively, whereas the mean concentration of O 2 was 203.53 thousand ppm. As per results, the concentration ofair pollutants, including SOx and NO x were significantly higher than to the NEQS (National Environmental Quality Standards and NAAQS (National Ambient Air Quality Standards. The concentration ofCO was lower than to the NAAQS, but higher than to the NEQs, while the concentration of O2 was slightly lower than to the standard value. The workers who were exposed to these air pollutants are being suffering from chronic diseases related to breathing and allergies. Moreover, labour staff was lifting heavy loads manually, which causes them to muscular and joint problems. In all the SRRMs under study, the electrical and mechanical equipments were used without any safety. The MSDS were not displayed on the workstations, the housekeeping was inadequate and most of the workers were performing their jobs without personal protective equipment. In addition to these, the other serious issues related to the occupational health and safety were an unhygienic supply of water, higher noise level, placement of explosive cylinders in the open atmosphere and unavailability of the first aid facilities in the Mill premises.

Self reported behavioral and emotional difficulties in relation to dentition status among school going children of Dilsukhnagar, Hyderabad, India

Directory of Open Access Journals (Sweden)

Adepu Srilatha

2016-01-01

Full Text Available Background: Oral health has strong biological, psychological, and social projections, which influence the quality of life. Thus, developing a common vision and a comprehensive approach to address children′s social, emotional, and behavioral health needs is an integral part of the child and adolescent′s overall health. Aim: To assess and compare the behavior and emotional difficulties among 15-year-olds and to correlate it with their dentition status based on gender. Study Settings and Design: A cross-sectional questionnaire study among 15-year-old schoolgoing children in six private schools in Dilsukhnagar, Hyderabad, India. Materials and Methods: The behavior and emotional difficulties were assessed using self-reported Strengths and Difficulties Questionnaire (SDQ. The dentition status was recorded by the criteria given by the World Health Organization (WHO in the Basic Oral Health Survey Assessment Form (1997. Statistical Analysis: Independent Student′s t-test was used for comparison among the variables. Correlation between scales of SDQ and dentition status was done using Karl Pearson′s correlation coefficient method. Results: Girls reported more emotional problems and good prosocial behavior and males had more conduct problems, hyperactivity, peer problems, and total difficulty problems. Total decayed-missing-filled teeth (DMFT and decayed component were significantly and positively correlated with total difficulty, emotional symptom, and conduct problems scale while missing component was correlated with the hyperactivity scale and filled component with prosocial behavior. Conclusion: DMFT and its components showed an association with all scales of SDQ except for peer problem scale. Thus, the oral health of children was significantly influenced by behavioral and emotional difficulties; so, changes in the mental health status will affect the oral health of children.

Outlier Loci Detect Intraspecific Biodiversity amongst Spring and Autumn Spawning Herring across Local Scales.

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Dorte Bekkevold

Full Text Available Herring, Clupea harengus, is one of the ecologically and commercially most important species in European northern seas, where two distinct ecotypes have been described based on spawning time; spring and autumn. To date, it is unknown if these spring and autumn spawning herring constitute genetically distinct units. We assessed levels of genetic divergence between spring and autumn spawning herring in the Baltic Sea using two types of DNA markers, microsatellites and Single Nucleotide Polymorphisms, and compared the results with data for autumn spawning North Sea herring. Temporally replicated analyses reveal clear genetic differences between ecotypes and hence support reproductive isolation. Loci showing non-neutral behaviour, so-called outlier loci, show convergence between autumn spawning herring from demographically disjoint populations, potentially reflecting selective processes associated with autumn spawning ecotypes. The abundance and exploitation of the two ecotypes have varied strongly over space and time in the Baltic Sea, where autumn spawners have faced strong depression for decades. The results therefore have practical implications by highlighting the need for specific management of these co-occurring ecotypes to meet requirements for sustainable exploitation and ensure optimal livelihood for coastal communities.

Organochlorine pesticides in surface soils from obsolete pesticide dumping ground in Hyderabad City, Pakistan: contamination levels and their potential for air-soil exchange.

Science.gov (United States)

Alamdar, Ambreen; Syed, Jabir Hussain; Malik, Riffat Naseem; Katsoyiannis, Athanasios; Liu, Junwen; Li, Jun; Zhang, Gan; Jones, Kevin C

2014-02-01

This study was conducted to examine organochlorine pesticides (OCPs) contamination levels in the surface soil and air samples together with air-soil exchange fluxes at an obsolete pesticide dumping ground and the associated areas from Hyderabad City, Pakistan. Among all the sampling sites, concentrations of OCPs in the soil and air samples were found highest in obsolete pesticide dumping ground, whereas dominant contaminants were dichlorodiphenyltrichloroethane (DDTs) (soil: 77-212,200 ng g(-1); air: 90,700 pg m(-3)) and hexachlorocyclohexane (HCHs) (soil: 43-4,090 ng g(-1); air: 97,400 pg m(-3)) followed by chlordane, heptachlor and hexachlorobenzene (HCB). OCPs diagnostic indicative ratios reflect historical use as well as fresh input in the study area. Moreover, the air and soil fugacity ratios (0.9-1.0) at the dumping ground reflecting a tendency towards net volatilization of OCPs, while at the other sampling sites, the fugacity ratios indicate in some cases deposition and in other cases volatilization. Elevated concentrations of DDTs and HCHs at pesticide dumping ground and its surroundings pose potential exposure risk to biological organisms, to the safety of agricultural products and to the human health. Our study thus emphasizes the need of spatio-temporal monitoring of OCPs at local and regional scale to assess and remediate the future adverse implications. © 2013.

DETECÇÃO DE OUTLIERS NO DESEMPENHO ECONÔMICO-FINANCEIRO DO SPORT CLUB CORINTHIANS PAULISTA NO PERÍODO 2008 A 2010

Directory of Open Access Journals (Sweden)

Marke Geisy da Silva Dantas

2011-12-01

Full Text Available Os ativos intangíveis permeiam o mercado de futebol onde os principais ativos das entidades futebolísticas são os contratos com os jogadores e os torcedores são considerados usuários importantes da informação contábil, uma vez que fornecem recursos para tais entidades. É dentro desse contexto que o estudo ganha relevância, visando analisar a presença de outliers nas contas do Sport Club Corinthians Paulista, referente aos anos de 2008 e 2009, quando o clube participou da Série B do Campeonato Brasileiro e quando foi efetivada a contratação de Ronaldo, respectivamente. No tocante aos procedimentos metodológicos, essa pesquisa se constitui de um estudo exploratório, demonstrando a utilização do teste de Grubbs para analisar o impacto dos ativos intangíveis sobre as contas do Corinthians, detectando anormalidades nos anos estudados. Os dados foram coletados em sites e artigos que tratavam sobre a mensuração e o enquadramento como ativo dos jogadores de futebol. Para o tratamento dos dados foi utilizada a planilha eletrônica MICROSOFT EXCEL®. Os resultados demonstraram um grande aumento percentual nas contas estudadas na comparação dos anos. Foram encontrados dois outliers em 2008 (Licenciamentos e franquias e Ativo Total, mas, em 2009 foram encontradas cinco contas que ultrapassaram a normalidade (“Licenciamentos e franquias”, “Patrocínio e publicidades”, “Arrecadação de jogos”, “Direitos de TV” e “Premiação em campeonatos”. Em 2010, só a conta “Direitos de TV”.

Principal component analysis applied to Fourier transform infrared spectroscopy for the design of calibration sets for glycerol prediction models in wine and for the detection and classification of outlier samples.

Science.gov (United States)

Nieuwoudt, Helene H; Prior, Bernard A; Pretorius, Isak S; Manley, Marena; Bauer, Florian F

2004-06-16

Principal component analysis (PCA) was used to identify the main sources of variation in the Fourier transform infrared (FT-IR) spectra of 329 wines of various styles. The FT-IR spectra were gathered using a specialized WineScan instrument. The main sources of variation included the reducing sugar and alcohol content of the samples, as well as the stage of fermentation and the maturation period of the wines. The implications of the variation between the different wine styles for the design of calibration models with accurate predictive abilities were investigated using glycerol calibration in wine as a model system. PCA enabled the identification and interpretation of samples that were poorly predicted by the calibration models, as well as the detection of individual samples in the sample set that had atypical spectra (i.e., outlier samples). The Soft Independent Modeling of Class Analogy (SIMCA) approach was used to establish a model for the classification of the outlier samples. A glycerol calibration for wine was developed (reducing sugar content 8% v/v) with satisfactory predictive ability (SEP = 0.40 g/L). The RPD value (ratio of the standard deviation of the data to the standard error of prediction) was 5.6, indicating that the calibration is suitable for quantification purposes. A calibration for glycerol in special late harvest and noble late harvest wines (RS 31-147 g/L, alcohol > 11.6% v/v) with a prediction error SECV = 0.65 g/L, was also established. This study yielded an analytical strategy that combined the careful design of calibration sets with measures that facilitated the early detection and interpretation of poorly predicted samples and outlier samples in a sample set. The strategy provided a powerful means of quality control, which is necessary for the generation of accurate prediction data and therefore for the successful implementation of FT-IR in the routine analytical laboratory.

Comparative Performance of Four Single Extreme Outlier Discordancy Tests from Monte Carlo Simulations

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Surendra P. Verma

2014-01-01

Full Text Available Using highly precise and accurate Monte Carlo simulations of 20,000,000 replications and 102 independent simulation experiments with extremely low simulation errors and total uncertainties, we evaluated the performance of four single outlier discordancy tests (Grubbs test N2, Dixon test N8, skewness test N14, and kurtosis test N15 for normal samples of sizes 5 to 20. Statistical contaminations of a single observation resulting from parameters called δ from ±0.1 up to ±20 for modeling the slippage of central tendency or ε from ±1.1 up to ±200 for slippage of dispersion, as well as no contamination (δ=0 and ε=±1, were simulated. Because of the use of precise and accurate random and normally distributed simulated data, very large replications, and a large number of independent experiments, this paper presents a novel approach for precise and accurate estimations of power functions of four popular discordancy tests and, therefore, should not be considered as a simple simulation exercise unrelated to probability and statistics. From both criteria of the Power of Test proposed by Hayes and Kinsella and the Test Performance Criterion of Barnett and Lewis, Dixon test N8 performs less well than the other three tests. The overall performance of these four tests could be summarized as N2≅N15>N14>N8.

Identification of unusual events in multichannel bridge monitoring data using wavelet transform and outlier analysis

Science.gov (United States)

Omenzetter, Piotr; Brownjohn, James M. W.; Moyo, Pilate

2003-08-01

Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure. However, converting large amount of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of static, hourly sampled strains recorded by a multi-sensor SHM system installed in a major bridge structure in Singapore and operating continuously for a long time. Such events may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. A method of outlier detection in multivariate data has been applied to the problem of finding and localizing sudden events in the strain data. For sharp discrimination of abrupt strain changes from slowly varying ones wavelet transform has been used. The proposed method has been successfully tested using known events recorded during construction of the bridge, and later effectively used for detection of anomalous post-construction events.

Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003-2012.

Science.gov (United States)

Khan, Diba; Rossen, Lauren M; Hamilton, Brady E; He, Yulei; Wei, Rong; Dienes, Erin

2017-06-01

Teen birth rates have evidenced a significant decline in the United States over the past few decades. Most of the states in the US have mirrored this national decline, though some reports have illustrated substantial variation in the magnitude of these decreases across the U.S. Importantly, geographic variation at the county level has largely not been explored. We used National Vital Statistics Births data and Hierarchical Bayesian space-time interaction models to produce smoothed estimates of teen birth rates at the county level from 2003-2012. Results indicate that teen birth rates show evidence of clustering, where hot and cold spots occur, and identify spatial outliers. Findings from this analysis may help inform efforts targeting the prevention efforts by illustrating how geographic patterns of teen birth rates have changed over the past decade and where clusters of high or low teen birth rates are evident. Published by Elsevier Ltd.

Detecting Outliers in Marathon Data by Means of the Andrews Plot

Science.gov (United States)

Stehlík, Milan; Wald, Helmut; Bielik, Viktor; Petrovič, Juraj

2011-09-01

For an optimal race performance, it is important, that the runner keeps steady pace during most of the time of the competition. First time runners or athletes without many competitions often experience an "blow out" after a few kilometers of the race. This could happen, because of strong emotional experiences or low control of running intensity. Competition pace of half marathon of the middle level recreational athletes is approximately 10 sec quicker than their training pace. If an athlete runs the first third of race (7 km) at a pace that is 20 sec quicker than is his capacity (trainability), he would experience an "blow out" in the last third of the race. This would be reflected by reducing the running intensity and inability to keep steady pace in the last kilometers of the race and in the final time as well. In sports science, there are many diagnostic methods ([3], [2], [6]) that are used for prediction of optimal race pace tempo and final time. Otherwise there is lacking practical evidence of diagnostics methods and its use in the field (competition, race). One of the conditions that needs to be carried out is that athletes have not only similar final times, but it is important that they keep constant pace as much as possible during whole race. For this reason it is very important to find outliers. Our experimental group consisted of 20 recreational trained athletes (mean age 32,6 years±8,9). Before the race the athletes were instructed to run on the basis of their subjective feeling and previous experience. The data (running pace of each kilometer, average and maximal heart rate of each kilometer) were collected by GPS-enabled personal trainer Forerunner 305.

Detection of outliers by neural network on the gas centrifuge experimental data of isotopic separation process; Aplicacao de redes neurais para deteccao de erros grosseiros em dados de processo de separacao de isotopos de uranio por ultracentrifugacao

Energy Technology Data Exchange (ETDEWEB)

Andrade, Monica de Carvalho Vasconcelos

2004-07-01

This work presents and discusses the neural network technique aiming at the detection of outliers on a set of gas centrifuge isotope separation experimental data. In order to evaluate the application of this new technique, the result obtained of the detection is compared to the result of the statistical analysis combined with the cluster analysis. This method for the detection of outliers presents a considerable potential in the field of data analysis and it is at the same time easier and faster to use and requests very less knowledge of the physics involved in the process. This work established a procedure for detecting experiments which are suspect to contain gross errors inside a data set where the usual techniques for identification of these errors cannot be applied or its use/demands an excessively long work. (author)

New associates | Announcements | Indian Academy of Sciences

Indian Academy of Sciences (India)

Sushmee Badhulika, Indian Institute of Technology, Hyderabad ... Sankar Chakma, Indian Institute of Science Education & Research, Bhopal Joydeep ... B Praveen Kumar, Indian National Centre for Ocean Information Services, Hyderabad

Journal of Chemical Sciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. N Navaneetha1 P A Nagarjun2 S Satyanarayana1. Department of Chemistry, Osmania University, Hyderabad 500 007; Department of Microbiology, Osmania University, Hyderabad 500 007 ...

81st Annual Meeting | Annual Meetings | Events | Indian Academy of ...

Indian Academy of Sciences (India)

Rama Kant, University of Delhi, Delhi ... Anunay Samanta, University of Hyderabad, Hyderabad ... Visible light communications: An emerging area in wireless ... List of Fellows and Honorary Fellow elected during 2017 (effective 2018).

Journal of Chemical Sciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

, Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru N. Jayaraman, Indian Institute of Science, Bengaluru K C Kumara Swamy, University of Hyderabad, Hyderabad J N Moorthy, Indian Institute of Technology, Kanpur

Nangia, Prof. Ashwini

Indian Academy of Sciences (India)

. Ashwini Ph.D. (Yale), FRSC, FNA, FNASc. Date of birth: 10 November 1960. Specialization: Crystal Engineering, Supramolecular Chemistry and Polymorphism Address: School of Chemistry, University of Hyderabad, Hyderabad 500 046, A.P.

New Fellows and Honorary Fellow

Indian Academy of Sciences (India)

SV Univ.), FNASc, FNA. Date of birth: 1 July 1957. Specialization: Environmental Microbiology, Biodegradation, Bioremediation Address: Department of Animal Biology, School of Life Sciences, University of Hyderabad, Hyderabad 500 046, A.P.

Periasamy, Prof. Mariappan

Indian Academy of Sciences (India)

D. (IISc), FNA. Date of birth: 6 October 1952. Specialization: Organometallics, Chiral Reagents, Organic Molecules, Solar Energy Harvesting Address: Emeritus Professor, School of Chemistry, University of Hyderabad, Hyderabad 500 046, A.P.

An alternative method to specify the degree of resonator stability

Indian Academy of Sciences (India)

*School of Physics, University of Hyderabad, Hyderabad 500 134, India. E-mail: ... Degree of optical stability; S parameter; misalignment tolerance. ... maximum value of the degree of stability corresponding to S = 100%, automatically.

Resonance – Journal of Science Education | Indian Academy of ...

Indian Academy of Sciences (India)

Author Affiliations. Bhaskar G Maiya1 G Hariprasad2 L Giribabu1. School of Chemistry, University of Hyderabad, Hyderabad 500 046, India. US Department of Veteran Affairs Medical Center, Columbia, MO (USA).

Journal of Chemical Sciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Journal of Chemical Sciences; Volume 129; Issue 6 ... Nitrogen rich compounds; high energy materials; density functional theory. ... India; School of Chemistry, University of Hyderabad, Hyderabad, Telengana 500 046, India ...

Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003–2012

Science.gov (United States)

Khan, Diba; Rossen, Lauren M.; Hamilton, Brady E.; He, Yulei; Wei, Rong; Dienes, Erin

2017-01-01

Teen birth rates have evidenced a significant decline in the United States over the past few decades. Most of the states in the US have mirrored this national decline, though some reports have illustrated substantial variation in the magnitude of these decreases across the U.S. Importantly, geographic variation at the county level has largely not been explored. We used National Vital Statistics Births data and Hierarchical Bayesian space-time interaction models to produce smoothed estimates of teen birth rates at the county level from 2003–2012. Results indicate that teen birth rates show evidence of clustering, where hot and cold spots occur, and identify spatial outliers. Findings from this analysis may help inform efforts targeting the prevention efforts by illustrating how geographic patterns of teen birth rates have changed over the past decade and where clusters of high or low teen birth rates are evident. PMID:28552189

Synthesis of new pyrano[2,3-c]carbazoles, pyrano[3,2-b]carbazoles ...

Indian Academy of Sciences (India)

nagarajan

b]carbazole derivatives via iodocyclization. T. Krishna Chaitanya and Rajagopal Nagarajan*. School of Chemistry, University of Hyderabad, Hyderabad-500046, India. E-mail: rnsc@uohyd.ernet.in. Table of contents page number. Spectra (. 1.

An alternative method to specify the degree of resonator stability

Indian Academy of Sciences (India)

Degree of optical stability; parameter; misalignment tolerance. ... The value of zero corresponds to marginally stable resonator and < 0 corresponds ... 452 013, India; School of Physics, University of Hyderabad, Hyderabad 500 134, India ...

Optimization of waste to energy routes through biochemical and thermochemical treatment options of municipal solid waste in Hyderabad, Pakistan

International Nuclear Information System (INIS)

Korai, Muhammad Safar; Mahar, Rasool Bux; Uqaili, Muhammad Aslam

2016-01-01

Highlights: • Existing practice of municipal solid waste management of Hyderabad city, Pakistan have been analyzed. • Development of scenarios on basis of nature of waste components for optimizing waste to energy route. • Analyzing the biochemical and thermochemical potential of MSW through various scenarios. • Evaluation of various treatment technologies under scenarios to optimize waste to energy route. - Abstract: Improper disposal of municipal solid waste (MSW) has created many environmental problems in Pakistan and the country is facing energy shortages as well. The present study evaluates the biochemical and thermochemical treatment options of MSW in order to address both the endemic environmental challenges and in part the energy shortage. According to the nature of waste components, a number of scenarios were developed to optimize the waste to energy (WTE) routes. The evaluation of treatment options has been performed by mathematical equations using the special characteristics of MSW. The power generation potential (PGP) of biochemical (anaerobic digestion) has been observed in the range of 5.9–11.3 kW/ton day under various scenarios. The PGP of Refuse Derived Fuel (RDF), Mass Burn Incinerator (MBI), Gasification/Pyrolysis (Gasi./Pyro.) and Plasma Arc Gasification (PAG) have been found to be in the range of 2.7–118.6 kW/ton day, 3.8–164.7 kW/ton day, 4.2–184.5 kW/ton day and 5.2–224 kW/ton day, respectively. The highest values of biochemical and all thermochemical technologies have been obtained through the use of scenarios including the putrescible components (PCs) of MSW such as food and yard wastes, and the non-biodegradable components (NBCs) of MSW such as plastic, rubber, leather, textile and wood respectively. Therefore, routes which include these components are the optimized WTE routes for maximum PGP by biochemical and thermochemical treatments of MSW. The findings of study lead to recommend that socio-economic and environmental

Synthesis of pyrano[2,3-c]carbazoles, pyrano[3,2-b]carbazoles and ...

Indian Academy of Sciences (India)

2,3-c]carbazoles, pyrano[3,2-b]carbazoles and furo[3,2-b]carbazole derivatives via iodocyclization. KRISHNA CHAITANYA TALLURI and RAJAGOPAL NAGARAJAN. ∗. School of Chemistry, University of Hyderabad, Hyderabad 500046, India.

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Indian Academy of Sciences (India)

... than at any time in the past, we are undergoing both environmental and societal change ... biology, and on the roles and actions of big international conservation NGOs. ... School of Chemistry, University of Hyderabad, Hyderabad 500046.

phosphine oxide

Indian Academy of Sciences (India)

School of Chemistry, University of Hyderabad, Gachibowli, Hyderabad 500 046, India e-mail: ... batteries is always in demand to replace the organic liquid electrolyte. Wright and ... by distillation under nitrogen atmosphere. The com- pounds ...

Characterization of Botrytis cinerea isolates from chickpea: DNA ...

African Journals Online (AJOL)

Administrator

2010-11-15

Nov 15, 2010 ... 2Department of Plant Sciences, University of Hyderabad, Hyderabad 500 046, India. ... similarity of the isolates varied from 14-44%, and the isolates were separated ..... application to human mitochondrial DNA restriction sites.

Principal components in the discrimination of outliers: A study in simulation sample data corrected by Pearson's and Yates´s chi-square distance

Directory of Open Access Journals (Sweden)

Manoel Vitor de Souza Veloso

2016-04-01

Full Text Available Current study employs Monte Carlo simulation in the building of a significance test to indicate the principal components that best discriminate against outliers. Different sample sizes were generated by multivariate normal distribution with different numbers of variables and correlation structures. Corrections by chi-square distance of Pearson´s and Yates's were provided for each sample size. Pearson´s correlation test showed the best performance. By increasing the number of variables, significance probabilities in favor of hypothesis H0 were reduced. So that the proposed method could be illustrated, a multivariate time series was applied with regard to sales volume rates in the state of Minas Gerais, obtained in different market segments.

National Statistical Commission and Indian Official Statistics

Indian Academy of Sciences (India)

Author Affiliations. T J Rao1. C. R. Rao Advanced Institute of Mathematics, Statistics and Computer Science (AIMSCS) University of Hyderabad Campus Central University Post Office, Prof. C. R. Rao Road Hyderabad 500 046, AP, India.

Effect of increasing lanthanum substitution and the sintering ...

Indian Academy of Sciences (India)

Administrator

University of Hyderabad, P.O. Central University, Hyderabad 500 046, India. MS received 27 ... sintering can cause problems in the stoichiometry of the final product owing to ..... Rambabu greatfully acknowledges the financial support from the ...

Pramana – Journal of Physics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. S N Kaul1 2 Anita Semwal1. School of Physics, University of Hyderabad, Central University P.O., Hyderabad 500 046, India; Departamento CITIMAC, Facultad de Ciencias, Universidad de Cantabria, 39005 Santander, Spain ...

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Indian Academy of Sciences (India)

School of Chemistry, University of Hyderabad, Central University (PO), Hyderabad ... Scheme 1. Synthesis of di(diindolylmethyl)carbazoles. Table 1. Synthesis of .... Chem. 47 87 142. 8. Jones R A 1992 Pyrroles, Part II (New York: Wiley). 9.

Exploiting the information content of hydrological ''outliers'' for goodness-of-fit testing

Directory of Open Access Journals (Sweden)

F. Laio

2010-10-01

Full Text Available Validation of probabilistic models based on goodness-of-fit tests is an essential step for the frequency analysis of extreme events. The outcome of standard testing techniques, however, is mainly determined by the behavior of the hypothetical model, F_X(x, in the central part of the distribution, while the behavior in the tails of the distribution, which is indeed very relevant in hydrological applications, is relatively unimportant for the results of the tests. The maximum-value test, originally proposed as a technique for outlier detection, is a suitable, but seldom applied, technique that addresses this problem. The test is specifically targeted to verify if the maximum (or minimum values in the sample are consistent with the hypothesis that the distribution F_X(x is the real parent distribution. The application of this test is hindered by the fact that the critical values for the test should be numerically obtained when the parameters of F_X(x are estimated on the same sample used for verification, which is the standard situation in hydrological applications. We propose here a simple, analytically explicit, technique to suitably account for this effect, based on the application of censored L-moments estimators of the parameters. We demonstrate, with an application that uses artificially generated samples, the superiority of this modified maximum-value test with respect to the standard version of the test. We also show that the test has comparable or larger power with respect to other goodness-of-fit tests (e.g., chi-squared test, Anderson-Darling test, Fung and Paul test, in particular when dealing with small samples (sample size lower than 20–25 and when the parent distribution is similar to the distribution being tested.

A positive deviance approach to early childhood obesity: cross-sectional characterization of positive outliers.

Science.gov (United States)

Foster, Byron Alexander; Farragher, Jill; Parker, Paige; Hale, Daniel E

2015-06-01

Positive deviance methodology has been applied in the developing world to address childhood malnutrition and has potential for application to childhood obesity in the United States. We hypothesized that among children at high-risk for obesity, evaluating normal weight children will enable identification of positive outlier behaviors and practices. In a community at high-risk for obesity, a cross-sectional mixed-methods analysis was done of normal weight, overweight, and obese children, classified by BMI percentile. Parents were interviewed using a semistructured format in regard to their children's general health, feeding and activity practices, and perceptions of weight. Interviews were conducted in 40 homes in the lower Rio Grande Valley in Texas with a largely Hispanic (87.5%) population. Demographics, including income, education, and food assistance use, did not vary between groups. Nearly all (93.8%) parents of normal weight children perceived their child to be lower than the median weight. Group differences were observed for reported juice and yogurt consumption. Differences in both emotional feeding behaviors and parents' internalization of reasons for healthy habits were identified as different between groups. We found subtle variations in reported feeding and activity practices by weight status among healthy children in a population at high risk for obesity. The behaviors and attitudes described were consistent with previous literature; however, the local strategies associated with a healthy weight are novel, potentially providing a basis for a specific intervention in this population.

Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

... Oryza sativa; indica rice; cDNA libraries; rice genome; drought tolerance. ... Putative functions were assigned at a stringency E value of 10-6 in BLASTN and ... School of Life Sciences, University of Hyderabad, Hyderabad 500 046, India ...

Comparison of cephalometric norms of pleasing faces with patients reported in the out patients department of orthodontic at liaquat university of medical and health sciences hyderabad/ jamshoro

International Nuclear Information System (INIS)

Nisa, Q.U.

2013-01-01

Objective: This was a cross sectional study aimed to analyze Cephalometric norms of patients reporting to outpatients department of Orthodontic Department Liaquat University of Medical and health sciences, Hyderabad / Jamshoro in comparison with the Caucasian norms. Methods: The study was carried out on true lateral cephalometric radiographs of 150 subjects (75 male, 75 female) between 18-28 years, with esthetically pleasing and harmonious faces, competent lips, class 1 molar relationship, with all permanent teeth present, no facial trauma and no history of previous orthodontic treatment. The mean, standard deviation and ranges of all measurements were compared with the norms established by Steiner. For all statistical evaluation was performed by SPSS 16.0 version software, the student t-test were performed to compare the sample with Steiner means. Results: several significant findings were notable in the result of the present study. The result of the present study sample showed retrusive mandible (p < 0.000), horizontal growth pattern, procline upper incisors (p < 0.000), decrease inter-incisal angle (p < 0.001) when compared with the Caucasian norms taken by Steiner. No significant findings were found between male and female in present study sample.Conclusion: There were no significant differences between the male and female Population cephalometric norms Even though, a careful analysis of cephalom norms of patients along with other diagnostic considerations before initiating orthodontic treatment for better stability. (author)

Much of the variation in breast pathology quality assurance data in the UK can be explained by the random order in which cases arrive at individual centres, but some true outliers do exist.

Science.gov (United States)

Cross, Simon S; Stephenson, Timothy J; Harrison, Robert F

2011-10-01

To investigate the role of random temporal order of patient arrival at screening centres in the variability seen in rates of node positivity and breast cancer grade between centres in the NHS Breast Screening Programme. Computer simulations were performed of the variation in node positivity and breast cancer grade with the random temporal arrival of patients at screening centres based on national UK audit data. Cumulative mean graphs of these data were plotted. Confidence intervals for the parameters were generated, using the binomial distribution. UK audit data were plotted on these control limit graphs. The results showed that much of the variability in the audit data could be accounted for by the effects of random order of arrival of cases at the screening centres. Confidence intervals of 99.7% identified true outliers in the data. Much of the variation in breast pathology quality assurance data in the UK can be explained by the random order in which cases arrive at individual centres. Control charts with confidence intervals of 99.7% plotted against the number of reported cases are useful tools for identification of true outliers. 2011 Blackwell Publishing Limited.

World wide web - A graphical approach

Digital Repository Service at National Institute of Oceanography (India)

Lakshminarayana, S.; Chavan, V.S.

stream_size 3 stream_content_type text/plain stream_name Internet_India_IEEE_Hyderabad_1997_21.pdf.txt stream_source_info Internet_India_IEEE_Hyderabad_1997_21.pdf.txt Content-Encoding ISO-8859-1 Content-Type text/plain; charset...

Dutta Gupta, Prof. Aparna

Indian Academy of Sciences (India)

Specialization: Insect Molecular Physiology, Integrated Insect Pest Management, Comparative Physiology, Endocrinology Address: Department of Animal Biology, School of Life Sciences, University of Hyderabad, Hyderabad 500 046, A.P.. Contact: Office: (040) 2313 4560. Residence: 78930 46218. Mobile: 93910 74729

Annotation and BAC/PAC localization of nonredundant ESTs from ...

Indian Academy of Sciences (India)

Unknown

2002-04-25

Apr 25, 2002 ... School of Life Sciences, University of Hyderabad, Hyderabad 500 046, India. Abstract ... Putative functions were assigned at a stringency E value of 10–6 in ... drought and salinity tolerance governed by multiple genes, as ...

Universal Linear Fit Identification: A Method Independent of Data, Outliers and Noise Distribution Model and Free of Missing or Removed Data Imputation.

Science.gov (United States)

Adikaram, K K L B; Hussein, M A; Effenberger, M; Becker, T

2015-01-01

Data processing requires a robust linear fit identification method. In this paper, we introduce a non-parametric robust linear fit identification method for time series. The method uses an indicator 2/n to identify linear fit, where n is number of terms in a series. The ratio Rmax of amax - amin and Sn - amin*n and that of Rmin of amax - amin and amax*n - Sn are always equal to 2/n, where amax is the maximum element, amin is the minimum element and Sn is the sum of all elements. If any series expected to follow y = c consists of data that do not agree with y = c form, Rmax > 2/n and Rmin > 2/n imply that the maximum and minimum elements, respectively, do not agree with linear fit. We define threshold values for outliers and noise detection as 2/n * (1 + k1) and 2/n * (1 + k2), respectively, where k1 > k2 and 0 ≤ k1 ≤ n/2 - 1. Given this relation and transformation technique, which transforms data into the form y = c, we show that removing all data that do not agree with linear fit is possible. Furthermore, the method is independent of the number of data points, missing data, removed data points and nature of distribution (Gaussian or non-Gaussian) of outliers, noise and clean data. These are major advantages over the existing linear fit methods. Since having a perfect linear relation between two variables in the real world is impossible, we used artificial data sets with extreme conditions to verify the method. The method detects the correct linear fit when the percentage of data agreeing with linear fit is less than 50%, and the deviation of data that do not agree with linear fit is very small, of the order of ±10-4%. The method results in incorrect detections only when numerical accuracy is insufficient in the calculation process.

Universal Linear Fit Identification: A Method Independent of Data, Outliers and Noise Distribution Model and Free of Missing or Removed Data Imputation.

Directory of Open Access Journals (Sweden)

K K L B Adikaram

Full Text Available Data processing requires a robust linear fit identification method. In this paper, we introduce a non-parametric robust linear fit identification method for time series. The method uses an indicator 2/n to identify linear fit, where n is number of terms in a series. The ratio Rmax of amax - amin and Sn - amin*n and that of Rmin of amax - amin and amax*n - Sn are always equal to 2/n, where amax is the maximum element, amin is the minimum element and Sn is the sum of all elements. If any series expected to follow y = c consists of data that do not agree with y = c form, Rmax > 2/n and Rmin > 2/n imply that the maximum and minimum elements, respectively, do not agree with linear fit. We define threshold values for outliers and noise detection as 2/n * (1 + k1 and 2/n * (1 + k2, respectively, where k1 > k2 and 0 ≤ k1 ≤ n/2 - 1. Given this relation and transformation technique, which transforms data into the form y = c, we show that removing all data that do not agree with linear fit is possible. Furthermore, the method is independent of the number of data points, missing data, removed data points and nature of distribution (Gaussian or non-Gaussian of outliers, noise and clean data. These are major advantages over the existing linear fit methods. Since having a perfect linear relation between two variables in the real world is impossible, we used artificial data sets with extreme conditions to verify the method. The method detects the correct linear fit when the percentage of data agreeing with linear fit is less than 50%, and the deviation of data that do not agree with linear fit is very small, of the order of ±10-4%. The method results in incorrect detections only when numerical accuracy is insufficient in the calculation process.

Kaul, Prof. Sharika Nandan

Indian Academy of Sciences (India)

Date of birth: 4 August 1949. Specialization: Condensed Matter Physics, Phase Transitions & Critical Phenomena, Disordered Systems Percolation and Magnetism & Magnetic Materials, Physics at Nanometer Length Scale Address: INSA Senior Scientist, School of Physics, University of Hyderabad, Hyderabad 500 046, ...

Polymerization behavior of butyl bis(hydroxymethyl)phosphine oxide ...

Indian Academy of Sciences (India)

lenovo

Polymerization behavior of butyl bis(hydroxymethyl)phosphine oxide: Phosphorus containing polyethers for. Li‒ion conductivities. Heeralal Vignesh Babu, Billakanti Srinivas and Krishnamurthi Muralidharan*. School of Chemistry, University of Hyderabad, Hyderabad - 500046, India. Table of Contents. TGA plots of SPE2.

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Indian Academy of Sciences (India)

Guthikonda Nagaraju, School of Physics, University of Hyderabad,. Hyderabad, India. Haldar Sudip Kumar, Lady Brabourne College, Kolkata, India. Jagtap B N, Bhabha Atomic Research Centre, Mumbai, India. Jain Jinesh, National Energy Technology Laboratory, Mississippi, USA. Jane Alam Mohammad, Aligarh Muslim ...

Biology Today symposium | Mid Year Meetings | Events | Indian ...

Indian Academy of Sciences (India)

11.15, D. P. KASBEKAR, Centre for Cellular and Molecular Biology, Hyderabad Neurospora abhors a transposon. 11.45, IMRAN SIDDIQI, Centre for Cellular and Molecular Biology, Hyderabad Meiotic chromosome organization. 12.15, VIDYANAND NANJUNDIAH, Indian Institute of Science, Bengaluru Social amoebae.

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Narendra Gajbhiye1 V Eswaran2 A K Saha1 Anoop Kumar3. Department of Mechanical Engineering, IIT Kanpur, Kanpur 208016, India; Department of Mechanical and Aerospace Engineering, IIT Hyderabad, Hyderabad 502205, India; Department of Mechanical Engineering, NIT Hamirpur, Hamirpur 177005, India ...

Muralidhar, Prof. Kambadur

Indian Academy of Sciences (India)

Date of birth: 25 December 1948. Specialization: Biochemistry, Endocrinology and Reproductive Biology Address: School of Life Sciences, University of Hyderabad, Hyderabad 500 046, A.P.. Contact: Mobile: 98109 27705. Email: kambadur2015@gmail.com, kambadurmurali2001@rediffmail.com. YouTube; Twitter ...

Journal of Biosciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. Rahul Kumar1 Ashima Khurana2. Repository of Tomato Genomics Resources, Department of Plant Sciences, School of Life Sciences, University of Hyderabad, Hyderabad 500 046, India; Zakir Husain Delhi College, Botany Department, University of Delhi, New Delhi 110 002, India ...

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. I A Pasha1 P S Moharir2 N Sudarshan Rao3. Shadan College of Engineering & Technology, Hyderabad 500 008, India; National Geophysical Research Institute, Hyderabad 500 007, India; Department of Electrical Communication Engineering, Villanova University, Villanova, PA 19111, USA ...

Resonance – Journal of Science Education | Indian Academy of ...

Indian Academy of Sciences (India)

Author Affiliations. K S Mallesh1 S Chaturvedi2 R Simon3 N Mukunda. Department of Studies in Physics University of Mysore Manasagangotri Mysore 570 006; School of Physics, University of Hyderabad, Hyderabad 500 046; The Institute of Mathematical Sciences, CIT Campus Chennai 600 113.

Quality assurance using outlier detection on an automatic segmentation method for the cerebellar peduncles

Science.gov (United States)

Li, Ke; Ye, Chuyang; Yang, Zhen; Carass, Aaron; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

Cerebellar peduncles (CPs) are white matter tracts connecting the cerebellum to other brain regions. Automatic segmentation methods of the CPs have been proposed for studying their structure and function. Usually the performance of these methods is evaluated by comparing segmentation results with manual delineations (ground truth). However, when a segmentation method is run on new data (for which no ground truth exists) it is highly desirable to efficiently detect and assess algorithm failures so that these cases can be excluded from scientific analysis. In this work, two outlier detection methods aimed to assess the performance of an automatic CP segmentation algorithm are presented. The first one is a univariate non-parametric method using a box-whisker plot. We first categorize automatic segmentation results of a dataset of diffusion tensor imaging (DTI) scans from 48 subjects as either a success or a failure. We then design three groups of features from the image data of nine categorized failures for failure detection. Results show that most of these features can efficiently detect the true failures. The second method—supervised classification—was employed on a larger DTI dataset of 249 manually categorized subjects. Four classifiers—linear discriminant analysis (LDA), logistic regression (LR), support vector machine (SVM), and random forest classification (RFC)—were trained using the designed features and evaluated using a leave-one-out cross validation. Results show that the LR performs worst among the four classifiers and the other three perform comparably, which demonstrates the feasibility of automatically detecting segmentation failures using classification methods.

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Indian Academy of Sciences (India)

of people are present in the audience. Eminently sensible. For the conservatively minded, who value etiquette and form, this book would be a useful t:'eference. Rajat Tandon, Department of Mathematics & Statis· tics, University of Hyderabad, Hyderabad 500 046, India,. Email: rtsm@uohycLemet.in. --------~---------~. 92.

Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. Gargi Meur1 K. Gaikwad2 S. R. Bhat2 S. Prakash2 P. B. Kirti1. Department of Plant Sciences, University of Hyderabad, Hyderabad 500 046, India; National Research Centre on Plant Biotechnology, Indian Agricultural Research Institute, New Delhi 110 012, India ...

supp1.doc

Indian Academy of Sciences (India)

Supporting Information. Salts and cocrystals of Theobromine and their phase transformations in water. PALASH SANPHUI and ASHWINI NANGIA*. School of Chemistry, University of Hyderabad, Prof. C. R. Rao Road, Gachibowli, Central University P.O., Hyderabad 500 046, India. Table S1. Hydrogen bonds in crystal ...

Resonance – Journal of Science Education | Indian Academy of ...

Indian Academy of Sciences (India)

Keywords. Quantum mechanics; EPR argument; local realism. Author Affiliations. S Chaturvedi1 N Mukunda2 R Simon3. School of Physics, University of Hyderabad, Hyderabad 500 046, India. Centre for High Energy Physics Indian Institute of Science Bangalore 560 012, India. Institute of Mathematical Sciences Chennai ...

Ricinus communis L. (castor bean) as a potential candidate for revegetating industrial waste contaminated sites in peri-urban Greater Hyderabad: remarks on seed oil.

Science.gov (United States)

Boda, Ravi Kiran; Majeti, Narasimha Vara Prasad; Suthari, Sateesh

2017-08-01

Ricinus communis L. (castor bean or castor oil plant) was found growing on metal-contaminated sites (4) of peri-urban Greater Hyderabad comprises of erstwhile industrial areas viz Bollaram, Patancheru, Bharatnagar, and Kattedan industrial areas. During 2013-2017, about 60 research papers have appeared focusing the role of castor bean in phytoremediation of co-contaminated soils, co-generation of biomaterials, and environmental cleanup, as bioenergy crop and sustainable development. The present study is focused on its use as a multipurpose phytoremediation crop for phytostabilization and revegetation of waste disposed peri-urban contaminated soils. To determine the plant tolerance level, metal accumulation, chlorophyll, protein, proline, lipid peroxidation, oil content, and soil properties were characterized. It was noticed that the castor plant and soils have high concentration of metals such as cadmium (Cd), lead (Pb), iron (Fe), manganese (Mn), and zinc (Zn). The soils have high phosphorous (P), adequate nitrogen (N), and low concentration of potassium (K). Iron (Fe) concentrations ranged from1672±50.91 to 2166±155.78 mg kg -1 in the soil. The trend of metal accumulation Fe>Zn>Mn>Pb>Cd was found in different plant parts at polluted sites. The translocation of Cd and Pb showed values more than one in industrial areas viz Bollaram, Kattedan, and Bharatnagar indicating the plants resistance to metal toxicity. Chlorophyll and protein content reduced while proline and malondialdehyde increased due to its tolerance level under metal exposure. The content of ricinoleic acid was higher, and the fatty acids composition of polluted areas was almost similar to that of the control area. Thus, R. communis L. can be employed for reclamation of heavy metal contaminated soils.

Outliers in American juvenile justice: the need for statutory reform in North Carolina and New York.

Science.gov (United States)

Tedeschi, Frank; Ford, Elizabeth

2015-05-01

There is a well-established and growing body of evidence from research that adolescents who commit crimes differ in many regards from their adult counterparts and are more susceptible to the negative effects of adjudication and incarceration in adult criminal justice systems. The age of criminal court jurisdiction in the United States has varied throughout history; yet, there are only two remaining states, New York and North Carolina, that continue to automatically charge 16 year olds as adults. This review traces the statutory history of juvenile justice in these two states with an emphasis on political and social factors that have contributed to their outlier status related to the age of criminal court jurisdiction. The neurobiological, psychological, and developmental aspects of the adolescent brain and personality, and how those issues relate both to a greater likelihood of rehabilitation in appropriate settings and to greater vulnerability in adult correctional facilities, are also reviewed. The importance of raising the age in New York and North Carolina not only lies in protecting incarcerated youths but also in preventing the associated stigma following release. Mental health practitioners are vital to the process of local and national juvenile justice reform. They can serve as experts on and advocates for appropriate mental health care and as experts on the adverse effects of the adult criminal justice system on adolescents.

compounds with N=N, C≡C or conjugated double-bonded systems

Indian Academy of Sciences (India)

Unusual products in the reactions of phosphorus(III) compounds with. N=N, C≡C or conjugated double-bonded systems. K C KUMARA SWAMY,* E BALARAMAN, M PHANI PAVAN, N N BHUVAN KUMAR,. K PRAVEEN KUMAR and N SATISH KUMAR. School of Chemistry, University of Hyderabad, Hyderabad 500 046.

Universal Linear Fit Identification: A Method Independent of Data, Outliers and Noise Distribution Model and Free of Missing or Removed Data Imputation

Science.gov (United States)

Adikaram, K. K. L. B.; Becker, T.

2015-01-01

Data processing requires a robust linear fit identification method. In this paper, we introduce a non-parametric robust linear fit identification method for time series. The method uses an indicator 2/n to identify linear fit, where n is number of terms in a series. The ratio R max of a max − a min and S n − a min *n and that of R min of a max − a min and a max *n − S n are always equal to 2/n, where a max is the maximum element, a min is the minimum element and S n is the sum of all elements. If any series expected to follow y = c consists of data that do not agree with y = c form, R max > 2/n and R min > 2/n imply that the maximum and minimum elements, respectively, do not agree with linear fit. We define threshold values for outliers and noise detection as 2/n * (1 + k 1 ) and 2/n * (1 + k 2 ), respectively, where k 1 > k 2 and 0 ≤ k 1 ≤ n/2 − 1. Given this relation and transformation technique, which transforms data into the form y = c, we show that removing all data that do not agree with linear fit is possible. Furthermore, the method is independent of the number of data points, missing data, removed data points and nature of distribution (Gaussian or non-Gaussian) of outliers, noise and clean data. These are major advantages over the existing linear fit methods. Since having a perfect linear relation between two variables in the real world is impossible, we used artificial data sets with extreme conditions to verify the method. The method detects the correct linear fit when the percentage of data agreeing with linear fit is less than 50%, and the deviation of data that do not agree with linear fit is very small, of the order of ±10−4%. The method results in incorrect detections only when numerical accuracy is insufficient in the calculation process. PMID:26571035

Assessment of drinking water quality using ICP-MS and microbiological methods in the Bholakpur area, Hyderabad, India.

Science.gov (United States)

Abdul, Rasheed M; Mutnuri, Lakshmi; Dattatreya, Patil J; Mohan, Dayal A

2012-03-01

A total of 16 people died and over 500 people were hospitalized due to diarrhoeal illness in the Bholakpur area of Hyderabad, India on 6th May 2009. A study was conducted with immediate effect to evaluate the quality of municipal tap water of the Bholakpur locality. The study consists of the determination of physico-chemical properties, trace metals, heavy metals, rare earth elements and microbiological quality of drinking water. The data showed the variation of the investigated parameters in samples as follows: pH 7.14 to 8.72, EC 455 to 769 μS/cm, TDS 303.51 to 515.23 ppm and DO 1.01 to 6.83 mg/L which are within WHO guidelines for drinking water quality. The water samples were analyzed for 27 elements (Li, Be, B, Na, Mg, Al, Si, K, Ca, V, Cr, Mn, Fe, Ni, Co, Cu, Zn, As, Se, Rb, Sr, Mo, Ag, Cd, Sb, Ba and Pb) using inductively coupled plasma-mass spectrometry (ICP-MS). The concentrations of Fe (0.12 to 1.13 mg/L), Pb (0.01 to 0.07 mg/L), Cu (0.01 to 0.19 mg/L), Ni (0.01 to 0.15 mg/L), Al (0.16 to 0.49 mg/L), and Na (38.36 to 68.69 mg/L) were obtained, which exceed the permissible limits of the World Health Organization (WHO) for drinking water quality guidelines. The remaining elements were within the permissible limits. The microbiological quality of water was tested using standard plate count, membrane filtration technique, thermotolerant coliform (TTC), and most probable number (MPN) methods. The total heterotrophic bacteria ranged from 1.0 × 10(5) to 18 × 10(7 )cfu/ml. Total viable bacteria in all the water samples were found to be too numerable to count and total number of coliform bacteria in all water samples were found to be of order of 1,100 to >2,400 MPN index/100 ml. TTC tested positive for coliform bacteria at 44.2°C. All the water samples of the study area exceeded the permissible counts of WHO and that (zero and minimal counts) of the control site (National Geophysical Research Institute) water samples. Excessively high colony numbers indicate

A duplicated coxI gene is associated with cytoplasmic male sterility ...

Indian Academy of Sciences (India)

In plants where male sterility broke down under high temperature during the later part of the growing season, the 2.4 kb coxI transcript was absent, which ... Institute, New Delhi 110012, India; Directorate of Oilseeds Research, Hyderabad, 500030, India; Department of Plant Sciences, University of Hyderabad, 500046, India ...

MutS: Recognition of DNA mismatches and initiation of repair

NARCIS (Netherlands)

G. Natrajan

2006-01-01

textabstractGanesh Natrajan was born on the 14th of April, 1973 in Alleppey, Kerala, India. In 1988, he completed his secondary schooling at the St. Anthony’s High School in Hyderabad, India. Upon completing his Master’s degree in Physics in 1996 at the University of Hyderabad, India, he enrolled

21st Annual Conference of Ramanujan Mathematical Society

Indian Academy of Sciences (India)

Paper Presentation: Those who want to present papers should send an abstract of the paper along with a hard copy of the paper so as to reach the Local Secretary, 21st Annual. Conference of Ramanujan Mathematical Society, Department of Mathematics and Statis- tics, University of Hyderabad, Hyderabad 500046 on or ...

Untitled

Indian Academy of Sciences (India)

Lakshminarayanan V 1969 2D schematic understanding system, B.Tech project report,. University of Hyderabad, Hyderabad. Lin WC, Pun J H 1978 Machine recognition and plotting of hand-sketched line figures. IEEE. Trans. Syst. Man Cybern. 8: 52-57. Lu H E, Wang PSP 1985 An improved fast parallel thinning algorithm ...

Journal of Biosciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. R Chakrabarty1 N Viswakarma1 S R Bhat1 P B Kirti2 B D Singh3 V L Chopra1. National Research Centre on Plant Biotechnology, Indian Agricultural Research Institute, New Delhi 110 012, India; Department of Plant Sciences, University of Hyderabad, Hyderabad 500 046, India; School of Biotechnology, ...

A User-Adaptive Algorithm for Activity Recognition Based on K-Means Clustering, Local Outlier Factor, and Multivariate Gaussian Distribution

Directory of Open Access Journals (Sweden)

Shizhen Zhao

2018-06-01

Full Text Available Mobile activity recognition is significant to the development of human-centric pervasive applications including elderly care, personalized recommendations, etc. Nevertheless, the distribution of inertial sensor data can be influenced to a great extent by varying users. This means that the performance of an activity recognition classifier trained by one user’s dataset will degenerate when transferred to others. In this study, we focus on building a personalized classifier to detect four categories of human activities: light intensity activity, moderate intensity activity, vigorous intensity activity, and fall. In order to solve the problem caused by different distributions of inertial sensor signals, a user-adaptive algorithm based on K-Means clustering, local outlier factor (LOF, and multivariate Gaussian distribution (MGD is proposed. To automatically cluster and annotate a specific user’s activity data, an improved K-Means algorithm with a novel initialization method is designed. By quantifying the samples’ informative degree in a labeled individual dataset, the most profitable samples can be selected for activity recognition model adaption. Through experiments, we conclude that our proposed models can adapt to new users with good recognition performance.

Effect of β−β′ fusion on metal ion complexation of porphycene

Indian Academy of Sciences (India)

School of Chemistry, University of Hyderabad, Hyderabad 500 046, India e-mail: ... plays a higher absorption cross-section in the red region making it a ..... for structures 2b in this study have been deposited in ... free of charge on application to CCDC, 12 Union Road, ... Teixidó J and Juarranz A 1996 Anti-Cancer Drug Des.

TrigDB for improving the reliability of the epicenter locations by considering the neighborhood station's trigger and cutting out of outliers in operation of Earthquake Early Warning System.

Science.gov (United States)

Chi, H. C.; Park, J. H.; Lim, I. S.; Seong, Y. J.

2016-12-01

TrigDB is initially developed for the discrimination of teleseismic-origin false alarm in the case with unreasonably associated triggers producing mis-located epicenters. We have applied TrigDB to the current EEWS(Earthquake Early Warning System) from 2014. During the early stage of testing EEWS from 2011, we adapted ElarmS from US Berkeley BSL to Korean seismic network and applied more than 5 years. We found out that the real-time testing results of EEWS in Korea showed that all events inside of seismic network with bigger than magnitude 3.0 were well detected. However, two events located at sea area gave false location results with magnitude over 4.0 due to the long period and relatively high amplitude signals related to the teleseismic waves or regional deep sources. These teleseismic-relevant false events were caused by logical co-relation during association procedure and the corresponding geometric distribution of associated stations is crescent-shaped. Seismic stations are not deployed uniformly, so the expected bias ratio varies with evaluated epicentral location. This ratio is calculated in advance and stored into database, called as TrigDB, for the discrimination of teleseismic-origin false alarm. We upgraded this method, so called `TrigDB back filling', updating location with supplementary association of stations comparing triggered times between sandwiched stations which was not associated previously based on predefined criteria such as travel-time. And we have tested a module to reject outlier trigger times by setting a criteria comparing statistical values(Sigma) to the triggered times. The criteria of cutting off the outlier is slightly slow to work until the number of stations more than 8, however, the result of location is very much improved.

Moving standard deviation and moving sum of outliers as quality tools for monitoring analytical precision.

Science.gov (United States)

Liu, Jiakai; Tan, Chin Hon; Badrick, Tony; Loh, Tze Ping

2018-02-01

An increase in analytical imprecision (expressed as CV a ) can introduce additional variability (i.e. noise) to the patient results, which poses a challenge to the optimal management of patients. Relatively little work has been done to address the need for continuous monitoring of analytical imprecision. Through numerical simulations, we describe the use of moving standard deviation (movSD) and a recently described moving sum of outlier (movSO) patient results as means for detecting increased analytical imprecision, and compare their performances against internal quality control (QC) and the average of normal (AoN) approaches. The power of detecting an increase in CV a is suboptimal under routine internal QC procedures. The AoN technique almost always had the highest average number of patient results affected before error detection (ANPed), indicating that it had generally the worst capability for detecting an increased CV a . On the other hand, the movSD and movSO approaches were able to detect an increased CV a at significantly lower ANPed, particularly for measurands that displayed a relatively small ratio of biological variation to CV a. CONCLUSION: The movSD and movSO approaches are effective in detecting an increase in CV a for high-risk measurands with small biological variation. Their performance is relatively poor when the biological variation is large. However, the clinical risks of an increase in analytical imprecision is attenuated for these measurands as an increased analytical imprecision will only add marginally to the total variation and less likely to impact on the clinical care. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

ROBUST: an interactive FORTRAN-77 package for exploratory data analysis using parametric, ROBUST and nonparametric location and scale estimates, data transformations, normality tests, and outlier assessment

Science.gov (United States)

Rock, N. M. S.

ROBUST calculates 53 statistics, plus significance levels for 6 hypothesis tests, on each of up to 52 variables. These together allow the following properties of the data distribution for each variable to be examined in detail: (1) Location. Three means (arithmetic, geometric, harmonic) are calculated, together with the midrange and 19 high-performance robust L-, M-, and W-estimates of location (combined, adaptive, trimmed estimates, etc.) (2) Scale. The standard deviation is calculated along with the H-spread/2 (≈ semi-interquartile range), the mean and median absolute deviations from both mean and median, and a biweight scale estimator. The 23 location and 6 scale estimators programmed cover all possible degrees of robustness. (3) Normality: Distributions are tested against the null hypothesis that they are normal, using the 3rd (√ h1) and 4th ( b 2) moments, Geary's ratio (mean deviation/standard deviation), Filliben's probability plot correlation coefficient, and a more robust test based on the biweight scale estimator. These statistics collectively are sensitive to most usual departures from normality. (4) Presence of outliers. The maximum and minimum values are assessed individually or jointly using Grubbs' maximum Studentized residuals, Harvey's and Dixon's criteria, and the Studentized range. For a single input variable, outliers can be either winsorized or eliminated and all estimates recalculated iteratively as desired. The following data-transformations also can be applied: linear, log 10, generalized Box Cox power (including log, reciprocal, and square root), exponentiation, and standardization. For more than one variable, all results are tabulated in a single run of ROBUST. Further options are incorporated to assess ratios (of two variables) as well as discrete variables, and be concerned with missing data. Cumulative S-plots (for assessing normality graphically) also can be generated. The mutual consistency or inconsistency of all these measures

Supplementary Information- JCS

Indian Academy of Sciences (India)

Nagarajan

School of Chemistry, University of Hyderabad,. Central University (P.O.), Hyderabad-500 046, INDIA. E-mail: rnsc@uohyd.ernet.in. Fax: 91-40-23012460. Table of Contents. Page number. Analytical data for compounds 3b– 3p. S2-S8. Analytical data for compounds 6a-6i. S8-S12. UV/vis titration spectra of 3f with DNA. S12.

Robust data reconciliation and outlier detection with swarm intelligence in a thermal reactor power calculation

Energy Technology Data Exchange (ETDEWEB)

Valdetaro, Eduardo Damianik, E-mail: valdtar@eletronuclear.gov.br [ELETRONUCLEAR - ELETROBRAS, Angra dos Reis, RJ (Brazil). Angra 2 Operating Dept.; Coordenacao dos Programas de Pos-Graduacao de Engenharia (PEN/COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Nuclear; Schirru, Roberto, E-mail: schirru@lmp.ufrj.br [Coordenacao dos Programas de Pos-Graduacao de Engenharia (PEN/COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Nuclear

2011-07-01

In Nuclear power plants, Data Reconciliation (DR) and Gross Errors Detection (GED) are techniques of increasing interest and are primarily used to keep mass and energy balance into account, which brings outcomes as a direct and indirect financial benefits. Data reconciliation is formulated by a constrained minimization problem, where the constraints correspond to energy and mass balance model. Statistical methods are used combined with the minimization of quadratic error form. Solving nonlinear optimization problem using conventional methods can be troublesome, because a multimodal function with differentiated solutions introduces some difficulties to search an optimal solution. Many techniques were developed to solve Data Reconciliation and Outlier Detection, some of them use, for example, Quadratic Programming, Lagrange Multipliers, Mixed-Integer Non Linear Programming and others use evolutionary algorithms like Genetic Algorithms (GA) and recently the use of the Particle Swarm Optimization (PSO) showed to be a potential tool as a global optimization algorithm when applied to data reconciliation. Robust Statistics is also increasing in interest and it is being used when measured data are contaminated by random errors and one can not assume the error is normally distributed, situation which reflects real problems situation. The aim of this work is to present a brief comparison between the classical data reconciliation technique and the robust data reconciliation and gross error detection with swarm intelligence procedure in calculating the thermal reactor power for a simplified heat circuit diagram of a steam turbine plant using real data obtained from Angra 2 Nuclear power plant. The main objective is to test the potential of the robust DR and GED method in a integrated framework using swarm intelligence and the three part redescending estimator of Hampel when applied to a real process condition. The results evaluate the potential use of the robust technique in

Robust data reconciliation and outlier detection with swarm intelligence in a thermal reactor power calculation

International Nuclear Information System (INIS)

Valdetaro, Eduardo Damianik; Coordenacao dos Programas de Pos-Graduacao de Engenharia; Schirru, Roberto

2011-01-01

In Nuclear power plants, Data Reconciliation (DR) and Gross Errors Detection (GED) are techniques of increasing interest and are primarily used to keep mass and energy balance into account, which brings outcomes as a direct and indirect financial benefits. Data reconciliation is formulated by a constrained minimization problem, where the constraints correspond to energy and mass balance model. Statistical methods are used combined with the minimization of quadratic error form. Solving nonlinear optimization problem using conventional methods can be troublesome, because a multimodal function with differentiated solutions introduces some difficulties to search an optimal solution. Many techniques were developed to solve Data Reconciliation and Outlier Detection, some of them use, for example, Quadratic Programming, Lagrange Multipliers, Mixed-Integer Non Linear Programming and others use evolutionary algorithms like Genetic Algorithms (GA) and recently the use of the Particle Swarm Optimization (PSO) showed to be a potential tool as a global optimization algorithm when applied to data reconciliation. Robust Statistics is also increasing in interest and it is being used when measured data are contaminated by random errors and one can not assume the error is normally distributed, situation which reflects real problems situation. The aim of this work is to present a brief comparison between the classical data reconciliation technique and the robust data reconciliation and gross error detection with swarm intelligence procedure in calculating the thermal reactor power for a simplified heat circuit diagram of a steam turbine plant using real data obtained from Angra 2 Nuclear power plant. The main objective is to test the potential of the robust DR and GED method in a integrated framework using swarm intelligence and the three part redescending estimator of Hampel when applied to a real process condition. The results evaluate the potential use of the robust technique in

Treatment on outliers in UBJ-SARIMA models for forecasting dengue cases on age groups not eligible for vaccination in Baguio City, Philippines

Science.gov (United States)

Magsakay, Clarenz B.; De Vera, Nora U.; Libatique, Criselda P.; Addawe, Rizavel C.; Addawe, Joel M.

2017-11-01

Dengue vaccination has become a breakthrough in the fight against dengue infection. This is however not applicable to all ages. Individuals from 0 to 8 years old and adults older than 45 years old remain susceptible to the vector-borne disease dengue. Forecasting future dengue cases accurately from susceptible age groups would aid in the efforts to prevent further increase in dengue infections. For the age groups of individuals not eligible for vaccination, the presence of outliers was observed and was treated using winsorization, square root, and logarithmic transformations to create a SARIMA model. The best model for the age group 0 to 8 years old was found to be ARIMA(13,1,0)(1,0,0)12 with 10 fixed variables using square root transformation with a 95% winsorization, and the best model for the age group older than 45 years old is ARIMA(7,1,0)(1,0,0)12 with 5 fixed variables using logarithmic transformation with 90% winsorization. These models are then used to forecast the monthly dengue cases for Baguio City for the age groups considered.

Isotropy of quadratic forms

Indian Academy of Sciences (India)

V. Suresh University Of Hyderabad Hyderabad

2008-10-31

Oct 31, 2008 ... We say that (a1,··· ,an) is a zero of the polynomial f if f (a1,··· ,an) = 0. One of the main problems in Mathematics is to determine whether the given polynomial has a (non-trivial) zero or not. For example, let us recall the Fermat's last theorem: V. Suresh University Of Hyderabad Hyderabad. Isotropy of quadratic ...

A comparative study of outlier detection for large-scale traffic data by one-class SVM and kernel density estimation

Science.gov (United States)

Ngan, Henry Y. T.; Yung, Nelson H. C.; Yeh, Anthony G. O.

2015-02-01

This paper aims at presenting a comparative study of outlier detection (OD) for large-scale traffic data. The traffic data nowadays are massive in scale and collected in every second throughout any modern city. In this research, the traffic flow dynamic is collected from one of the busiest 4-armed junction in Hong Kong in a 31-day sampling period (with 764,027 vehicles in total). The traffic flow dynamic is expressed in a high dimension spatial-temporal (ST) signal format (i.e. 80 cycles) which has a high degree of similarities among the same signal and across different signals in one direction. A total of 19 traffic directions are identified in this junction and lots of ST signals are collected in the 31-day period (i.e. 874 signals). In order to reduce its dimension, the ST signals are firstly undergone a principal component analysis (PCA) to represent as (x,y)-coordinates. Then, these PCA (x,y)-coordinates are assumed to be conformed as Gaussian distributed. With this assumption, the data points are further to be evaluated by (a) a correlation study with three variant coefficients, (b) one-class support vector machine (SVM) and (c) kernel density estimation (KDE). The correlation study could not give any explicit OD result while the one-class SVM and KDE provide average 59.61% and 95.20% DSRs, respectively.

Fetal cardiac cine imaging using highly accelerated dynamic MRI with retrospective motion correction and outlier rejection.

Science.gov (United States)

van Amerom, Joshua F P; Lloyd, David F A; Price, Anthony N; Kuklisova Murgasova, Maria; Aljabar, Paul; Malik, Shaihan J; Lohezic, Maelene; Rutherford, Mary A; Pushparajah, Kuberan; Razavi, Reza; Hajnal, Joseph V

2018-01-01

Development of a MRI acquisition and reconstruction strategy to depict fetal cardiac anatomy in the presence of maternal and fetal motion. The proposed strategy involves i) acquisition and reconstruction of highly accelerated dynamic MRI, followed by image-based ii) cardiac synchronization, iii) motion correction, iv) outlier rejection, and finally v) cardiac cine reconstruction. Postprocessing entirely was automated, aside from a user-defined region of interest delineating the fetal heart. The method was evaluated in 30 mid- to late gestational age singleton pregnancies scanned without maternal breath-hold. The combination of complementary acquisition/reconstruction and correction/rejection steps in the pipeline served to improve the quality of the reconstructed 2D cine images, resulting in increased visibility of small, dynamic anatomical features. Artifact-free cine images successfully were produced in 36 of 39 acquired data sets; prolonged general fetal movements precluded processing of the remaining three data sets. The proposed method shows promise as a motion-tolerant framework to enable further detail in MRI studies of the fetal heart and great vessels. Processing data in image-space allowed for spatial and temporal operations to be applied to the fetal heart in isolation, separate from extraneous changes elsewhere in the field of view. Magn Reson Med 79:327-338, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Grid laser with modified pro re nata injection of bevacizumab and ranibizumab in macular edema due to branch retinal vein occlusion: MARVEL report no 2

OpenAIRE

Narayanan, Raja; Stewart,Michael; Das,Taraprasad; Chhablani,Jay; Jalali,Subhadra; Ali,Mohammad Hasnat; Panchal,Bhavik

2016-01-01

Raja Narayanan,1 Bhavik Panchal,1 Michael W Stewart,2 Taraprasad Das,1 Jay Chhablani,1 Subhadra Jalali,1 Mohd Hasnat Ali3 On behalf of MARVEL study group 1Smt. Kanuri Santhamma Centre for Vitreo Retinal Diseases, L V Prasad Eye Institute, Hyderabad, India; 2Department of Ophthalmology, Mayo Clinic, Jacksonville, FL, USA; 3Department of Biostatistics, L V Prasad Eye Institute, Hyderabad, India Purpose: The purpose of this study was to prospectively study the efficacy of grid laser combined ...

A STUDY TO ASSESS THE CHILD LABOUR PREVALENCE, RISK FACTORS AND MORBIDITY IN A POPULATION WORKING IN THE VEGETABLE AND FRUIT MARKETS OF HYDERABAD, A.P. DURING 2012-13

Directory of Open Access Journals (Sweden)

Chintamala Koteswaramma

2016-06-01

Full Text Available Every child is a supremely important asset of the nation because future welfare of nation and society is entirely determined on how its children grow and develop. But child labour is the one which deprives the children all means. The markets are those who employ the children without any facilities. So far study was conducted to know the problems of these child labourers. METHODS & MATERIALS The present study was an analytical study done during 2012-2013, among the working children at vegetable and fruit markets of Greater Hyderabad, Andhra Pradesh with sample size of 200 from such major markets of 12. Selection of markets and study subjects were done by simple random sampling method. And data was gathered with pre-designed and pilot tested tool by conducting a medical camp in a weekday, in the market premises after taking the permission from the market yard chairman and consent of the child or parent to participate in the study. We gave medical treatment and also made suitable referrals if required. RESULTS AND CONCLUSIONS Present study shows the child labour prevalence rate as 22.79%. And it was high among male children. Gender discrimination was seen in school dropout rate and never attending school rate, which are the significant causes in female child to become a labourer. Scheduled caste, Scheduled tribes and Muslim children are more prone to child labour. Poverty was the leading cause of child labour in both the age groups (96.1% followed by illiteracy, ignorance and bad habits of the parent(s. RECOMMENDATIONS Strict implementation of the child trafficking and child labour prevention act by labour department along with external agencies’ supervision in urgent need. Along child welfare, family and female education and empowerment activities, below poverty line families’ income generation schemes can reduce child labour.

Awareness of association between periodontitis and PLBW among selected population of practising gynecologists in Andhra Pradesh

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Rajasekhar Nutalapati

2011-01-01

Settings and Design: Random, cross-sectional study in a population of practicing gynecologists from Andhra Pradesh. Materials and Methods: A random study population was selected from the practicing gynecologists in Khammam and Hyderabad. Sixty practicing gynecologists, 30 each in Khammam and Hyderabad, were approached and they consented to join the study. Data were collected in questionnaire format from the subject population. Collected data were statistically analyzed. Chi-square test with Yates correction was used to analyze the data. A " P" value of <0.05 was taken as a significant difference. Results: 73.3% of the gynecologists said that their patients complain of bleeding gums, swellings and mobility. 58.3% of the gynecologists were aware that gum diseases occur at a higher rate in pregnant females. 38.3% of the gynecologists were aware that periodontal diseases can affect the outcome of delivery. No significant difference was found between the awareness levels of gynecologists in Khammam and in Hyderabad. Conclusions: There is a need for interdisciplinary approach for the prevention of PLBW cases by the integration of periodontal care into obstetric management. Effort should be made to increase awareness among the gynecologists.

Delaying Onset of Dementia: Are Two Languages Enough?

Directory of Open Access Journals (Sweden)

Morris Freedman

2014-01-01

Full Text Available There is an emerging literature suggesting that speaking two or more languages may significantly delay the onset of dementia. Although the mechanisms are unknown, it has been suggested that these may involve cognitive reserve, a concept that has been associated with factors such as higher levels of education, occupational status, social networks, and physical exercise. In the case of bilingualism, cognitive reserve may involve reorganization and strengthening of neural networks that enhance executive control. We review evidence for protective effects of bilingualism from a multicultural perspective involving studies in Toronto and Montreal, Canada, and Hyderabad, India. Reports from Toronto and Hyderabad showed a significant effect of speaking two or more languages in delaying onset of Alzheimer’s disease by up to 5 years, whereas the Montreal study showed a significant protective effect of speaking at least four languages and a protective effect of speaking at least two languages in immigrants. Although there were differences in results across studies, a common theme was the significant effect of language use history as one of the factors in determining the onset of Alzheimer’s disease. Moreover, the Hyderabad study extended the findings to frontotemporal dementia and vascular dementia.

Delaying onset of dementia: are two languages enough?

Science.gov (United States)

Freedman, Morris; Alladi, Suvarna; Chertkow, Howard; Bialystok, Ellen; Craik, Fergus I M; Phillips, Natalie A; Duggirala, Vasanta; Raju, Surampudi Bapi; Bak, Thomas H

2014-01-01

There is an emerging literature suggesting that speaking two or more languages may significantly delay the onset of dementia. Although the mechanisms are unknown, it has been suggested that these may involve cognitive reserve, a concept that has been associated with factors such as higher levels of education, occupational status, social networks, and physical exercise. In the case of bilingualism, cognitive reserve may involve reorganization and strengthening of neural networks that enhance executive control. We review evidence for protective effects of bilingualism from a multicultural perspective involving studies in Toronto and Montreal, Canada, and Hyderabad, India. Reports from Toronto and Hyderabad showed a significant effect of speaking two or more languages in delaying onset of Alzheimer's disease by up to 5 years, whereas the Montreal study showed a significant protective effect of speaking at least four languages and a protective effect of speaking at least two languages in immigrants. Although there were differences in results across studies, a common theme was the significant effect of language use history as one of the factors in determining the onset of Alzheimer's disease. Moreover, the Hyderabad study extended the findings to frontotemporal dementia and vascular dementia.

Bhargava, Dr Purnima

Indian Academy of Sciences (India)

Specialization: Molecular Biology, Eukaryotic Transcription, Epigenetics & Chromatin Address: Scientist F, Centre for Cellular & Molecular Biology, Uppal Road, Hyderabad 500 007, ... Biotechnology techniques in Biodiversity conservation

Journal of Chemical Sciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. Sitansh Sharma1 Purshotam Sharma1 Harjinder Singh1. Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032 ...

cycloaddition reactions

Indian Academy of Sciences (India)

Unknown

Molecular Modeling Group, Organic Chemical Sciences, Indian Institute of Chemical Technology,. Hyderabad ... thus obtained are helpful to model the regioselectivity ... compromise to model Diels–Alder reactions involving ...... acceptance.

Least-Squares Linear Regression and Schrodinger's Cat: Perspectives on the Analysis of Regression Residuals.

Science.gov (United States)

Hecht, Jeffrey B.

The analysis of regression residuals and detection of outliers are discussed, with emphasis on determining how deviant an individual data point must be to be considered an outlier and the impact that multiple suspected outlier data points have on the process of outlier determination and treatment. Only bivariate (one dependent and one independent)…

Journal of Chemical Sciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. S Ramakrishna1 Siladitya Padhi1 U Deva Priyakumar1. Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032, India ...

Simple Method for Enhanced Production of Secondary Metabolites ...

African Journals Online (AJOL)

iict

2013-04-10

Apr 10, 2013 ... 2Department of Biochemistry and Biotechnology, Aurora's Degree & PG College, Chikkadpally, Hyderabad .... HPTLC is a major instrumental innovation in the field of separation .... European Communities Research Project:.

AJBR 9_1_ 67- 68new

African Journals Online (AJOL)

Dr. S.B. OLALEYE

Indian Institute of Chemical Technology,. Hyderabad 500 007, India. ABSTRACT. Different concentrations of Spilanthes acmella flower head extract were evaluated for .... this, non-volatile sesquiterpenoids and saponins are also reported.

Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. B. Starling Emerald1 2 L. S. Shashidhara1. Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad, India 500 007; European Molecular Biology Laboratory, Heidelberg, Germany ...

Suction Cup Induced Palatal Fistula: Surgical Closure by Palatal ...

African Journals Online (AJOL)

1Department of Pediatrics, Pragna Children's Hospital, Hyderabad, ... Eluru, 4Department of Conservative Dentistry and Endodontics, KIMS Dental College and ... The surgical closure of palatal fistula planned under general anesthesia.

Associateship | Indian Academy of Sciences

Indian Academy of Sciences (India)

, Dr G. Date of birth: 30 October 1958. Specialization: Computer Software Address during Associateship: ANURAG, Defence Research & Development, Organisation, Kanchanbagh P.O., Hyderabad 500 058. YouTube; Twitter; Facebook; Blog ...

Resonance – Journal of Science Education | Indian Academy of ...

Indian Academy of Sciences (India)

Author Affiliations. Subramania Ranganathan1 Anand Ranganathan2. Discovery Laboratory Indian Institute of Chemical Technology Hyderabad 500 007, India. International Center for Genetic Engineering and Biotechnology New Delhi 110 067, India.

Publications | Page 191 | IDRC - International Development ...

International Development Research Centre (IDRC) Digital Library (Canada)

Journal articles. Papers ... Centre for Regional Studies, School of Social Sciences, Hyderabad Central University ... Poor communities rarely benefit from global emissions trading schemes, because of the high transaction costs of participation.

Comparative study of methods on outlying data detection in experimental results

International Nuclear Information System (INIS)

Oliveira, P.M.S.; Munita, C.S.; Hazenfratz, R.

2009-01-01

The interpretation of experimental results through multivariate statistical methods might reveal the outliers existence, which is rarely taken into account by the analysts. However, their presence can influence the results interpretation, generating false conclusions. This paper shows the importance of the outliers determination for one data base of 89 samples of ceramic fragments, analyzed by neutron activation analysis. The results were submitted to five procedures to detect outliers: Mahalanobis distance, cluster analysis, principal component analysis, factor analysis, and standardized residual. The results showed that although cluster analysis is one of the procedures most used to identify outliers, it can fail by not showing the samples that are easily identified as outliers by other methods. In general, the statistical procedures for the identification of the outliers are little known by the analysts. (author)

Synthesis and solid state structures of Chalcogenide compounds of ...

Indian Academy of Sciences (India)

-ylidene-1,1-Diphenyl-phosphinamine. KISHOR NAKTODEa, SUMAN DASa, ABHINANDA KUNDUa, HARI PADA NAYEKb and TARUN K PANDAa,∗. aDepartment of Chemistry, Indian Institute of Technology Hyderabad, Kandi 502 285, ...

Biological control of Aspergillus flavus growth and subsequent ...

African Journals Online (AJOL)

ONOS

2010-07-05

Jul 5, 2010 ... 1School of Biological Sciences, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia,. 2Department of Botany, Osmania University, Hyderabad, India. ... the biocontrol agents tested, culture filtrate of Rhodococcus ...

Fellowship | Indian Academy of Sciences

Indian Academy of Sciences (India)

Madras). Date of birth: 2 June 1963. Specialization: Population Genetics, Evolutionary Biology, Clinical & Medical Genetics, Ancient DNA & Forensic Genetics Address: Centre for Cellular & Molecular Biology, Uppal Road, Hyderabad 500 007, A.P.

Multiple-load series resonant inverter for induction cooking ...

Indian Academy of Sciences (India)

P Sharath Kumar

Department of Electrical & Electronics Engineering, CVR College of Engineering, Hyderabad, ... 8, August 2017, pp. 1309–1316 ..... ference: Towards Sustainable Energy. pp 1–6 ... industrial induction cooker system: circuit design, control.

Chaudhuri, Dr Arabinda

Indian Academy of Sciences (India)

Rutgers). Date of birth: 6 January 1958. Specialization: Dendritic Cell Targeted Cancer Immunotherapy Address: Chief Scientist, Department of Chemical Biology, Indian Institute of Chemical Technology, Uppal Road, Hyderabad 500 007, A.P.

Endothelial nitric oxide synthase polymorphism G298T in ...

Indian Academy of Sciences (India)

1Department of Genetics, Osmania University, Hyderabad 500 007, India. 2Durgabai ... tion of this degenerative disease with increase in prevalence of cardiovascular risk .... sure, obesity, diabetes mellitus, smoking and nonvegetarian diet.

Spectrum of benign breast diseases

International Nuclear Information System (INIS)

Khanzada, T.W.; Samad, A.; Sushel, C.

2009-01-01

Objective: To determine the frequencies of various benign breast diseases (BBD) in female patients in three private hospitals of Hyderabad. Methodology: This is a prospective cohort study of all female patients visiting the surgical clinic with breast problems. This study was conducted at Isra University Hospital Hyderabad and two other private hospitals of Hyderabad over a period of about three years starting from March 2004 to February 2007. All female patients visiting the surgical clinic with breast problems were included in the study. Patients with obvious clinical features of malignancy or those who on work up were diagnosed as carcinoma were excluded from the study. Results: A total of 275 patients were included in the study. About 44% (120/275) patients belonged to third decade of life (age between: 21-30 years) followed by 33% from forth decade (age between: 31- 40 years). Fibroadenoma was the most common benign breast disease, seen in 27% (75/275) of patients, followed by fibrocystic disease seen in about 21% (57/275) patients. Conclusion: Benign Breast Diseases (BBD) are common problems in females of reproductive age. Fibroadenoma is the commonest of all benign breast disease in our set up mostly seen in second and third decade of life. Fibrocystic disease of the breast is the next common BBD whose incidence increases with increasing age. (author)

Efficient Estimation of Dynamic Density Functions with Applications in Streaming Data

KAUST Repository

Qahtan, Abdulhakim Ali Ali

2016-01-01

application is to detect outliers in data streams from sensor networks based on the estimated PDF. The method detects outliers accurately and outperforms baseline methods designed for detecting and cleaning outliers in sensor data. The third application

Gowrishankar, Dr Jayaraman

Indian Academy of Sciences (India)

Madras), Ph.D. (Melbourne), FNA, FNASc. Date of birth: 24 March 1956. Specialization: Microbial & Molecular Genetics Address: INSA Senior Scientist, Centre for DNA Fingerprinting and Diagnostics (CDFD), Uppal, Hyderabad 500 039, A.P.

Tumour necrosis factor alpha and interleukin 10 gene ...

Indian Academy of Sciences (India)

2011-08-19

Aug 19, 2011 ... 1Bhagwan Mahavir Medical Research Centre, Hyderabad 500 004, India. 2Institute of ... diagnosis and ischemic stroke cases were differentiated ... Diabetes Mellitus 2009). ..... South Indian patients with type 2 diabetes.

Static charged spheres with anisotropic pressure in general relativity

Indian Academy of Sciences (India)

Department of Mathematics, Vasavi Engineering College, Hyderabad 500 031, India. £ ... In both cases the field equations are integrated completely. ... 1. Introduction. Spherically symmetric static charged dust/perfect fluid distributions of null ...

Mapping and introgression of QTL for yield and related traits in two ...

Indian Academy of Sciences (India)

1Directorate of Rice Research, Rajendranagar, Hyderabad 500 030, India ... Genetics and Biotechnology Division, International Rice Research Institute, DAPO Box ... Advanced backcross QTL (AB-QTL) analysis was carried out in two Oryza ...

Sen, Dr Ranjan

Indian Academy of Sciences (India)

SINP), FNA, FNASc. Date of birth: 16 November 1967. Specialization: Microbiology Address: Centre for DNA Fingerprinting and Diagnostics, Nampally, Hyderabad 500 001, A.P.. Contact: Office: (040) 2474 9428. Residence: (040) 2715 8703

BODY MASS STATUS AMONG PRIMARY SCHOOL GOING CHILDREN

Directory of Open Access Journals (Sweden)

Kashmala khan

2016-08-01

Full Text Available Background: School going children is important part of our society. Their growth, development and body weight is of utmost significance and presents general health status of a community and nation as a whole. For the assessment of nutritional status WHO Asian cuts-off BMI for age recommended BMI less than 18.5 kg/m considered underweight, 18.5-24.9 normal weight, more than 25 overweight. The objective of this study is to access body mass status among primary school going children of Hyderabad. Methods: The study design was cross sectional study in which different school of Hyderabad were selected to collect data (semi government and private sector.This study has assessed the body mass index between 7-14 years old age group of both genders of primary school going children of Hyderabad. BMI has calculated with the help of weight and height of the body. Result: In this study out of 100 children 10%were 7-8 year old 20% were 9-10 year old, 20% were 11-12year old and 30% were 13-14 year old. The analysis shows 80% were underweight (below 18.5, 18% were normal weight (18.5-24.9 and only 2% overweight (above 25 according to the Asian cut-off value of BMI for Asian children. When it was analyzed by gender 62% of the boys and 18% of the girls were underweight, 6% of boys and 12% out of girls were normal weight, 2% of the boys were overweight no girl found overweight in the study. In the above study 80% found underweight, 18% normal weight, 2% overweight. Conclusion: Under nutrition among the school going children is currently a health problem faced by Hyderabad school going children. There is need to be taken address these problems in order to prevent nation from nutritional deficiency among school going children and buildup a strong and healthy nation in future.

Mixture based outlier filtration

Czech Academy of Sciences Publication Activity Database

Pecherková, Pavla; Nagy, Ivan

2006-01-01

Roč. 46, č. 2 (2006), s. 30-35 ISSN 1210-2709 R&D Projects: GA MŠk 1M0572; GA MDS 1F43A/003/120 Institutional research plan: CEZ:AV0Z10750506 Keywords : data filtration * system modelling * mixture models Subject RIV: BD - Theory of Information http://library.utia.cas.cz/prace/20060165.pdf

Cross-species amplification of human microsatellite markers in pig ...

Indian Academy of Sciences (India)

Author Affiliations. Sapna Godavarthi1 Archana Jayaraman1 Ajay Gaur1. Laboratory for the Conservation of Endangered Species (LaCONES), Centre for Cellular and Molecular Biology Annexe 1, Attapur, Hyderabad 500 048, India ...

INDeGenIUS, a new method for high-throughput identification of ...

Indian Academy of Sciences (India)

Bio-Sciences Division, Innovation Labs, Tata Consultancy Services, 1 Software Units Layout,. Hyderabad 500 ...... symbionts and pathogens in their quest for interaction with ... vaccines and treatment for a number of human pathogens. Thus ...

SHORT COMMUNICATION INTERMEDIATE OBTAINED FROM ...

African Journals Online (AJOL)

Preferred Customer

Printed in Ethiopia. © 2014 Chemical Society of Ethiopia ... 2Departments of Chemistry, Osmania University, Hyderabad-500007, India. 3Departments of Chemistry ... is composed primarily of water-aniline hydrogen bond [9]. Literature survey ...

International seminar on therapeutic applications of radiopharmaceuticals. Programme. Book of extended synopses

International Nuclear Information System (INIS)

1998-12-01

The document includes extended synopses of 64 presentations given at the International Seminar on Therapeutic Applications of Radiopharmaceuticals, held in Hyderabad, India, 18-22 January 1999. A separate indexing was prepared for each presentation

Environmental radiation monitoring of Mumbai to Visakhapatnam by rail route

International Nuclear Information System (INIS)

Pujari, R.N.; Saindane, Shashank; Narsaiah, M.V.R.; Sreekanth, B.; Joshi, G.H.; Pradeepkumar, K.S.

2014-01-01

The paper describes study of variation of environmental radiation dose rates in natural background from Mumbai to Visakhapatnam by using various state of the art radiation monitoring instruments deployed in the railway coach. The study determines the radiation levels on the rail route of the region as a part of National Level Preparedness for response to Radiological Emergencies which will act as a baseline data for reference. The survey indicated a rising trend in the natural radiation background along Mumbai to Visakhapatnam route and maximum level in the Deccan plateau was observed near Hyderabad. The distance covered during the survey from Mumbai to Visakhapatnam via Pune, Solapur, Gulbarga, Hyderabad, Warangal and Vijayawada was 1650 kms, average speed was 55 km/h and around 10,500 data points were recorded

Observed to expected or logistic regression to identify hospitals with high or low 30-day mortality?

Science.gov (United States)

Helgeland, Jon; Clench-Aas, Jocelyne; Laake, Petter; Veierød, Marit B.

2018-01-01

Introduction A common quality indicator for monitoring and comparing hospitals is based on death within 30 days of admission. An important use is to determine whether a hospital has higher or lower mortality than other hospitals. Thus, the ability to identify such outliers correctly is essential. Two approaches for detection are: 1) calculating the ratio of observed to expected number of deaths (OE) per hospital and 2) including all hospitals in a logistic regression (LR) comparing each hospital to a form of average over all hospitals. The aim of this study was to compare OE and LR with respect to correctly identifying 30-day mortality outliers. Modifications of the methods, i.e., variance corrected approach of OE (OE-Faris), bias corrected LR (LR-Firth), and trimmed mean variants of LR and LR-Firth were also studied. Materials and methods To study the properties of OE and LR and their variants, we performed a simulation study by generating patient data from hospitals with known outlier status (low mortality, high mortality, non-outlier). Data from simulated scenarios with varying number of hospitals, hospital volume, and mortality outlier status, were analysed by the different methods and compared by level of significance (ability to falsely claim an outlier) and power (ability to reveal an outlier). Moreover, administrative data for patients with acute myocardial infarction (AMI), stroke, and hip fracture from Norwegian hospitals for 2012–2014 were analysed. Results None of the methods achieved the nominal (test) level of significance for both low and high mortality outliers. For low mortality outliers, the levels of significance were increased four- to fivefold for OE and OE-Faris. For high mortality outliers, OE and OE-Faris, LR 25% trimmed and LR-Firth 10% and 25% trimmed maintained approximately the nominal level. The methods agreed with respect to outlier status for 94.1% of the AMI hospitals, 98.0% of the stroke, and 97.8% of the hip fracture hospitals

Single-nucleotide polymorphisms in peroxisome proliferator ...

Indian Academy of Sciences (India)

Prakash

1Molecular Biology Unit, National Institute of Nutrition, Jamai Osmania, Hyderabad 500 .... to stimulate several pro-inflammatory cytokines including ... were found to be lower in Ala carriers (Pro/Ala+Ala/Ala ...... or skeletal muscle; Biochem.

Search Results | Page 67 | IDRC - International Development ...

International Development Research Centre (IDRC) Digital Library (Canada)

Results 661 - 670 of 8489 ... State and community responses to drug-related violence in Mexico. Published ... Everyday life information seeking behaviour of urban homeless youth ... Caught in the space between : Hyderabad's muslim youth and ...

Data analysis and approximate models model choice, location-scale, analysis of variance, nonparametric regression and image analysis

CERN Document Server

Davies, Patrick Laurie

2014-01-01

Introduction IntroductionApproximate Models Notation Two Modes of Statistical AnalysisTowards One Mode of Analysis Approximation, Randomness, Chaos, Determinism ApproximationA Concept of Approximation Approximation Approximating a Data Set by a Model Approximation Regions Functionals and EquivarianceRegularization and Optimality Metrics and DiscrepanciesStrong and Weak Topologies On Being (almost) Honest Simulations and Tables Degree of Approximation and p-values ScalesStability of Analysis The Choice of En(α, P) Independence Procedures, Approximation and VaguenessDiscrete Models The Empirical Density Metrics and Discrepancies The Total Variation Metric The Kullback-Leibler and Chi-Squared Discrepancies The Po(λ) ModelThe b(k, p) and nb(k, p) Models The Flying Bomb Data The Student Study Times Data OutliersOutliers, Data Analysis and Models Breakdown Points and Equivariance Identifying Outliers and Breakdown Outliers in Multivariate Data Outliers in Linear Regression Outliers in Structured Data The Location...

Robust Subjective Visual Property Prediction from Crowdsourced Pairwise Labels.

Science.gov (United States)

Fu, Yanwei; Hospedales, Timothy M; Xiang, Tao; Xiong, Jiechao; Gong, Shaogang; Wang, Yizhou; Yao, Yuan

2016-03-01

The problem of estimating subjective visual properties from image and video has attracted increasing interest. A subjective visual property is useful either on its own (e.g. image and video interestingness) or as an intermediate representation for visual recognition (e.g. a relative attribute). Due to its ambiguous nature, annotating the value of a subjective visual property for learning a prediction model is challenging. To make the annotation more reliable, recent studies employ crowdsourcing tools to collect pairwise comparison labels. However, using crowdsourced data also introduces outliers. Existing methods rely on majority voting to prune the annotation outliers/errors. They thus require a large amount of pairwise labels to be collected. More importantly as a local outlier detection method, majority voting is ineffective in identifying outliers that can cause global ranking inconsistencies. In this paper, we propose a more principled way to identify annotation outliers by formulating the subjective visual property prediction task as a unified robust learning to rank problem, tackling both the outlier detection and learning to rank jointly. This differs from existing methods in that (1) the proposed method integrates local pairwise comparison labels together to minimise a cost that corresponds to global inconsistency of ranking order, and (2) the outlier detection and learning to rank problems are solved jointly. This not only leads to better detection of annotation outliers but also enables learning with extremely sparse annotations.

On the possible involvement of bovine serum albumin precursor in ...

Indian Academy of Sciences (India)

2014-01-27

Jan 27, 2014 ... Biomaterials Group, CSIR-Indian Institute of Chemical Technology, Hyderabad 500 007,. India. † ..... PAGE (lane 3, figure 1B) was air dried, trypsin digested and ..... Mixed bag of regular and anomalous transfection profiles.

OutRank

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Steinhausen, Uwe

2008-01-01

Outlier detection is an important data mining task for consistency checks, fraud detection, etc. Binary decision making on whether or not an object is an outlier is not appropriate in many applications and moreover hard to parametrize. Thus, recently, methods for outlier ranking have been proposed...

Multilayer perceptron for robust nonlinear interval regression analysis using genetic algorithms.

Science.gov (United States)

Hu, Yi-Chung

2014-01-01

On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets.

Numerical simulation and observations of very severe cyclone ...

Indian Academy of Sciences (India)

1Indian National Centre for Ocean Information Services, Pragathi Nagar, Hyderabad 500 090, India. 2Centre .... moored and wave rider buoys are represented by pink and blue respectively. ..... Further, slight shift in the peak frequency of the.

All projects related to india | Page 15 | IDRC - International ...

International Development Research Centre (IDRC) Digital Library (Canada)

The city of Hyderabad, Gujarat, India, has a long history of communal conflict. Start Date: ... Project. Urbanization, housing and poverty are very much interrelated in sub-Saharan Africa. ... Dalit Women's Rights and Citizenship in India - Phase I.

Synthesis and antibacterial profile of novel azomethine derivatives ...

African Journals Online (AJOL)

3, Banjara hills, Hyderabad, India, 3Universiti Teknologi MARA. (UiTM), Faculty of Pharmacy, Puncak Alam Campus, Selangor D.E, Malaysia ... Results: The structures of azomethine were in full agreement with their spectral data. Among all ...

INTERNET5: Shaping an Internet for women's empowerment | IDRC ...

International Development Research Centre (IDRC) Digital Library (Canada)

2017-12-08

Dec 8, 2017 ... Young women learn computer skills, Hyderabad, Pakistan ... works in building social, political, and economic empowerment for women and girls. ... to the Internet and to explore how digital and networking tools can best be ...

Publications | Page 237 | IDRC - International Development ...

International Development Research Centre (IDRC) Digital Library (Canada)

... the agro-pastoral systems of Tanzania : a gendered analysis (open access) ... This paper deals with the ways in which gender and caste identities marginalise particular groups from access to water in a village in periurban Hyderabad, India.

Fellowship | Indian Academy of Sciences

Indian Academy of Sciences (India)

Date of birth: 28 June 1947. Specialization: Medicinal Chemistry, Drug Design & Discovery, Organometallic Chemistry and Catalysis Address: Chairman, Cosmic Therapeutics, 48, Villa Greens, Gandipet, Hyderabad 500 075, A.P.. Contact: Residence: (040) 2419 3132. Mobile: 98497 99444

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

... Institute of Information Technology, Visakhapatnam 530 046; Jawaharlal Nehru Technological University, Kukatpally, Hyderabad 500 085; St. Martin's Engineering College, Dulapally, Quthbullapur, Secunderabad 500 014; Department of Electrical and Electronics Engineering, Vignan's Institute of Engineering for Women, ...

Fulltext PDF

Indian Academy of Sciences (India)

National Geophysical Research Institute (CSIR), Hyderabad 500 007, India. ∗ ..... ity of this assumption can be tested by examining ..... Rautian et al (1978) reports that Qs is observed to .... provided financial support for this work vide ref-.

International seminar on therapeutic applications of radiopharmaceuticals. Programme. Book of extended synopses

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-12-01

The document includes extended synopses of 64 presentations given at the International Seminar on Therapeutic Applications of Radiopharmaceuticals, held in Hyderabad, India, 18-22 January 1999. A separate indexing was prepared for each presentation Refs, figs, tabs

Evolving partnerships in the collection of urban solid waste in the developing world

NARCIS (Netherlands)

Post, J.; Baud, I.S.A.; Furedy, C.; Post, J.

2004-01-01

-Post, Johan. (2004) Evolving Partnerships in the Collection of Urban Solid Waste in the Developing World, in: Baud, Isa., Johan. Post and Christine Furedy (2004) Solid Waste Management and Recycling; Actors, Partnerships and Policies in Hyderabad, India

Scientific Ballooning in India - Recent Developments

Science.gov (United States)

Manchanda, R. K.; Srinivasan, S.; Subbarao, J. V.

Established in 1972, the National Balloon Facility operated by TIFR in Hyderabad, India is is a unique facility in the country, which provides a complete solution in scientific ballooning. It is also one of its kind in the world since it combines both, the in-house balloon production and a complete flight support for scientific ballooning. With a large team working through out the year to design, fabricate and launch scientific balloons, the Hyderabad Facility is a unique centre of expertise where the balloon design, Research and Development, the production and launch facilities are located under one roof. Our balloons are manufactured from 100% indigenous components. The mission specific balloon design, high reliability control and support instrumentation, in-house competence in tracking, telemetry, telecommand, data processing, system design and mechanics is a hallmark of the Hyderabad balloon facility. In the past few years we have executed a major programme of upgradation of different components of balloon production, telemetry and telecommand hardware and various support facilities. This paper focuses on our increased capability of balloon production of large sizes up to size of 780,000 M^3 using Antrix film, development of high strength balloon load tapes with the breaking strength of 182 kg, and the recent introduction of S-band telemetry and a commandable timer cut-off unit in the flight hardware. A summary of the various flights conducted in recent years will be presented along with the plans for new facilities.

Search Results | Page 2 | IDRC - International Development ...

International Development Research Centre (IDRC) Digital Library (Canada)

Results 11 - 20 of 157 ... Water resources and adaptation to climate change in North China Plain ... water use : a case of Aliabad village in peri-urban Hyderabad, India ... Adaptation pathways for inland aquaculture in the tropics and subtropics.

Microstructure and oxidation performance of a γ–γ′ Pt-aluminide ...

Indian Academy of Sciences (India)

Microstructure and oxidation performance of a –' Pt-aluminide bond coat on directionally solidified superalloy CM-247LC ... Keywords. Platinum aluminide bond coat; coating; cyclic oxidation; superalloy; microstructure. ... Defence Metallurgical Research Laboratory, Kanchanbagh, Hyderabad 500 058, India ...

Thermal and IR studies on copper doped polyvinyl alcohol

Indian Academy of Sciences (India)

TECS

and K VEERA BRAHMAM*. Advanced Systems Laboratory, Kanchanbagh, Hyderabad 500 058, India ... and transient data storage materials or as a basic material for the fabrication of ... of the polymer. The aim of the present work was to study.

Bulletin of Materials Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. RAVI KANT1 UJJWAL PRAKASH1 VIJAYA AGARWALA1 V V SATYA PRASAD2. Department of Metallurgical and Materials Engineering, IIT Roorkee, Roorkee 247 667, India; Defence Metallurgical Research Laboratory, Kanchanbagh, Hyderabad 500 058, India ...

New associates | Announcements | Indian Academy of Sciences

Indian Academy of Sciences (India)

Translational Health Science and Technology Institute, Faridabad. Praveen Kumar Indian Institute of Science, Bengaluru. S Mishra Sabyashachi Mishra Indian Institute of Technology, Kharagpur. Jagannath Mondal TIFR Centre for Interdisciplinary Sciences, Hyderabad. Samrat Mondal Wildlife Institute of India, Dehradun.

Ashwagandha

Science.gov (United States)

... Q-10, fish oil, L-arginine, lyceum, stinging nettle, theanine, and others.Herbs/supplements with sleep-promoting ( ... BY MOUTH: For stress: Ashwagandha root extract (KSM66, Ixoreal Biomed, Hyderabad, India) 300 mg twice daily after food for 60 days.

Journal of Chemical Sciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Journal of Chemical Sciences; Volume 119; Issue 5. Controlling dynamics in diatomic systems ... Department of Chemistry, Panjab University, Chandigarh 160 014; Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032 ...

Design of Robust Neural Network Classifiers

DEFF Research Database (Denmark)

Larsen, Jan; Andersen, Lars Nonboe; Hintz-Madsen, Mads

1998-01-01

This paper addresses a new framework for designing robust neural network classifiers. The network is optimized using the maximum a posteriori technique, i.e., the cost function is the sum of the log-likelihood and a regularization term (prior). In order to perform robust classification, we present...... a modified likelihood function which incorporates the potential risk of outliers in the data. This leads to the introduction of a new parameter, the outlier probability. Designing the neural classifier involves optimization of network weights as well as outlier probability and regularization parameters. We...... suggest to adapt the outlier probability and regularisation parameters by minimizing the error on a validation set, and a simple gradient descent scheme is derived. In addition, the framework allows for constructing a simple outlier detector. Experiments with artificial data demonstrate the potential...

The Role of SPINK1 in ETS Rearrangement Negative Prostate Cancers

Science.gov (United States)

Tomlins, Scott A.; Rhodes, Daniel R.; Yu, Jianjun; Varambally, Sooryanarayana; Mehra, Rohit; Perner, Sven; Demichelis, Francesca; Helgeson, Beth E.; Laxman, Bharathi; Morris, David S.; Cao, Qi; Cao, Xuhong; Andrén, Ove; Fall, Katja; Johnson, Laura; Wei, John T.; Shah, Rajal B.; Al-Ahmadie, Hikmat; Eastham, James A.; Eggener, Scott E.; Fine, Samson W.; Hotakainen, Kristina; Stenman, Ulf-Håkan; Tsodikov, Alex; Gerald, William L.; Lilja, Hans; Reuter, Victor E.; Kantoff, Phillip W.; Scardino, Peter T.; Rubin, Mark A.; Bjartell, Anders S.; Chinnaiyan, Arul M.

2009-01-01

Summary ETS gene fusions have been characterized in a majority of prostate cancers, however the key molecular alterations in ETS negative cancers are unclear. Here we used an outlier meta-analysis (meta-COPA) to identify SPINK1 outlier-expression exclusively in a subset of ETS rearrangement negative cancers (~10% of total cases). We validated the mutual exclusivity of SPINK1 expression and ETS fusion status, demonstrated that SPINK1 outlier-expression can be detected non-invasively in urine and observed that SPINK1 outlier-expression is an independent predictor of biochemical recurrence after resection. We identified the aggressive 22RV1 cell line as a SPINK1 outlier-expression model, and demonstrate that SPINK1 knockdown in 22RV1 attenuates invasion, suggesting a functional role in ETS rearrangement negative prostate cancers. PMID:18538735

Structural Origami

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 8; Issue 5. Structural Origami - A Geodesic Dome from Five Postcards. Subramania Ranganathan. General Article ... Author Affiliations. Subramania Ranganathan1. Discovery Laboratory Indian Institute of Chemical Technology Hyderabad 500 007, India.

High purity tellurium production using dry refining processes

Indian Academy of Sciences (India)

Unknown

Centre for Materials for Electronics Technology (C-MET), IDA Phase II, Cherlapally, HCL Post, Hyderabad 500 051,. India ... The total content of gas and gas forming impurities like O, N and C are found to be .... (DIT), Government of India.

Deciphering heavy metal contamination zones in soils of a granitic ...

Indian Academy of Sciences (India)

., Ba, Cr, Cu,. Ni, Pb, Rb, Sr ... metal contamination in soils of different regions. The study ... in the Hyderabad city. ... A network of first and second order streams ... In this case, redun- ...... strategy for developing countries; In: Lead, mercury, cad-.

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Department of Industrial Engineering and Management, Maulana Abul Kalam Azad University of Technology, Kolkata 700064, India; Indian Institute of Management Raipur, GEC Campus, Sejbahar, Raipur 492015, India; Indian National Centre for Ocean Information Services, Ministry of Earth Sciences, Hyderabad 500090, ...

Fermi–Dirac Statistics

Indian Academy of Sciences (India)

IAS Admin

Pauli exclusion principle, Fermi–. Dirac statistics, identical and in- distinguishable particles, Fermi gas. Fermi–Dirac Statistics. Derivation and Consequences. S Chaturvedi and Shyamal Biswas. (left) Subhash Chaturvedi is at University of. Hyderabad. His current research interests include phase space descriptions.

Search Results | Page 23 | IDRC - International Development ...

International Development Research Centre (IDRC) Digital Library (Canada)

Results 221 - 230 of 292 ... Filter by type. (-) Remove .... The northern border of Ecuador has been prone to conflict over the past several years. Security ... The city of Hyderabad, Gujarat, India, has a long history of communal conflict. Muslim ...

JCSC_128_9_1469_1473_SI.docx

Indian Academy of Sciences (India)

Userman

Base-oxidant promoted metal free N-demethylation of arylamines. VINAYAK BOTLA, CHIRANJEEVI BARREDDI, RAMANA V DAGGUPATI and CHANDRASEKHARAM MALAPAKA. I&PC Division, CSIR-Indian Institute of Chemical Technology, Uppal Road, Tarnaka, Hyderabad 500 007, India. e-mail: chandra@iict.res.in.

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Modelling spatial density using continuous wavelet transforms ... Space debris; wavelets; Mexican hat; Laplace distribution; random search; parameter estimation. ... of peaks and peak locations of spatial density model using continuous wavelets. ... Department of Mathematics, Osmania University, Hyderabad 500 007, India ...

Salts and Co-crystals of Theobromine and their phase ...

Indian Academy of Sciences (India)

Co-crystal; dissolution; phase transformation; salts; solubility; stability; synthon. ... Salts of theobromine with hydrochloric acid, phosphoric acid, methanesulfonic acid, benzenesulfonic acid and -toluenesulfonic acid were prepared using ... C. R. Rao Road, Gachibowli, Central University P.O., Hyderabad 500 046, India ...

Studies on dehydrogenation of cyclohexanol to cyclohexanone over ...

Indian Academy of Sciences (India)

B SRIDEVI

cGovernment College for Women, Osmania University, Koti, Hyderabad, ... MS received 12 September 2016; revised 22 February 2017; accepted 28 ..... Burri D R, Jun K W, Kim Y H, Kim J M, Park S E .... troscopy (New York: Plenum Press).

JCSC_128_6_929_939_SI.docx

Indian Academy of Sciences (India)

RAM

bDepartment of Chemistry, Jawaharlal Nehru Technological University Anantapuramu, College of Engineering Anantapur, Andhra Pradesh, 500 085 India. dMedicinal Chemistry and Pharmacology Division, CSIR-Indian Institute of Chemical Technology, Tarnaka, Hyderabad 500 007, India. eDepartment of Biotechnology, ...

to view fulltext PDF

Indian Academy of Sciences (India)

Prakash

complexes in mouse, pollen killer in wheat, and female gamete eliminator in tomato ...... me to arrange our meeting in Hyderabad. He wrote – “I have learned ... fungus Neurospora crassa; Nature (London) 422 859–868. Gallegos A, Jacobson ...

ACKNOWLEDGEMENTS

Indian Academy of Sciences (India)

C T Achutankutty, National Institute of Oceanography, Goa. Rajesh Agnihotri, Max Planck Institute For Chemistry, Germany. S Ahmed, National Geophysical Research Institute, Hyderabad. B R Arora, Wadia Institute of Himalayan Geology, Dehradun. K Balakrishna, National Institute of Technology Karnataka, Surathkal.

Bulletin of Materials Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

Materials Chemistry Laboratory, Department of Materials Science, Gulbarga University, Gulbarga 585 106, India; Veeco-India Nanotechnology Laboratory, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bangalore 560 064, India; R&D Centre Premier Explosives Pvt. Ltd., Hyderabad 500 015, India ...

Basavaiah, Prof. Deevi

Indian Academy of Sciences (India)

Elected: 1997 Section: Chemistry ... Date of birth: 11 August 1950 ... Address: Professor, School of Chemistry, University of Hyderabad, ... The 29th Mid-year meeting of the Academy will be held from 29–30 June 2018 in Infosys, Mysuru ...

Volatility persistence in crude oil markets

International Nuclear Information System (INIS)

Charles, Amélie; Darné, Olivier

2014-01-01

Financial market participants and policy-makers can benefit from a better understanding of how shocks can affect volatility over time. This study assesses the impact of structural changes and outliers on volatility persistence of three crude oil markets – Brent, West Texas Intermediate (WTI) and Organization of Petroleum Exporting Countries (OPEC) – between January 2, 1985 and June 17, 2011. We identify outliers using a new semi-parametric test based on conditional heteroscedasticity models. These large shocks can be associated with particular event patterns, such as the invasion of Kuwait by Iraq, the Operation Desert Storm, the Operation Desert Fox, and the Global Financial Crisis as well as OPEC announcements on production reduction or US announcements on crude inventories. We show that outliers can bias (i) the estimates of the parameters of the equation governing volatility dynamics; (ii) the regularity and non-negativity conditions of GARCH-type models (GARCH, IGARCH, FIGARCH and HYGARCH); and (iii) the detection of structural breaks in volatility, and thus the estimation of the persistence of the volatility. Therefore, taking into account the outliers on the volatility modelling process may improve the understanding of volatility in crude oil markets. - Highlights: • We study the impact of outliers on volatility persistence of crude oil markets. • We identify outliers and patches of outliers due to specific events. • We show that outliers can bias (i) the estimates of the parameters of GARCH models, (ii) the regularity and non-negativity conditions of GARCH-type models, (iii) the detection of structural breaks in volatility of crude oil markets

The effectiveness of robust RMCD control chart as outliers’ detector

Science.gov (United States)

Darmanto; Astutik, Suci

2017-12-01

A well-known control chart to monitor a multivariate process is Hotelling’s T 2 which its parameters are estimated classically, very sensitive and also marred by masking and swamping of outliers data effect. To overcome these situation, robust estimators are strongly recommended. One of robust estimators is re-weighted minimum covariance determinant (RMCD) which has robust characteristics as same as MCD. In this paper, the effectiveness term is accuracy of the RMCD control chart in detecting outliers as real outliers. In other word, how effectively this control chart can identify and remove masking and swamping effects of outliers. We assessed the effectiveness the robust control chart based on simulation by considering different scenarios: n sample sizes, proportion of outliers, number of p quality characteristics. We found that in some scenarios, this RMCD robust control chart works effectively.

Improved nanostructure reconstruction by performing data refinement in optical scatterometry

Science.gov (United States)

Zhu, Jinlong; Jiang, Hao; Shi, Yating; Chen, Xiuguo; Zhang, Chuanwei; Liu, Shiyuan

2016-01-01

Recently, we have indirectly demonstrated that nanostructure reconstruction accuracy is degraded by the outliers in optical scatterometry, and we have applied the robust estimation method to suppress these outliers. However, the existence of a possible heavy masking effect could result in the risk of low measurement accuracy, since the detection of outliers is simply based on the judgment of residual value. In this work, a novel method is introduced to directly detect outliers, which can provide the intuitional display of outliers in a two-dimensional coordinate system. Moreover, a robust correction step based on the principle of least trimmed squared estimator regression is proposed to replace the conventional Gauss-Newton iteration step, by which the more reliable and accurate nanostructure reconstruction is achieved. The improved reconstruction of a one-dimensional etched Si grating has demonstrated the feasibility of the proposed methods.

Improved nanostructure reconstruction by performing data refinement in optical scatterometry

International Nuclear Information System (INIS)

Zhu, Jinlong; Jiang, Hao; Shi, Yating; Chen, Xiuguo; Zhang, Chuanwei; Liu, Shiyuan

2016-01-01

Recently, we have indirectly demonstrated that nanostructure reconstruction accuracy is degraded by the outliers in optical scatterometry, and we have applied the robust estimation method to suppress these outliers. However, the existence of a possible heavy masking effect could result in the risk of low measurement accuracy, since the detection of outliers is simply based on the judgment of residual value. In this work, a novel method is introduced to directly detect outliers, which can provide the intuitional display of outliers in a two-dimensional coordinate system. Moreover, a robust correction step based on the principle of least trimmed squared estimator regression is proposed to replace the conventional Gauss–Newton iteration step, by which the more reliable and accurate nanostructure reconstruction is achieved. The improved reconstruction of a one-dimensional etched Si grating has demonstrated the feasibility of the proposed methods. (paper)

Mukhopadhyay, Dr Sangita

Indian Academy of Sciences (India)

Elected: 2013 Section: Medicine. Mukhopadhyay, Dr Sangita Ph.D. (Utkal), FNASc. Date of birth: 1 January 1966. Specialization: Immunology, Cell Signalling, Communicable Diseases Address: Group Leader, Molecular Cell Biology, Centre for DNA Fingerprinting & Diagnostics, Nampally, Hyderabad 500 001, A.P.. Contact ...

Women's political participation leads to stronger local economies ...

International Development Research Centre (IDRC) Digital Library (Canada)

Edgard Rodriguez - IDRC. Women attend a self-help group meeting near Hyderabad, India. Keenara Khanderia. Under changes to India's constitution, Indian women are gaining a stronger political voice. Legal reforms are encouraging women to contribute to economic growth and investments in community growth.

Majumdar, Dr Subeer Suhash

Indian Academy of Sciences (India)

Fellow Profile. Elected: 2014 Section: Animal Sciences. Majumdar, Dr Subeer Suhash Ph.D. (nagpur), FNA, FNASc. Date of birth: 21 May 1961. Specialization: Animal Biotechnology, Transgenic Animals, Endocrinology Address: Director, National Institute of Animal Biotechnology, Gopan Pally, Hyderabad 500 046, A.P.

ACKNOWLEDGEMENTS

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

P K Gupta, Roorkee. Boris Gurevich, Australia. Simon Harley, Edinburgh, Scotland. Anand K Inamdar, California. A Jayaraman, Ahmedabad. K N Khattri, Dehradun. Ralf Kretz, Canada. S Krishnaswami, Ahmedabad. R K Lal, Varanasi. D C Mishra, Hyderabad. Asoke Mookherjee, Kolkata. Dhruba Mukhopadhyay, Kolkata.

Carbocation lifetimes and entropy of water addition to carbocations ...

Indian Academy of Sciences (India)

Unknown

Carbocation lifetimes and entropy of water addition to carbocations dependent on their stability. V JAGANNADHAM. Department of Chemistry, Osmania University, Hyderabad 500 007, India e-mail: jvandanapu@hotmail.com. MS received 11 January 2002. Abstract. Iminodiazonium ions (α-azidobenzyl carbocations) were ...

Proceedings – Mathematical Sciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. Indranil Biswas1 N Raghavendra1 2. School of Mathematics, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India; Advanced Technology Centre, Tata Consultancy Services, K.L.K. Estate, Fateh Maidan Road, Hyderabad 500 001, India ...

Bulletin of Materials Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. R Senthur Pandi1 M Mahendran1 R Chokkalingam1 M Manivelraja2 V Chandrashekaran2. Smart Materials Laboratory, Department of Physics, Thiagarajar College of Engineering, Madurai 625 015, India; Advanced Magnetics Group, Defence Metallurgical Research Laboratory, Hyderabad 500 058, ...

Journal of Biosciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

Author Affiliations. Ramkumar Sambasivan1 2 Grace K Pavlath3 Jyotsna Dhawan1. Centre for Cellular and Molecular Biology, Hyderabad 500 007, India; Department of Developmental Biology, Pasteur Institute, 75724 Cedex 15 Paris, Franc; Department of Pharmacology, Emory University, Atlanta, GA 30322, USA ...

Associateship | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Fellowship; Associateship. Associate Profile. Period: 2004–2007. Chakrabarti, Dr Subhabrata. Date of birth: 27 November 1972. Specialization: Molecular Genetics of Ocular Disorders Address during Associateship: LV Prasad Eye Institute, LV Prasad Marg, Banjara Hills, Hyderabad 500 034. YouTube; Twitter ...

Fulltext PDF

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

Abbott, Dallas, Lamont-Doherty Earth Observatory of the Columbia University, USA. Ahmad, Talat, Delhi University, Delhi. Anderson, Don L, California Institute of Technology, USA. Anderson, Steven, Black Hills State University,USA. Anil Kumar, G, National Geophysical Research Institute, Hyderabad. Asthana, Deepanker ...

GJB2 and GJB6 gene mutations found in Indian probands with ...

Indian Academy of Sciences (India)

of milestones (table 1), birth ranks of the probands (table 2), parental age at the ... pital, Hyderabad, India, and schools for deaf that are in and around the district of .... nonsyndromic hearing loss and in normal hearing controls. No. of. No. of.

ACKNOWLEDGEMENTS

Indian Academy of Sciences (India)

Parkash B, Indian Institute of Technology, Roorkee. Parthasarathy G, National Geophysical Research Institute, Hyderabad. Parvez Imtiyaz, CSIR Centre for ... Raman Sethu, North Carolina State University, Raleigh, USA. Ramana M V, National Institute of Oceanography, Dona Paula, Goa. Ramana Muvva, Scripps Institution ...

Cosmic ray induced charged particle albedos in the upper atmosphere

International Nuclear Information System (INIS)

Bhatnagar, S.P.; Verma, S.D.

1982-01-01

There are several observations made in balloon and satellite experiments of relativistic albedo electrons in 50 to 10,000 MeV energy region. The spectrum of these electrons is a power law with negative exponent. At lower energies, 1 to 50 MeV region theoretical evaluations indicate that their energy spectrum will have a similar shape, thus the flux at low energies will be much higher. The only spectrum measurements available below 20 MeV were taken at Ft. Churchill by Hovestadt and Meyer (1969). The flux and energy spectrum of the Re-entrant albedos electrons have been calculated in the energy range 3-50 MeV for Ft. Churchill, Canada, Palestein, Texas and Hyderabad, India, and are presented. The angular distribution of re-entrant electrons in the upper atmosphere is not yet observed, however Kurnosova et. al. (1979) have measured the Vertical and Horizontal integral flux at Hyderabad, India

supp4.doc

Indian Academy of Sciences (India)

Naresh Duvva,a Ravi Kumar Kanaparthi,a Jaipal Kandhadi,a Gabriele Marotta,b Paolo Salvatori,b Filippo De Angelis,*b Lingamallu Giribabu*a. aInorganic & Physical Chemistry Division, CSIR-Indian Institute of Chemical Technology, Hyderabad 500607, India. bComputational Laboratory for Hybrid/Organic Photovoltaics ...

SU-8 photoresist-derived electrospun carbon nanofibres as high ...

Indian Academy of Sciences (India)

2017-06-09

Jun 9, 2017 ... as high-capacity anode material for lithium ion battery. M KAKUNURI, S KAUSHIK, A SAINI and C S SHARMA. ∗. Creative and Advanced Research Based On Nanomaterials (CARBON) Laboratory, Department of Chemical Engineering,. Indian Institute of Technology, Hyderabad, Kandi 502285, India. ∗.

Research Article Marker aided selection and validation of various Pi ...

Indian Academy of Sciences (India)

mithila

4International Crop Research Institute for Semi-Arid Tropics, Hyderabad. 5Acharya ... Rice is the staple food of more than half of the world's population – more than 3.5 billion people depend on .... PCR products were resolved on. 1.5 to 3% ...

Amidinate Ligands in Zinc coordination sphere: Synthesis and ...

Indian Academy of Sciences (India)

Amidinate Ligands in Zinc coordination sphere: Synthesis and structural diversity. SRINIVAS ANGA, INDRANI BANERJEE and TARUN K PANDA. ∗. Department of Chemistry, Indian Institute of Technology Hyderabad, Kandi 502 285,. Sangareddy, Telangana, India e-mail: tpanda@iith.ac.in. MS received 25 February 2016; ...

Balasubramanian, Dr Dorairajan

Indian Academy of Sciences (India)

Council Service: 2001-12; Vice-President: 2004-2006; President:2007-2009. Date of birth: 28 August 1939. Specialization: Biophysical Chemistry & Biochemistry of Eye Diseases and Public Understanding of Science Address: Director of Research, Hyderabad Eye Research Foundation, LV Prasad Eye Institute, LV Prasad ...

Fulltext PDF

Indian Academy of Sciences (India)

Catalysis for Sustainable Development. Foreword. This Special Issue contains the contributions of invited speakers and eminent personalities who participated in the 21st National Symposium on Catalysis. (CATSYMP21) held at CSIR-Indian Institute of Chemical Technology, Hyderabad,. India during 11–13 February, 2013.

Ranganathan, Dr Darshan

Indian Academy of Sciences (India)

Elected: 1991 Section: Chemistry. Ranganathan, Dr Darshan Ph.D. (Delhi), FNA. Date of birth: 4 June 1941. Date of death: 4 June 2001. Specialization: Organic Chemistry, Bio-Organic Chemistry and Supramolecular Chemistry Last known address: Scientist, Indian Institue of Chemical, Technology, Uppal Road, Hyderabad ...

ISe-Pt-emb-er

Indian Academy of Sciences (India)

times in his lectures. ... "Space and time are commonly regarded as the forms of existence of the real world, ... study of motion is at the same time also a .... 15 km outside the city of Hyderabad), 10) whether the applicant can bear his/her travel.

Mishra, Dr Rakesh K

Indian Academy of Sciences (India)

Mishra, Dr Rakesh K Ph.D. (Allahabad), FNASc, FNA. Date of birth: 14 April 1961. Specialization: Genomics, Chromatin, Epigenetics Address: Director, Centre for Cellular & Molecular Biology, Uppal Road, Hyderabad 500 007, A.P.. Contact: Office: (040) 2719 2600. Residence: (040) 2720 6400. Mobile: 94419 02188

Parnaik, Dr Veena Krishnaji

Indian Academy of Sciences (India)

Elected: 2008 Section: Animal Sciences. Parnaik, Dr Veena Krishnaji Ph.D. (Ohio State), FNA. Date of birth: 22 August 1953. Specialization: Cell Biology, Molecular Biology, Lamins and Nuclear Organisation Address: INSA Senior Scientist, Centre for Cellular & Molecular Biology, Uppal Road, Hyderabad 500 007, A.P.