TEXT CLASSIFICATION FOR AUTOMATIC DETECTION OF E-CIGARETTE USE AND USE FOR SMOKING CESSATION FROM TWITTER: A FEASIBILITY PILOT.

Science.gov (United States)

Aphinyanaphongs, Yin; Lulejian, Armine; Brown, Duncan Penfold; Bonneau, Richard; Krebs, Paul

2016-01-01

Rapid increases in e-cigarette use and potential exposure to harmful byproducts have shifted public health focus to e-cigarettes as a possible drug of abuse. Effective surveillance of use and prevalence would allow appropriate regulatory responses. An ideal surveillance system would collect usage data in real time, focus on populations of interest, include populations unable to take the survey, allow a breadth of questions to answer, and enable geo-location analysis. Social media streams may provide this ideal system. To realize this use case, a foundational question is whether we can detect e-cigarette use at all. This work reports two pilot tasks using text classification to identify automatically Tweets that indicate e-cigarette use and/or e-cigarette use for smoking cessation. We build and define both datasets and compare performance of 4 state of the art classifiers and a keyword search for each task. Our results demonstrate excellent classifier performance of up to 0.90 and 0.94 area under the curve in each category. These promising initial results form the foundation for further studies to realize the ideal surveillance solution.

Video Sensor Architecture for Surveillance Applications

Directory of Open Access Journals (Sweden)

José E. Simó

2012-02-01

Full Text Available This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

Health surveillance of radiological work

International Nuclear Information System (INIS)

Pauw, H.; Vliet, J.V.D.; Zuidema, H.

1988-01-01

Shielding x-ray devices and issuing film badges to radiological workers in 1936 can be considered the start of radiological protection in the Philips enterprises in the Netherlands. Shielding and equipment were constantly improved based upon the dosimetry results of the filmbadges. The problem of radioactive waste led to the foundation of a central Philips committee for radiological protection in 1956, which in 1960 also issued an internal license system in order to regulate the proper precautions to be taken : workplace design and layout, technological provisions and working procedures. An evaluation of all radiological work in 1971 learnt that a stricter health surveillance program was needed to follow up the precautions issued by the license. On one hand a health surveillance program was established and on the other hand all types of radiological work were classified. In this way an obligatory and optimal health surveillance program was issued for each type of radiological work

Ideology, Critique and Surveillance

Directory of Open Access Journals (Sweden)

Heidi Herzogenrath-Amelung

2013-11-01

Full Text Available The 2013 revelations concerning global surveillance programmes demonstrate in unprecedented clarity the need for Critical Theory of information and communication technologies (ICTs to address the mechanisms and implications of increasingly global, ubiquitous surveillance. This is all the more urgent because of the dominance of the “surveillance ideology” (the promise of security through surveillance that supports the political economy of surveillance. This paper asks which theoretical arguments and concepts can be useful for philosophically grounding a critique of this surveillance ideology. It begins by examining how the surveillance ideology works through language and introduces the concept of the ‘ideological packaging’ of ICTs to show how rhetoric surrounding the implementation of surveillance technologies reinforces the surveillance ideology. It then raises the problem of how ideology-critique can work if it relies on language itself and argues that Martin Heidegger’s philosophy can make a useful contribution to existing critical approaches to language.

Extending cluster Lot Quality Assurance Sampling designs for surveillance programs

OpenAIRE

Hund, Lauren; Pagano, Marcello

2014-01-01

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance based on the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than ...

Redefining syndromic surveillance

Directory of Open Access Journals (Sweden)

Rebecca Katz

2011-12-01

Full Text Available With growing concerns about international spread of disease and expanding use of early disease detection surveillance methods, the field of syndromic surveillance has received increased attention over the last decade. The purpose of this article is to clarify the various meanings that have been assigned to the term syndromic surveillance and to propose a refined categorization of the characteristics of these systems. Existing literature and conference proceedings were examined on syndromic surveillance from 1998 to 2010, focusing on low- and middle-income settings. Based on the 36 unique definitions of syndromic surveillance found in the literature, five commonly accepted principles of syndromic surveillance systems were identified, as well as two fundamental categories: specific and non-specific disease detection. Ultimately, the proposed categorization of syndromic surveillance distinguishes between systems that focus on detecting defined syndromes or outcomes of interest and those that aim to uncover non-specific trends that suggest an outbreak may be occurring. By providing an accurate and comprehensive picture of this field’s capabilities, and differentiating among system types, a unified understanding of the syndromic surveillance field can be developed, encouraging the adoption, investment in, and implementation of these systems in settings that need bolstered surveillance capacity, particularly low- and middle-income countries.

Congenital rubella syndrome surveillance as a platform for surveillance of other congenital infections, Peru, 2004-2007.

Science.gov (United States)

Whittembury, Alvaro; Galdos, Jorge; Lugo, María; Suárez-Ognio, Luis; Ortiz, Ana; Cabezudo, Edwin; Martínez, Mario; Castillo-Solórzano, Carlos; Andrus, Jon Kim

2011-09-01

Rubella during pregnancy can cause serious fetal abnormalities and death. Peru has had integrated measles/rubella surveillance since 2000 but did not implement congenital rubella syndrome (CRS) surveillance until 2004, in accordance with the Pan American Health Organization recommendations for rubella elimination. The article describes the experience from the CRS sentinel surveillance system in Peru. Peru has maintained a national sentinel surveillance system for reporting confirmed and suspected CRS cases since 2004. A surveillance protocol was implemented with standardized case definitions and instruments in the selected sentinel sites. Each sentinel site completes their case investigations and report forms and sends the reports to the Health Region Epidemiology Department, which forwards the data to the national Epidemiology Department. CRS surveillance data were analyzed for the period 2004-2007. During the period 2004-2007, 16 health facilities, which are located in 9 of the 33 health regions, representing the 3 main geographical areas (coast, mountain, and jungle), were included as sentinel sites for the CRS surveillance. A total of 2061 suspected CRS cases were reported to the system. Of these, 11 were classified as CRS and 23 as congenital rubella infection. Factors significantly associated with rubella vertical transmission were: (1) in the mother, maternal history of rash during pregnancy (odds ratio [OR], 12.0; 95% confidence interval [CI], 3.8-37.8); (2) and in the infant, pigmentary retinopathy (OR, 18.4; 95% CI, 3.2-104.6), purpura (OR, 14.7; 95% CI, 2.8-78.3), and developmental delay (OR, 4.4; 95% CI, 1.75-11.1). The surveillance system has been able to identify rubella vertical transmission, reinforcing the evidence that rubella was a public health problem in Peru. This system may serve as a platform to implement surveillance for other congenital infections in Peru.

Strengthening foodborne disease surveillance in the WHO African

African Journals Online (AJOL)

OMS

2012-06-04

Jun 4, 2012 ... region including acute aflatoxicosis in Kenya in 2004 and bromide poisoning in ... Global Food Infections Network (GFN), has been supporting countries to strengthen ... The surveillance system uses standard case definitions for classifying .... Figure 4: Participating countries and training sites for foodborne.

Twitter Influenza Surveillance: Quantifying Seasonal Misdiagnosis Patterns and their Impact on Surveillance Estimates.

Science.gov (United States)

Mowery, Jared

2016-01-01

Influenza (flu) surveillance using Twitter data can potentially save lives and increase efficiency by providing governments and healthcare organizations with greater situational awareness. However, research is needed to determine the impact of Twitter users' misdiagnoses on surveillance estimates. This study establishes the importance of Twitter users' misdiagnoses by showing that Twitter flu surveillance in the United States failed during the 2011-2012 flu season, estimates the extent of misdiagnoses, and tests several methods for reducing the adverse effects of misdiagnoses. Metrics representing flu prevalence, seasonal misdiagnosis patterns, diagnosis uncertainty, flu symptoms, and noise were produced using Twitter data in conjunction with OpenSextant for geo-inferencing, and a maximum entropy classifier for identifying tweets related to illness. These metrics were tested for correlations with World Health Organization (WHO) positive specimen counts of flu from 2011 to 2014. Twitter flu surveillance erroneously indicated a typical flu season during 2011-2012, even though the flu season peaked three months late, and erroneously indicated plateaus of flu tweets before the 2012-2013 and 2013-2014 flu seasons. Enhancements based on estimates of misdiagnoses removed the erroneous plateaus and increased the Pearson correlation coefficients by .04 and .23, but failed to correct the 2011-2012 flu season estimate. A rough estimate indicates that approximately 40% of flu tweets reflected misdiagnoses. Further research into factors affecting Twitter users' misdiagnoses, in conjunction with data from additional atypical flu seasons, is needed to enable Twitter flu surveillance systems to produce reliable estimates during atypical flu seasons.

Fingerprint prediction using classifier ensembles

CSIR Research Space (South Africa)

Molale, P

2011-11-01

Full Text Available ); logistic discrimination (LgD), k-nearest neighbour (k-NN), artificial neural network (ANN), association rules (AR) decision tree (DT), naive Bayes classifier (NBC) and the support vector machine (SVM). The performance of several multiple classifier systems...

Outdoor Air Quality Level Inference via Surveillance Cameras

Directory of Open Access Journals (Sweden)

Zheng Zhang

2016-01-01

Full Text Available Air pollution is a universal problem confronted by many developing countries. Because there are very few air quality monitoring stations in cities, it is difficult for people to know the exact air quality level anytime and anywhere. Fortunately, large amount of surveillance cameras have been deployed in the cities and can capture image densely and conveniently in the cities. In this case, this provides the possibility to utilize surveillance cameras as sensors to obtain data and predict the air quality level. To this end, we present a novel air quality level inference approach based on outdoor images. Firstly, we explore several features extracted from images as the robust representation for air quality prediction. Then, to effectively fuse these heterogeneous and complementary features, we adopt multikernel learning to learn an adaptive classifier for air quality level inference. In addition, to facilitate the research, we construct an Outdoor Air Quality Image Set (OAQIS dataset, which contains high quality registered and calibrated images with rich labels, that is, concentration of particles mass (PM, weather, temperature, humidity, and wind. Extensive experiments on the OAQIS dataset demonstrate the effectiveness of the proposed approach.

An efficient approach for surveillance of childhood diabetes by type derived from electronic health record data: the SEARCH for Diabetes in Youth Study

Science.gov (United States)

Zhong, Victor W; Obeid, Jihad S; Craig, Jean B; Pfaff, Emily R; Thomas, Joan; Jaacks, Lindsay M; Beavers, Daniel P; Carey, Timothy S; Lawrence, Jean M; Dabelea, Dana; Hamman, Richard F; Bowlby, Deborah A; Pihoker, Catherine; Saydah, Sharon H

2016-01-01

Objective To develop an efficient surveillance approach for childhood diabetes by type across 2 large US health care systems, using phenotyping algorithms derived from electronic health record (EHR) data. Materials and Methods Presumptive diabetes cases diabetes-related billing codes, patient problem list, and outpatient anti-diabetic medications. EHRs of all the presumptive cases were manually reviewed, and true diabetes status and diabetes type were determined. Algorithms for identifying diabetes cases overall and classifying diabetes type were either prespecified or derived from classification and regression tree analysis. Surveillance approach was developed based on the best algorithms identified. Results We developed a stepwise surveillance approach using billing code–based prespecified algorithms and targeted manual EHR review, which efficiently and accurately ascertained and classified diabetes cases by type, in both health care systems. The sensitivity and positive predictive values in both systems were approximately ≥90% for ascertaining diabetes cases overall and classifying cases with type 1 or type 2 diabetes. About 80% of the cases with “other” type were also correctly classified. This stepwise surveillance approach resulted in a >70% reduction in the number of cases requiring manual validation compared to traditional surveillance methods. Conclusion EHR data may be used to establish an efficient approach for large-scale surveillance for childhood diabetes by type, although some manual effort is still needed. PMID:27107449

Text mining electronic hospital records to automatically classify admissions against disease: Measuring the impact of linking data sources.

Science.gov (United States)

Kocbek, Simon; Cavedon, Lawrence; Martinez, David; Bain, Christopher; Manus, Chris Mac; Haffari, Gholamreza; Zukerman, Ingrid; Verspoor, Karin

2016-12-01

Text and data mining play an important role in obtaining insights from Health and Hospital Information Systems. This paper presents a text mining system for detecting admissions marked as positive for several diseases: Lung Cancer, Breast Cancer, Colon Cancer, Secondary Malignant Neoplasm of Respiratory and Digestive Organs, Multiple Myeloma and Malignant Plasma Cell Neoplasms, Pneumonia, and Pulmonary Embolism. We specifically examine the effect of linking multiple data sources on text classification performance. Support Vector Machine classifiers are built for eight data source combinations, and evaluated using the metrics of Precision, Recall and F-Score. Sub-sampling techniques are used to address unbalanced datasets of medical records. We use radiology reports as an initial data source and add other sources, such as pathology reports and patient and hospital admission data, in order to assess the research question regarding the impact of the value of multiple data sources. Statistical significance is measured using the Wilcoxon signed-rank test. A second set of experiments explores aspects of the system in greater depth, focusing on Lung Cancer. We explore the impact of feature selection; analyse the learning curve; examine the effect of restricting admissions to only those containing reports from all data sources; and examine the impact of reducing the sub-sampling. These experiments provide better understanding of how to best apply text classification in the context of imbalanced data of variable completeness. Radiology questions plus patient and hospital admission data contribute valuable information for detecting most of the diseases, significantly improving performance when added to radiology reports alone or to the combination of radiology and pathology reports. Overall, linking data sources significantly improved classification performance for all the diseases examined. However, there is no single approach that suits all scenarios; the choice of the

A Supervised Multiclass Classifier for an Autocoding System

Directory of Open Access Journals (Sweden)

Yukako Toko

2017-11-01

Full Text Available Classification is often required in various contexts, including in the field of official statistics. In the previous study, we have developed a multiclass classifier that can classify short text descriptions with high accuracy. The algorithm borrows the concept of the naïve Bayes classifier and is so simple that its structure is easily understandable. The proposed classifier has the following two advantages. First, the processing times for both learning and classifying are extremely practical. Second, the proposed classifier yields high-accuracy results for a large portion of a dataset. We have previously developed an autocoding system for the Family Income and Expenditure Survey in Japan that has a better performing classifier. While the original system was developed in Perl in order to improve the efficiency of the coding process of short Japanese texts, the proposed system is implemented in the R programming language in order to explore versatility and is modified to make the system easily applicable to English text descriptions, in consideration of the increasing number of R users in the field of official statistics. We are planning to publish the proposed classifier as an R-package. The proposed classifier would be generally applicable to other classification tasks including coding activities in the field of official statistics, and it would contribute greatly to improving their efficiency.

Window of Opportunity for New Disease Surveillance: Developing Keyword Lists for Monitoring Mental Health and Injury Through Syndromic Surveillance.

Science.gov (United States)

Lauper, Ursula; Chen, Jian-Hua; Lin, Shao

2017-04-01

Studies have documented the impact that hurricanes have on mental health and injury rates before, during, and after the event. Since timely tracking of these disease patterns is crucial to disaster planning, response, and recovery, syndromic surveillance keyword filters were developed by the New York State Department of Health to study the short- and long-term impacts of Hurricane Sandy. Emergency department syndromic surveillance is recognized as a valuable tool for informing public health activities during and immediately following a disaster. Data typically consist of daily visit reports from hospital emergency departments (EDs) of basic patient data and free-text chief complaints. To develop keyword lists, comparisons were made with existing CDC categories and then integrated with lists from the New York City and New Jersey health departments in a collaborative effort. Two comprehensive lists were developed, each containing multiple subcategories and over 100 keywords for both mental health and injury. The data classifiers using these keywords were used to assess impacts of Sandy on mental health and injuries in New York State. The lists will be validated by comparing the ED chief complaint keyword with the final ICD diagnosis code. (Disaster Med Public Health Preparedness. 2017;11:173-178).

Use of information barriers to protect classified information

International Nuclear Information System (INIS)

MacArthur, D.; Johnson, M.W.; Nicholas, N.J.; Whiteson, R.

1998-01-01

This paper discusses the detailed requirements for an information barrier (IB) for use with verification systems that employ intrusive measurement technologies. The IB would protect classified information in a bilateral or multilateral inspection of classified fissile material. Such a barrier must strike a balance between providing the inspecting party the confidence necessary to accept the measurement while protecting the inspected party's classified information. The authors discuss the structure required of an IB as well as the implications of the IB on detector system maintenance. A defense-in-depth approach is proposed which would provide assurance to the inspected party that all sensitive information is protected and to the inspecting party that the measurements are being performed as expected. The barrier could include elements of physical protection (such as locks, surveillance systems, and tamper indicators), hardening of key hardware components, assurance of capabilities and limitations of hardware and software systems, administrative controls, validation and verification of the systems, and error detection and resolution. Finally, an unclassified interface could be used to display and, possibly, record measurement results. The introduction of an IB into an analysis system may result in many otherwise innocuous components (detectors, analyzers, etc.) becoming classified and unavailable for routine maintenance by uncleared personnel. System maintenance and updating will be significantly simplified if the classification status of as many components as possible can be made reversible (i.e. the component can become unclassified following the removal of classified objects)

Classification of protein-protein interaction full-text documents using text and citation network features.

Science.gov (United States)

Kolchinsky, Artemy; Abi-Haidar, Alaa; Kaur, Jasleen; Hamed, Ahmed Abdeen; Rocha, Luis M

2010-01-01

We participated (as Team 9) in the Article Classification Task of the Biocreative II.5 Challenge: binary classification of full-text documents relevant for protein-protein interaction. We used two distinct classifiers for the online and offline challenges: 1) the lightweight Variable Trigonometric Threshold (VTT) linear classifier we successfully introduced in BioCreative 2 for binary classification of abstracts and 2) a novel Naive Bayes classifier using features from the citation network of the relevant literature. We supplemented the supplied training data with full-text documents from the MIPS database. The lightweight VTT classifier was very competitive in this new full-text scenario: it was a top-performing submission in this task, taking into account the rank product of the Area Under the interpolated precision and recall Curve, Accuracy, Balanced F-Score, and Matthew's Correlation Coefficient performance measures. The novel citation network classifier for the biomedical text mining domain, while not a top performing classifier in the challenge, performed above the central tendency of all submissions, and therefore indicates a promising new avenue to investigate further in bibliome informatics.

Arabic text classification using Polynomial Networks

Directory of Open Access Journals (Sweden)

Mayy M. Al-Tahrawi

2015-10-01

Full Text Available In this paper, an Arabic statistical learning-based text classification system has been developed using Polynomial Neural Networks. Polynomial Networks have been recently applied to English text classification, but they were never used for Arabic text classification. In this research, we investigate the performance of Polynomial Networks in classifying Arabic texts. Experiments are conducted on a widely used Arabic dataset in text classification: Al-Jazeera News dataset. We chose this dataset to enable direct comparisons of the performance of Polynomial Networks classifier versus other well-known classifiers on this dataset in the literature of Arabic text classification. Results of experiments show that Polynomial Networks classifier is a competitive algorithm to the state-of-the-art ones in the field of Arabic text classification.

Fragrances and work-related asthma-California surveillance data, 1993-2012.

Science.gov (United States)

Weinberg, Justine Lew; Flattery, Jennifer; Harrison, Robert

2017-12-01

Fragrance chemicals are used in a large array of products. Workers may be exposed to these chemicals in the workplace directly when used as air fresheners, or indirectly in personal care products used by coworkers or others. This study characterizes work-related asthma (WRA) cases associated with fragrance exposures in California workplaces from 1993 through 2012. We used the California Work-Related Asthma Prevention Program's surveillance database to identify individuals with physician-diagnosed WRA associated with the use of air fresheners and scented personal care products (perfumes, colognes, etc.). Cases were classified using previously published, standardized surveillance methods. Perfume was the ninth most common exposure identified from 1993 through 2012. A total of 270 WRA cases associated with fragrance exposure were reported during this period, representing 3.8% of all confirmed cases. These 270 cases included 242 associated with perfume or cologne, 32 associated with air freshener, and 4 associated with both. Similar to non-fragrance cases, nearly a quarter of fragrance-associated cases were classified as new-onset asthma. Fragrance-associated cases were significantly more likely to be in office, health, and education jobs than non-fragrance-associated cases. When compared to non-fragrance cases, fragrance cases were significantly more likely to be female (94% vs 62%) and be classified as having work-aggravated asthma (38% vs 20%), yet had similar outcomes compared with cases associated with other exposures. Our surveillance data show that fragrance use in the workplace is associated with WRA. Prevention methods include employee education, enforced fragrance-free policies, well-designed ventilation systems, and good building maintenance.

Evaluation of a Spotted Fever Group Rickettsia Public Health Surveillance System in Tennessee.

Science.gov (United States)

Fill, Mary-Margaret A; Moncayo, Abelardo C; Bloch, Karen C; Dunn, John R; Schaffner, William; Jones, Timothy F

2017-09-01

Spotted fever group (SFG) rickettsioses are endemic in Tennessee, with ∼2,500 cases reported during 2000-2012. Because of this substantial burden of disease, we performed a three-part evaluation of Tennessee's routine surveillance for SFG rickettsioses cases and deaths to assess the system's effectiveness. Tennessee Department of Health (TDH) SFG rickettsioses surveillance records were matched to three patient series: 1) patients with positive serologic specimens from a commercial reference laboratory during 2010-2011, 2) tertiary medical center patients with positive serologic tests during 2007-2013, and 3) patients identified from death certificates issued during 1995-2014 with SFG rickettsiosis-related causes of death. Chart reviews were performed and patients were classified according to the Council of State and Territorial Epidemiologists' case definition. Of 254 SFG Rickettsia -positive serologic specimens from the reference laboratory, 129 (51%) met the case definition for confirmed or probable cases of rickettsial disease after chart review. The sensitivity of the TDH surveillance system to detect cases was 45%. Of the 98 confirmed or probable cases identified from the medical center, the sensitivity of the TDH surveillance system to detect cases was 34%. Of 27 patients identified by death certificates, 12 (44%) were classified as confirmed or probable cases; four (33%) were reported to TDH, but none were correctly identified as deceased. Cases of SFG rickettsioses were underreported and fatalities not correctly identified. Efforts are needed to improve SFG rickettsiosis surveillance in Tennessee.

Influenza surveillance

Directory of Open Access Journals (Sweden)

Karolina Bednarska

2016-04-01

Full Text Available Influenza surveillance was established in 1947. From this moment WHO (World Health Organization has been coordinating international cooperation, with a goal of monitoring influenza virus activity, effective diagnostic of the circulating viruses and informing society about epidemics or pandemics, as well as about emergence of new subtypes of influenza virus type A. Influenza surveillance is an important task, because it enables people to prepare themselves for battle with the virus that is constantly mutating, what leads to circulation of new and often more virulent strains of influenza in human population. As vaccination is the most effective method of fighting the virus, one of the major tasks of GISRS is developing an optimal antigenic composition of the vaccine for the current epidemic season. European Influenza Surveillance Network (EISN has also developed over the years. EISN is running integrated epidemiological and virological influenza surveillance, to provide appropriate data to public health experts in member countries, to enable them undertaking relevant activities based on the current information about influenza activity. In close cooperation with GISRS and EISN are National Influenza Centres - national institutions designated by the Ministry of Health in each country.

Enhanced surveillance program FY97 accomplishments. Progress report

Energy Technology Data Exchange (ETDEWEB)

Mauzy, A. [ed.; Laake, B. [comp.

1997-10-01

This annual report is one volume of the Enhanced Surveillance Program (ESP) FY97 Accomplishments. The complete accomplishments report consists of 11 volumes. Volume 1 includes an ESP overview and a summary of selected unclassified FY97 program highlights. Volume 1 specifically targets a general audience, reflecting about half of the tasks conducted in FY97 and emphasizing key program accomplishments and contributions. The remaining volumes of the accomplishments report are classified, organized by program focus area, and present in technical detail the progress achieved in each of the 104 FY97 program tasks. Focus areas are as follows: pits; high explosives; organics; dynamics; diagnostics; systems; secondaries; nonnuclear materials; nonnuclear components; and Surveillance Test Program upgrades.

Applied learning-based color tone mapping for face recognition in video surveillance system

Science.gov (United States)

Yew, Chuu Tian; Suandi, Shahrel Azmin

2012-04-01

In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

Microbiological Food Safety Surveillance in China

Directory of Open Access Journals (Sweden)

Xiaoyan Pei

2015-08-01

Full Text Available Microbiological food safety surveillance is a system that collects data regarding food contamination by foodborne pathogens, parasites, viruses, and other harmful microbiological factors. It helps to understand the spectrum of food safety, timely detect food safety hazards, and provide relevant data for food safety supervision, risk assessment, and standards-setting. The study discusses the microbiological surveillance of food safety in China, and introduces the policies and history of the national microbiological surveillance system. In addition, the function and duties of different organizations and institutions are provided in this work, as well as the generation and content of the surveillance plan, quality control, database, and achievement of the microbiological surveillance of food safety in China.

Layout-aware text extraction from full-text PDF of scientific articles

Directory of Open Access Journals (Sweden)

Ramakrishnan Cartic

2012-05-01

Full Text Available Abstract Background The Portable Document Format (PDF is the most commonly used file format for online scientific publications. The absence of effective means to extract text from these PDF files in a layout-aware manner presents a significant challenge for developers of biomedical text mining or biocuration informatics systems that use published literature as an information source. In this paper we introduce the ‘Layout-Aware PDF Text Extraction’ (LA-PDFText system to facilitate accurate extraction of text from PDF files of research articles for use in text mining applications. Results Our paper describes the construction and performance of an open source system that extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles and is meant as a baseline for further experiments into more advanced extraction methods that handle multi-modal content, such as images and graphs. The system works in a three-stage process: (1 Detecting contiguous text blocks using spatial layout processing to locate and identify blocks of contiguous text, (2 Classifying text blocks into rhetorical categories using a rule-based method and (3 Stitching classified text blocks together in the correct order resulting in the extraction of text from section-wise grouped blocks. We show that our system can identify text blocks and classify them into rhetorical categories with Precision1 = 0.96% Recall = 0.89% and F1 = 0.91%. We also present an evaluation of the accuracy of the block detection algorithm used in step 2. Additionally, we have compared the accuracy of the text extracted by LA-PDFText to the text from the Open Access subset of PubMed Central. We then compared this accuracy with that of the text extracted by the PDF2Text system, 2commonly used to extract text from PDF

Layout-aware text extraction from full-text PDF of scientific articles.

Science.gov (United States)

Ramakrishnan, Cartic; Patnia, Abhishek; Hovy, Eduard; Burns, Gully Apc

2012-05-28

The Portable Document Format (PDF) is the most commonly used file format for online scientific publications. The absence of effective means to extract text from these PDF files in a layout-aware manner presents a significant challenge for developers of biomedical text mining or biocuration informatics systems that use published literature as an information source. In this paper we introduce the 'Layout-Aware PDF Text Extraction' (LA-PDFText) system to facilitate accurate extraction of text from PDF files of research articles for use in text mining applications. Our paper describes the construction and performance of an open source system that extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles and is meant as a baseline for further experiments into more advanced extraction methods that handle multi-modal content, such as images and graphs. The system works in a three-stage process: (1) Detecting contiguous text blocks using spatial layout processing to locate and identify blocks of contiguous text, (2) Classifying text blocks into rhetorical categories using a rule-based method and (3) Stitching classified text blocks together in the correct order resulting in the extraction of text from section-wise grouped blocks. We show that our system can identify text blocks and classify them into rhetorical categories with Precision1 = 0.96% Recall = 0.89% and F1 = 0.91%. We also present an evaluation of the accuracy of the block detection algorithm used in step 2. Additionally, we have compared the accuracy of the text extracted by LA-PDFText to the text from the Open Access subset of PubMed Central. We then compared this accuracy with that of the text extracted by the PDF2Text system, 2commonly used to extract text from PDF. Finally, we discuss preliminary error analysis for

World Alliance for Risk Factor Surveillance White Paper on Surveillance and Health Promotion

Directory of Open Access Journals (Sweden)

Stefano Campostrini

2015-02-01

Full Text Available This is not a research paper on risk factor surveillance. It is an effort by a key group of researchers and practitioners of risk factor surveillance to define the current state of the art and to identify the key issues involved in the current practice of behavioral risk factor surveillance. Those of us who are the principal authors have worked and carried out research in this area for some three decades. As a result of a series of global meetings beginning in 1999 and continuing every two years since then, a collective working group of the International Union of Health Promotion and Education (IUHPE was formed under the name World Alliance of Risk Factor Surveillance (WARFS. Under this banner the organization sought to write a comprehensive statement on the importance of surveillance to health promotion and public health. This paper, which has been revised and reviewed by established peers in the field, is the result. It provides the reader with a clear summary of the major issues that need to be considered by any and all seeking to carry out behavioral risk factor surveillance.

Hybrid Neuro-Fuzzy Classifier Based On Nefclass Model

Directory of Open Access Journals (Sweden)

Bogdan Gliwa

2011-01-01

Full Text Available The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which wasmodified. The presented classifier was compared to popular classifiers – neural networks andk-nearest neighbours. Efficiency of modifications in classifier was compared with methodsused in original model NEFCLASS (learning methods. Accuracy of classifier was testedusing 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin.Moreover, influence of ensemble classification methods on classification accuracy waspresented.

Surveillance of surgical site infection after cholecystectomy using the hospital in Europe link for infection control through surveillance protocol.

Science.gov (United States)

Bogdanic, Branko; Bosnjak, Zrinka; Budimir, Ana; Augustin, Goran; Milosevic, Milan; Plecko, Vanda; Kalenic, Smilja; Fiolic, Zlatko; Vanek, Maja

2013-06-01

The third most common healthcare-associated infection is surgical site infection (SSI), accounting for 14%-16% of infections. These SSIs are associated with high morbidity, numerous deaths, and greater cost. A prospective study was conducted to assess the incidence of SSI in a single university hospital in Croatia. We used the Hospital in Europe Link for Infection Control through Surveillance (HELICS) protocol for surveillance. The SSIs were classified using the standard definition of the National Nosocomial Infections Surveillance (NNIS) system. The overall incidence of SSI was 1.44%. The incidence of infection in the open cholecystectomy group was 6.06%, whereas in the laparoscopic group, it was only 0.60%. The incidence density of in-hospital SSIs per 1,000 post-operative days was 5.76. Patients who underwent a laparoscopic cholecystectomy were significantly younger (53.65±14.65 vs. 64.42±14.17 years; pconcept for the monitoring of SSI, but in the case of cholecystectomy, additional factors such as antibiotic appropriateness, gallbladder entry, empyema of the gallbladder, and obstructive jaundice must be considered.

Information Gain Based Dimensionality Selection for Classifying Text Documents

Energy Technology Data Exchange (ETDEWEB)

Dumidu Wijayasekara; Milos Manic; Miles McQueen

2013-06-01

Selecting the optimal dimensions for various knowledge extraction applications is an essential component of data mining. Dimensionality selection techniques are utilized in classification applications to increase the classification accuracy and reduce the computational complexity. In text classification, where the dimensionality of the dataset is extremely high, dimensionality selection is even more important. This paper presents a novel, genetic algorithm based methodology, for dimensionality selection in text mining applications that utilizes information gain. The presented methodology uses information gain of each dimension to change the mutation probability of chromosomes dynamically. Since the information gain is calculated a priori, the computational complexity is not affected. The presented method was tested on a specific text classification problem and compared with conventional genetic algorithm based dimensionality selection. The results show an improvement of 3% in the true positives and 1.6% in the true negatives over conventional dimensionality selection methods.

Genomic Analysis and Surveillance of the Coronavirus Dominant in Ducks in China.

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Qing-Ye Zhuang

Full Text Available The genetic diversity, evolution, distribution, and taxonomy of some coronaviruses dominant in birds other than chickens remain enigmatic. In this study we sequenced the genome of a newly identified coronavirus dominant in ducks (DdCoV, and performed a large-scale surveillance of coronaviruses in chickens and ducks using a conserved RT-PCR assay. The viral genome harbors a tandem repeat which is rare in vertebrate RNA viruses. The repeat is homologous to some proteins of various cellular organisms, but its origin remains unknown. Many substitutions, insertions, deletions, and some frameshifts and recombination events have occurred in the genome of the DdCoV, as compared with the coronavirus dominant in chickens (CdCoV. The distances between DdCoV and CdCoV are large enough to separate them into different species within the genus Gammacoronavirus. Our surveillance demonstrated that DdCoVs and CdCoVs belong to different lineages and occupy different ecological niches, further supporting that they should be classified into different species. Our surveillance also demonstrated that DdCoVs and CdCoVs are prevalent in live poultry markets in some regions of China. In conclusion, this study shed novel insight into the genetic diversity, evolution, distribution, and taxonomy of the coronaviruses circulating in chickens and ducks.

Text mining in the classification of digital documents

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Marcial Contreras Barrera

2016-11-01

Full Text Available Objective: Develop an automated classifier for the classification of bibliographic material by means of the text mining. Methodology: The text mining is used for the development of the classifier, based on a method of type supervised, conformed by two phases; learning and recognition, in the learning phase, the classifier learns patterns across the analysis of bibliographical records, of the classification Z, belonging to library science, information sciences and information resources, recovered from the database LIBRUNAM, in this phase is obtained the classifier capable of recognizing different subclasses (LC. In the recognition phase the classifier is validated and evaluates across classification tests, for this end bibliographical records of the classification Z are taken randomly, classified by a cataloguer and processed by the automated classifier, in order to obtain the precision of the automated classifier. Results: The application of the text mining achieved the development of the automated classifier, through the method classifying documents supervised type. The precision of the classifier was calculated doing the comparison among the assigned topics manually and automated obtaining 75.70% of precision. Conclusions: The application of text mining facilitated the creation of automated classifier, allowing to obtain useful technology for the classification of bibliographical material with the aim of improving and speed up the process of organizing digital documents.

Critical Surveillance Studies in the Information Society

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Thomas Allmer

2011-11-01

Full Text Available The overall aim of this paper is to clarify how we can theorize and systemize economic surveillance. Surveillance studies scholars like David Lyon stress that economic surveillance such as monitoring consumers or the workplace are central aspects of surveillance societies. The approach that is advanced in this work recognizes the importance of the role of the economy in contemporary surveillance societies. The paper at hand constructs theoretically founded typologies in order to systemize the existing literature of surveillance studies and to analyze examples of surveillance. Therefore, it mainly is a theoretical approach combined with illustrative examples. This contribution contains a systematic discussion of the state of the art of surveillance and clarifies how different notions treat economic aspects of surveillance. In this work it is argued that the existing literature is insufficient for studying economic surveillance. In contrast, a typology of surveillance in the modern economy, which is based on foundations of a political economy approach, allows providing a systematic analysis of economic surveillance on the basis of current developments on the Internet. Finally, some political recommendations are drawn in order to overcome economic surveillance. This contribution can be fruitful for scholars who want to undertake a systematic analysis of surveillance in the modern economy and who want to study the field of surveillance critically.

Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

Science.gov (United States)

Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen

2014-02-01

The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

SpectraClassifier 1.0: a user friendly, automated MRS-based classifier-development system

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Julià-Sapé Margarida

2010-02-01

Full Text Available Abstract Background SpectraClassifier (SC is a Java solution for designing and implementing Magnetic Resonance Spectroscopy (MRS-based classifiers. The main goal of SC is to allow users with minimum background knowledge of multivariate statistics to perform a fully automated pattern recognition analysis. SC incorporates feature selection (greedy stepwise approach, either forward or backward, and feature extraction (PCA. Fisher Linear Discriminant Analysis is the method of choice for classification. Classifier evaluation is performed through various methods: display of the confusion matrix of the training and testing datasets; K-fold cross-validation, leave-one-out and bootstrapping as well as Receiver Operating Characteristic (ROC curves. Results SC is composed of the following modules: Classifier design, Data exploration, Data visualisation, Classifier evaluation, Reports, and Classifier history. It is able to read low resolution in-vivo MRS (single-voxel and multi-voxel and high resolution tissue MRS (HRMAS, processed with existing tools (jMRUI, INTERPRET, 3DiCSI or TopSpin. In addition, to facilitate exchanging data between applications, a standard format capable of storing all the information needed for a dataset was developed. Each functionality of SC has been specifically validated with real data with the purpose of bug-testing and methods validation. Data from the INTERPRET project was used. Conclusions SC is a user-friendly software designed to fulfil the needs of potential users in the MRS community. It accepts all kinds of pre-processed MRS data types and classifies them semi-automatically, allowing spectroscopists to concentrate on interpretation of results with the use of its visualisation tools.

The Copyright Surveillance Industry

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Mike Zajko

2015-09-01

Full Text Available Creative works are now increasingly distributed as digital “content” through the internet, and copyright law has created powerful incentives to monitor and control these flows. This paper analyzes the surveillance industry that has emerged as a result. Copyright surveillance systems identify copyright infringement online and identify persons to hold responsible for infringing acts. These practices have raised fundamental questions about the nature of identification and attribution on the internet, as well as the increasing use of algorithms to make legal distinctions. New technologies have threatened the profits of some media industries through copyright infringement, but also enabled profitable forms of mass copyright surveillance and enforcement. Rather than a system of perfect control, copyright enforcement continues to be selective and uneven, but its broad reach results in systemic harm and provides opportunities for exploitation. It is only by scrutinizing copyright surveillance practices and copyright enforcement measures that we can evaluate these consequences.

Sanitary surveillance and bioethics

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Volnei Garrafa

2017-08-01

Full Text Available Regulatory practices in the field of health surveillance are indispensable. The aim of this study is to show ‒ taking the Brazilian National Surveillance Agency, governing body of sanitary surveillance in Brazil as a reference ‒ that bioethics provides public bodies a series of theoretical tools from the field of applied ethics for the proper exercise and control of these practices. To that end, the work uses two references of bioethics for the development of a comparative and supportive analysis to regulatory activities in the field of health surveillance: the Universal Declaration on Bioethics and Human Rights of Unesco and the theory of intervention bioethics. We conclude that organizations and staff working with regulatory activities can take advantage of the principles and frameworks proposed by bioethics, especially those related to the Declaration and the theory of intervention bioethics, the latter being set by the observation and use of the principles of prudence, precaution, protection and prevention.

A GIS-driven integrated real-time surveillance pilot system for national West Nile virus dead bird surveillance in Canada

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Aramini Jeff

2006-04-01

Full Text Available Abstract Background An extensive West Nile virus surveillance program of dead birds, mosquitoes, horses, and human infection has been launched as a result of West Nile virus first being reported in Canada in 2001. Some desktop and web GIS have been applied to West Nile virus dead bird surveillance. There have been urgent needs for a comprehensive GIS services and real-time surveillance. Results A pilot system was developed to integrate real-time surveillance, real-time GIS, and Open GIS technology in order to enhance West Nile virus dead bird surveillance in Canada. Driven and linked by the newly developed real-time web GIS technology, this integrated real-time surveillance system includes conventional real-time web-based surveillance components, integrated real-time GIS components, and integrated Open GIS components. The pilot system identified the major GIS functions and capacities that may be important to public health surveillance. The six web GIS clients provide a wide range of GIS tools for public health surveillance. The pilot system has been serving Canadian national West Nile virus dead bird surveillance since 2005 and is adaptable to serve other disease surveillance. Conclusion This pilot system has streamlined, enriched and enhanced national West Nile virus dead bird surveillance in Canada, improved productivity, and reduced operation cost. Its real-time GIS technology, static map technology, WMS integration, and its integration with non-GIS real-time surveillance system made this pilot system unique in surveillance and public health GIS.

Robust Framework to Combine Diverse Classifiers Assigning Distributed Confidence to Individual Classifiers at Class Level

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Shehzad Khalid

2014-01-01

Full Text Available We have presented a classification framework that combines multiple heterogeneous classifiers in the presence of class label noise. An extension of m-Mediods based modeling is presented that generates model of various classes whilst identifying and filtering noisy training data. This noise free data is further used to learn model for other classifiers such as GMM and SVM. A weight learning method is then introduced to learn weights on each class for different classifiers to construct an ensemble. For this purpose, we applied genetic algorithm to search for an optimal weight vector on which classifier ensemble is expected to give the best accuracy. The proposed approach is evaluated on variety of real life datasets. It is also compared with existing standard ensemble techniques such as Adaboost, Bagging, and Random Subspace Methods. Experimental results show the superiority of proposed ensemble method as compared to its competitors, especially in the presence of class label noise and imbalance classes.

Extending cluster lot quality assurance sampling designs for surveillance programs.

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Hund, Lauren; Pagano, Marcello

2014-07-20

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance on the basis of the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible nonparametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. Copyright © 2014 John Wiley & Sons, Ltd.

Nutritional surveillance.

Science.gov (United States)

Mason, J B; Mitchell, J T

1983-01-01

The concept of nutritional surveillance is derived from disease surveillance, and means "to watch over nutrition, in order to make decisions that lead to improvements in nutrition in populations". Three distinct objectives have been defined for surveillance systems, primarily in relation to problems of malnutrition in developing countries: to aid long-term planning in health and development; to provide input for programme management and evaluation; and to give timely warning of the need for intervention to prevent critical deteriorations in food consumption. Decisions affecting nutrition are made at various administrative levels, and the uses of different types of nutritional surveillance information can be related to national policies, development programmes, public health and nutrition programmes, and timely warning and intervention programmes. The information should answer specific questions, for example concerning the nutritional status and trends of particular population groups.Defining the uses and users of the information is the first essential step in designing a system; this is illustrated with reference to agricultural and rural development planning, the health sector, and nutrition and social welfare programmes. The most usual data outputs are nutritional outcome indicators (e.g., prevalence of malnutrition among preschool children), disaggregated by descriptive or classifying variables, of which the commonest is simply administrative area. Often, additional "status" indicators, such as quality of housing or water supply, are presented at the same time. On the other hand, timely warning requires earlier indicators of the possibility of nutritional deterioration, and agricultural indicators are often the most appropriate.DATA COME FROM TWO MAIN TYPES OF SOURCE: administrative (e.g., clinics and schools) and household sample surveys. Each source has its own advantages and disadvantages: for example, administrative data often already exist, and can be

A CLASSIFIER SYSTEM USING SMOOTH GRAPH COLORING

Directory of Open Access Journals (Sweden)

JORGE FLORES CRUZ

2017-01-01

Full Text Available Unsupervised classifiers allow clustering methods with less or no human intervention. Therefore it is desirable to group the set of items with less data processing. This paper proposes an unsupervised classifier system using the model of soft graph coloring. This method was tested with some classic instances in the literature and the results obtained were compared with classifications made with human intervention, yielding as good or better results than supervised classifiers, sometimes providing alternative classifications that considers additional information that humans did not considered.

A new entropy function for feature extraction with the refined scores as a classifier for the unconstrained ear verification

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Mamta Bansal

2017-05-01

Full Text Available For high end security like surveillance there is a need for a robust system capable of verifying a person under the unconstrained conditions. This paper presents the ear based verification system using a new entropy function that changes not only the information gain function but also the information source values. This entropy function displays peculiar characteristics such as splitting into two modes. Two types of entropy features: Effective Gaussian Information source value and Effective Exponential Information source value functions are derived using the entropy function. To classify the entropy features we have devised refined scores (RS method that refines the scores generated using the Euclidean distance. The experimental results vindicate the superiority of proposed method over literature.

N-CDAD in Canada: Results of the Canadian Nosocomial Infection Surveillance Program 1997 N-CDAD Prevalence Surveillance Project

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Meaghen Hyland

2001-01-01

Full Text Available BACKGROUND: A 1996 preproject survey among Canadian Hospital Epidemiology Committee (CHEC sites revealed variations in the prevention, detection, management and surveillance of Clostridium difficile-associated diarrhea (CDAD. Facilities wanted to establish national rates of nosocomially acquired CDAD (N-CDAD to understand the impact of control or prevention measures, and the burden of N-CDAD on health care resources. The CHEC, in collaboration with the Laboratory Centre for Disease Control (Health Canada and under the Canadian Nosocomial Infection Surveillance Program, undertook a prevalence surveillance project among selected hospitals throughout Canada.

Implementation of a data fusion algorithm for RODS, a real-time outbreak and disease surveillance system.

Energy Technology Data Exchange (ETDEWEB)

Brown, Douglas (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA)

2005-10-01

Due to the nature of many infectious agents, such as anthrax, symptoms may either take several days to manifest or resemble those of less serious illnesses leading to misdiagnosis. Thus, bioterrorism attacks that include the release of such agents are particularly dangerous and potentially deadly. For this reason, a system is needed for the quick and correct identification of disease outbreaks. The Real-time Outbreak Disease Surveillance System (RODS), initially developed by Carnegie Mellon University and the University of Pittsburgh, was created to meet this need. The RODS software implements different classifiers for pertinent health surveillance data in order to determine whether or not an outbreak has occurred. In an effort to improve the capability of RODS at detecting outbreaks, we incorporate a data fusion method. Data fusion is used to improve the results of a single classification by combining the output of multiple classifiers. This paper documents the first stages of the development of a data fusion system that can combine the output of the classifiers included in RODS.

Informatics enables public health surveillance

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Scott J. N McNabb

2017-01-01

Full Text Available Over the past decade, the world has radically changed. New advances in information and communication technologies (ICT connect the world in ways never imagined. Public health informatics (PHI leveraged for public health surveillance (PHS, can enable, enhance, and empower essential PHS functions (i.e., detection, reporting, confirmation, analyses, feedback, response. However, the tail doesn't wag the dog; as such, ICT cannot (should not drive public health surveillance strengthening. Rather, ICT can serve PHS to more effectively empower core functions. In this review, we explore promising ICT trends for prevention, detection, and response, laboratory reporting, push notification, analytics, predictive surveillance, and using new data sources, while recognizing that it is the people, politics, and policies that most challenge progress for implementation of solutions.

Intelligent Garbage Classifier

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Ignacio Rodríguez Novelle

2008-12-01

Full Text Available IGC (Intelligent Garbage Classifier is a system for visual classification and separation of solid waste products. Currently, an important part of the separation effort is based on manual work, from household separation to industrial waste management. Taking advantage of the technologies currently available, a system has been built that can analyze images from a camera and control a robot arm and conveyor belt to automatically separate different kinds of waste.

Towards One Health disease surveillance: The Southern African Centre for Infectious Disease Surveillance approach

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Esron D. Karimuribo

2012-06-01

Full Text Available Africa has the highest burden of infectious diseases in the world and yet the least capacity for its risk management. It has therefore become increasingly important to search for ‘fit-for- purpose’ approaches to infectious disease surveillance and thereby targeted disease control. The fact that the majority of human infectious diseases are originally of animal origin means we have to consider One Health (OH approaches which require inter-sectoral collaboration for custom-made infectious disease surveillance in the endemic settings of Africa. A baseline survey was conducted to assess the current status and performance of human and animal health surveillance systems and subsequently a strategy towards OH surveillance system was developed. The strategy focused on assessing the combination of participatory epidemiological approaches and the deployment of mobile technologies to enhance the effectiveness of disease alerts and surveillance at the point of occurrence, which often lies in remote areas. We selected three study sites, namely the Ngorongoro, Kagera River basin and Zambezi River basin ecosystems. We have piloted and introduced the next-generation Android mobile phones running the EpiCollect application developed by Imperial College to aid geo-spatial and clinical data capture and transmission of this data from the field to the remote Information Technology (IT servers at the research hubs for storage, analysis, feedback and reporting. We expect that the combination of participatory epidemiology and technology will significantly improve OH disease surveillance in southern Africa.

Intelligent agents for adaptive security market surveillance

Science.gov (United States)

Chen, Kun; Li, Xin; Xu, Baoxun; Yan, Jiaqi; Wang, Huaiqing

2017-05-01

Market surveillance systems have increasingly gained in usage for monitoring trading activities in stock markets to maintain market integrity. Existing systems primarily focus on the numerical analysis of market activity data and generally ignore textual information. To fulfil the requirements of information-based surveillance, a multi-agent-based architecture that uses agent intercommunication and incremental learning mechanisms is proposed to provide a flexible and adaptive inspection process. A prototype system is implemented using the techniques of text mining and rule-based reasoning, among others. Based on experiments in the scalping surveillance scenario, the system can identify target information evidence up to 87.50% of the time and automatically identify 70.59% of cases depending on the constraints on the available information sources. The results of this study indicate that the proposed information surveillance system is effective. This study thus contributes to the market surveillance literature and has significant practical implications.

Naive Bayesian classifiers for multinomial features: a theoretical analysis

CSIR Research Space (South Africa)

Van Dyk, E

2007-11-01

Full Text Available The authors investigate the use of naive Bayesian classifiers for multinomial feature spaces and derive error estimates for these classifiers. The error analysis is done by developing a mathematical model to estimate the probability density...

Surveillance

DEFF Research Database (Denmark)

Albrechtslund, Anders; Coeckelbergh, Mark; Matzner, Tobias

Studying surveillance involves raising questions about the very nature of concepts such as information, technology, identity, space and power. Besides the maybe all too obvious ethical issues often discussed with regard to surveillance, there are several other angles and approaches that we should...... like to encourage. Therefore, our panel will focus on the philosophical, yet non-ethical issues of surveillance in order to stimulate an intense debate with the audience on the ethical implications of our enquiries. We also hope to provide a broader and deeper understanding of surveillance....

Liberal luxury: Decentering Snowden, surveillance and privilege

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Piro Rexhepi

2016-11-01

Full Text Available This paper reflects on the continued potency of veillance theories to traverse beyond the taxonomies of surveillance inside liberal democracies. It provides a commentary on the ability of sousveillance to destabilise and disrupt suer/violence by shifting its focus from the centre to the periphery, where Big Data surveillance is tantamount to sur/violence. In these peripheral political spaces, surveillance is not framed by concerns over privacy, democracy and civil society; rather, it is a matter of life and death, a technique of both biopolitical and thanatopolitical power. I argue that the universalist, and universalizing, debates over surveillance cannot be mapped through the anxieties of privileged middle classes as they would neither transcend nor make possible alternative ways of tackling the intersection of surveillance and violence so long as they are couched in the liberal concerns for democracy. I call this phenomenon “liberal luxury,” whereby debates over surveillance have over-emphasised liberal proclivities at the expense of disengaging those peripheral populations most severely affected by sur/violence.

Reviewing surveillance activities in nuclear power plants

International Nuclear Information System (INIS)

1989-03-01

This document provides guidance to Operational Safety Review Teams (OSARTs) for reviewing surveillance activities at a nuclear power plant. In addition, the document contains reference material to support the review of surveillance activities, to assist within the Technical Support area and to ensure consistency between individual reviews. Drafts of the document have already been used on several OSART missions and found to be useful. The document first considers the objectives of an excellent surveillance programme. Investigations to determine the quality of the surveillance programme are then discussed. The attributes of an excellent surveillance programme are listed. Advice follows on how to phrase questions so as to obtain an informative response on surveillance features. Finally, specific equipment is mentioned that should be considered when reviewing functional tests. Four annexes provide examples drawn from operating nuclear power plants. They were selected to supplement the main text of the document with the best international practices as found in OSART reviews. They should in no way limit the acceptance and development of alternative approaches that lead to equivalent or better results. Refs, figs and tabs

The role of supplementary environmental surveillance to complement acute flaccid paralysis surveillance for wild poliovirus in Pakistan - 2011-2013.

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Tori L Cowger

Full Text Available More than 99% of poliovirus infections are non-paralytic and therefore, not detected by acute flaccid paralysis (AFP surveillance. Environmental surveillance (ES can detect circulating polioviruses from sewage without relying on clinical presentation. With extensive ES and continued circulation of polioviruses, Pakistan presents a unique opportunity to quantify the impact of ES as a supplement to AFP surveillance on overall completeness and timeliness of poliovirus detection.Genetic, geographic and temporal data were obtained for all wild poliovirus (WPV isolates detected in Pakistan from January 2011 through December 2013. We used viral genetics to assess gaps in AFP surveillance and ES as measured by detection of 'orphan viruses' (≥1.5% different in VP1 capsid nucleotide sequence. We compared preceding detection of closely related circulating isolates (≥99% identity detected by AFP surveillance or ES to determine which surveillance system first detected circulation before the presentation of each polio case.A total of 1,127 WPV isolates were detected by AFP surveillance and ES in Pakistan from 2011-2013. AFP surveillance and ES combined exhibited fewer gaps (i.e., % orphan viruses in detection than AFP surveillance alone (3.3% vs. 7.7%, respectively. ES detected circulation before AFP surveillance in nearly 60% of polio cases (200 of 346. For polio cases reported from provinces conducting ES, ES detected circulation nearly four months sooner on average (117.6 days than did AFP surveillance.Our findings suggest ES in Pakistan is providing earlier, more sensitive detection of wild polioviruses than AFP surveillance alone. Overall, targeted ES through strategic selection of sites has important implications in the eradication endgame strategy.

Enhancing disease surveillance reporting using public transport in ...

African Journals Online (AJOL)

Enhancing disease surveillance reporting using public transport in Dodoma District, Central Tanzania. ... LEG Mboera, SF Rumisha, EJ Mwanemile, E Mziwanda, PK Mmbuji ... Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

Data characteristics that determine classifier performance

CSIR Research Space (South Africa)

Van der Walt, Christiaan M

2006-11-01

Full Text Available available at [11]. The kNN uses a LinearNN nearest neighbour search algorithm with an Euclidean distance metric [8]. The optimal k value is determined by performing 10-fold cross-validation. An optimal k value between 1 and 10 is used for Experiments 1... classifiers. 10-fold cross-validation is used to evaluate and compare the performance of the classifiers on the different data sets. 3.1. Artificial data generation Multivariate Gaussian distributions are used to generate artificial data sets. We use d...

History and evolution of surveillance in public health

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Varun Kumar

2014-01-01

Full Text Available The modern concept of surveillance has evolved over the centuries. Public health surveillance provides the scientific database essential for decision making and appropriate public health action. It is considered as the best public health tool to prevent the occurrence of epidemics and is the backbone of public health programs and provides information so that effective action can be taken in controlling and preventing diseases of public health importance. This article reviews the history of evolution of public health surveillance from historical perspective: from Hippocrates, Black Death and quarantine, recording of vital events for the first time, first field investigation, legislations that were developed over time and modern concepts in public health surveillance. Eradication of small pox is an important achievement in public health surveillance but the recent Severe Acute Respiratory Syndrome (SARS and Influenza pandemics suggest still there is a room for improvement. Recently new global disease surveillance networks like FluNet and DengueNet were developed as internet sites for monitoring influenza and dengue information. In spite of these developments, global public health surveillance still remains unevenly distributed. There is a need for increased international cooperation to address the global needs of public health surveillance.

Sunglass detection method for automation of video surveillance system

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Sikandar, Tasriva; Samsudin, Wan Nur Azhani W.; Hawari Ghazali, Kamarul; Mohd, Izzeldin I.; Fazle Rabbi, Mohammad

2018-04-01

Wearing sunglass to hide face from surveillance camera is a common activity in criminal incidences. Therefore, sunglass detection from surveillance video has become a demanding issue in automation of security systems. In this paper we propose an image processing method to detect sunglass from surveillance images. Specifically, a unique feature using facial height and width has been employed to identify the covered region of the face. The presence of covered area by sunglass is evaluated using facial height-width ratio. Threshold value of covered area percentage is used to classify the glass wearing face. Two different types of glasses have been considered i.e. eye glass and sunglass. The results of this study demonstrate that the proposed method is able to detect sunglasses in two different illumination conditions such as, room illumination as well as in the presence of sunlight. In addition, due to the multi-level checking in facial region, this method has 100% accuracy of detecting sunglass. However, in an exceptional case where fabric surrounding the face has similar color as skin, the correct detection rate was found 93.33% for eye glass.

Active prospective surveillance study with post-discharge surveillance of surgical site infections in Cambodia

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José Guerra

2015-05-01

Full Text Available Summary: Barriers to the implementation of the Centers for Disease Control and Prevention (CDC guidelines for surgical site infection (SSI surveillance have been described in resource-limited settings. This study aimed to estimate the SSI incidence rate in a Cambodian hospital and to compare different modalities of SSI surveillance. We performed an active prospective study with post-discharge surveillance. During the hospital stay, trained surveyors collected the CDC criteria to identify SSI by direct examination of the surgical site. After discharge, a card was given to each included patient to be presented to all practitioners examining the surgical site. Among 167 patients, direct examination of the surgical site identified a cumulative incidence rate of 14 infections per 100 patients. An independent review of medical charts presented a sensitivity of 16%. The sensitivity of the purulent drainage criterion to detect SSIs was 83%. After hospital discharge, 87% of the patients provided follow-up data, and nine purulent drainages were reported by a practitioner (cumulative incidence rate: 20%. Overall, the incidence rate was dependent on the surveillance modalities. The review of medical charts to identify SSIs during hospitalization was not effective; the use of a follow-up card with phone calls for post-discharge surveillance was effective. Keywords: Surgical wound infection, Cambodia, Infection control, Developing countries, Follow-up studies, Feasibility studies

Healthcare Text Classification System and its Performance Evaluation: A Source of Better Intelligence by Characterizing Healthcare Text.

Science.gov (United States)

Srivastava, Saurabh Kumar; Singh, Sandeep Kumar; Suri, Jasjit S

2018-04-13

A machine learning (ML)-based text classification system has several classifiers. The performance evaluation (PE) of the ML system is typically driven by the training data size and the partition protocols used. Such systems lead to low accuracy because the text classification systems lack the ability to model the input text data in terms of noise characteristics. This research study proposes a concept of misrepresentation ratio (MRR) on input healthcare text data and models the PE criteria for validating the hypothesis. Further, such a novel system provides a platform to amalgamate several attributes of the ML system such as: data size, classifier type, partitioning protocol and percentage MRR. Our comprehensive data analysis consisted of five types of text data sets (TwitterA, WebKB4, Disease, Reuters (R8), and SMS); five kinds of classifiers (support vector machine with linear kernel (SVM-L), MLP-based neural network, AdaBoost, stochastic gradient descent and decision tree); and five types of training protocols (K2, K4, K5, K10 and JK). Using the decreasing order of MRR, our ML system demonstrates the mean classification accuracies as: 70.13 ± 0.15%, 87.34 ± 0.06%, 93.73 ± 0.03%, 94.45 ± 0.03% and 97.83 ± 0.01%, respectively, using all the classifiers and protocols. The corresponding AUC is 0.98 for SMS data using Multi-Layer Perceptron (MLP) based neural network. All the classifiers, the best accuracy of 91.84 ± 0.04% is shown to be of MLP-based neural network and this is 6% better over previously published. Further we observed that as MRR decreases, the system robustness increases and validated by standard deviations. The overall text system accuracy using all data types, classifiers, protocols is 89%, thereby showing the entire ML system to be novel, robust and unique. The system is also tested for stability and reliability.

Integrating HIV Surveillance and Field Services: Data Quality and Care Continuum in King County, Washington, 2010-2015.

Science.gov (United States)

Hood, Julia E; Katz, David A; Bennett, Amy B; Buskin, Susan E; Dombrowski, Julia C; Hawes, Stephen E; Golden, Matthew R

2017-12-01

To assess how integration of HIV surveillance and field services might influence surveillance data and linkage to care metrics. We used HIV surveillance and field services data from King County, Washington, to assess potential impact of misclassification of prior diagnoses on numbers of new diagnoses. The relationship between partner services and linkage to care was evaluated with multivariable log-binomial regression models. Of the 2842 people who entered the King County HIV Surveillance System in 2010 to 2015, 52% were newly diagnosed, 41% had a confirmed prior diagnosis in another state, and 7% had an unconfirmed prior diagnosis. Twelve percent of those classified as newly diagnosed for purposes of national HIV surveillance self-reported a prior HIV diagnosis that was unconfirmed. Partner services recipients were more likely than nonrecipients to link to care within 30 days (adjusted risk ratio [RR] = 1.10; 95% confidence interval [CI] = 1.03, 1.18) and 90 days (adjusted RR = 1.07; 95% CI = 1.01, 1.14) of diagnosis. Integration of HIV surveillance, partner services, and care linkage efforts may improve the accuracy of HIV surveillance data and facilitate timely linkage to care.

Combining multiple classifiers for age classification

CSIR Research Space (South Africa)

Van Heerden, C

2009-11-01

Full Text Available The authors compare several different classifier combination methods on a single task, namely speaker age classification. This task is well suited to combination strategies, since significantly different feature classes are employed. Support vector...

Introduction to surveillance studies

CERN Document Server

Petersen, JK

2012-01-01

Introduction & OverviewIntroduction Brief History of Surveillance Technologies & TechniquesOptical SurveillanceAerial Surveillance Audio Surveillance Radio-Wave SurveillanceGlobal Positioning Systems Sensors Computers & the Internet Data Cards Biochemical Surveillance Animal Surveillance Biometrics Genetics Practical ConsiderationsPrevalence of Surveillance Effectiveness of Surveillance Freedom & Privacy IssuesConstitutional Freedoms Privacy Safeguards & Intrusions ResourcesReferences Glossary Index

Citizen surveillance for environmental monitoring: combining the efforts of citizen science and crowdsourcing in a quantitative data framework.

Science.gov (United States)

Welvaert, Marijke; Caley, Peter

2016-01-01

Citizen science and crowdsourcing have been emerging as methods to collect data for surveillance and/or monitoring activities. They could be gathered under the overarching term citizen surveillance . The discipline, however, still struggles to be widely accepted in the scientific community, mainly because these activities are not embedded in a quantitative framework. This results in an ongoing discussion on how to analyze and make useful inference from these data. When considering the data collection process, we illustrate how citizen surveillance can be classified according to the nature of the underlying observation process measured in two dimensions-the degree of observer reporting intention and the control in observer detection effort. By classifying the observation process in these dimensions we distinguish between crowdsourcing, unstructured citizen science and structured citizen science. This classification helps the determine data processing and statistical treatment of these data for making inference. Using our framework, it is apparent that published studies are overwhelmingly associated with structured citizen science, and there are well developed statistical methods for the resulting data. In contrast, methods for making useful inference from purely crowd-sourced data remain under development, with the challenges of accounting for the unknown observation process considerable. Our quantitative framework for citizen surveillance calls for an integration of citizen science and crowdsourcing and provides a way forward to solve the statistical challenges inherent to citizen-sourced data.

Surveillance for Lyme Disease - United States, 2008-2015.

Science.gov (United States)

Schwartz, Amy M; Hinckley, Alison F; Mead, Paul S; Hook, Sarah A; Kugeler, Kiersten J

2017-11-10

Lyme disease is the most commonly reported vectorborne disease in the United States but is geographically focal. The majority of Lyme disease cases occur in the Northeast, mid-Atlantic, and upper Midwest regions. Lyme disease can cause varied clinical manifestations, including erythema migrans, arthritis, facial palsy, and carditis. Lyme disease occurs most commonly among children and older adults, with a slight predominance among males. 2008-2015. Lyme disease has been a nationally notifiable condition in the United States since 1991. Possible Lyme disease cases are reported to local and state health departments by clinicians and laboratories. Health department staff conduct case investigations to classify cases according to the national surveillance case definition. Those that qualify as confirmed or probable cases of Lyme disease are reported to CDC through the National Notifiable Diseases Surveillance System. States with an average annual incidence during this reporting period of ≥10 confirmed Lyme disease cases per 100,000 population were classified as high incidence. States that share a border with those states or that are located between areas of high incidence were classified as neighboring states. All other states were classified as low incidence. During 2008-2015, a total of 275,589 cases of Lyme disease were reported to CDC (208,834 confirmed and 66,755 probable). Although most cases continue to be reported from states with high incidence in the Northeast, mid-Atlantic, and upper Midwest regions, case counts in most of these states have remained stable or decreased during the reporting period. In contrast, case counts have increased in states that neighbor those with high incidence. Overall, demographic characteristics associated with confirmed cases were similar to those described previously, with a slight predominance among males and a bimodal age distribution with peaks among young children and older adults. Yet, among the subset of cases reported

An automated, broad-based, near real-time public health surveillance system using presentations to hospital Emergency Departments in New South Wales, Australia

Directory of Open Access Journals (Sweden)

Chiu Clayton

2005-12-01

Full Text Available Abstract Background In a climate of concern over bioterrorism threats and emergent diseases, public health authorities are trialling more timely surveillance systems. The 2003 Rugby World Cup (RWC provided an opportunity to test the viability of a near real-time syndromic surveillance system in metropolitan Sydney, Australia. We describe the development and early results of this largely automated system that used data routinely collected in Emergency Departments (EDs. Methods Twelve of 49 EDs in the Sydney metropolitan area automatically transmitted surveillance data from their existing information systems to a central database in near real-time. Information captured for each ED visit included patient demographic details, presenting problem and nursing assessment entered as free-text at triage time, physician-assigned provisional diagnosis codes, and status at departure from the ED. Both diagnoses from the EDs and triage text were used to assign syndrome categories. The text information was automatically classified into one or more of 26 syndrome categories using automated "naïve Bayes" text categorisation techniques. Automated processes were used to analyse both diagnosis and free text-based syndrome data and to produce web-based statistical summaries for daily review. An adjusted cumulative sum (cusum was used to assess the statistical significance of trends. Results During the RWC the system did not identify any major public health threats associated with the tournament, mass gatherings or the influx of visitors. This was consistent with evidence from other sources, although two known outbreaks were already in progress before the tournament. Limited baseline in early monitoring prevented the system from automatically identifying these ongoing outbreaks. Data capture was invisible to clinical staff in EDs and did not add to their workload. Conclusion We have demonstrated the feasibility and potential utility of syndromic surveillance using

Video sensor architecture for surveillance applications.

Science.gov (United States)

Sánchez, Jordi; Benet, Ginés; Simó, José E

2012-01-01

This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software) in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

[Population surveillance of coronary heart disease].

Science.gov (United States)

Ben Romdhane, Habiba; Bougatef, Souha; Skhiri, Hajer; Gharbi, Donia; Haouala, Habib; Achour, Noureddine

2005-05-01

A cross-sectional population survey was carried out in the Ariana region in 2000-01. The aim of this study is to report the prevalence of CHD as indicated by ECG Minnesota coding. A randomly selected sample included 1837 adults 40-70 years. Data on socio-economic status, demographic, medical history, health behaviour, clinical and biological investigations were recorded. Risk factors (hypertension, dyslipedemia, obesity, diabetes) are defined according to WHO criterias. Standard supine 12 lead ECGs were recorded. All ECGs are red and classified according to the Minnesota codes criteria on CHD probable, CHD possible and on Major abnormalities and minor abnormalities. CHD prevalence was higher on women. Major abnormalities are more common on women (20.6% vs 13%), while minor abnormalities prevalence was higher on men (15.5% vs 7.5%) (p<0.0001). The prevalence increased with age in both genders. This study tested how feasible is the population approach on CVDs surveillance. It highlighted the burden of cardiovascular diseases and support that women are at risk as men are. The value of ECG findings must be integrated in the cardiovascular diseases surveillance to identify high risk population.

A Super-resolution Reconstruction Algorithm for Surveillance Video

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Jian Shao

2017-01-01

Full Text Available Recent technological developments have resulted in surveillance video becoming a primary method of preserving public security. Many city crimes are observed in surveillance video. The most abundant evidence collected by the police is also acquired through surveillance video sources. Surveillance video footage offers very strong support for solving criminal cases, therefore, creating an effective policy, and applying useful methods to the retrieval of additional evidence is becoming increasingly important. However, surveillance video has had its failings, namely, video footage being captured in low resolution (LR and bad visual quality. In this paper, we discuss the characteristics of surveillance video and describe the manual feature registration – maximum a posteriori – projection onto convex sets to develop a super-resolution reconstruction method, which improves the quality of surveillance video. From this method, we can make optimal use of information contained in the LR video image, but we can also control the image edge clearly as well as the convergence of the algorithm. Finally, we make a suggestion on how to adjust the algorithm adaptability by analyzing the prior information of target image.

Ensemble of classifiers based network intrusion detection system performance bound

CSIR Research Space (South Africa)

Mkuzangwe, Nenekazi NP

2017-11-01

Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...

Mapping HIV/STI behavioural surveillance in Europe

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Lert France

2010-10-01

Full Text Available Abstract Background Used in conjunction with biological surveillance, behavioural surveillance provides data allowing for a more precise definition of HIV/STI prevention strategies. In 2008, mapping of behavioural surveillance in EU/EFTA countries was performed on behalf of the European Centre for Disease prevention and Control. Method Nine questionnaires were sent to all 31 member States and EEE/EFTA countries requesting data on the overall behavioural and second generation surveillance system and on surveillance in the general population, youth, men having sex with men (MSM, injecting drug users (IDU, sex workers (SW, migrants, people living with HIV/AIDS (PLWHA, and sexually transmitted infection (STI clinics patients. Requested data included information on system organisation (e.g. sustainability, funding, institutionalisation, topics covered in surveys and main indicators. Results Twenty-eight of the 31 countries contacted supplied data. Sixteen countries reported an established behavioural surveillance system, and 13 a second generation surveillance system (combination of biological surveillance of HIV/AIDS and STI with behavioural surveillance. There were wide differences as regards the year of survey initiation, number of populations surveyed, data collection methods used, organisation of surveillance and coordination with biological surveillance. The populations most regularly surveyed are the general population, youth, MSM and IDU. SW, patients of STI clinics and PLWHA are surveyed less regularly and in only a small number of countries, and few countries have undertaken behavioural surveys among migrant or ethnic minorities populations. In many cases, the identification of populations with risk behaviour and the selection of populations to be included in a BS system have not been formally conducted, or are incomplete. Topics most frequently covered are similar across countries, although many different indicators are used. In most

General Text-Chunk Localization in Scene Images using a Codebook-based Classifier

NARCIS (Netherlands)

Sriman, Bowornrat; Schomaker, Lambertus; Pruksasri, Potchara

Text localization is a main portal to character recognition in scene images. The detection of text regions in an image is a great challenge. However, many locating methods use a bottom-up scheme that consumes relatively high computation to identify the text regions. Therefore, this paper presents a

Identifying aggressive prostate cancer foci using a DNA methylation classifier.

Science.gov (United States)

Mundbjerg, Kamilla; Chopra, Sameer; Alemozaffar, Mehrdad; Duymich, Christopher; Lakshminarasimhan, Ranjani; Nichols, Peter W; Aron, Manju; Siegmund, Kimberly D; Ukimura, Osamu; Aron, Monish; Stern, Mariana; Gill, Parkash; Carpten, John D; Ørntoft, Torben F; Sørensen, Karina D; Weisenberger, Daniel J; Jones, Peter A; Duddalwar, Vinay; Gill, Inderbir; Liang, Gangning

2017-01-12

Slow-growing prostate cancer (PC) can be aggressive in a subset of cases. Therefore, prognostic tools to guide clinical decision-making and avoid overtreatment of indolent PC and undertreatment of aggressive disease are urgently needed. PC has a propensity to be multifocal with several different cancerous foci per gland. Here, we have taken advantage of the multifocal propensity of PC and categorized aggressiveness of individual PC foci based on DNA methylation patterns in primary PC foci and matched lymph node metastases. In a set of 14 patients, we demonstrate that over half of the cases have multiple epigenetically distinct subclones and determine the primary subclone from which the metastatic lesion(s) originated. Furthermore, we develop an aggressiveness classifier consisting of 25 DNA methylation probes to determine aggressive and non-aggressive subclones. Upon validation of the classifier in an independent cohort, the predicted aggressive tumors are significantly associated with the presence of lymph node metastases and invasive tumor stages. Overall, this study provides molecular-based support for determining PC aggressiveness with the potential to impact clinical decision-making, such as targeted biopsy approaches for early diagnosis and active surveillance, in addition to focal therapy.

Harnessing information from injury narratives in the 'big data' era: understanding and applying machine learning for injury surveillance.

Science.gov (United States)

Vallmuur, Kirsten; Marucci-Wellman, Helen R; Taylor, Jennifer A; Lehto, Mark; Corns, Helen L; Smith, Gordon S

2016-04-01

Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semiautomatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and PPV and reduced the need for human coding to less than a third of cases in one large occupational injury database. The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of 'big injury narrative data' opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

A comprehensive review on intelligent surveillance systems

Directory of Open Access Journals (Sweden)

Sutrisno Warsono Ibrahim

2016-05-01

Full Text Available Intelligent surveillance system (ISS has received growing attention due to the increasing demand on security and safety. ISS is able to automatically analyze image, video, audio or other type of surveillance data without or with limited human intervention. The recent developments in sensor devices, computer vision, and machine learning have an important role in enabling such intelligent system. This paper aims to provide general overview of intelligent surveillance system and discuss some possible sensor modalities and their fusion scenarios such as visible camera (CCTV, infrared camera, thermal camera and radar. This paper also discusses main processing steps in ISS: background-foreground segmentation, object detection and classification, tracking, and behavioral analysis.

Arabic Text Categorization Using Improved k-Nearest neighbour Algorithm

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Wail Hamood KHALED

2014-10-01

Full Text Available The quantity of text information published in Arabic language on the net requires the implementation of effective techniques for the extraction and classifying of relevant information contained in large corpus of texts. In this paper we presented an implementation of an enhanced k-NN Arabic text classifier. We apply the traditional k-NN and Naive Bayes from Weka Toolkit for comparison purpose. Our proposed modified k-NN algorithm features an improved decision rule to skip the classes that are less similar and identify the right class from k nearest neighbours which increases the accuracy. The study evaluates the improved decision rule technique using the standard of recall, precision and f-measure as the basis of comparison. We concluded that the effectiveness of the proposed classifier is promising and outperforms the classical k-NN classifier.

Classifying Microorganisms

DEFF Research Database (Denmark)

Sommerlund, Julie

2006-01-01

This paper describes the coexistence of two systems for classifying organisms and species: a dominant genetic system and an older naturalist system. The former classifies species and traces their evolution on the basis of genetic characteristics, while the latter employs physiological characteris......This paper describes the coexistence of two systems for classifying organisms and species: a dominant genetic system and an older naturalist system. The former classifies species and traces their evolution on the basis of genetic characteristics, while the latter employs physiological...... characteristics. The coexistence of the classification systems does not lead to a conflict between them. Rather, the systems seem to co-exist in different configurations, through which they are complementary, contradictory and inclusive in different situations-sometimes simultaneously. The systems come...

Evaluation of the national Notifiable Diseases Surveillance System for dengue fever in Taiwan, 2010-2012.

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Caoimhe McKerr

2015-03-01

Full Text Available In Taiwan, around 1,500 cases of dengue fever are reported annually and incidence has been increasing over time. A national web-based Notifiable Diseases Surveillance System (NDSS has been in operation since 1997 to monitor incidence and trends and support case and outbreak management. We present the findings of an evaluation of the NDSS to ascertain the extent to which dengue fever surveillance objectives are being achieved.We extracted the NDSS data on all laboratory-confirmed dengue fever cases reported during 1 January 2010 to 31 December 2012 to assess and describe key system attributes based on the Centers for Disease Control and Prevention surveillance evaluation guidelines. The system's structure and processes were delineated and operational staff interviewed using a semi-structured questionnaire. Crude and age-adjusted incidence rates were calculated and key demographic variables were summarised to describe reporting activity. Data completeness and validity were described across several variables.Of 5,072 laboratory-confirmed dengue fever cases reported during 2010-2012, 4,740 (93% were reported during July to December. The system was judged to be simple due to its minimal reporting steps. Data collected on key variables were correctly formatted and usable in > 90% of cases, demonstrating good data completeness and validity. The information collected was considered relevant by users with high acceptability. Adherence to guidelines for 24-hour reporting was 99%. Of 720 cases (14% recorded as travel-related, 111 (15% had an onset >14 days after return, highlighting the potential for misclassification. Information on hospitalization was missing for 22% of cases. The calculated PVP was 43%.The NDSS for dengue fever surveillance is a robust, well maintained and acceptable system that supports the collection of complete and valid data needed to achieve the surveillance objectives. The simplicity of the system engenders compliance leading to

Time series modeling for syndromic surveillance

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Mandl Kenneth D

2003-01-01

Full Text Available Abstract Background Emergency department (ED based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. Methods Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. Results Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. Conclusions Time series methods applied to historical ED utilization data are an important tool

State surveillance as a threat to personal security of individuals

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Sławomir Czapnik

2015-12-01

Full Text Available Changes in modern society are crucial to individuals. Article starts with analysis of control in nowadays societies. Then author tries to understand useful categories, as "Panopticon", "ban-opticon" and "synopticon". Last part is focused on stete surveillance, i.e. surveillance by American National Security Agency.

Strategies to Increase Accuracy in Text Classification

NARCIS (Netherlands)

D. Blommesteijn (Dennis)

2014-01-01

htmlabstractText classification via supervised learning involves various steps from processing raw data, features extraction to training and validating classifiers. Within these steps implementation decisions are critical to the resulting classifier accuracy. This paper contains a report of the

Evaluation of two surveillance methods for surgical site infection

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M. Haji Abdolbaghi

2006-08-01

Full Text Available Background: Surgical wound infection surveillance is an important facet of hospital infection control processes. There are several surveillance methods for surgical site infections. The objective of this study is to evaluate the accuracy of two different surgical site infection surveillance methods. Methods: In this prospective cross sectional study 3020 undergoing surgey in general surgical wards of Imam Khomeini hospital were included. Surveillance methods consisted of review of medical records for postoperative fever and review of nursing daily note for prescription of antibiotics postoperatively and during patient’s discharge. Review of patient’s history and daily records and interview with patient’s surgeon and the head-nurse of the ward considered as a gold standard for surveillance. Results: The postoperative antibiotic consumption especially when considering its duration is a proper method for surgical wound infection surveillance. Accomplishments of a prospective study with postdischarge follow up until 30 days after surgery is recommended. Conclusion: The result of this study showed that postoperative antibiotic surveillance method specially with consideration of the antibiotic usage duration is a proper method for surgical site infection surveillance in general surgery wards. Accomplishments of a prospective study with post discharge follow up until 30 days after surgery is recommended.

Epidemiological Concepts Regarding Disease Monitoring and Surveillance

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Christensen Jette

2001-03-01

Full Text Available Definitions of epidemiological concepts regarding disease monitoring and surveillance can be found in textbooks on veterinary epidemiology. This paper gives a review of how the concepts: monitoring, surveillance, and disease control strategies are defined. Monitoring and surveillance systems (MO&SS involve measurements of disease occurrence, and the design of the monitoring determines which types of disease occurrence measures can be applied. However, the knowledge of the performance of diagnostic tests (sensitivity and specificity is essential to estimate the true occurrence of the disease. The terms, disease control programme (DCP or disease eradication programme (DEP, are defined, and the steps of DCP/DEP are described to illustrate that they are a process rather than a static MO&SS.

Reinforcement Learning Based Artificial Immune Classifier

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Mehmet Karakose

2013-01-01

Full Text Available One of the widely used methods for classification that is a decision-making process is artificial immune systems. Artificial immune systems based on natural immunity system can be successfully applied for classification, optimization, recognition, and learning in real-world problems. In this study, a reinforcement learning based artificial immune classifier is proposed as a new approach. This approach uses reinforcement learning to find better antibody with immune operators. The proposed new approach has many contributions according to other methods in the literature such as effectiveness, less memory cell, high accuracy, speed, and data adaptability. The performance of the proposed approach is demonstrated by simulation and experimental results using real data in Matlab and FPGA. Some benchmark data and remote image data are used for experimental results. The comparative results with supervised/unsupervised based artificial immune system, negative selection classifier, and resource limited artificial immune classifier are given to demonstrate the effectiveness of the proposed new method.

Evaluation of the influenza sentinel surveillance system in Madagascar, 2009-2014.

Science.gov (United States)

Rakotoarisoa, Alain; Randrianasolo, Laurence; Tempia, Stefano; Guillebaud, Julia; Razanajatovo, Norosoa; Randriamampionona, Lea; Piola, Patrice; Halm, Ariane; Heraud, Jean-Michel

2017-05-01

Evaluation of influenza surveillance systems is poor, especially in Africa. In 2007, the Institut Pasteur de Madagascar and the Malagasy Ministry of Public Health implemented a countrywide system for the prospective syndromic and virological surveillance of influenza-like illnesses. In assessing this system's performance, we identified gaps and ways to promote the best use of resources. We investigated acceptability, data quality, flexibility, representativeness, simplicity, stability, timeliness and usefulness and developed qualitative and/or quantitative indicators for each of these attributes. Until 2007, the influenza surveillance system in Madagascar was only operational in Antananarivo and the observations made could not be extrapolated to the entire country. By 2014, the system covered 34 sentinel sites across the country. At 12 sites, nasopharyngeal and/or oropharyngeal samples were collected and tested for influenza virus. Between 2009 and 2014, 177 718 fever cases were detected, 25 809 (14.5%) of these fever cases were classified as cases of influenza-like illness. Of the 9192 samples from patients with influenza-like illness that were tested for influenza viruses, 3573 (38.9%) tested positive. Data quality for all evaluated indicators was categorized as above 90% and the system also appeared to be strong in terms of its acceptability, simplicity and stability. However, sample collection needed improvement. The influenza surveillance system in Madagascar performed well and provided reliable and timely data for public health interventions. Given its flexibility and overall moderate cost, this system may become a useful platform for syndromic and laboratory-based surveillance in other low-resource settings.

Reassembling Surveillance Creep

DEFF Research Database (Denmark)

Bøge, Ask Risom; Lauritsen, Peter

2017-01-01

We live in societies in which surveillance technologies are constantly introduced, are transformed, and spread to new practices for new purposes. How and why does this happen? In other words, why does surveillance “creep”? This question has received little attention either in theoretical developm......We live in societies in which surveillance technologies are constantly introduced, are transformed, and spread to new practices for new purposes. How and why does this happen? In other words, why does surveillance “creep”? This question has received little attention either in theoretical...... development or in empirical analyses. Accordingly, this article contributes to this special issue on the usefulness of Actor-Network Theory (ANT) by suggesting that ANT can advance our understanding of ‘surveillance creep’. Based on ANT’s model of translation and a historical study of the Danish DNA database......, we argue that surveillance creep involves reassembling the relations in surveillance networks between heterogeneous actors such as the watchers, the watched, laws, and technologies. Second, surveillance creeps only when these heterogeneous actors are adequately interested and aligned. However...

Surveillance, Snowden, and Big Data: Capacities, consequences, critique

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David Lyon

2014-07-01

Full Text Available The Snowden revelations about National Security Agency surveillance, starting in 2013, along with the ambiguous complicity of internet companies and the international controversies that followed provide a perfect segue into contemporary conundrums of surveillance and Big Data. Attention has shifted from late C20th information technologies and networks to a C21st focus on data, currently crystallized in “Big Data.” Big Data intensifies certain surveillance trends associated with information technology and networks, and is thus implicated in fresh but fluid configurations. This is considered in three main ways: One, the capacities of Big Data (including metadata intensify surveillance by expanding interconnected datasets and analytical tools. Existing dynamics of influence, risk-management, and control increase their speed and scope through new techniques, especially predictive analytics. Two, while Big Data appears to be about size, qualitative change in surveillance practices is also perceptible, accenting consequences. Important trends persist – the control motif, faith in technology, public-private synergies, and user-involvement – but the future-orientation increasingly severs surveillance from history and memory and the quest for pattern-discovery is used to justify unprecedented access to data. Three, the ethical turn becomes more urgent as a mode of critique. Modernity's predilection for certain definitions of privacy betrays the subjects of surveillance who, so far from conforming to the abstract, disembodied image of both computing and legal practices, are engaged and embodied users-in-relation whose activities both fuel and foreclose surveillance.

Active epidemiological surveillance in the program of poliomyelitis eradication in Serbia

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Jevremović Ivana

2002-01-01

Full Text Available The main strategy of the worldwide Program of Poliomyelitis Eradication is based on immunization with oral poliovirus vaccine and active epidemiological surveillance aimed to demonstrate the absence of wild poliovirus circulation. The specification of the surveillance in the program, reporting and investigation of certain syndrome – the acute flaccid paralysis - as a specific feature of surveillance of poliomyelitis, is a new experience both for clinicians and epidemiologists. Along with the achieved results, problems in conducting the active epidemiological surveillance in Serbia, applied measures, and suggestions for improving its quality were presented. This experience might help in implementing the active surveillance for some other diseases that could be prevented by vaccine immunization.

Using Acute Flaccid Paralysis Surveillance as a Platform for Vaccine-Preventable Disease Surveillance.

Science.gov (United States)

Wassilak, Steven G F; Williams, Cheryl L; Murrill, Christopher S; Dahl, Benjamin A; Ohuabunwo, Chima; Tangermann, Rudolf H

2017-07-01

Surveillance for acute flaccid paralysis (AFP) is a fundamental cornerstone of the global polio eradication initiative (GPEI). Active surveillance (with visits to health facilities) is a critical strategy of AFP surveillance systems for highly sensitive and timely detection of cases. Because of the extensive resources devoted to AFP surveillance, multiple opportunities exist for additional diseases to be added using GPEI assets, particularly because there is generally 1 district officer responsible for all disease surveillance. For this reason, integrated surveillance has become a standard practice in many countries, ranging from adding surveillance for measles and rubella to integrated disease surveillance for outbreak-prone diseases (integrated disease surveillance and response). This report outlines the current level of disease surveillance integration in 3 countries (Nepal, India, and Nigeria) and proposes that resources continue for long-term maintenance in resource-poor countries of AFP surveillance as a platform for surveillance of vaccine-preventable diseases and other outbreak-prone diseases. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America.

Automated intelligent video surveillance system for ships

Science.gov (United States)

Wei, Hai; Nguyen, Hieu; Ramu, Prakash; Raju, Chaitanya; Liu, Xiaoqing; Yadegar, Jacob

2009-05-01

To protect naval and commercial ships from attack by terrorists and pirates, it is important to have automatic surveillance systems able to detect, identify, track and alert the crew on small watercrafts that might pursue malicious intentions, while ruling out non-threat entities. Radar systems have limitations on the minimum detectable range and lack high-level classification power. In this paper, we present an innovative Automated Intelligent Video Surveillance System for Ships (AIVS3) as a vision-based solution for ship security. Capitalizing on advanced computer vision algorithms and practical machine learning methodologies, the developed AIVS3 is not only capable of efficiently and robustly detecting, classifying, and tracking various maritime targets, but also able to fuse heterogeneous target information to interpret scene activities, associate targets with levels of threat, and issue the corresponding alerts/recommendations to the man-in- the-loop (MITL). AIVS3 has been tested in various maritime scenarios and shown accurate and effective threat detection performance. By reducing the reliance on human eyes to monitor cluttered scenes, AIVS3 will save the manpower while increasing the accuracy in detection and identification of asymmetric attacks for ship protection.

Defending Malicious Script Attacks Using Machine Learning Classifiers

Directory of Open Access Journals (Sweden)

Nayeem Khan

2017-01-01

Full Text Available The web application has become a primary target for cyber criminals by injecting malware especially JavaScript to perform malicious activities for impersonation. Thus, it becomes an imperative to detect such malicious code in real time before any malicious activity is performed. This study proposes an efficient method of detecting previously unknown malicious java scripts using an interceptor at the client side by classifying the key features of the malicious code. Feature subset was obtained by using wrapper method for dimensionality reduction. Supervised machine learning classifiers were used on the dataset for achieving high accuracy. Experimental results show that our method can efficiently classify malicious code from benign code with promising results.

Evaluation of surveillance of dengue fever cases in the public health centre of Putat Jaya based on attribute surveillance

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Zumaroh Zumaroh

2015-01-01

Full Text Available Dengue Hemorrhagic Fever (DHF is a public health problem in the village of Putat Jaya which is an endemic area. Surveilans activity in DHF control program is the most important activity in controlling and monitoring disease progression. The program is expected to achieve incidence rate 55/100.000 population. This study aimed to evaluate the implementation of case surveilans in health centre of putat jaya based on attribute surveillance. Attribute surveillance is an indicator that describes the characteristics of the surveillance system. This research was an evaluation research with descriptive study design. As informants were clinic staff who deal specifically with cases of dengue hemorrhagic fever and laboratory workers. The techniques of data collection by interviews and document study. The variables of this study were simplicity, flexibility, acceptability, sensitivity, positive predictive value, representativeness, timeliness, data quality and data stability. It could be seen from Incidence Rate in 2013 has reached 133/100.00 population. The activity of surveilance in the village of Putat Jaya reviewed from disease contol program management was not succeed into decrease incidence rate of DHF. Therefore, dengue control programs in health centers Putat Jaya need to do cross-sector cooperation and cross-program cooperation, strengthening the case reporting system by way increasing in the utilization of information and communication technology electromedia. Keywords: case surveillance, dengue hemorrhagic fever, evaluation, attribute surveillance, Putat Jaya

Binary naive Bayesian classifiers for correlated Gaussian features: a theoretical analysis

CSIR Research Space (South Africa)

Van Dyk, E

2008-11-01

Full Text Available classifier with Gaussian features while using any quadratic decision boundary. Therefore, the analysis is not restricted to Naive Bayesian classifiers alone and can, for instance, be used to calculate the Bayes error performance. We compare the analytical...

Distributed data processing for public health surveillance

Directory of Open Access Journals (Sweden)

Yih Katherine

2006-09-01

Full Text Available Abstract Background Many systems for routine public health surveillance rely on centralized collection of potentially identifiable, individual, identifiable personal health information (PHI records. Although individual, identifiable patient records are essential for conditions for which there is mandated reporting, such as tuberculosis or sexually transmitted diseases, they are not routinely required for effective syndromic surveillance. Public concern about the routine collection of large quantities of PHI to support non-traditional public health functions may make alternative surveillance methods that do not rely on centralized identifiable PHI databases increasingly desirable. Methods The National Bioterrorism Syndromic Surveillance Demonstration Program (NDP is an example of one alternative model. All PHI in this system is initially processed within the secured infrastructure of the health care provider that collects and holds the data, using uniform software distributed and supported by the NDP. Only highly aggregated count data is transferred to the datacenter for statistical processing and display. Results Detailed, patient level information is readily available to the health care provider to elucidate signals observed in the aggregated data, or for ad hoc queries. We briefly describe the benefits and disadvantages associated with this distributed processing model for routine automated syndromic surveillance. Conclusion For well-defined surveillance requirements, the model can be successfully deployed with very low risk of inadvertent disclosure of PHI – a feature that may make participation in surveillance systems more feasible for organizations and more appealing to the individuals whose PHI they hold. It is possible to design and implement distributed systems to support non-routine public health needs if required.

Mobile phones used for public health surveillance

Directory of Open Access Journals (Sweden)

Kebede Deribe

2011-08-01

Full Text Available In Darfur, the Ministry of Health, WHO and partners have developed a mobile phone-based infectious disease surveillance system for use where resources and facilities may be limited.

The plays and arts of surveillance: studying surveillance as entertainment

NARCIS (Netherlands)

Albrechtslund, Anders; Dubbeld, L.

2006-01-01

This paper suggests a direction in the development of Surveillance Studies that goes beyond current attention for the caring, productive and enabling aspects of surveillance practices. That is, surveillance could be considered not just as positively protective, but even as a comical, playful,

TEXT CLASSIFICATION USING NAIVE BAYES UPDATEABLE ALGORITHM IN SBMPTN TEST QUESTIONS

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Ristu Saptono

2017-01-01

Full Text Available Document classification is a growing interest in the research of text mining. Classification can be done based on the topics, languages, and so on. This study was conducted to determine how Naive Bayes Updateable performs in classifying the SBMPTN exam questions based on its theme. Increment model of one classification algorithm often used in text classification Naive Bayes classifier has the ability to learn from new data introduces with the system even after the classifier has been produced with the existing data. Naive Bayes Classifier classifies the exam questions based on the theme of the field of study by analyzing keywords that appear on the exam questions. One of feature selection method DF-Thresholding is implemented for improving the classification performance. Evaluation of the classification with Naive Bayes classifier algorithm produces 84,61% accuracy.

A Culture-Proven Case of Community-Acquired Legionella Pneumonia Apparently Classified as Nosocomial: Diagnostic and Public Health Implications

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Annalisa Bargellini

2013-01-01

Full Text Available We report a case of Legionella pneumonia in a 78-year-old patient affected by cerebellar haemangioblastoma continuously hospitalised for 24 days prior to the onset of overt symptoms. According to the established case definition, this woman should have been definitely classified as a nosocomial case (patient spending all of the ten days in hospital before onset of symptoms. Water samples from the oncology ward were negative, notably the patient’s room and the oxygen bubbler, and the revision of the case history induced us to verify possible contamination in water samples collected at home. We found that the clinical strain had identical rep-PCR fingerprint of L. pneumophila serogroup 1 isolated at home. The description of this culture-proven case of Legionnaires’ disease has major clinical, legal, and public health consequences as the complexity of hospitalised patients poses limitations to the rule-of-thumb surveillance definition of nosocomial pneumonia based on 2–10-day incubation period.

Epidemic Intelligence. Langmuir and the Birth of Disease Surveillance

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Lyle Fearnley

2010-12-01

Full Text Available In the wake of the SARS and influenza epidemics of the past decade, one public health solution has become a refrain: surveillance systems for detection of disease outbreaks. This paper is an effort to understand how disease surveillance for outbreak detection gained such paramount rationality in contemporary public health. The epidemiologist Alexander Langmuir is well known as the creator of modern disease surveillance. But less well known is how he imagined disease surveillance as one part of what he called “epidemic intelligence.” Langmuir developed the practice of disease surveillance during an unprecedented moment in which the threat of biological warfare brought civil defense experts and epidemiologists together around a common problem. In this paper, I describe how Langmuir navigated this world, experimenting with new techniques and rationales of epidemic control. Ultimately, I argue, Langmuir′s experiments resulted in a set of techniques and infrastructures – a system of epidemic intelligence – that transformed the epidemic as an object of human art.

Single-Pol Synthetic Aperture Radar Terrain Classification using Multiclass Confidence for One-Class Classifiers

Energy Technology Data Exchange (ETDEWEB)

Koch, Mark William [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Steinbach, Ryan Matthew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Moya, Mary M [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-10-01

Except in the most extreme conditions, Synthetic aperture radar (SAR) is a remote sensing technology that can operate day or night. A SAR can provide surveillance over a long time period by making multiple passes over a wide area. For object-based intelligence it is convenient to segment and classify the SAR images into objects that identify various terrains and man-made structures that we call “static features.” In this paper we introduce a novel SAR image product that captures how different regions decorrelate at different rates. Using superpixels and their first two moments we develop a series of one-class classification algorithms using a goodness-of-fit metric. P-value fusion is used to combine the results from different classes. We also show how to combine multiple one-class classifiers to get a confidence about a classification. This can be used by downstream algorithms such as a conditional random field to enforce spatial constraints.

Surveillance guidelines for smallpox vaccine (vaccinia) adverse reactions.

Science.gov (United States)

Casey, Christine; Vellozzi, Claudia; Mootrey, Gina T; Chapman, Louisa E; McCauley, Mary; Roper, Martha H; Damon, Inger; Swerdlow, David L

2006-02-03

CDC and the U.S. Food and Drug Administration rely on state and local health departments, health-care providers, and the public to report the occurrence of adverse events after vaccination to the Vaccine Adverse Event Reporting System. With such data, trends can be accurately monitored, unusual occurrences of adverse events can be detected, and the safety of vaccination intervention activities can be evaluated. On January 24, 2003, the U.S. Department of Health and Human Services (DHHS) implemented a preparedness program in which smallpox (vaccinia) vaccine was administered to federal, state, and local volunteers who might be first responders during a biologic terrorism event. As part of the DHHS Smallpox Preparedness and Response Program, CDC in consultation with experts, established surveillance case definitions for adverse events after smallpox vaccination. Adverse reactions after smallpox vaccination identified during the 1960s surveillance activities were classified on the basis of clinical description and included eczema vaccinatum; fetal vaccinia; generalized vaccinia; accidental autoinoculation, nonocular; ocular vaccinia; progressive vaccinia; erythema multiforme major; postvaccinial encephalitis or encephalomyelitis; and pyogenic infection of the vaccination site. This report provides uniform criteria used for the surveillance case definition and classification for these previously recognized adverse reactions used during the DHHS Smallpox Preparedness and Response Program. Inadvertent inoculation was changed to more precisely describe this event as inadvertent autoinoculation and contact transmission, nonocular and ocular vaccinia. Pyogenic infection also was renamed superinfection of the vaccination site or regional lymph nodes. Finally, case definitions were developed for a new cardiac adverse reaction (myo/pericarditis) and for a cardiac adverse event (dilated cardiomyopathy) and are included in this report. The smallpox vaccine surveillance case

Surveillance and Resilience in Theory and Practice

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Charles D. Raab

2015-09-01

Full Text Available Surveillance is often used as a tool in resilience strategies towards the threat posed by terrorist attacks and other serious crime. “Resilience” is a contested term with varying and ambiguous meaning in governmental, business and social discourses, and it is not clear how it relates to other terms that characterise processes or states of being. Resilience is often assumed to have positive connotations, but critics view it with great suspicion, regarding it as a neo-liberal governmental strategy. However, we argue that surveillance, introduced in the name of greater security, may itself erode social freedoms and public goods such as privacy, paradoxically requiring societal resilience, whether precautionary or in mitigation of the harms it causes to the public goods of free societies. This article develops new models and extends existing ones to describe resilience processes unfolding over time and in anticipation of, or in reaction to, adversities of different kinds and severity, and explores resilience both on the plane of abstract analysis and in the context of societal responses to mass surveillance. The article thus focuses upon surveillance as a special field for conceptual analysis and modelling of situations, and for evaluating contemporary developments in “surveillance societies”.

Colorectal Cancer Surveillance after Index Colonoscopy: Guidance from the Canadian Association of Gastroenterology

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Desmond Leddin

2013-01-01

Full Text Available BACKGROUND: Differences between American (United States [US] and European guidelines for colonoscopy surveillance may create confusion for the practicing clinician. Under- or overutilization of surveillance colonoscopy can impact patient care.

Theorizing Surveillance in the UK Crime Control Field

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Michael McCahill

2015-09-01

Full Text Available Drawing upon the work of Pierre Bourdieu and Loic Wacquant, this paper argues that the demise of the Keynesian Welfare State (KWS and the rise of neo-liberal economic policies in the UK has placed new surveillance technologies at the centre of a reconfigured “crime control field” (Garland, 2001 designed to control the problem populations created by neo-liberal economic policies (Wacquant, 2009a. The paper also suggests that field theory could be usefully deployed in future research to explore how wider global trends or social forces, such as neo-liberalism or bio-power, are refracted through the crime control field in different national jurisdictions. We conclude by showing how this approach provides a bridge between society-wide analysis and micro-sociology by exploring how the operation of new surveillance technologies is mediated by the “habitus” of surveillance agents working in the crime control field and contested by surveillance subjects.

Utilizing Multi-Field Text Features for Efficient Email Spam Filtering

Directory of Open Access Journals (Sweden)

Wuying Liu

2012-06-01

Full Text Available Large-scale spam emails cause a serious waste of time and resources. This paper investigates the text features of email documents and the feature noises among multi-field texts, resulting in an observation of a power law distribution of feature strings within each text field. According to the observation, we propose an efficient filtering approach including a compound weight method and a lightweight field text classification algorithm. The compound weight method considers both the historical classifying ability of each field classifier and the classifying contribution of each text field in the current classified email. The lightweight field text classification algorithm straightforwardly calculates the arithmetical average of multiple conditional probabilities predicted from feature strings according to a string-frequency index for labeled emails storing. The string-frequency index structure has a random-sampling-based compressible property owing to the power law distribution and can largely reduce the storage space. The experimental results in the TREC spam track show that the proposed approach can complete the filtering task in low space cost and high speed, whose overall performance 1-ROCA exceeds the best one among the participators at the trec07p evaluation.

An Autonomous Mobile Robotic System for Surveillance of Indoor Environments

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Donato Di Paola

2010-02-01

Full Text Available The development of intelligent surveillance systems is an active research area. In this context, mobile and multi-functional robots are generally adopted as means to reduce the environment structuring and the number of devices needed to cover a given area. Nevertheless, the number of different sensors mounted on the robot, and the number of complex tasks related to exploration, monitoring, and surveillance make the design of the overall system extremely challenging. In this paper, we present our autonomous mobile robot for surveillance of indoor environments. We propose a system able to handle autonomously general-purpose tasks and complex surveillance issues simultaneously. It is shown that the proposed robotic surveillance scheme successfully addresses a number of basic problems related to environment mapping, localization and autonomous navigation, as well as surveillance tasks, like scene processing to detect abandoned or removed objects and people detection and following. The feasibility of the approach is demonstrated through experimental tests using a multisensor platform equipped with a monocular camera, a laser scanner, and an RFID device. Real world applications of the proposed system include surveillance of wide areas (e.g. airports and museums and buildings, and monitoring of safety equipment.

An Autonomous Mobile Robotic System for Surveillance of Indoor Environments

Directory of Open Access Journals (Sweden)

Donato Di Paola

2010-03-01

Full Text Available The development of intelligent surveillance systems is an active research area. In this context, mobile and multi-functional robots are generally adopted as means to reduce the environment structuring and the number of devices needed to cover a given area. Nevertheless, the number of different sensors mounted on the robot, and the number of complex tasks related to exploration, monitoring, and surveillance make the design of the overall system extremely challenging. In this paper, we present our autonomous mobile robot for surveillance of indoor environments. We propose a system able to handle autonomously general-purpose tasks and complex surveillance issues simultaneously. It is shown that the proposed robotic surveillance scheme successfully addresses a number of basic problems related to environment mapping, localization and autonomous navigation, as well as surveillance tasks, like scene processing to detect abandoned or removed objects and people detection and following. The feasibility of the approach is demonstrated through experimental tests using a multisensor platform equipped with a monocular camera, a laser scanner, and an RFID device. Real world applications of the proposed system include surveillance of wide areas (e.g. airports and museums and buildings, and monitoring of safety equipment.

Who is Surveilling Whom?

DEFF Research Database (Denmark)

Mortensen, Mette

2014-01-01

This article concerns the particular form of counter-surveillance termed “sousveillance”, which aims to turn surveillance at the institutions responsible for surveillance. Drawing on the theoretical perspectives “mediatization” and “aerial surveillance,” the article studies WikiLeaks’ publication...

SOA-surveillance Nederland

NARCIS (Netherlands)

Rijlaarsdam J; Bosman A; Laar MJW van de; CIE

2000-01-01

In May 1999 a working group was started to evaluate the current surveillance systems for sexually transmitted diseases (STD) and to make suggestions for a renewed effective and efficient STD surveillance system in the Netherlands. The surveillance system has to provide insight into the prevalence

Classified facilities for environmental protection

International Nuclear Information System (INIS)

Anon.

1993-02-01

The legislation of the classified facilities governs most of the dangerous or polluting industries or fixed activities. It rests on the law of 9 July 1976 concerning facilities classified for environmental protection and its application decree of 21 September 1977. This legislation, the general texts of which appear in this volume 1, aims to prevent all the risks and the harmful effects coming from an installation (air, water or soil pollutions, wastes, even aesthetic breaches). The polluting or dangerous activities are defined in a list called nomenclature which subjects the facilities to a declaration or an authorization procedure. The authorization is delivered by the prefect at the end of an open and contradictory procedure after a public survey. In addition, the facilities can be subjected to technical regulations fixed by the Environment Minister (volume 2) or by the prefect for facilities subjected to declaration (volume 3). (A.B.)

A Web-Based, Hospital-Wide Health Care-Associated Bloodstream Infection Surveillance and Classification System: Development and Evaluation.

Science.gov (United States)

Tseng, Yi-Ju; Wu, Jung-Hsuan; Lin, Hui-Chi; Chen, Ming-Yuan; Ping, Xiao-Ou; Sun, Chun-Chuan; Shang, Rung-Ji; Sheng, Wang-Huei; Chen, Yee-Chun; Lai, Feipei; Chang, Shan-Chwen

2015-09-21

Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent. To develop an automatic surveillance and classification system for health care-associated bloodstream infection (HABSI), and to evaluate its performance by comparing it with a conventional infection control personnel (ICP)-based surveillance system. We developed a Web-based system that was integrated into the medical information system of a 2200-bed teaching hospital in Taiwan. The system automatically detects and classifies HABSIs. In this study, the number of computer-detected HABSIs correlated closely with the number of HABSIs detected by ICP by department (n=20; r=.999 Psystem performed excellently with regard to sensitivity (98.16%), specificity (99.96%), positive predictive value (95.81%), and negative predictive value (99.98%). The system enabled decreasing the delay in confirmation of HABSI cases, on average, by 29 days. This system provides reliable and objective HABSI data for quality indicators, improving the delay caused by a conventional surveillance system.

Development of The Viking Speech Scale to classify the speech of children with cerebral palsy.

Science.gov (United States)

Pennington, Lindsay; Virella, Daniel; Mjøen, Tone; da Graça Andrada, Maria; Murray, Janice; Colver, Allan; Himmelmann, Kate; Rackauskaite, Gija; Greitane, Andra; Prasauskiene, Audrone; Andersen, Guro; de la Cruz, Javier

2013-10-01

Surveillance registers monitor the prevalence of cerebral palsy and the severity of resulting impairments across time and place. The motor disorders of cerebral palsy can affect children's speech production and limit their intelligibility. We describe the development of a scale to classify children's speech performance for use in cerebral palsy surveillance registers, and its reliability across raters and across time. Speech and language therapists, other healthcare professionals and parents classified the speech of 139 children with cerebral palsy (85 boys, 54 girls; mean age 6.03 years, SD 1.09) from observation and previous knowledge of the children. Another group of health professionals rated children's speech from information in their medical notes. With the exception of parents, raters reclassified children's speech at least four weeks after their initial classification. Raters were asked to rate how easy the scale was to use and how well the scale described the child's speech production using Likert scales. Inter-rater reliability was moderate to substantial (k>.58 for all comparisons). Test-retest reliability was substantial to almost perfect for all groups (k>.68). Over 74% of raters found the scale easy or very easy to use; 66% of parents and over 70% of health care professionals judged the scale to describe children's speech well or very well. We conclude that the Viking Speech Scale is a reliable tool to describe the speech performance of children with cerebral palsy, which can be applied through direct observation of children or through case note review. Copyright © 2013 Elsevier Ltd. All rights reserved.

Scintillation mitigation for long-range surveillance video

CSIR Research Space (South Africa)

Delport, JP

2010-09-01

Full Text Available Atmospheric turbulence is a naturally occurring phenomenon that can severely degrade the quality of long-range surveillance video footage. Major effects include image blurring, image warping and temporal wavering of objects in the scene. Mitigating...

75 FR 37253 - Classified National Security Information

Science.gov (United States)

2010-06-28

... ``Secret.'' (3) Each interior page of a classified document shall be marked at the top and bottom either... ``(TS)'' for Top Secret, ``(S)'' for Secret, and ``(C)'' for Confidential will be used. (2) Portions... from the informational text. (1) Conspicuously place the overall classification at the top and bottom...

A LITERATURE SURVEY ON VARIOUS ILLUMINATION NORMALIZATION TECHNIQUES FOR FACE RECOGNITION WITH FUZZY K NEAREST NEIGHBOUR CLASSIFIER

Directory of Open Access Journals (Sweden)

A. Thamizharasi

2015-05-01

Full Text Available The face recognition is popular in video surveillance, social networks and criminal identifications nowadays. The performance of face recognition would be affected by variations in illumination, pose, aging and partial occlusion of face by Wearing Hats, scarves and glasses etc. The illumination variations are still the challenging problem in face recognition. The aim is to compare the various illumination normalization techniques. The illumination normalization techniques include: Log transformations, Power Law transformations, Histogram equalization, Adaptive histogram equalization, Contrast stretching, Retinex, Multi scale Retinex, Difference of Gaussian, DCT, DCT Normalization, DWT, Gradient face, Self Quotient, Multi scale Self Quotient and Homomorphic filter. The proposed work consists of three steps. First step is to preprocess the face image with the above illumination normalization techniques; second step is to create the train and test database from the preprocessed face images and third step is to recognize the face images using Fuzzy K nearest neighbor classifier. The face recognition accuracy of all preprocessing techniques is compared using the AR face database of color images.

Just-in-time adaptive classifiers-part II: designing the classifier.

Science.gov (United States)

Alippi, Cesare; Roveri, Manuel

2008-12-01

Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolution adaptive solutions must be envisaged to track its dynamics; in this direction, adaptive classifiers are generally designed by assuming the stationary hypothesis for the process generating the data with very few results addressing nonstationary environments. This paper proposes a methodology based on k-nearest neighbor (NN) classifiers for designing adaptive classification systems able to react to changing conditions just-in-time (JIT), i.e., exactly when it is needed. k-NN classifiers have been selected for their computational-free training phase, the possibility to easily estimate the model complexity k and keep under control the computational complexity of the classifier through suitable data reduction mechanisms. A JIT classifier requires a temporal detection of a (possible) process deviation (aspect tackled in a companion paper) followed by an adaptive management of the knowledge base (KB) of the classifier to cope with the process change. The novelty of the proposed approach resides in the general framework supporting the real-time update of the KB of the classification system in response to novel information coming from the process both in stationary conditions (accuracy improvement) and in nonstationary ones (process tracking) and in providing a suitable estimate of k. It is shown that the classification system grants consistency once the change targets the process generating the data in a new stationary state, as it is the case in many real applications.

Bayesian Classifier for Medical Data from Doppler Unit

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J. Málek

2006-01-01

Full Text Available Nowadays, hand-held ultrasonic Doppler units (probes are often used for noninvasive screening of atherosclerosis in the arteries of the lower limbs. The mean velocity of blood flow in time and blood pressures are measured on several positions on each lower limb. By listening to the acoustic signal generated by the device or by reading the signal displayed on screen, a specialist can detect peripheral arterial disease (PAD.This project aims to design software that will be able to analyze data from such a device and classify it into several diagnostic classes. At the Department of Functional Diagnostics at the Regional Hospital in Liberec a database of several hundreds signals was collected. In cooperation with the specialist, the signals were manually classified into four classes. For each class, selected signal features were extracted and then used for training a Bayesian classifier. Another set of signals was used for evaluating and optimizing the parameters of the classifier. Slightly above 84 % of successfully recognized diagnostic states, was recently achieved on the test data. 

Cluster Based Text Classification Model

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

2011-01-01

We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

Reliability of case definitions for public health surveillance assessed by Round-Robin test methodology

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Claus Hermann

2006-05-01

Full Text Available Abstract Background Case definitions have been recognized to be important elements of public health surveillance systems. They are to assure comparability and consistency of surveillance data and have crucial impact on the sensitivity and the positive predictive value of a surveillance system. The reliability of case definitions has rarely been investigated systematically. Methods We conducted a Round-Robin test by asking all 425 local health departments (LHD and the 16 state health departments (SHD in Germany to classify a selection of 68 case examples using case definitions. By multivariate analysis we investigated factors linked to classification agreement with a gold standard, which was defined by an expert panel. Results A total of 7870 classifications were done by 396 LHD (93% and all SHD. Reporting sensitivity was 90.0%, positive predictive value 76.6%. Polio case examples had the lowest reporting precision, salmonellosis case examples the highest (OR = 0.008; CI: 0.005–0.013. Case definitions with a check-list format of clinical criteria resulted in higher reporting precision than case definitions with a narrative description (OR = 3.08; CI: 2.47–3.83. Reporting precision was higher among SHD compared to LHD (OR = 1.52; CI: 1.14–2.02. Conclusion Our findings led to a systematic revision of the German case definitions and build the basis for general recommendations for the creation of case definitions. These include, among others, that testable yes/no criteria in a check-list format is likely to improve reliability, and that software used for data transmission should be designed in strict accordance with the case definitions. The findings of this study are largely applicable to case definitions in many other countries or international networks as they share the same structural and editorial characteristics of the case definitions evaluated in this study before their revision.

Pixel Classification of SAR ice images using ANFIS-PSO Classifier

Directory of Open Access Journals (Sweden)

G. Vasumathi

2016-12-01

Full Text Available Synthetic Aperture Radar (SAR is playing a vital role in taking extremely high resolution radar images. It is greatly used to monitor the ice covered ocean regions. Sea monitoring is important for various purposes which includes global climate systems and ship navigation. Classification on the ice infested area gives important features which will be further useful for various monitoring process around the ice regions. Main objective of this paper is to classify the SAR ice image that helps in identifying the regions around the ice infested areas. In this paper three stages are considered in classification of SAR ice images. It starts with preprocessing in which the speckled SAR ice images are denoised using various speckle removal filters; comparison is made on all these filters to find the best filter in speckle removal. Second stage includes segmentation in which different regions are segmented using K-means and watershed segmentation algorithms; comparison is made between these two algorithms to find the best in segmenting SAR ice images. The last stage includes pixel based classification which identifies and classifies the segmented regions using various supervised learning classifiers. The algorithms includes Back propagation neural networks (BPN, Fuzzy Classifier, Adaptive Neuro Fuzzy Inference Classifier (ANFIS classifier and proposed ANFIS with Particle Swarm Optimization (PSO classifier; comparison is made on all these classifiers to propose which classifier is best suitable for classifying the SAR ice image. Various evaluation metrics are performed separately at all these three stages.

Hot complaint intelligent classification based on text mining

Directory of Open Access Journals (Sweden)

XIA Haifeng

2013-10-01

Full Text Available The complaint recognizer system plays an important role in making sure the correct classification of the hot complaint,improving the service quantity of telecommunications industry.The customers’ complaint in telecommunications industry has its special particularity which should be done in limited time,which cause the error in classification of hot complaint.The paper presents a model of complaint hot intelligent classification based on text mining,which can classify the hot complaint in the correct level of the complaint navigation.The examples show that the model can be efficient to classify the text of the complaint.

History of trichinellosis surveillance

Directory of Open Access Journals (Sweden)

Blancou J.

2001-06-01

Full Text Available The origin of trichinellosis, which existed in ancient times as testified by the discovery of parasite larvae on an Egyptian mummy, unfolded in several stages: discovery of encapsulated larvae (in the 1820s, identification and scientific description of these larvae (Paget Owen, 1835, followed by experimental infestations of animals (dogs, pigs, rabbits, mice or of humans as from 1850.The main occurrences of trichinellosis were followed with particular attention in Europe (Germany, Denmark, France, etc. and in the United States of America at the end of the XIXth century. They affected numerous domestic animal species (pigs, horses, etc. or wildlife and humans. Germany paid the heaviest toll with regard to the disease in humans, between 1860 and 1880, with several thousands of patients and more than 500 deaths.Different trichinellosis surveillance systems were set up in the relevant countries in the 1860s. In humans, this surveillance was carried out on affected living patients by a biopsy of the biceps muscles and subsequently by an analysis of eosinophilia (1895. In animals, surveillance was for a long time solely based on postmortem examination of the muscles of the affected animals. This method was used for the first time in 863 in Germany, and from the 1 890s, on several hundreds of thousands of pigs in Europe or in the United States of America.

Hybrid classifiers methods of data, knowledge, and classifier combination

CERN Document Server

Wozniak, Michal

2014-01-01

This book delivers a definite and compact knowledge on how hybridization can help improving the quality of computer classification systems. In order to make readers clearly realize the knowledge of hybridization, this book primarily focuses on introducing the different levels of hybridization and illuminating what problems we will face with as dealing with such projects. In the first instance the data and knowledge incorporated in hybridization were the action points, and then a still growing up area of classifier systems known as combined classifiers was considered. This book comprises the aforementioned state-of-the-art topics and the latest research results of the author and his team from Department of Systems and Computer Networks, Wroclaw University of Technology, including as classifier based on feature space splitting, one-class classification, imbalance data, and data stream classification.

A profile of the online dissemination of national influenza surveillance data

Directory of Open Access Journals (Sweden)

Ho Lai

2009-09-01

Full Text Available Abstract Background Influenza surveillance systems provide important and timely information to health service providers on trends in the circulation of influenza virus and other upper respiratory tract infections. Online dissemination of surveillance data is useful for risk communication to health care professionals, the media and the general public. We reviewed national influenza surveillance websites from around the world to describe the main features of surveillance data dissemination. Methods We searched for national influenza surveillance websites for every country and reviewed the resulting sites where available during the period from November 2008 through February 2009. Literature about influenza surveillance was searched at MEDLINE for relevant hyperlinks to related websites. Non-English websites were translated into English using human translators or Google language tools. Results A total of 70 national influenza surveillance websites were identified. The percentage of developing countries with surveillance websites was lower than that of developed countries (22% versus 57% respectively. Most of the websites (74% were in English or provided an English version. The most common surveillance methods included influenza-like illness consultation rates in primary care settings (89% and laboratory surveillance (44%. Most websites (70% provided data within a static report format and 66% of the websites provided data with at least weekly resolution. Conclusion Appropriate dissemination of surveillance data is important to maximize the utility of collected data. There may be room for improvement in the style and content of the dissemination of influenza data to health care professionals and the general public.

Surveillance of items important to safety in nuclear power plants

International Nuclear Information System (INIS)

1990-01-01

The Guide was prepared as part of the IAEA's programme, referred to as the NUSS Programme, for establishing Codes and Safety Guides relating to nuclear power plants. THe Guide supplements the Code on the Safety of Nuclear Power Plants: Operation, IAEA Safety Series No. 50-C-O(Rev.1). The operating organization has overall responsibility for the safe operation of the nuclear power plant. Therefore, it shall ensure that adequate surveillance activities are carried out in order to verify that the plant is operated within the prescribed operational limits and conditions, and to detect in time any deterioration of structures, systems and components as well as any adverse trend that could lead to an unsafe condition. These activities can be classified as: Monitoring plant parameters and system status; Checking and calibrating instrumentation; Testing and inspecting structures, systems and components. This Safety Guide provides guidance and recommendations on surveillance activities to ensure that structures, systems and components important to safety are available to perform their functions in accordance with design intent and assumptions

Secure and Efficient Reactive Video Surveillance for Patient Monitoring

Directory of Open Access Journals (Sweden)

An Braeken

2016-01-01

Full Text Available Video surveillance is widely deployed for many kinds of monitoring applications in healthcare and assisted living systems. Security and privacy are two promising factors that align the quality and validity of video surveillance systems with the caliber of patient monitoring applications. In this paper, we propose a symmetric key-based security framework for the reactive video surveillance of patients based on the inputs coming from data measured by a wireless body area network attached to the human body. Only authenticated patients are able to activate the video cameras, whereas the patient and authorized people can consult the video data. User and location privacy are at each moment guaranteed for the patient. A tradeoff between security and quality of service is defined in order to ensure that the surveillance system gets activated even in emergency situations. In addition, the solution includes resistance against tampering with the device on the patient’s side.

Formal and informal surveillance systems: how to build links

Directory of Open Access Journals (Sweden)

S. Desvaux

2015-11-01

Full Text Available Within the framework of highly pathogenic avian influenza (HPAI surveillance in Vietnam, interviews were carried out with poultry farmers and local animal health operators in two municipalities of the Red River delta with a view to documenting the circulation of health information concerning poultry (content of the information; method, scope and speed of circulation; actors involved; actions triggered as a result of the information received; economic and social incentives for disseminating or withholding information. The main results show that (i active informal surveillance networks exist, (ii the alert levels vary and the measures applied by the poultry farmers are myriad and often far-removed from the official recommendations, and (iii the municipal veterinarian is at the interface between the formal and the informal surveillance systems. The conclusions emphasize the need for the authorities to separate distinctly surveillance and control activities, and to regionalize control strategies, taking into account epidemiological specificities and social dynamics at local level.

SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

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Zhang Xinzheng

2017-10-01

Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

A quick survey of text categorization algorithms

Directory of Open Access Journals (Sweden)

Dan MUNTEANU

2007-12-01

Full Text Available This paper contains an overview of basic formulations and approaches to text classification. This paper surveys the algorithms used in text categorization: handcrafted rules, decision trees, decision rules, on-line learning, linear classifier, Rocchio’s algorithm, k Nearest Neighbor (kNN, Support Vector Machines (SVM.

Inferring epidemic network topology from surveillance data.

Directory of Open Access Journals (Sweden)

Xiang Wan

Full Text Available The transmission of infectious diseases can be affected by many or even hidden factors, making it difficult to accurately predict when and where outbreaks may emerge. One approach at the moment is to develop and deploy surveillance systems in an effort to detect outbreaks as timely as possible. This enables policy makers to modify and implement strategies for the control of the transmission. The accumulated surveillance data including temporal, spatial, clinical, and demographic information, can provide valuable information with which to infer the underlying epidemic networks. Such networks can be quite informative and insightful as they characterize how infectious diseases transmit from one location to another. The aim of this work is to develop a computational model that allows inferences to be made regarding epidemic network topology in heterogeneous populations. We apply our model on the surveillance data from the 2009 H1N1 pandemic in Hong Kong. The inferred epidemic network displays significant effect on the propagation of infectious diseases.

Surveillance Culture

DEFF Research Database (Denmark)

2017-01-01

What does it mean to live in a world full of surveillance? In this documentary film, we take a look at everyday life in Denmark and how surveillance technologies and practices influence our norms and social behaviour. Researched and directed by Btihaj Ajana and Anders Albrechtslund....

What are the benefits of medical screening and surveillance?

Directory of Open Access Journals (Sweden)

D. Wilken

2012-06-01

Full Text Available Pre-employment examination is considered to be an important practice and is commonly performed in several countries within the European Union. The benefits of medical surveillance programmes are not generally accepted and their structure is often inconsistent. The aim of this review was to evaluate, on the basis of the available literature, the usefulness of medical screening and surveillance. MEDLINE was searched from its inception up to March 2010. Retrieved literature was evaluated in a peer-review process and relevant data was collected following a systematic extraction schema. Pre-placement screening identifies subjects who are at an increased risk for developing work-related allergic disease, but pre-employment screening is too low to be used as exclusion criteria. Medical surveillance programmes can identify workers who have, or who are developing, work-related asthma. These programmes can also be used to avoid worsening of symptoms by implementing preventive measures. A combination of different tools within the surveillance programme, adjusted for the risk of the individual worker, improves the predictive value. Medical surveillance programmes provide medical as well as socioeconomic benefits. However, pre-employment screening cannot be used to exclude workers. They may act as a starting point for surveillance strategies. A stratified approach can increase the effectiveness and reduce the costs for such programmes.

A cardiorespiratory classifier of voluntary and involuntary electrodermal activity

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Sejdic Ervin

2010-02-01

Full Text Available Abstract Background Electrodermal reactions (EDRs can be attributed to many origins, including spontaneous fluctuations of electrodermal activity (EDA and stimuli such as deep inspirations, voluntary mental activity and startling events. In fields that use EDA as a measure of psychophysiological state, the fact that EDRs may be elicited from many different stimuli is often ignored. This study attempts to classify observed EDRs as voluntary (i.e., generated from intentional respiratory or mental activity or involuntary (i.e., generated from startling events or spontaneous electrodermal fluctuations. Methods Eight able-bodied participants were subjected to conditions that would cause a change in EDA: music imagery, startling noises, and deep inspirations. A user-centered cardiorespiratory classifier consisting of 1 an EDR detector, 2 a respiratory filter and 3 a cardiorespiratory filter was developed to automatically detect a participant's EDRs and to classify the origin of their stimulation as voluntary or involuntary. Results Detected EDRs were classified with a positive predictive value of 78%, a negative predictive value of 81% and an overall accuracy of 78%. Without the classifier, EDRs could only be correctly attributed as voluntary or involuntary with an accuracy of 50%. Conclusions The proposed classifier may enable investigators to form more accurate interpretations of electrodermal activity as a measure of an individual's psychophysiological state.

Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier

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Keming Mao

2016-01-01

Full Text Available This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

A Bayesian Classifier for X-Ray Pulsars Recognition

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Hao Liang

2016-01-01

Full Text Available Recognition for X-ray pulsars is important for the problem of spacecraft’s attitude determination by X-ray Pulsar Navigation (XPNAV. By using the nonhomogeneous Poisson model of the received photons and the minimum recognition error criterion, a classifier based on the Bayesian theorem is proposed. For X-ray pulsars recognition with unknown Doppler frequency and initial phase, the features of every X-ray pulsar are extracted and the unknown parameters are estimated using the Maximum Likelihood (ML method. Besides that, a method to recognize unknown X-ray pulsars or X-ray disturbances is proposed. Simulation results certificate the validity of the proposed Bayesian classifier.

A surveillance sector review applied to infectious diseases at a country level

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Easther Sally

2010-06-01

Full Text Available Abstract Background The new International Health Regulations (IHR require World Health Organization (WHO member states to assess their core capacity for surveillance. Such reviews also have the potential to identify important surveillance gaps, improve the organisation of disparate surveillance systems and to focus attention on upstream hazards, determinants and interventions. Methods We developed a surveillance sector review method for evaluating all of the surveillance systems and related activities across a sector, in this case those concerned with infectious diseases in New Zealand. The first stage was a systematic description of these surveillance systems using a newly developed framework and classification system. Key informant interviews were conducted to validate the available information on the systems identified. Results We identified 91 surveillance systems and related activities in the 12 coherent categories of infectious diseases examined. The majority (n = 40 or 44% of these were disease surveillance systems. They covered all categories, particularly for more severe outcomes including those resulting in death or hospitalisations. Except for some notifiable diseases and influenza, surveillance of less severe, but important infectious diseases occurring in the community was largely absent. There were 31 systems (34% for surveillance of upstream infectious disease hazards, including risk and protective factors. This area tended to have many potential gaps and lack integration, partly because such systems were operated by a range of different agencies, often outside the health sector. There were fewer surveillance systems for determinants, including population size and characteristics (n = 9, and interventions (n = 11. Conclusions It was possible to create and populate a workable framework for describing all the infectious diseases surveillance systems and related activities in a single developed country and to identify potential

An Intelligent System For Arabic Text Categorization

NARCIS (Netherlands)

Syiam, M.M.; Tolba, Mohamed F.; Fayed, Z.T.; Abdel-Wahab, Mohamed S.; Ghoniemy, Said A.; Habib, Mena Badieh

Text Categorization (classification) is the process of classifying documents into a predefined set of categories based on their content. In this paper, an intelligent Arabic text categorization system is presented. Machine learning algorithms are used in this system. Many algorithms for stemming and

COMPARISON OF SVM AND FUZZY CLASSIFIER FOR AN INDIAN SCRIPT

Directory of Open Access Journals (Sweden)

M. J. Baheti

2012-01-01

Full Text Available With the advent of technological era, conversion of scanned document (handwritten or printed into machine editable format has attracted many researchers. This paper deals with the problem of recognition of Gujarati handwritten numerals. Gujarati numeral recognition requires performing some specific steps as a part of preprocessing. For preprocessing digitization, segmentation, normalization and thinning are done with considering that the image have almost no noise. Further affine invariant moments based model is used for feature extraction and finally Support Vector Machine (SVM and Fuzzy classifiers are used for numeral classification. . The comparison of SVM and Fuzzy classifier is made and it can be seen that SVM procured better results as compared to Fuzzy Classifier.

Current Directional Protection of Series Compensated Line Using Intelligent Classifier

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M. Mollanezhad Heydarabadi

2016-12-01

Full Text Available Current inversion condition leads to incorrect operation of current based directional relay in power system with series compensated device. Application of the intelligent system for fault direction classification has been suggested in this paper. A new current directional protection scheme based on intelligent classifier is proposed for the series compensated line. The proposed classifier uses only half cycle of pre-fault and post fault current samples at relay location to feed the classifier. A lot of forward and backward fault simulations under different system conditions upon a transmission line with a fixed series capacitor are carried out using PSCAD/EMTDC software. The applicability of decision tree (DT, probabilistic neural network (PNN and support vector machine (SVM are investigated using simulated data under different system conditions. The performance comparison of the classifiers indicates that the SVM is a best suitable classifier for fault direction discriminating. The backward faults can be accurately distinguished from forward faults even under current inversion without require to detect of the current inversion condition.

Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier

Directory of Open Access Journals (Sweden)

Rashed Mustafa

2014-01-01

Full Text Available Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier.

Possibilities of Applying Video Surveillance and other ICT Tools and Services in the Production Process

Directory of Open Access Journals (Sweden)

Adis Rahmanović

2018-02-01

Full Text Available The paper presents the possibilities of applying Video surveillance and other ICT tools and services in the production process. The first part of the paper presented the system for controlling video surveillance for and the given opportunity of application of video surveillance for the security of the employees and the assets. In the second part of the paper an analysis of the system for controlling production is given and then a video surveillance of a work excavator. The next part of the paper presents integration of video surveillance and the accompanying tools. At the end of the paper, suggestions were also given for further works in the field of data protection and cryptography in video surveillance use.

Evaluation of health surveillance activities of hajj 2013 in the hajj embarkation Palangkaraya

Directory of Open Access Journals (Sweden)

Elvan Virgo Hoesea

2014-05-01

Full Text Available ABSTRACT Meningococcal meningitis and MERS-CoV is a disease that can be transmitted to a wary pilgrim considering the high incidence of both diseases in the Middle East region. This study was conducted to evaluate the surveillance activities conducted at embarkation Palangkaraya pilgrimage between 2013 and assess the surveillance activities based on the attributes of surveillance and barriers that occur in the implementation of activities. Experiment was conducted with descriptive design using quantitative approach. Questionnaires were completed at 6 implementing surveillance activities. Interviews were conducted to obtain information about the variables under study includes data collection, processing, analysis and interpretation, dissemination of information and surveillance attributes such as simplicity, flexibility, acceptability, sensitivity, positive predictive value, representatif, timeliness, data quality and data stability. Implementation health surveillance in the hajj embarkation Palangkaraya in 2013 showed all stages of the surveillance activities have been conducted in accordance with the procedures as well as evaluating surveillance activities in accordance attribute shows all the attributes of surveillance can be assessed, unless the sensitivity and positive predictive value because no cases of meningococcal meningitis. Conclusion that the implementation of health surveillance activities Hajj has been running quite well based approach to surveillance and surveillance attributes. The report has been used by the agency activities related to the activities of hajj embarkation. Need to increase the quantity and quality of manpower resources and facilities Keywords: disease transmission, hajj health surveillance, assessment                             attributes

Recognition of Arabic Sign Language Alphabet Using Polynomial Classifiers

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M. Al-Rousan

2005-08-01

Full Text Available Building an accurate automatic sign language recognition system is of great importance in facilitating efficient communication with deaf people. In this paper, we propose the use of polynomial classifiers as a classification engine for the recognition of Arabic sign language (ArSL alphabet. Polynomial classifiers have several advantages over other classifiers in that they do not require iterative training, and that they are highly computationally scalable with the number of classes. Based on polynomial classifiers, we have built an ArSL system and measured its performance using real ArSL data collected from deaf people. We show that the proposed system provides superior recognition results when compared with previously published results using ANFIS-based classification on the same dataset and feature extraction methodology. The comparison is shown in terms of the number of misclassified test patterns. The reduction in the rate of misclassified patterns was very significant. In particular, we have achieved a 36% reduction of misclassifications on the training data and 57% on the test data.

RETURNING THE GAZE: CULTURE AND THE POLITICS OF SURVEILLANCE IN IRELAND

Directory of Open Access Journals (Sweden)

Spurgeon Thompson

2002-12-01

Full Text Available This essay seeks to examine the modalities of colonial state surveillance as well as severa1 ways in which they have been problematised in recent lrish literary writing, film, painting, photography and practice. Works by Ciaran Carson, Willie Doherty, Dave Fox, Teny George and Jim Sheridan, and Dermot Seymour are al1 therefore examined with the thernatic of "returning the gaze" in rnind. Further, this essay seeks to advance contemporary theories of surveillance away from an information-based or textual model to one which considers the spatial violence of surveillance and the subject positions it delimits, particularly in the context of colonialism and postcolonial theory.

Limits on surveillance: frictions, fragilities and failures in the operation of camera surveillance.

NARCIS (Netherlands)

Dubbeld, L.

2004-01-01

Public video surveillance tends to be discussed in either utopian or dystopian terms: proponents maintain that camera surveillance is the perfect tool in the fight against crime, while critics argue that the use of security cameras is central to the development of a panoptic, Orwellian surveillance

Research on Classification of Chinese Text Data Based on SVM

Science.gov (United States)

Lin, Yuan; Yu, Hongzhi; Wan, Fucheng; Xu, Tao

2017-09-01

Data Mining has important application value in today’s industry and academia. Text classification is a very important technology in data mining. At present, there are many mature algorithms for text classification. KNN, NB, AB, SVM, decision tree and other classification methods all show good classification performance. Support Vector Machine’ (SVM) classification method is a good classifier in machine learning research. This paper will study the classification effect based on the SVM method in the Chinese text data, and use the support vector machine method in the chinese text to achieve the classify chinese text, and to able to combination of academia and practical application.

Adherence to colorectal polyp surveillance guidelines: is there a 'scope' to increase the opportunities for screening?

LENUS (Irish Health Repository)

O'Connor, Anthony

2012-02-01

Colorectal polyps are usually asymptomatic and are found opportunistically. Individuals with adenomata are at increased risk for cancer and therefore guidelines exist for surveillance of these lesions including those of the British Society of Gastroenterology (BSG). Deviation from these guidelines is common and increases the workload of endoscopy. We examined those individuals waiting for endoscopy for polyp surveillance to see whether strict adherence to BSG guidelines could facilitate opportunities for screening. A total of 413 patients with earlier colonic polyps were examined, of whom 50 patients were excluded based on having alternative indications for surveillance, 179 (49.3%) were appropriately scheduled for surveillance and 184 patients (55.9%) were scheduled incorrectly. Seventy-nine patients (30%) could have been discharged; of these, 59 had hyperplastic polyps. Of the remaining 105 inappropriate triages under surveillance at the wrong interval, seven patients were scheduled for too infrequent surveillance and 98 were too frequent. A total of 284 patients with adenomatous polyps were under surveillance of whom 11 patients (3.8%) were in the high-risk category and all were appropriately scheduled, and 75 patients (26.4%) were in the intermediate-risk category, of whom 48 were appropriately scheduled, 20 were incorrectly triaged as high risk and seven were triaged as low risk. A total of 198 (69.7%) patients were in the low-risk category, 117 of these were correctly triaged, 15 were incorrectly triaged as high risk and 66 were classified as intermediate risk. Over a five-year period, 318 unnecessary colonoscopies are being performed. On the basis of the data obtained from a population-based colorectal screening programme using immunohistochemical-faecal occult blood testing in our department another 1516 patients could be screened annually without requiring any additional endoscopy resources, if strict adherence to guidelines was assured.

Text categorization of biomedical data sets using graph kernels and a controlled vocabulary.

Science.gov (United States)

Bleik, Said; Mishra, Meenakshi; Huan, Jun; Song, Min

2013-01-01

Recently, graph representations of text have been showing improved performance over conventional bag-of-words representations in text categorization applications. In this paper, we present a graph-based representation for biomedical articles and use graph kernels to classify those articles into high-level categories. In our representation, common biomedical concepts and semantic relationships are identified with the help of an existing ontology and are used to build a rich graph structure that provides a consistent feature set and preserves additional semantic information that could improve a classifier's performance. We attempt to classify the graphs using both a set-based graph kernel that is capable of dealing with the disconnected nature of the graphs and a simple linear kernel. Finally, we report the results comparing the classification performance of the kernel classifiers to common text-based classifiers.

Handbook of surveillance technologies

CERN Document Server

Petersen, JK

2012-01-01

From officially sanctioned, high-tech operations to budget spy cameras and cell phone video, this updated and expanded edition of a bestselling handbook reflects the rapid and significant growth of the surveillance industry. The Handbook of Surveillance Technologies, Third Edition is the only comprehensive work to chronicle the background and current applications of the full-range of surveillance technologies--offering the latest in surveillance and privacy issues.Cutting-Edge--updates its bestselling predecessor with discussions on social media, GPS circuits in cell phones and PDAs, new GIS s

SparkText: Biomedical Text Mining on Big Data Framework.

Science.gov (United States)

Ye, Zhan; Tafti, Ahmad P; He, Karen Y; Wang, Kai; He, Max M

Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

Containment and surveillance devices

International Nuclear Information System (INIS)

Campbell, J.W.; Johnson, C.S.; Stieff, L.R.

The growing acceptance of containment and surveillance as a means to increase safeguards effectiveness has provided impetus to the development of improved surveillance and containment devices. Five recently developed devices are described. The devices include one photographic and two television surveillance systems and two high security seals that can be verified while installed

An Active Learning Classifier for Further Reducing Diabetic Retinopathy Screening System Cost

Directory of Open Access Journals (Sweden)

Yinan Zhang

2016-01-01

Full Text Available Diabetic retinopathy (DR screening system raises a financial problem. For further reducing DR screening cost, an active learning classifier is proposed in this paper. Our approach identifies retinal images based on features extracted by anatomical part recognition and lesion detection algorithms. Kernel extreme learning machine (KELM is a rapid classifier for solving classification problems in high dimensional space. Both active learning and ensemble technique elevate performance of KELM when using small training dataset. The committee only proposes necessary manual work to doctor for saving cost. On the publicly available Messidor database, our classifier is trained with 20%–35% of labeled retinal images and comparative classifiers are trained with 80% of labeled retinal images. Results show that our classifier can achieve better classification accuracy than Classification and Regression Tree, radial basis function SVM, Multilayer Perceptron SVM, Linear SVM, and K Nearest Neighbor. Empirical experiments suggest that our active learning classifier is efficient for further reducing DR screening cost.

Child injury surveillance capabilities in NSW: informing policy and practice

Directory of Open Access Journals (Sweden)

Rebecca Mitchell

2017-10-01

Full Text Available Injury is one of the most common reasons why a child is hospitalised. Information gained from injury surveillance activities provides an estimate of the injury burden, describes injury event circumstances, can be used to monitor injury trends over time, and is used to design and evaluate injury prevention activities. This perspective article provides an overview of child injury surveillance capabilities within New South Wales (NSW, Australia, following a stocktake of population-based injury-related data collections using the Evaluation Framework for Injury Surveillance Systems. Information about childhood injury in NSW is obtained from multiple administrative data collections that were not specifically designed to conduct injury surveillance. Obtaining good information for child injury surveillance in NSW will involve better coordination of information from agencies that record information about childhood injury. Regular reporting about childhood injury to provide a comprehensive profile of injuries of children and young people in the state should be considered, along with the provision and/or linkage of child injury information from multiple data collections. This could support the development of a suite of injury performance indicators to monitor childhood injury reduction strategies across NSW.

An integrated national mortality surveillance system for death registration and mortality surveillance, China.

Science.gov (United States)

Liu, Shiwei; Wu, Xiaoling; Lopez, Alan D; Wang, Lijun; Cai, Yue; Page, Andrew; Yin, Peng; Liu, Yunning; Li, Yichong; Liu, Jiangmei; You, Jinling; Zhou, Maigeng

2016-01-01

In China, sample-based mortality surveillance systems, such as the Chinese Center for Disease Control and Prevention's disease surveillance points system and the Ministry of Health's vital registration system, have been used for decades to provide nationally representative data on health status for health-care decision-making and performance evaluation. However, neither system provided representative mortality and cause-of-death data at the provincial level to inform regional health service needs and policy priorities. Moreover, the systems overlapped to a considerable extent, thereby entailing a duplication of effort. In 2013, the Chinese Government combined these two systems into an integrated national mortality surveillance system to provide a provincially representative picture of total and cause-specific mortality and to accelerate the development of a comprehensive vital registration and mortality surveillance system for the whole country. This new system increased the surveillance population from 6 to 24% of the Chinese population. The number of surveillance points, each of which covered a district or county, increased from 161 to 605. To ensure representativeness at the provincial level, the 605 surveillance points were selected to cover China's 31 provinces using an iterative method involving multistage stratification that took into account the sociodemographic characteristics of the population. This paper describes the development and operation of the new national mortality surveillance system, which is expected to yield representative provincial estimates of mortality in China for the first time.

Using Unlabeled Data to Improve Text Classification

National Research Council Canada - National Science Library

Nigam, Kamal P

2001-01-01

.... This dissertation demonstrates that supervised learning algorithms that use a small number of labeled examples and many inexpensive unlabeled examples can create high-accuracy text classifiers...

Data Stream Classification Based on the Gamma Classifier

Directory of Open Access Journals (Sweden)

Abril Valeria Uriarte-Arcia

2015-01-01

Full Text Available The ever increasing data generation confronts us with the problem of handling online massive amounts of information. One of the biggest challenges is how to extract valuable information from these massive continuous data streams during single scanning. In a data stream context, data arrive continuously at high speed; therefore the algorithms developed to address this context must be efficient regarding memory and time management and capable of detecting changes over time in the underlying distribution that generated the data. This work describes a novel method for the task of pattern classification over a continuous data stream based on an associative model. The proposed method is based on the Gamma classifier, which is inspired by the Alpha-Beta associative memories, which are both supervised pattern recognition models. The proposed method is capable of handling the space and time constrain inherent to data stream scenarios. The Data Streaming Gamma classifier (DS-Gamma classifier implements a sliding window approach to provide concept drift detection and a forgetting mechanism. In order to test the classifier, several experiments were performed using different data stream scenarios with real and synthetic data streams. The experimental results show that the method exhibits competitive performance when compared to other state-of-the-art algorithms.

Digital dashboard design using multiple data streams for disease surveillance with influenza surveillance as an example.

Science.gov (United States)

Cheng, Calvin K Y; Ip, Dennis K M; Cowling, Benjamin J; Ho, Lai Ming; Leung, Gabriel M; Lau, Eric H Y

2011-10-14

Great strides have been made exploring and exploiting new and different sources of disease surveillance data and developing robust statistical methods for analyzing the collected data. However, there has been less research in the area of dissemination. Proper dissemination of surveillance data can facilitate the end user's taking of appropriate actions, thus maximizing the utility of effort taken from upstream of the surveillance-to-action loop. The aims of the study were to develop a generic framework for a digital dashboard incorporating features of efficient dashboard design and to demonstrate this framework by specific application to influenza surveillance in Hong Kong. Based on the merits of the national websites and principles of efficient dashboard design, we designed an automated influenza surveillance digital dashboard as a demonstration of efficient dissemination of surveillance data. We developed the system to synthesize and display multiple sources of influenza surveillance data streams in the dashboard. Different algorithms can be implemented in the dashboard for incorporating all surveillance data streams to describe the overall influenza activity. We designed and implemented an influenza surveillance dashboard that utilized self-explanatory figures to display multiple surveillance data streams in panels. Indicators for individual data streams as well as for overall influenza activity were summarized in the main page, which can be read at a glance. Data retrieval function was also incorporated to allow data sharing in standard format. The influenza surveillance dashboard serves as a template to illustrate the efficient synthesization and dissemination of multiple-source surveillance data, which may also be applied to other diseases. Surveillance data from multiple sources can be disseminated efficiently using a dashboard design that facilitates the translation of surveillance information to public health actions.

Towards an information ecosystem for animal disease surveillance using voice services

CSIR Research Space (South Africa)

Sharma Grover, A

2013-01-01

Full Text Available In this paper we introduce a solution for disease surveillance and monitoring in the primary animal health care (PAHC) domain that uses inbound voice-based services and voice- and text-based outbound services for connecting rural veterinarians...

Catheter Associated Urinary Tract Infection Based on Surveillance Attributes in RSU Haji Surabaya

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Spica Redina Vebrilian

2017-03-01

Full Text Available Surveillance system is instrumental in reducing the incidence of nosocomial infection. The implementation of this surveillance system is necessary in the hospital. Surveillance CAUTI is one of the focus prevention and infection control program in RSU Haji Surabaya 2015. The success of surveillance system highly depends on the association of attributes inside it. Surveillance attributes are indicator that describes the characteristics ofsurveillance system. In 2015, there was a delay in the collection of data reports which exceeds the prescribed time limit and there was also a lot of blank space in the confi rmation sheet. It affects the surveillance system in RSU Haji Surabaya. The purpose of this research is to evaluate the surveillance CAUTI based on the surveillance attributes in RSU Haji Surabaya2015. This research is a descriptive evaluative research. Subjects in this study are the surveillance attributes (simplicity, flexibility, acceptability, sensitivity, positive predictive value, representativeness, timeliness, data quality, and stability CAUTI in RSU Haji Surabaya, while survey respondents are IPCN, IPCLN, and head nurse. Data collected by interview and documentation study. The results showed that the attributes of surveillance is already has simplicity, high acceptability, high sensitivity, high positive predictive value, representative, and high stability. However, other attributes were not fl exible, not timeliness, and has a low data quality. Alternative solutions that can be done are to improve the regulatory function in every unit, establish standardization of hospital data, and manage reward and punishment system. Keywords: surveillance system, surveillance attributes, evaluation, nosocomial infections, CAUTI

Scoring and Classifying Examinees Using Measurement Decision Theory

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Lawrence M. Rudner

2009-04-01

Full Text Available This paper describes and evaluates the use of measurement decision theory (MDT to classify examinees based on their item response patterns. The model has a simple framework that starts with the conditional probabilities of examinees in each category or mastery state responding correctly to each item. The presented evaluation investigates: (1 the classification accuracy of tests scored using decision theory; (2 the effectiveness of different sequential testing procedures; and (3 the number of items needed to make a classification. A large percentage of examinees can be classified accurately with very few items using decision theory. A Java Applet for self instruction and software for generating, calibrating and scoring MDT data are provided.

Mass Surveillance and the Militarization of Cyberspace in Post-Coup Thailand

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Pinkaew Laungaramsri

2016-12-01

Full Text Available Post-coup Thailand has witnessed a troubling shift toward censorship, surveillance, and suppression in cyberspace. With cyber security ranking prominently on the military’s agenda and the expansion of the military’s cyber intervention, the country’s online infrastructure has undergone politicization, securitization, and militarization. This paper argues that the militarization of cyberspace in Thailand represents the process in which cyber warfare capabilities have been integrated with other military forces and with support from the masses. This process has been effective through at least three significant mechanisms, including mass surveillance, surveillance by the masses, and normalization of surveillance. Social media have been turned into an absolute digital panopticon. Cyber dystopia, created by the 2014 coup and supported by the masses, has served to sustain a ‘state of exception’ not only within the territorial borders of the state, but also more importantly, within the virtual space of civil society. Cyber surveillance by the military and the masses has continued to jeopardize the already vulnerable Thai democracy.

The politics of surveillance policy: UK regulatory dynamics after Snowden

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Arne Hintz

2016-09-01

Full Text Available The revelations by NSA whistleblower Edward Snowden have illustrated the scale and extent of digital surveillance carried out by different security and intelligence agencies. The publications have led to a variety of concerns, public debate, and some diplomatic fallout regarding the legality of the surveillance, the extent of state interference in civic life, and the protection of civil rights in the context of security. Debates about the policy environment of surveillance emerged quickly after the leaks began, but actual policy change is only starting. In the UK, a draft law (Investigatory Powers Bill has been proposed and is currently discussed. In this paper, we will trace the forces and dynamics that have shaped this particular policy response. Addressing surveillance policy as a site of struggle between different social forces and drawing on different fields across communication policy research, we suggest eight dynamics that, often in conflicting ways, have shaped the regulatory framework of surveillance policy in the UK since the Snowden leaks. These include the governmental context; national and international norms; court rulings; civil society advocacy; technical standards; private sector interventions; media coverage; and public opinion. We investigate how state surveillance has been met with criticism by parts of the technology industry and civil society, and that policy change was required as a result of legal challenges, review commissions and normative interventions. However a combination of specific government compositions, the strong role of security agendas and discourses, media justification and a muted reaction by the public have hindered a more fundamental review of surveillance practices so far and have moved policy debate towards the expansion, rather than the restriction, of surveillance in the aftermath of Snowden.

Extended surveillance as a support to PLIM

International Nuclear Information System (INIS)

Walle, Eric van

2002-01-01

Full text: The safe exploitation of the reactor pressure vessel was and is always a major concern in nuclear power plant life management. At present, issues like Plant Life Extension, where utilities look into the possibility of license renewal after 40 years of operation, are becoming relevant in the USA. In other countries PLIM beyond the design life of the NPP could also be desirable from the economic viewpoint. The limiting factor could, however, be the integrity of the reactor pressure vessel. The reactor pressure vessel surveillance procedures as defined by regulatory legislation is limited and can be supplemented with valuable information that can be extracted in parallel to conventional surveillance testing or through additional testing on surveillance material. This is justified for several reasons: 1. The current methodology is semi-empirical, contains flaws and is in a number of cases over conservative. Without giving in on safety, we need to try and understand the material behavior more fundamentally; 2. Some reactor surveillance materials demonstrate inconsistent behavior with respect to the overall trend. These materials are called 'outlier' materials. But are they really outliers or is this connected to the indexing methodology used? 3. Additional data, for example the results of instrumented Charpy-V impact tests, have been obtained on many surveillance test specimens and are not adequately exploited in the actual surveillance methodology; 4. Scientific research provides substantial information and understanding of degradation mechanisms in reactor pressure vessel steels. Although we will not concentrate on this topic, the development of powerful microscopic investigation techniques, like FEGSTEM, APFIM, SANS, positron annihilation, internal friction, ... led to an intensified development of radiation damage modelling and are an input to micromechanical modelling. Moreover, due to the ever increasing computer power, additional multi-scale (time and

Surveillance Patterns After Curative-Intent Colorectal Cancer Surgery in Ontario

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Jensen Tan

2014-01-01

Full Text Available BACKGROUND: Postoperative surveillance following curative-intent resection of colorectal cancer (CRC is variably performed due to existing guideline differences and to the limited data supporting different strategies.

SparkText: Biomedical Text Mining on Big Data Framework.

Directory of Open Access Journals (Sweden)

Zhan Ye

Full Text Available Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment.In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM, and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes.This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

Regional Disease Surveillance Meeting - Final Paper

Energy Technology Data Exchange (ETDEWEB)

Lesperance, Ann M.; Mahy, Heidi A.

2006-08-08

On June 1, 2006, public health officials working in surveillance, epidemiological modeling, and information technology communities from the Seattle/Tacoma area and State of Washington met with members of the Pacific Northwest National Laboratory (PNNL) to discuss the current state of disease surveillance and gaps and needs to improve the current systems. The meeting also included a discussion of PNNL initiatives that might be appropriate to enhance disease surveillance and the current tools being used for disease surveillance. Participants broke out into two groups to identify critical gaps and needs for improving a surveillance system, and discuss the requirements for developing improved surveillance. Each group developed a list of key priorities summarizing the requirements for improved surveillance. The objective of this meeting was to work towards the development of an improved disease surveillance system.

Is the HIV sentinel surveillance system adequate in China? Findings from an evaluation of the national HIV sentinel surveillance system

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Marc Bulterys

2012-11-01

Full Text Available Background: An external evaluation was conducted to assess the performance of the national HIV sentinel surveillance system (HSS, identify operational challenges at national and local levels and provide recommendations for improvement.Methods: The United States Centers for Disease Control and Prevention’s (CDC Updated Guidelines for Evaluating Public Health Surveillance Systems were followed to assess the key attributes of HSS. Comprehensive assessment activities were conducted, including: using a detailed checklist to review surveillance guidelines, protocols and relevant documents; conducting self-administered, anonymous surveys with 286 local China CDC staff; and carrying out field observations in 32 sentinel sites in four provinces.Results: China has built an extensive HSS with 1888 sentinel sites to monitor HIV epidemic trends by population groups over time. The strengths of HSS lie in its flexibility, simplicity, usefulness and increase in coverage in locations and populations. With its rapid expansion in 2010, HSS faces challenges in maintaining acceptability, timeliness, data quality, representativeness and sustainability.Recommendations: Implementation of the national guidelines should be standardized by strengthening training, monitoring and supervision of all staff involved, including community-based organizations. National surveillance guidelines need to be revised to strengthen data quality and representativeness, particularly to include specific instructions on HIV testing result provision, collection of identifying information, sample size and sampling methods particularly for men who have sex with men (MSM, collection of refusal information, and data interpretation. Sustainability of China’s HSS could be strengthened by applying locally tailored surveillance strategies, strengthening coordination and cooperation among government agencies and ensuring financial and human resources.

A review of zoonotic disease surveillance supported by the Armed Forces Health Surveillance Center.

Science.gov (United States)

Burke, R L; Kronmann, K C; Daniels, C C; Meyers, M; Byarugaba, D K; Dueger, E; Klein, T A; Evans, B P; Vest, K G

2012-05-01

The Armed Forces Health Surveillance Center (AFHSC), Division of Global Emerging Infections Surveillance and Response System conducts disease surveillance through a global network of US Department of Defense research laboratories and partnerships with foreign ministries of agriculture, health and livestock development in over 90 countries worldwide. In 2010, AFHSC supported zoonosis survey efforts were organized into four main categories: (i) development of field assays for animal disease surveillance during deployments and in resource limited environments, (ii) determining zoonotic disease prevalence in high-contact species which may serve as important reservoirs of diseases and sources of transmission, (iii) surveillance in high-risk human populations which are more likely to become exposed and subsequently infected with zoonotic pathogens and (iv) surveillance at the human-animal interface examining zoonotic disease prevalence and transmission within and between human and animal populations. These efforts have aided in the detection, identification and quantification of the burden of zoonotic diseases such as anthrax, brucellosis, Crimean Congo haemorrhagic fever, dengue fever, Hantaan virus, influenza, Lassa fever, leptospirosis, melioidosis, Q fever, Rift Valley fever, sandfly fever Sicilian virus, sandfly fever Naples virus, tuberculosis and West Nile virus, which are of military and public health importance. Future zoonotic surveillance efforts will seek to develop local capacity for zoonotic surveillance focusing on high risk populations at the human-animal interface. © 2011 Blackwell Verlag GmbH.

Factors that affect the accuracy of text-based language identification

CSIR Research Space (South Africa)

Botha, GR

2007-11-01

Full Text Available its excellent accuracy, another significant ad- vantage of the NB classifier is that new language doc- uments can simply be merged into an existing classifier by adding the n-gram statistics of these documents to the current language model...

Evaluating Surveillance Breast Imaging and Biopsy in Older Breast Cancer Survivors

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Tracy Onega

2012-01-01

Full Text Available Background. Patterns of surveillance among breast cancer survivors are not well characterized and lack evidence-based practice guidelines, particularly for imaging modalities other than mammography. We characterized breast imaging and related biopsy longitudinally among breast cancer survivors in relation to women’s characteristics. Methods. Using data from a state-wide (New Hampshire breast cancer screening registry linked to Medicare claims, we examined use of mammography, ultrasound (US, magnetic resonance imaging (MRI, and biopsy among breast cancer survivors. We used generalized estimating equations (GEE to model associations of breast surveillance with women’s characteristics. Results. The proportion of women with mammography was high over the follow-up period (81.5% at 78 months, but use of US or MRI was much lower (8.0%—first follow-up window, 4.7% by 78 months. Biopsy use was consistent throughout surveillance periods (7.4%–9.4%. Surveillance was lower among older women and for those with a higher stage of diagnosis. Primary therapy was significantly associated with greater likelihood of breast surveillance. Conclusions. Breast cancer surveillance patterns for mammography, US, MRI, and related biopsy seem to be associated with age, stage, and treatment, but need a larger evidence-base for clinical recommendations.

Use of emergency department electronic medical records for automated epidemiological surveillance of suicide attempts: a French pilot study.

Science.gov (United States)

Metzger, Marie-Hélène; Tvardik, Nastassia; Gicquel, Quentin; Bouvry, Côme; Poulet, Emmanuel; Potinet-Pagliaroli, Véronique

2017-06-01

The aim of this study was to determine whether an expert system based on automated processing of electronic health records (EHRs) could provide a more accurate estimate of the annual rate of emergency department (ED) visits for suicide attempts in France, as compared to the current national surveillance system based on manual coding by emergency practitioners. A feasibility study was conducted at Lyon University Hospital, using data for all ED patient visits in 2012. After automatic data extraction and pre-processing, including automatic coding of medical free-text through use of the Unified Medical Language System, seven different machine-learning methods were used to classify the reasons for ED visits into "suicide attempts" versus "other reasons". The performance of these different methods was compared by using the F-measure. In a test sample of 444 patients admitted to the ED in 2012 (98 suicide attempts, 48 cases of suicidal ideation, and 292 controls with no recorded non-fatal suicidal behaviour), the F-measure for automatic detection of suicide attempts ranged from 70.4% to 95.3%. The random forest and naïve Bayes methods performed best. This study demonstrates that machine-learning methods can improve the quality of epidemiological indicators as compared to current national surveillance of suicide attempts. Copyright © 2016 John Wiley & Sons, Ltd.

“Veillant Panoptic Assemblage”: Mutual Watching and Resistance to Mass Surveillance after Snowden

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Vian Bakir

2015-10-01

Full Text Available The Snowden leaks indicate the extent, nature, and means of contemporary mass digital surveillance of citizens by their intelligence agencies and the role of public oversight mechanisms in holding intelligence agencies to account. As such, they form a rich case study on the interactions of “veillance” (mutual watching involving citizens, journalists, intelligence agencies and corporations. While Surveillance Studies, Intelligence Studies and Journalism Studies have little to say on surveillance of citizens’ data by intelligence agencies (and complicit surveillant corporations, they offer insights into the role of citizens and the press in holding power, and specifically the political-intelligence elite, to account. Attention to such public oversight mechanisms facilitates critical interrogation of issues of surveillant power, resistance and intelligence accountability. It directs attention to the veillant panoptic assemblage (an arrangement of profoundly unequal mutual watching, where citizens’ watching of self and others is, through corporate channels of data flow, fed back into state surveillance of citizens. Finally, it enables evaluation of post-Snowden steps taken towards achieving an equiveillant panoptic assemblage (where, alongside state and corporate surveillance of citizens, the intelligence-power elite, to ensure its accountability, faces robust scrutiny and action from wider civil society.

Portable digital video surveillance system for monitoring flower-visiting bumblebees

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Thorsdatter Orvedal Aase, Anne Lene

2011-08-01

Full Text Available In this study we used a portable event-triggered video surveillance system for monitoring flower-visiting bumblebees. The system consist of mini digital recorder (mini-DVR with a video motion detection (VMD sensor which detects changes in the image captured by the camera, the intruder triggers the recording immediately. The sensitivity and the detection area are adjustable, which may prevent unwanted recordings. To our best knowledge this is the first study using VMD sensor to monitor flower-visiting insects. Observation of flower-visiting insects has traditionally been monitored by direct observations, which is time demanding, or by continuous video monitoring, which demands a great effort in reviewing the material. A total of 98.5 monitoring hours were conducted. For the mini-DVR with VMD, a total of 35 min were spent reviewing the recordings to locate 75 pollinators, which means ca. 0.35 sec reviewing per monitoring hr. Most pollinators in the order Hymenoptera were identified to species or group level, some were only classified to family (Apidae or genus (Bombus. The use of the video monitoring system described in the present paper could result in a more efficient data sampling and reveal new knowledge to pollination ecology (e.g. species identification and pollinating behaviour.

Surveillant militaire, j’ai vu la fin du bagne

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Marc Renneville

2006-01-01

Full Text Available Surveillant principal (assimilé Lieutenant, Emile Demaret est peut-être le dernier survivant du corps des surveillants militaires des services pénitentiaires coloniaux de la Guyane. Né le 26 juin 1918 à Toulouse, il a été mousse à l’Ecole des Apprentis marins de Brest le 4 avril 1934, engagé dans la Marine nationale pour cinq ans à partir du 17 août 1934, embarqué sur les cuirassés Jean Bart et Paris, matelot timonier le 1er octobre 1935 sur le torpilleur Enseigne Roux à Bizerte (Tunisie, q...

The Role of MRI in Prostate Cancer Active Surveillance

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Linda M. Johnson

2014-01-01

Full Text Available Prostate cancer is the most common cancer diagnosis in American men, excluding skin cancer. The clinical behavior of prostate cancer varies from low-grade, slow growing tumors to high-grade aggressive tumors that may ultimately progress to metastases and cause death. Given the high incidence of men diagnosed with prostate cancer, conservative treatment strategies such as active surveillance are critical in the management of prostate cancer to reduce therapeutic complications of radiation therapy or radical prostatectomy. In this review, we will review the role of multiparametric MRI in the selection and follow-up of patients on active surveillance.

Safety aspects of core power distribution surveillance and control

International Nuclear Information System (INIS)

Beraha, D.; Grumbach, R.; Hoeld, A.; Werner, W.

1978-01-01

The incentives for improved core surveillance and core control systems are outlined. An efficient code for evaluating the power distribution is indispensable for designing and testing such a system. The characteristics of the core simulator QUABOX/CUBBOX and the features required for off-line and on-line applications are described. The important role of the simulator for the safety assessment of a digital core control system is underlined. With regard to the safety aspects of core control, possible disturbances are classified. Simulation results are given concerning the failure of a control actuator. It is shown that means can be devised to prevent unstable behaviour of the control system and, furthermore, to contribute to a safe reactor operation by accounting for process disturbances. (author)

Methods of nutrition surveillance in low-income countries

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Veronica Tuffrey

2016-03-01

Full Text Available Abstract Background In 1974 a joint FAO/UNICEF/WHO Expert Committee met to develop methods for nutrition surveillance. There has been much interest and activity in this topic since then, however there is a lack of guidance for practitioners and confusion exists around the terminology of nutrition surveillance. In this paper we propose a classification of data collection activities, consider the technical issues for each category, and examine the potential applications and challenges related to information and communication technology. Analysis There are three major approaches used to collect primary data for nutrition surveillance: repeated cross-sectional surveys; community-based sentinel monitoring; and the collection of data in schools. There are three major sources of secondary data for surveillance: from feeding centres, health facilities, and community-based data collection, including mass screening for malnutrition in children. Surveillance systems involving repeated surveys are suitable for monitoring and comparing national trends and for planning and policy development. To plan at a local level, surveys at district level or in programme implementation areas are ideal, but given the usually high cost of primary data collection, data obtained from health systems are more appropriate provided they are interpreted with caution and with contextual information. For early warning, data from health systems and sentinel site assessments may be valuable, if consistent in their methods of collection and any systematic bias is deemed to be steady. For evaluation purposes, surveillance systems can only give plausible evidence of whether a programme is effective. However the implementation of programmes can be monitored as long as data are collected on process indicators such as access to, and use of, services. Surveillance systems also have an important role to provide information that can be used for advocacy and for promoting accountability for

The force awakens: Birth of national surveillance state

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Avramović Dragutin S.

2016-01-01

Full Text Available University of Yale professor of Constitutional Law Jack Balkin convincingly declared emergence of a new sort of the state called 'national surveillance state'. Although the very name announces quite clearly an Orwellian scenario, Balkin is in doubt which path that kind of state will follow - the authoritarian or the democratic one. Nevertheless quite optimistic approaches of J. Balkin, O. Kerr and other authors considering democratic type of the national surveillance state the author of this paper holds the opposite opinion. Taking as a starting point an anthropological feature that 'passion warps the rule even of the best men' (Aristotle, 1287a, the author doubts in democratic character of the national surveillance state. He criticizes Balkin's explanations that the problem could be solved by 'control of the controllers' or 'observation of the observers'. One who has supreme right to dispose over information (no matter which state body could it be, can always, or most often will abuse that right having in mind some interest, particularly when the interest can be vested within socially and politically acceptable tune, like the fight against terrorism, national interest or similar. Proper and firm normative framework could contribute to successful balance between privacy and security of citizens and eventually diminish potential misuse of surveillance of citizens. However, many people provide information for the 'Big Brother' by sacrificing their own privacy voluntarily, forming their own 'digital database' through different social networking. Balkin's generous but native belief that democratic national surveillance state is possible could hardly survive the test of the coming time and challenges. It is quite evident that, particularly the most developed states, fairly fast incline towards repressive national surveillance state. Maybe the process could be only decelerated by activities of NGOs, by developing awareness of every single citizen of

Surface Environmental Surveillance Procedures Manual

International Nuclear Information System (INIS)

Hanf, Robert W.; Poston, Ted M.

2000-01-01

Shows and explains certain procedures needed for surface environmental surveillance. Hanford Site environmental surveillance is conducted by the Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy (DOE) under the Surface Environmental Surveillance Project (SESP). The basic requirements for site surveillance are set fourth in DOE Order 5400.1, General Environmental Protection Program Requirements. Guidance for the SESP is provided in DOE Order 5484.1, Environmental Protection, Safety, and Health Protection Information Reporting Requirements and DOE Order 5400.5, Radiation Protection of the Public and Environment. Guidelines for environmental surveillance activities are provided in DOE/EH-0173T, Environmental Regulatory Guide for Radiological Effluent Monitoring and Environmental Surveillance. An environmental monitoring plan for the Hanford Site is outlined in DOE/RL 91-50 Rev. 2, Environmental Monitoring Plan, United States Department of Energy, Richland Operations Office. Environmental surveillance data are used in assessing the impact of current and past site operations on human health and the environment, demonstrating compliance with applicable local, state, and federal environmental regulations, and verifying the adequacy of containment and effluent controls. SESP sampling schedules are reviewed, revised, and published each calendar year in the Hanford Site Environmental Surveillance Master Sampling Schedule. Environmental samples are collected by SESP staff in accordance with the approved sample collection procedures documented in this manual. Personnel training requirements are documented in SESP-TP-01 Rev.2, Surface Environmental Surveillance Project Training Program.

Polio eradication initiative in Africa: influence on other infectious disease surveillance development

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Cochi Stephen

2002-12-01

Full Text Available Abstract Background The World Health Organization (WHO and partners are collaborating to eradicate poliomyelitis. To monitor progress, countries perform surveillance for acute flaccid paralysis (AFP. The WHO African Regional Office (WHO-AFRO and the U.S Centers for Disease Control and Prevention are also involved in strengthening infectious disease surveillance and response in Africa. We assessed whether polio-eradication initiative resources are used in the surveillance for and response to other infectious diseases in Africa. Methods During October 1999-March 2000, we developed and administered a survey questionnaire to at least one key informant from the 38 countries that regularly report on polio activities to WHO. The key informants included WHO-AFRO staff assigned to the countries and Ministry of Health personnel. Results We obtained responses from 32 (84% of the 38 countries. Thirty-one (97% of the 32 countries had designated surveillance officers for AFP surveillance, and 25 (78% used the AFP resources for the surveillance and response to other infectious diseases. In 28 (87% countries, AFP program staff combined detection for AFP and other infectious diseases. Fourteen countries (44% had used the AFP laboratory specimen transportation system to transport specimens to confirm other infectious disease outbreaks. The majority of the countries that performed AFP surveillance adequately (i.e., non polio AFP rate = 1/100,000 children aged Conclusions Despite concerns regarding the targeted nature of AFP surveillance, it is partially integrated into existing surveillance and response systems in multiple African countries. Resources provided for polio eradication should be used to improve surveillance for and response to other priority infectious diseases in Africa.

SparkText: Biomedical Text Mining on Big Data Framework

Science.gov (United States)

He, Karen Y.; Wang, Kai

2016-01-01

Background Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. Results In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. Conclusions This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research. PMID:27685652

Descriptive review of tuberculosis surveillance systems across the circumpolar regions

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Annie-Claude Bourgeois

2016-04-01

Full Text Available Background: Tuberculosis is highly prevalent in many Arctic areas. Members of the International Circumpolar Surveillance Tuberculosis (ICS-TB Working Group collaborate to increase knowledge about tuberculosis in Arctic regions. Objective: To establish baseline knowledge of tuberculosis surveillance systems used by ICS-TB member jurisdictions. Design: Three questionnaires were developed to reflect the different surveillance levels (local, regional and national; all 3 were forwarded to the official representative of each of the 15 ICS-TB member jurisdictions in 2013. Respondents self-identified the level of surveillance conducted in their region and completed the applicable questionnaire. Information collected included surveillance system objectives, case definitions, data collection methodology, storage and dissemination. Results: Thirteen ICS-TB jurisdictions [Canada (Labrador, Northwest Territories, Nunavik, Nunavut, Yukon, Finland, Greenland, Norway, Sweden, Russian Federation (Arkhangelsk, Khanty-Mansiysk Autonomous Okrug, Yakutia (Sakha Republic, United States (Alaska] voluntarily completed the survey – representing 2 local, 7 regional and 4 national levels. Tuberculosis reporting is mandatory in all jurisdictions, and case definitions are comparable across regions. The common objectives across systems are to detect outbreaks, and inform the evaluation/planning of public health programmes and policies. All jurisdictions collect data on confirmed active tuberculosis cases and treatment outcomes; 11 collect contact tracing results. Faxing of standardized case reporting forms is the most common reporting method. Similar core data elements are collected; 8 regions report genotyping results. Data are stored using customized programmes (n=7 and commercial software (n=6. Nine jurisdictions provide monthly, bi-annual or annual reports to principally government and/or scientific/medical audiences. Conclusion: This review successfully establishes

Ebola virus disease surveillance and response preparedness in northern Ghana

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Martin N. Adokiya

2016-05-01

Full Text Available Background: The recent Ebola virus disease (EVD outbreak has been described as unprecedented in terms of morbidity, mortality, and geographical extension. It also revealed many weaknesses and inadequacies for disease surveillance and response systems in Africa due to underqualified staff, cultural beliefs, and lack of trust for the formal health care sector. In 2014, Ghana had high risk of importation of EVD cases. Objective: The objective of this study was to assess the EVD surveillance and response system in northern Ghana. Design: This was an observational study conducted among 47 health workers (district directors, medical, disease control, and laboratory officers in all 13 districts of the Upper East Region representing public, mission, and private health services. A semi-structured questionnaire with focus on core and support functions (e.g. detection, confirmation was administered to the informants. Their responses were recorded according to specific themes. In addition, 34 weekly Integrated Disease Surveillance and Response reports (August 2014 to March 2015 were collated from each district. Results: In 2014 and 2015, a total of 10 suspected Ebola cases were clinically diagnosed from four districts. Out of the suspected cases, eight died and the cause of death was unexplained. All the 10 suspected cases were reported, none was confirmed. The informants had knowledge on EVD surveillance and data reporting. However, there were gaps such as delayed reporting, low quality protective equipment (e.g. gloves, aprons, inadequate staff, and lack of laboratory capacity. The majority (38/47 of the respondents were not satisfied with EVD surveillance system and response preparedness due to lack of infrared thermometers, ineffective screening, and lack of isolation centres. Conclusion: EVD surveillance and response preparedness is insufficient and the epidemic is a wake-up call for early detection and response preparedness. Ebola surveillance remains

Quantum ensembles of quantum classifiers.

Science.gov (United States)

Schuld, Maria; Petruccione, Francesco

2018-02-09

Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

Accuracy Evaluation of C4.5 and Naive Bayes Classifiers Using Attribute Ranking Method

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S. Sivakumari

2009-03-01

Full Text Available This paper intends to classify the Ljubljana Breast Cancer dataset using C4.5 Decision Tree and Nai?ve Bayes classifiers. In this work, classification is carriedout using two methods. In the first method, dataset is analysed using all the attributes in the dataset. In the second method, attributes are ranked using information gain ranking technique and only the high ranked attributes are used to build the classification model. We are evaluating the results of C4.5 Decision Tree and Nai?ve Bayes classifiers in terms of classifier accuracy for various folds of cross validation. Our results show that both the classifiers achieve good accuracy on the dataset.

Pertussis incidence rates in Novi Sad (Serbia before and during improved surveillance

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Petrović Vladimir

2017-01-01

Full Text Available Introduction/Objective. The Global Pertussis Initiative (GPI proposed clinical case definitions for pertussis diagnosis in three different age cohorts in order to improve surveillance of pertussis especially in older children, adolescents, and adults. The main goal of this research was to compare the burden of pertussis in the city of Novi Sad before and after the introduction of improved surveillance using the GPI clinical case definitions of pertussis. Methods. Baseline data on pertussis were obtained from routine (non-sentinel reporting before improved surveillance was introduced. From September 16, 2012, clinical case definitions proposed by GPI were applied within improved (sentinel and hospital surveillance, while surveillance clinical case definitions were not introduced within non-sentinel. To confirm the suspected diagnosis, sampling of nasopharyngeal swab and/or blood was obtained from all cases. The choice of laboratory method (PCR or ELISA depended on the duration of coughing and the age of the patients. Data were statistically processed by SPSS Statistics, version 22. Results. During the 12-year period before the introduction of improved surveillance, only two clinical pertussis cases were registered. In contrast, during the two-year period of improved surveillance, a total of 14 (season 2012/13 and 146 (season 2013/2014 confirmed pertussis cases were reported. Significant differences were determined in distribution of pertussis according to the type of surveillance and the level of health care. Conclusion. Introduction of clinical case definitions proposed by GPI improved the quality of surveillance and enabled an insight in the distribution of pertussis in all age groups and at all levels of health care.

Analysis of a Pareto Mixture Distribution for Maritime Surveillance Radar

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Graham V. Weinberg

2012-01-01

Full Text Available The Pareto distribution has been shown to be an excellent model for X-band high-resolution maritime surveillance radar clutter returns. Given the success of mixture distributions in radar, it is thus of interest to consider the effect of Pareto mixture models. This paper introduces a formulation of a Pareto intensity mixture distribution and investigates coherent multilook radar detector performance using this new clutter model. Clutter parameter estimates are derived from data sets produced by the Defence Science and Technology Organisation's Ingara maritime surveillance radar.

Evaluation of the novel respiratory virus surveillance program: Pediatric Early Warning Sentinel Surveillance (PEWSS).

Science.gov (United States)

Armour, Patricia A; Nguyen, Linh M; Lutman, Michelle L; Middaugh, John P

2013-01-01

Infections caused by respiratory viruses are associated with recurrent epidemics and widespread morbidity and mortality. Routine surveillance of these pathogens is necessary to determine virus activity, monitor for changes in circulating strains, and plan for public health preparedness. The Southern Nevada Health District in Las Vegas, Nevada, recruited five pediatric medical practices to serve as sentinel sites for the Pediatric Early Warning Sentinel Surveillance (PEWSS) program. Sentinel staff collected specimens throughout the year from ill children who met the influenza-like illness case definition and submitted specimens to the Southern Nevada Public Health Laboratory for molecular testing for influenza and six non-influenza viruses. Laboratory results were analyzed and reported to the medical and general communities in weekly bulletins year-round. PEWSS data were also used to establish viral respiratory seasonal baselines and in influenza vaccination campaigns. The surveillance program was evaluated using the Centers for Disease Control and Prevention's (CDC's) Updated Guidelines for Evaluating Public Health Surveillance Systems. PEWSS met three of six program usefulness criteria and seven of nine surveillance system attributes, which exceeded the CDC Guidelines evaluation criteria for a useful and complete public health surveillance program. We found that PEWSS is a useful and complete public health surveillance system that is simple, flexible, accessible, and stable.

Surveillance of the environmental radioactivity

International Nuclear Information System (INIS)

Schneider, Th.; Gitzinger, C.; Jaunet, P.; Eberbach, F.; Clavel, B.; Hemidy, P.Y.; Perrier, G.; Kiper, Ch.; Peres, J.M.; Josset, M.; Calvez, M.; Leclerc, M.; Leclerc, E.; Aubert, C.; Levelut, M.N.; Debayle, Ch.; Mayer, St.; Renaud, Ph.; Leprieur, F.; Petitfrere, M.; Catelinois, O.; Monfort, M.; Baron, Y.; Target, A.

2008-01-01

The objective of these days was to present the organisation of the surveillance of the environmental radioactivity and to allow an experience sharing and a dialog on this subject between the different actors of the radiation protection in france. The different presentations were as follow: evolution and stakes of the surveillance of radioactivity in environment; the part of the European commission, regulatory aspects; the implementation of the surveillance: the case of Germany; Strategy and logic of environmental surveillance around the EDF national centers of energy production; environmental surveillance: F.B.F.C. site of Romans on Isere; steps of the implementation 'analysis for release decree at the F.B.F.C./C.E.R.C.A. laboratory of Romans; I.R.S.N. and the environmental surveillance: situation and perspectives; the part of a non institutional actor, the citizenship surveillance done by A.C.R.O.; harmonization of sampling methods: the results of inter operators G.T. sampling; sustainable observatory of environment: data traceability and samples conservation; inter laboratories tests of radioactivity measurements; national network of environmental radioactivity measurement: laboratories agreements; the networks of environmental radioactivity telemetry: modernization positioning; programme of observation and surveillance of surface environment and installations of the H.A.-M.A.V.L. project (high activity and long life medium activity); Evolution of radionuclides concentration in environment and adaptation of measurements techniques to the surveillance needs; the national network of radioactivity measurement in environment; modes of data restoration of surveillance: the results of the Loire environment pilot action; method of sanitary impacts estimation in the area of ionizing radiations; the radiological impact of atmospheric nuclear tests in French Polynesia; validation of models by the measure; network of measurement and alert management of the atmospheric

Inappropriate colonoscopic surveillance of hyperplastic polyps.

LENUS (Irish Health Repository)

Keane, R A

2011-11-15

Colonoscopic surveillance of hyperplastic polyps alone is controversial and may be inappropriate. The colonoscopy surveillance register at a university teaching hospital was audited to determine the extent of such hyperplastic polyp surveillance. The surveillance endoscopy records were reviewed, those patients with hyperplastic polyps were identified, their clinical records were examined and contact was made with each patient. Of the 483 patients undergoing surveillance for colonic polyps 113 (23%) had hyperplastic polyps alone on last colonoscopy. 104 patients remained after exclusion of those under appropriate surveillance. 87 of the 104 patients (84%) were successfully contacted. 37 patients (8%) were under appropriate colonoscopic surveillance for a significant family history of colorectal carcinoma. 50 (10%) patients with hyperplastic polyps alone and no other clinical indication for colonoscopic surveillance were booked for follow up colonoscopy. This represents not only a budgetary but more importantly a clinical opportunity cost the removal of which could liberate valuable colonoscopy time for more appropriate indications.

Parallel Key Frame Extraction for Surveillance Video Service in a Smart City.

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Ran Zheng

Full Text Available Surveillance video service (SVS is one of the most important services provided in a smart city. It is very important for the utilization of SVS to provide design efficient surveillance video analysis techniques. Key frame extraction is a simple yet effective technique to achieve this goal. In surveillance video applications, key frames are typically used to summarize important video content. It is very important and essential to extract key frames accurately and efficiently. A novel approach is proposed to extract key frames from traffic surveillance videos based on GPU (graphics processing units to ensure high efficiency and accuracy. For the determination of key frames, motion is a more salient feature in presenting actions or events, especially in surveillance videos. The motion feature is extracted in GPU to reduce running time. It is also smoothed to reduce noise, and the frames with local maxima of motion information are selected as the final key frames. The experimental results show that this approach can extract key frames more accurately and efficiently compared with several other methods.

Converging requirements and emerging challenges to public health diseases surveillance and bio surveillance

International Nuclear Information System (INIS)

Rao, V.; Abel, T.

2009-01-01

Disease surveillance systems are a critical component of an early warning system for public health agencies to prepare and respond to major public health catastrophes. With a growing emphasis for more robust early indicator and warning systems to track emerging and dangerous diseases of suspicious nature, considerable emphasis is now placed on deployment of more expanded electronic disease surveillance systems. The architectural considerations for bio surveillance information system are based on collection, analysis and dissemination of human, veterinary and agricultural related disease surveillance to broader regional areas likely to be affected in the event of an emerging disease, or due to bioterrorism and better coordinate plans, preparations and response by governmental agencies and multilateral forums. The diseases surveillance systems architectures by intent and design could as well support biological threat monitoring and threat reduction initiatives. As an illustrative sample set, this paper will describe the comparative informatics requirements for a disease surveillance systems developed by CSC for the US Centers for Diseases Control and Prevention (CDC) currently operational nationwide, and biological weapons threat assessment developed as part of the Threat Agent Detection and Response (TADR) Network under the US Biological Threat Reduction Program and deployed at Uzbekistan, Kazakhstan, Georgia, and Azerbaijan.(author)

Legionnaires’ disease Surveillance in Italy

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Maria Luisa Ricci

2004-12-01

Full Text Available

In the report presented, data on legionellosis diagnosed in the year 2003 in Italy and notified to the National Surveillance System are analysed. Overall, 617 cases were notified, of which 517 were confirmed and 46 were presumptive.

The characteristics of the patients are very similar to those reported in the previous years in terms of male/female ratio, age–specific distribution, occupation, etc. Legionella pneumophila serogroup 1 was responsible for approximately 90% of the cases.

Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras

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Jaehoon Jung

2016-06-01

Full Text Available Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i generation of a three-dimensional (3D human model; (ii human object-based automatic scene calibration; and (iii metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system.

Silhouettes of War: Technologies of U.S. Soldiering and Surveillance

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Jessica J. Behm

2010-03-01

Full Text Available This paper forwards a theory of silhouetting in relation to technological augmenta-tion in U.S. Military uniforms and suggests that the increasing utilization of metamaterials, nanotechnology, and surveillance technologies operates under a rhetoric of invisibility that complicates the technologies' visible destruction. Methodologically, the paper attends to three general technological developments in the evolution of the U.S. Army uniform: the design of the new Army Combat Uniform (ACU; the technological advances in the uniform, including embedded wearables, biometric identification devices, and 3D combat enhancement systems; and the bio-networking, GPS, and digital communication arrays that physically link digital uniforms to a larger geopolitical network of U.S. military strategy and surveillance. Throughout, the work traces the aforementioned theory of silhouet-ting in relation to select sociopolitical consequences of linking digitally enhanced soldiers into a transnational grid of surveillance.

A target recognition method for maritime surveillance radars based on hybrid ensemble selection

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Fan, Xueman; Hu, Shengliang; He, Jingbo

2017-11-01

In order to improve the generalisation ability of the maritime surveillance radar, a novel ensemble selection technique, termed Optimisation and Dynamic Selection (ODS), is proposed. During the optimisation phase, the non-dominated sorting genetic algorithm II for multi-objective optimisation is used to find the Pareto front, i.e. a set of ensembles of classifiers representing different tradeoffs between the classification error and diversity. During the dynamic selection phase, the meta-learning method is used to predict whether a candidate ensemble is competent enough to classify a query instance based on three different aspects, namely, feature space, decision space and the extent of consensus. The classification performance and time complexity of ODS are compared against nine other ensemble methods using a self-built full polarimetric high resolution range profile data-set. The experimental results clearly show the effectiveness of ODS. In addition, the influence of the selection of diversity measures is studied concurrently.

Surveillance of antibiotic resistance

Science.gov (United States)

Johnson, Alan P.

2015-01-01

Surveillance involves the collection and analysis of data for the detection and monitoring of threats to public health. Surveillance should also inform as to the epidemiology of the threat and its burden in the population. A further key component of surveillance is the timely feedback of data to stakeholders with a view to generating action aimed at reducing or preventing the public health threat being monitored. Surveillance of antibiotic resistance involves the collection of antibiotic susceptibility test results undertaken by microbiology laboratories on bacteria isolated from clinical samples sent for investigation. Correlation of these data with demographic and clinical data for the patient populations from whom the pathogens were isolated gives insight into the underlying epidemiology and facilitates the formulation of rational interventions aimed at reducing the burden of resistance. This article describes a range of surveillance activities that have been undertaken in the UK over a number of years, together with current interventions being implemented. These activities are not only of national importance but form part of the international response to the global threat posed by antibiotic resistance. PMID:25918439

A Joint Watermarking and ROI Coding Scheme for Annotating Traffic Surveillance Videos

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Su Po-Chyi

2010-01-01

Full Text Available We propose a new application of information hiding by employing the digital watermarking techniques to facilitate the data annotation in traffic surveillance videos. There are two parts in the proposed scheme. The first part is the object-based watermarking, in which the information of each vehicle collected by the intelligent transportation system will be conveyed/stored along with the visual data via information hiding. The scheme is integrated with H.264/AVC, which is assumed to be adopted by the surveillance system, to achieve an efficient implementation. The second part is a Region of Interest (ROI rate control mechanism for encoding traffic surveillance videos, which helps to improve the overall performance. The quality of vehicles in the video will be better preserved and a good rate-distortion performance can be attained. Experimental results show that this potential scheme works well in traffic surveillance videos.

Approach for Text Classification Based on the Similarity Measurement between Normal Cloud Models

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Jin Dai

2014-01-01

Full Text Available The similarity between objects is the core research area of data mining. In order to reduce the interference of the uncertainty of nature language, a similarity measurement between normal cloud models is adopted to text classification research. On this basis, a novel text classifier based on cloud concept jumping up (CCJU-TC is proposed. It can efficiently accomplish conversion between qualitative concept and quantitative data. Through the conversion from text set to text information table based on VSM model, the text qualitative concept, which is extraction from the same category, is jumping up as a whole category concept. According to the cloud similarity between the test text and each category concept, the test text is assigned to the most similar category. By the comparison among different text classifiers in different feature selection set, it fully proves that not only does CCJU-TC have a strong ability to adapt to the different text features, but also the classification performance is also better than the traditional classifiers.

Least Square Support Vector Machine Classifier vs a Logistic Regression Classifier on the Recognition of Numeric Digits

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Danilo A. López-Sarmiento

2013-11-01

Full Text Available In this paper is compared the performance of a multi-class least squares support vector machine (LSSVM mc versus a multi-class logistic regression classifier to problem of recognizing the numeric digits (0-9 handwritten. To develop the comparison was used a data set consisting of 5000 images of handwritten numeric digits (500 images for each number from 0-9, each image of 20 x 20 pixels. The inputs to each of the systems were vectors of 400 dimensions corresponding to each image (not done feature extraction. Both classifiers used OneVsAll strategy to enable multi-classification and a random cross-validation function for the process of minimizing the cost function. The metrics of comparison were precision and training time under the same computational conditions. Both techniques evaluated showed a precision above 95 %, with LS-SVM slightly more accurate. However the computational cost if we found a marked difference: LS-SVM training requires time 16.42 % less than that required by the logistic regression model based on the same low computational conditions.

A Global Cancer Surveillance Framework Within Noncommunicable Disease Surveillance: Making the Case for Population-Based Cancer Registries.

Science.gov (United States)

Piñeros, Marion; Znaor, Ariana; Mery, Les; Bray, Freddie

2017-01-01

The growing burden of cancer among several major noncommunicable diseases (NCDs) requires national implementation of tailored public health surveillance. For many emerging economies where emphasis has traditionally been placed on the surveillance of communicable diseases, it is critical to understand the specificities of NCD surveillance and, within it, of cancer surveillance. We propose a general framework for cancer surveillance that permits monitoring the core components of cancer control. We examine communalities in approaches to the surveillance of other major NCDs as well as communicable diseases, illustrating key differences in the function, coverage, and reporting in each system. Although risk factor surveys and vital statistics registration are the foundation of surveillance of NCDs, population-based cancer registries play a unique fundamental role specific to cancer surveillance, providing indicators of population-based incidence and survival. With an onus now placed on governments to collect these data as part of the monitoring of NCD targets, the integration of cancer registries into existing and future NCD surveillance strategies is a vital requirement in all countries worldwide. The Global Initiative for Cancer Registry Development, endorsed by the World Health Organization, provides a means to enhance cancer surveillance capacity in low- and middle-income countries. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Opinion Mining in Latvian Text Using Semantic Polarity Analysis and Machine Learning Approach

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Gatis Špats

2016-07-01

Full Text Available In this paper we demonstrate approaches for opinion mining in Latvian text. Authors have applied, combined and extended results of several previous studies and public resources to perform opinion mining in Latvian text using two approaches, namely, semantic polarity analysis and machine learning. One of the most significant constraints that make application of opinion mining for written content classification in Latvian text challenging is the limited publicly available text corpora for classifier training. We have joined several sources and created a publically available extended lexicon. Our results are comparable to or outperform current achievements in opinion mining in Latvian. Experiments show that lexicon-based methods provide more accurate opinion mining than the application of Naive Bayes machine learning classifier on Latvian tweets. Methods used during this study could be further extended using human annotators, unsupervised machine learning and bootstrapping to create larger corpora of classified text.

The Necessity of Mobile Phone Technologies for Public Health Surveillance in Benin

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Yaovi M. G. Hounmanou

2016-01-01

Full Text Available A cross-sectional study was conducted in March 2016 to assess the need of mobile phone technologies for health surveillance and interventions in Benin. Questionnaires were administered to 130 individuals comprising 25 medical professionals, 33 veterinarians, and 72 respondents from the public. All respondents possess cell phones and 75%, 84%, and 100% of the public, medical professionals, and veterinarians, respectively, generally use them for medical purposes. 75% of respondents including 68% of medics, 84.8% of veterinarians, and 72.2% of the public acknowledged that the current surveillance systems are ineffective and do not capture and share real-time information. More than 92% of the all respondents confirmed that mobile phones have the potential to improve health surveillance in the country. All respondents reported adhering to a nascent project of mobile phone-based health surveillance and confirmed that there is no existing similar approach in the country. The most preferred methods by all respondents for effective implementation of such platform are phone calls (96.92% followed by SMS (49.23% and smart phone digital forms (41.53%. This study revealed urgent needs of mobile phone technologies for health surveillance and interventions in Benin for real-time surveillance and efficient disease prevention.

SVM Classifiers: The Objects Identification on the Base of Their Hyperspectral Features

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Demidova Liliya

2017-01-01

Full Text Available The problem of the objects identification on the base of their hyperspectral features has been considered. It is offered to use the SVM classifiers on the base of the modified PSO algorithm, adapted to specifics of the problem of the objects identification on the base of their hyperspectral features. The results of the objects identification on the base of their hyperspectral features with using of the SVM classifiers have been presented.

A Constrained Multi-Objective Learning Algorithm for Feed-Forward Neural Network Classifiers

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M. Njah

2017-06-01

Full Text Available This paper proposes a new approach to address the optimal design of a Feed-forward Neural Network (FNN based classifier. The originality of the proposed methodology, called CMOA, lie in the use of a new constraint handling technique based on a self-adaptive penalty procedure in order to direct the entire search effort towards finding only Pareto optimal solutions that are acceptable. Neurons and connections of the FNN Classifier are dynamically built during the learning process. The approach includes differential evolution to create new individuals and then keeps only the non-dominated ones as the basis for the next generation. The designed FNN Classifier is applied to six binary classification benchmark problems, obtained from the UCI repository, and results indicated the advantages of the proposed approach over other existing multi-objective evolutionary neural networks classifiers reported recently in the literature.

General and Local: Averaged k-Dependence Bayesian Classifiers

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Limin Wang

2015-06-01

Full Text Available The inference of a general Bayesian network has been shown to be an NP-hard problem, even for approximate solutions. Although k-dependence Bayesian (KDB classifier can construct at arbitrary points (values of k along the attribute dependence spectrum, it cannot identify the changes of interdependencies when attributes take different values. Local KDB, which learns in the framework of KDB, is proposed in this study to describe the local dependencies implicated in each test instance. Based on the analysis of functional dependencies, substitution-elimination resolution, a new type of semi-naive Bayesian operation, is proposed to substitute or eliminate generalization to achieve accurate estimation of conditional probability distribution while reducing computational complexity. The final classifier, averaged k-dependence Bayesian (AKDB classifiers, will average the output of KDB and local KDB. Experimental results on the repository of machine learning databases from the University of California Irvine (UCI showed that AKDB has significant advantages in zero-one loss and bias relative to naive Bayes (NB, tree augmented naive Bayes (TAN, Averaged one-dependence estimators (AODE, and KDB. Moreover, KDB and local KDB show mutually complementary characteristics with respect to variance.

Entropy based classifier for cross-domain opinion mining

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Jyoti S. Deshmukh

2018-01-01

Full Text Available In recent years, the growth of social network has increased the interest of people in analyzing reviews and opinions for products before they buy them. Consequently, this has given rise to the domain adaptation as a prominent area of research in sentiment analysis. A classifier trained from one domain often gives poor results on data from another domain. Expression of sentiment is different in every domain. The labeling cost of each domain separately is very high as well as time consuming. Therefore, this study has proposed an approach that extracts and classifies opinion words from one domain called source domain and predicts opinion words of another domain called target domain using a semi-supervised approach, which combines modified maximum entropy and bipartite graph clustering. A comparison of opinion classification on reviews on four different product domains is presented. The results demonstrate that the proposed method performs relatively well in comparison to the other methods. Comparison of SentiWordNet of domain-specific and domain-independent words reveals that on an average 72.6% and 88.4% words, respectively, are correctly classified.

Surveillance of healthcare-associated infection in hospitalised South African children: Which method performs best?

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A Dramowski

2017-01-01

Full Text Available Background. In 2012, the South African (SA National Department of Health mandated surveillance of healthcare-associated infection (HAI, but made no recommendations of appropriate surveillance methods. Methods. Prospective clinical HAI surveillance (the reference method was conducted at Tygerberg Children’s Hospital, Cape Town, from 1 May to 31 October 2015. Performance of three surveillance methods (point prevalence surveys (PPSs, laboratory surveillance and tracking of antimicrobial prescriptions was compared with the reference method using surveillance evaluation guidelines. Factors associated with failure to detect HAI were identified by logistic regression analysis. Results. The reference method detected 417 HAIs among 1 347 paediatric hospitalisations (HAI incidence of 31/1000 patient days; 95% confidence interval (CI 28.2 - 34.2. Surveillance methods had variable sensitivity (S and positive predictive value (PPV: PPS S = 24.9% (95% CI 21 - 29.3, PPV = 100%; laboratory surveillance S = 48.4% (95% CI 43.7 - 53.2, PPV = 55.2% (95% CI 50.1 - 60.2; and antimicrobial prescriptions S = 66.4% (95% CI 61.8 - 70.8%, PPV = 88.5% (95% CI 84.5 - 91.6. Combined laboratory-antimicrobial surveillance achieved superior HAI detection (S = 84.7% (95% CI 80.9 - 87.8%, PPV = 97% (95% CI 94.6 - 98.4%. Factors associated with failure to detect HAI included patient transfer (odds ratio (OR 2.0, single HAI event (OR 2.8, age category 1 - 5 years (OR 2.1 and hospitalisation in a general ward (OR 2.3. Conclusions. Repeated PPSs, laboratory surveillance and/or antimicrobial prescription tracking are feasible HAI surveillance methods for low-resource settings. Combined laboratory-antimicrobial surveillance achieved the best sensitivity and PPV. SA paediatric healthcare facilities should individualise HAI surveillance, selecting a method suited to available resources and practice context.

Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance

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Sebastian Meyer

2017-05-01

Full Text Available The availability of geocoded health data and the inherent temporal structure of communicable diseases have led to an increased interest in statistical models and software for spatio-temporal data with epidemic features. The open source R package surveillance can handle various levels of aggregation at which infective events have been recorded: individual-level time-stamped geo-referenced data (case reports in either continuous space or discrete space, as well as counts aggregated by period and region. For each of these data types, the surveillance package implements tools for visualization, likelihoood inference and simulation from recently developed statistical regression frameworks capturing endemic and epidemic dynamics. Altogether, this paper is a guide to the spatio-temporal modeling of epidemic phenomena, exemplified by analyses of public health surveillance data on measles and invasive meningococcal disease.

Issues ignored in laboratory quality surveillance

International Nuclear Information System (INIS)

Zeng Jing; Li Xingyuan; Zhang Tingsheng

2008-01-01

According to the work requirement of the related laboratory quality surveillance in ISO17025, this paper analyzed and discussed the issued ignored in the laboratory quality surveillance. In order to solve the present problem, it is required to understand the work responsibility in the quality surveillance correctly, to establish the effective working routine in the quality surveillance, and to conduct, the quality surveillance work. The object in the quality surveillance shall be 'the operator' who engaged in the examination/calibration directly in the laboratory, especially the personnel in training (who is engaged in the examination/calibration). The quality supervisors shall be fully authorized, so that they can correctly understand the work responsibility in quality surveillance, and are with the rights for 'full supervision'. The laboratory also shall arrange necessary training to the quality supervisor, so that they can obtain sufficient guide in time and are with required qualification or occupation prerequisites. (authors)

Comprehensive effective and efficient global public health surveillance

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McNabb Scott JN

2010-12-01

Full Text Available Abstract At a crossroads, global public health surveillance exists in a fragmented state. Slow to detect, register, confirm, and analyze cases of public health significance, provide feedback, and communicate timely and useful information to stakeholders, global surveillance is neither maximally effective nor optimally efficient. Stakeholders lack a globa surveillance consensus policy and strategy; officials face inadequate training and scarce resources. Three movements now set the stage for transformation of surveillance: 1 adoption by Member States of the World Health Organization (WHO of the revised International Health Regulations (IHR[2005]; 2 maturation of information sciences and the penetration of information technologies to distal parts of the globe; and 3 consensus that the security and public health communities have overlapping interests and a mutual benefit in supporting public health functions. For these to enhance surveillance competencies, eight prerequisites should be in place: politics, policies, priorities, perspectives, procedures, practices, preparation, and payers. To achieve comprehensive, global surveillance, disparities in technical, logistic, governance, and financial capacities must be addressed. Challenges to closing these gaps include the lack of trust and transparency; perceived benefit at various levels; global governance to address data power and control; and specified financial support from globa partners. We propose an end-state perspective for comprehensive, effective and efficient global, multiple-hazard public health surveillance and describe a way forward to achieve it. This end-state is universal, global access to interoperable public health information when it’s needed, where it’s needed. This vision mitigates the tension between two fundamental human rights: first, the right to privacy, confidentiality, and security of personal health information combined with the right of sovereign, national entities

Developing regional workplace health and hazard surveillance in the Americas

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Choi Bernard C. K.

2001-01-01

Full Text Available An objective of the Workers' Health Program at the Pan American Health Organization (PAHO is to strengthen surveillance in workers' health in the Region of the Americas in order to implement prevention and control strategies. To date, four phases of projects have been organized to develop multinational workplace health and hazard surveillance in the Region. Phase 1 was a workshop held in 1999 in Washington, D.C., for the purpose of developing a methodology for identifying and prioritizing the top three occupational sentinel health events to be incorporated into the surveillance systems in the Region. Three surveillance protocols were developed, one each for fatal occupational injuries, pesticide poisoning,4 and low back pain, which were identified in the workshop as the most important occupational health problems. Phase 2 comprised projects to disseminate the findings and recommendations of the Washington Workshop, including publications, pilot projects, software development, electronic communication, and meetings. Phase 3 was a sub-regional meeting in 2000 in Rosario, Argentina, to follow up on the progress in carrying out the recommendations of the Washington workshop and to create a Virtual Regional Center for Latin America that could coordinate the efforts of member countries. Currently phase 4 includes a number of projects to achieve the objectives of this Center, such as pilot projects, capacity building, editing a compact disk, analyzing legal systems and intervention strategies, software training, and developing an internet course on surveillance. By documenting the joint efforts made to initiate and develop Regional multinational surveillance of occupational injuries and diseases in the Americas, this paper aims to provide experience and guidance for others wishing to initiate and develop regional multinational surveillance for other diseases or in other regions.

DVT surveillance program in the ICU: analysis of cost-effectiveness.

Directory of Open Access Journals (Sweden)

Ajai K Malhotra

Full Text Available BACKGROUND: Venous Thrombo-embolism (VTE--Deep venous thrombosis (DVT and/or pulmonary embolism (PE--in traumatized patients causes significant morbidity and mortality. The current study evaluates the effectiveness of DVT surveillance in reducing PE, and performs a cost-effectiveness analysis. METHODS: All traumatized patients admitted to the adult ICU underwent twice weekly DVT surveillance by bilateral lower extremity venous Duplex examination (48-month surveillance period--SP. The rates of DVT and PE were recorded and compared to the rates observed in the 36-month pre-surveillance period (PSP. All patients in both periods received mechanical and pharmacologic prophylaxis unless contraindicated. Total costs--diagnostic, therapeutic and surveillance--for both periods were recorded and the incremental cost for each Quality Adjusted Life Year (QALY gained was calculated. RESULTS: 4234 patients were eligible (PSP--1422 and SP--2812. Rate of DVT in SP (2.8% was significantly higher than in PSP (1.3% - p<0.05, and rate of PE in SP (0.7% was significantly lower than that in PSP (1.5% - p<0.05. Logistic regression demonstrated that surveillance was an independent predictor of increased DVT detection (OR: 2.53 - CI: 1.462-4.378 and decreased PE incidence (OR: 0.487 - CI: 0.262-0.904. The incremental cost was $509,091/life saved in the base case, translating to $29,102/QALY gained. A sensitivity analysis over four of the parameters used in the model indicated that the incremental cost ranged from $18,661 to $48,821/QALY gained. CONCLUSIONS: Surveillance of traumatized ICU patients increases DVT detection and reduces PE incidence. Costs in terms of QALY gained compares favorably with other interventions accepted by society.

On infectious intestinal disease surveillance using social media content

DEFF Research Database (Denmark)

Zou, Bin; Lampos, Vasileios; Gorton, Russell

2016-01-01

by traditional health surveillance methods. We employ a deep learning approach for creating a topical vocabulary, and then apply a regularised linear (Elastic Net) as well as a nonlinear (Gaussian Process) regression function for inference. We show that like previous text regression tasks, the nonlinear approach...

Deconstructing Cross-Entropy for Probabilistic Binary Classifiers

Directory of Open Access Journals (Sweden)

Daniel Ramos

2018-03-01

Full Text Available In this work, we analyze the cross-entropy function, widely used in classifiers both as a performance measure and as an optimization objective. We contextualize cross-entropy in the light of Bayesian decision theory, the formal probabilistic framework for making decisions, and we thoroughly analyze its motivation, meaning and interpretation from an information-theoretical point of view. In this sense, this article presents several contributions: First, we explicitly analyze the contribution to cross-entropy of (i prior knowledge; and (ii the value of the features in the form of a likelihood ratio. Second, we introduce a decomposition of cross-entropy into two components: discrimination and calibration. This decomposition enables the measurement of different performance aspects of a classifier in a more precise way; and justifies previously reported strategies to obtain reliable probabilities by means of the calibration of the output of a discriminating classifier. Third, we give different information-theoretical interpretations of cross-entropy, which can be useful in different application scenarios, and which are related to the concept of reference probabilities. Fourth, we present an analysis tool, the Empirical Cross-Entropy (ECE plot, a compact representation of cross-entropy and its aforementioned decomposition. We show the power of ECE plots, as compared to other classical performance representations, in two diverse experimental examples: a speaker verification system, and a forensic case where some glass findings are present.

Advanced digital video surveillance for safeguard and physical protection

International Nuclear Information System (INIS)

Kumar, R.

2002-01-01

Full text: Video surveillance is a very crucial component in safeguard and physical protection. Digital technology has revolutionized the surveillance scenario and brought in various new capabilities like better image quality, faster search and retrieval of video images, less storage space for recording, efficient transmission and storage of video, better protection of recorded video images, and easy remote accesses to live and recorded video etc. The basic safeguard requirement for verifiably uninterrupted surveillance has remained largely unchanged since its inception. However, changes to the inspection paradigm to admit automated review and remote monitoring have dramatically increased the demands on safeguard surveillance system. Today's safeguard systems can incorporate intelligent motion detection with very low rate of false alarm and less archiving volume, embedded image processing capability for object behavior and event based indexing, object recognition, efficient querying and report generation etc. It also demands cryptographically authenticating, encrypted, and highly compressed video data for efficient, secure, tamper indicating and transmission. In physical protection, intelligent on robust video motion detection, real time moving object detection and tracking from stationary and moving camera platform, multi-camera cooperative tracking, activity detection and recognition, human motion analysis etc. is going to play a key rote in perimeter security. Incorporation of front and video imagery exploitation tools like automatic number plate recognition, vehicle identification and classification, vehicle undercarriage inspection, face recognition, iris recognition and other biometric tools, gesture recognition etc. makes personnel and vehicle access control robust and foolproof. Innovative digital image enhancement techniques coupled with novel sensor design makes low cost, omni-directional vision capable, all weather, day night surveillance a reality

Monitors for the surveillance of NPP components

International Nuclear Information System (INIS)

Giera, H.D.; Grabner, A.; Hessel, G.; Koeppen, H.E.; Liewers, P.; Schumann, P.; Weiss, F.P.; Kunze, U.; Pfeiffer, G.

1985-01-01

Noise diagnostics have reached a level where it is possible and efficient to integrate this method as far as possible into the control and safety system of the NPP. The communication between the noise diagnostic system and the plant operator is the main problem of integration. It is necessary to refine the diagnostic results in such a manner that the operator can use them without being skilled in noise analysis respectively without contacting a noise specialist. Moreover, in this way the noise specialist can be released from routine surveillance. For selected processes which have already intensively been investigated because of their inherent risk this can be achieved by means of autonomously working monitors. Independently the monitors perform signal processing and diagnosis. In general this means that they classify the technical condition of the monitored component into one of the two categories: ''normal'' or ''anomalous''. The result will be annunciated to the plant operator who will in the first step of the development contact the noise specialist only if anomalies have occurred in order to clarify the cause. At the NPP ''Bruno Leuschner'' Greifswald, three hardware monitors for loose parts detection, control rod surveillance and main coolant pump diagnosis are being tested. Additionally a so-called software monitor for diagnosing the pressure vessel vibrations is in preparation. The techniques and the hardware used for the monitors as well as planned further improvements of the integration of noise diagnostics into the control and safety system are discussed in this paper. (author)

A systems biology-based classifier for hepatocellular carcinoma diagnosis.

Directory of Open Access Journals (Sweden)

Yanqiong Zhang

Full Text Available AIM: The diagnosis of hepatocellular carcinoma (HCC in the early stage is crucial to the application of curative treatments which are the only hope for increasing the life expectancy of patients. Recently, several large-scale studies have shed light on this problem through analysis of gene expression profiles to identify markers correlated with HCC progression. However, those marker sets shared few genes in common and were poorly validated using independent data. Therefore, we developed a systems biology based classifier by combining the differential gene expression with topological features of human protein interaction networks to enhance the ability of HCC diagnosis. METHODS AND RESULTS: In the Oncomine platform, genes differentially expressed in HCC tissues relative to their corresponding normal tissues were filtered by a corrected Q value cut-off and Concept filters. The identified genes that are common to different microarray datasets were chosen as the candidate markers. Then, their networks were analyzed by GeneGO Meta-Core software and the hub genes were chosen. After that, an HCC diagnostic classifier was constructed by Partial Least Squares modeling based on the microarray gene expression data of the hub genes. Validations of diagnostic performance showed that this classifier had high predictive accuracy (85.88∼92.71% and area under ROC curve (approximating 1.0, and that the network topological features integrated into this classifier contribute greatly to improving the predictive performance. Furthermore, it has been demonstrated that this modeling strategy is not only applicable to HCC, but also to other cancers. CONCLUSION: Our analysis suggests that the systems biology-based classifier that combines the differential gene expression and topological features of human protein interaction network may enhance the diagnostic performance of HCC classifier.

Intimate Surveillance: Normalizing Parental Monitoring and Mediation of Infants Online

Directory of Open Access Journals (Sweden)

Tama Leaver

2017-05-01

Full Text Available Parents are increasingly sharing information about infants online in various forms and capacities. To more meaningfully understand the way parents decide what to share about young people and the way those decisions are being shaped, this article focuses on two overlapping areas: parental monitoring of babies and infants through the example of wearable technologies and parental mediation through the example of the public sharing practices of celebrity and influencer parents. The article begins by contextualizing these parental practices within the literature on surveillance, with particular attention to online surveillance and the increasing importance of affect. It then gives a brief overview of work on pregnancy mediation, monitoring on social media, and via pregnancy apps, which is the obvious precursor to examining parental sharing and monitoring practices regarding babies and infants. The examples of parental monitoring and parental mediation will then build on the idea of “intimate surveillance” which entails close and seemingly invasive monitoring by parents. Parental monitoring and mediation contribute to the normalization of intimate surveillance to the extent that surveillance is (resituated as a necessary culture of care. The choice to not survey infants is thus positioned, worryingly, as a failure of parenting.

Surviving Surveillance: How Pregnant Women and Mothers Living With HIV Respond to Medical and Social Surveillance.

Science.gov (United States)

Greene, Saara; Ion, Allyson; Kwaramba, Gladys; Lazarus, Lisa; Loutfy, Mona

2017-12-01

Pregnant women and mothers living with HIV are under surveillance of service providers, family members, and the community at large. Surveillance occurs throughout the medical management of their HIV during pregnancy, preventing HIV transmission to their baby, infant feeding practices, and as part of assessments related to their ability to mother. Enacted and anticipatory HIV-related stigma can exacerbate the negative impact that being under surveillance has on mothers living with HIV as they move through their pregnancy, birthing, and mothering experiences. In response, women living with HIV find ways to manage their experiences of surveillance through engaging in acts of distancing, planning, and resisting at different points in time, and sometimes enacting all three practices at once. Positioning the narratives of pregnant women and mothers living with HIV in relation to their experiences of surveillance illuminates the relationship between the surveillance of mothers living with HIV and HIV-related stigma.

Real-Time Observation of Target Search by the CRISPR Surveillance Complex Cascade

Directory of Open Access Journals (Sweden)

Chaoyou Xue

2017-12-01

Full Text Available CRISPR-Cas systems defend bacteria and archaea against infection by bacteriophage and other threats. The central component of these systems are surveillance complexes that use guide RNAs to bind specific regions of foreign nucleic acids, marking them for destruction. Surveillance complexes must locate targets rapidly to ensure timely immune response, but the mechanism of this search process remains unclear. Here, we used single-molecule FRET to visualize how the type I-E surveillance complex Cascade searches DNA in real time. Cascade rapidly and randomly samples DNA through nonspecific electrostatic contacts, pausing at short PAM recognition sites that may be adjacent to the target. We identify Cascade motifs that are essential for either nonspecific sampling or positioning and readout of the PAM. Our findings provide a comprehensive structural and kinetic model for the Cascade target-search mechanism, revealing how CRISPR surveillance complexes can rapidly search large amounts of genetic material en route to target recognition.

Full-text automated detection of surgical site infections secondary to neurosurgery in Rennes, France.

Science.gov (United States)

Campillo-Gimenez, Boris; Garcelon, Nicolas; Jarno, Pascal; Chapplain, Jean Marc; Cuggia, Marc

2013-01-01

The surveillance of Surgical Site Infections (SSI) contributes to the management of risk in French hospitals. Manual identification of infections is costly, time-consuming and limits the promotion of preventive procedures by the dedicated teams. The introduction of alternative methods using automated detection strategies is promising to improve this surveillance. The present study describes an automated detection strategy for SSI in neurosurgery, based on textual analysis of medical reports stored in a clinical data warehouse. The method consists firstly, of enrichment and concept extraction from full-text reports using NOMINDEX, and secondly, text similarity measurement using a vector space model. The text detection was compared to the conventional strategy based on self-declaration and to the automated detection using the diagnosis-related group database. The text-mining approach showed the best detection accuracy, with recall and precision equal to 92% and 40% respectively, and confirmed the interest of reusing full-text medical reports to perform automated detection of SSI.

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

Science.gov (United States)

Al-Nawashi, Malek; Al-Hazaimeh, Obaida M; Saraee, Mohamad

2017-01-01

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.

IAEA safeguards and classified materials

International Nuclear Information System (INIS)

Pilat, J.F.; Eccleston, G.W.; Fearey, B.L.; Nicholas, N.J.; Tape, J.W.; Kratzer, M.

1997-01-01

The international community in the post-Cold War period has suggested that the International Atomic Energy Agency (IAEA) utilize its expertise in support of the arms control and disarmament process in unprecedented ways. The pledges of the US and Russian presidents to place excess defense materials, some of which are classified, under some type of international inspections raises the prospect of using IAEA safeguards approaches for monitoring classified materials. A traditional safeguards approach, based on nuclear material accountancy, would seem unavoidably to reveal classified information. However, further analysis of the IAEA's safeguards approaches is warranted in order to understand fully the scope and nature of any problems. The issues are complex and difficult, and it is expected that common technical understandings will be essential for their resolution. Accordingly, this paper examines and compares traditional safeguards item accounting of fuel at a nuclear power station (especially spent fuel) with the challenges presented by inspections of classified materials. This analysis is intended to delineate more clearly the problems as well as reveal possible approaches, techniques, and technologies that could allow the adaptation of safeguards to the unprecedented task of inspecting classified materials. It is also hoped that a discussion of these issues can advance ongoing political-technical debates on international inspections of excess classified materials

Investigation into Text Classification With Kernel Based Schemes

Science.gov (United States)

2010-03-01

Document Matrix TDMs Term-Document Matrices TMG Text to Matrix Generator TN True Negative TP True Positive VSM Vector Space Model xxii THIS PAGE...are represented as a term-document matrix, common evaluation metrics, and the software package Text to Matrix Generator ( TMG ). The classifier...AND METRICS This chapter introduces the indexing capabilities of the Text to Matrix Generator ( TMG ) Toolbox. Specific attention is placed on the

Reporting and Surveillance for Norovirus Outbreaks

Science.gov (United States)

... Vaccine Surveillance Network (NVSN) Foodborne Diseases Active Surveillance Network (FoodNet) National Outbreak Reporting System (NORS) Estimates of Foodborne Illness in the United States CDC's Vessel Sanitation Program CDC Feature: Surveillance for Norovirus Outbreaks Top ...

Interval algebra - an effective means of scheduling surveillance radar networks

CSIR Research Space (South Africa)

Focke, RW

2015-05-01

Full Text Available Interval Algebra provides an effective means to schedule surveillance radar networks, as it is a temporal ordering constraint language. Thus it provides a solution to a part of resource management, which is included in the revised Data Fusion...

Interval algebra: an effective means of scheduling surveillance radar networks

CSIR Research Space (South Africa)

Focke, RW

2015-05-01

Full Text Available Interval Algebra provides an effective means to schedule surveillance radar networks, as it is a temporal ordering constraint language. Thus it provides a solution to a part of resource management, which is included in the revised Data Fusion...

Reactor Vessel Surveillance Program for Advanced Reactor

Energy Technology Data Exchange (ETDEWEB)

Jeong, Kyeong-Hoon; Kim, Tae-Wan; Lee, Gyu-Mahn; Kim, Jong-Wook; Park, Keun-Bae; Kim, Keung-Koo

2008-10-15

This report provides the design requirements of an integral type reactor vessel surveillance program for an integral type reactor in accordance with the requirements of Korean MEST (Ministry of Education, Science and Technology Development) Notice 2008-18. This report covers the requirements for the design of surveillance capsule assemblies including their test specimens, test block materials, handling tools, and monitors of the surveillance capsule neutron fluence and temperature. In addition, this report provides design requirements for the program for irradiation surveillance of reactor vessel materials, a layout of specimens and monitors in the surveillance capsule, procedures of installation and retrieval of the surveillance capsule assemblies, and the layout of the surveillance capsule assemblies in the reactor.

The contribution of the vaccine adverse event text mining system to the classification of possible Guillain-Barré syndrome reports.

Science.gov (United States)

Botsis, T; Woo, E J; Ball, R

2013-01-01

We previously demonstrated that a general purpose text mining system, the Vaccine adverse event Text Mining (VaeTM) system, could be used to automatically classify reports of an-aphylaxis for post-marketing safety surveillance of vaccines. To evaluate the ability of VaeTM to classify reports to the Vaccine Adverse Event Reporting System (VAERS) of possible Guillain-Barré Syndrome (GBS). We used VaeTM to extract the key diagnostic features from the text of reports in VAERS. Then, we applied the Brighton Collaboration (BC) case definition for GBS, and an information retrieval strategy (i.e. the vector space model) to quantify the specific information that is included in the key features extracted by VaeTM and compared it with the encoded information that is already stored in VAERS as Medical Dictionary for Regulatory Activities (MedDRA) Preferred Terms (PTs). We also evaluated the contribution of the primary (diagnosis and cause of death) and secondary (second level diagnosis and symptoms) diagnostic VaeTM-based features to the total VaeTM-based information. MedDRA captured more information and better supported the classification of reports for GBS than VaeTM (AUC: 0.904 vs. 0.777); the lower performance of VaeTM is likely due to the lack of extraction by VaeTM of specific laboratory results that are included in the BC criteria for GBS. On the other hand, the VaeTM-based classification exhibited greater specificity than the MedDRA-based approach (94.96% vs. 87.65%). Most of the VaeTM-based information was contained in the secondary diagnostic features. For GBS, clinical signs and symptoms alone are not sufficient to match MedDRA coding for purposes of case classification, but are preferred if specificity is the priority.

The Contribution of the Vaccine Adverse Event Text Mining System to the Classification of Possible Guillain-Barré Syndrome Reports

Science.gov (United States)

Botsis, T.; Woo, E. J.; Ball, R.

2013-01-01

Background We previously demonstrated that a general purpose text mining system, the Vaccine adverse event Text Mining (VaeTM) system, could be used to automatically classify reports of an-aphylaxis for post-marketing safety surveillance of vaccines. Objective To evaluate the ability of VaeTM to classify reports to the Vaccine Adverse Event Reporting System (VAERS) of possible Guillain-Barré Syndrome (GBS). Methods We used VaeTM to extract the key diagnostic features from the text of reports in VAERS. Then, we applied the Brighton Collaboration (BC) case definition for GBS, and an information retrieval strategy (i.e. the vector space model) to quantify the specific information that is included in the key features extracted by VaeTM and compared it with the encoded information that is already stored in VAERS as Medical Dictionary for Regulatory Activities (MedDRA) Preferred Terms (PTs). We also evaluated the contribution of the primary (diagnosis and cause of death) and secondary (second level diagnosis and symptoms) diagnostic VaeTM-based features to the total VaeTM-based information. Results MedDRA captured more information and better supported the classification of reports for GBS than VaeTM (AUC: 0.904 vs. 0.777); the lower performance of VaeTM is likely due to the lack of extraction by VaeTM of specific laboratory results that are included in the BC criteria for GBS. On the other hand, the VaeTM-based classification exhibited greater specificity than the MedDRA-based approach (94.96% vs. 87.65%). Most of the VaeTM-based information was contained in the secondary diagnostic features. Conclusion For GBS, clinical signs and symptoms alone are not sufficient to match MedDRA coding for purposes of case classification, but are preferred if specificity is the priority. PMID:23650490

Between visibility and surveillance

DEFF Research Database (Denmark)

Uldam, Julie

As activists move from alternative media platforms to commercial social media platforms they face increasing challenges in protecting their online security and privacy. While government surveillance of activists is well-documented in both scholarly research and the media, corporate surveillance...

Web-based infectious disease surveillance systems and public health perspectives: a systematic review

Directory of Open Access Journals (Sweden)

Jihye Choi

2016-12-01

Full Text Available Abstract Background Emerging and re-emerging infectious diseases are a significant public health concern, and early detection and immediate response is crucial for disease control. These challenges have led to the need for new approaches and technologies to reinforce the capacity of traditional surveillance systems for detecting emerging infectious diseases. In the last few years, the availability of novel web-based data sources has contributed substantially to infectious disease surveillance. This study explores the burgeoning field of web-based infectious disease surveillance systems by examining their current status, importance, and potential challenges. Methods A systematic review framework was applied to the search, screening, and analysis of web-based infectious disease surveillance systems. We searched PubMed, Web of Science, and Embase databases to extensively review the English literature published between 2000 and 2015. Eleven surveillance systems were chosen for evaluation according to their high frequency of application. Relevant terms, including newly coined terms, development and classification of the surveillance systems, and various characteristics associated with the systems were studied. Results Based on a detailed and informative review of the 11 web-based infectious disease surveillance systems, it was evident that these systems exhibited clear strengths, as compared to traditional surveillance systems, but with some limitations yet to be overcome. The major strengths of the newly emerging surveillance systems are that they are intuitive, adaptable, low-cost, and operated in real-time, all of which are necessary features of an effective public health tool. The most apparent potential challenges of the web-based systems are those of inaccurate interpretation and prediction of health status, and privacy issues, based on an individual’s internet activity. Conclusion Despite being in a nascent stage with further modification

Privacy Implications of Surveillance Systems

DEFF Research Database (Denmark)

Thommesen, Jacob; Andersen, Henning Boje

2009-01-01

This paper presents a model for assessing the privacy „cost‟ of a surveillance system. Surveillance systems collect and provide personal information or observations of people by means of surveillance technologies such as databases, video or location tracking. Such systems can be designed for vari......This paper presents a model for assessing the privacy „cost‟ of a surveillance system. Surveillance systems collect and provide personal information or observations of people by means of surveillance technologies such as databases, video or location tracking. Such systems can be designed...... for various purposes, even as a service for those being observed, but in any case they will to some degree invade their privacy. The model provided here can indicate how invasive any particular system may be – and be used to compare the invasiveness of different systems. Applying a functional approach......, the model is established by first considering the social function of privacy in everyday life, which in turn lets us determine which different domains will be considered as private, and finally identify the different types of privacy invasion. This underlying model (function – domain – invasion) then serves...

Remote container monitoring and surveillance systems

International Nuclear Information System (INIS)

Resnik, W.M.; Kadner, S.P.

1995-01-01

Aquila Technologies Group is developing a monitoring and surveillance system to monitor containers of nuclear materials. The system will both visually and physically monitor the containers. The system is based on the combination of Aquila's Gemini All-Digital Surveillance System and on Aquila's AssetLAN trademark asset tracking technology. This paper discusses the Gemini Digital Surveillance system as well as AssetLAN technology. The Gemini architecture with emphasis on anti-tamper security features is also described. The importance of all-digital surveillance versus other surveillance methods is also discussed. AssetLAN trademark technology is described, emphasizing the ability to continually track containers (as assets) by location utilizing touch memory technology. Touch memory technology provides unique container identification, as well as the ability to store and retrieve digital information on the container. This information may relate to container maintenance, inspection schedules, and other information. Finally, this paper describes the combination of the Gemini system with AssetLAN technology, yielding a self contained, container monitoring and area/container surveillance system. Secure container fixture design considerations are discussed. Basic surveillance review functions are also discussed

English Metafunction Analysis in Chemistry Text: Characterization of Scientific Text

Directory of Open Access Journals (Sweden)

Ahmad Amin Dalimunte, M.Hum

2013-09-01

Full Text Available The objectives of this research are to identify what Metafunctions are applied in chemistry text and how they characterize a scientific text. It was conducted by applying content analysis. The data for this research was a twelve-paragraph chemistry text. The data were collected by applying a documentary technique. The document was read and analyzed to find out the Metafunction. The data were analyzed by some procedures: identifying the types of process, counting up the number of the processes, categorizing and counting up the cohesion devices, classifying the types of modulation and determining modality value, finally counting up the number of sentences and clauses, then scoring the grammatical intricacy index. The findings of the research show that Material process (71of 100 is mostly used, circumstance of spatial location (26 of 56 is more dominant than the others. Modality (5 is less used in order to avoid from subjectivity. Impersonality is implied through less use of reference either pronouns (7 or demonstrative (7, conjunctions (60 are applied to develop ideas, and the total number of the clauses are found much more dominant (109 than the total number of the sentences (40 which results high grammatical intricacy index. The Metafunction found indicate that the chemistry text has fulfilled the characteristics of scientific or academic text which truly reflects it as a natural science.

Classifying features in CT imagery: accuracy for some single- and multiple-species classifiers

Science.gov (United States)

Daniel L. Schmoldt; Jing He; A. Lynn Abbott

1998-01-01

Our current approach to automatically label features in CT images of hardwood logs classifies each pixel of an image individually. These feature classifiers use a back-propagation artificial neural network (ANN) and feature vectors that include a small, local neighborhood of pixels and the distance of the target pixel to the center of the log. Initially, this type of...

A Gene Expression Classifier of Node-Positive Colorectal Cancer

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Paul F. Meeh

2009-10-01

Full Text Available We used digital long serial analysis of gene expression to discover gene expression differences between node-negative and node-positive colorectal tumors and developed a multigene classifier able to discriminate between these two tumor types. We prepared and sequenced long serial analysis of gene expression libraries from one node-negative and one node-positive colorectal tumor, sequenced to a depth of 26,060 unique tags, and identified 262 tags significantly differentially expressed between these two tumors (P < 2 x 10-6. We confirmed the tag-to-gene assignments and differential expression of 31 genes by quantitative real-time polymerase chain reaction, 12 of which were elevated in the node-positive tumor. We analyzed the expression levels of these 12 upregulated genes in a validation panel of 23 additional tumors and developed an optimized seven-gene logistic regression classifier. The classifier discriminated between node-negative and node-positive tumors with 86% sensitivity and 80% specificity. Receiver operating characteristic analysis of the classifier revealed an area under the curve of 0.86. Experimental manipulation of the function of one classification gene, Fibronectin, caused profound effects on invasion and migration of colorectal cancer cells in vitro. These results suggest that the development of node-positive colorectal cancer occurs in part through elevated epithelial FN1 expression and suggest novel strategies for the diagnosis and treatment of advanced disease.

Building an automated SOAP classifier for emergency department reports.

Science.gov (United States)

Mowery, Danielle; Wiebe, Janyce; Visweswaran, Shyam; Harkema, Henk; Chapman, Wendy W

2012-02-01

Information extraction applications that extract structured event and entity information from unstructured text can leverage knowledge of clinical report structure to improve performance. The Subjective, Objective, Assessment, Plan (SOAP) framework, used to structure progress notes to facilitate problem-specific, clinical decision making by physicians, is one example of a well-known, canonical structure in the medical domain. Although its applicability to structuring data is understood, its contribution to information extraction tasks has not yet been determined. The first step to evaluating the SOAP framework's usefulness for clinical information extraction is to apply the model to clinical narratives and develop an automated SOAP classifier that classifies sentences from clinical reports. In this quantitative study, we applied the SOAP framework to sentences from emergency department reports, and trained and evaluated SOAP classifiers built with various linguistic features. We found the SOAP framework can be applied manually to emergency department reports with high agreement (Cohen's kappa coefficients over 0.70). Using a variety of features, we found classifiers for each SOAP class can be created with moderate to outstanding performance with F(1) scores of 93.9 (subjective), 94.5 (objective), 75.7 (assessment), and 77.0 (plan). We look forward to expanding the framework and applying the SOAP classification to clinical information extraction tasks. Copyright © 2011. Published by Elsevier Inc.

Localizing genes to cerebellar layers by classifying ISH images.

Directory of Open Access Journals (Sweden)

Lior Kirsch

Full Text Available Gene expression controls how the brain develops and functions. Understanding control processes in the brain is particularly hard since they involve numerous types of neurons and glia, and very little is known about which genes are expressed in which cells and brain layers. Here we describe an approach to detect genes whose expression is primarily localized to a specific brain layer and apply it to the mouse cerebellum. We learn typical spatial patterns of expression from a few markers that are known to be localized to specific layers, and use these patterns to predict localization for new genes. We analyze images of in-situ hybridization (ISH experiments, which we represent using histograms of local binary patterns (LBP and train image classifiers and gene classifiers for four layers of the cerebellum: the Purkinje, granular, molecular and white matter layer. On held-out data, the layer classifiers achieve accuracy above 94% (AUC by representing each image at multiple scales and by combining multiple image scores into a single gene-level decision. When applied to the full mouse genome, the classifiers predict specific layer localization for hundreds of new genes in the Purkinje and granular layers. Many genes localized to the Purkinje layer are likely to be expressed in astrocytes, and many others are involved in lipid metabolism, possibly due to the unusual size of Purkinje cells.

Performance Evaluations for Super-Resolution Mosaicing on UAS Surveillance Videos

Directory of Open Access Journals (Sweden)

Aldo Camargo

2013-05-01

Full Text Available Abstract Unmanned Aircraft Systems (UAS have been widely applied for reconnaissance and surveillance by exploiting information collected from the digital imaging payload. The super-resolution (SR mosaicing of low-resolution (LR UAS surveillance video frames has become a critical requirement for UAS video processing and is important for further effective image understanding. In this paper we develop a novel super-resolution framework, which does not require the construction of sparse matrices. The proposed method implements image operations in the spatial domain and applies an iterated back-projection to construct super-resolution mosaics from the overlapping UAS surveillance video frames. The Steepest Descent method, the Conjugate Gradient method and the Levenberg-Marquardt algorithm are used to numerically solve the nonlinear optimization problem for estimating a super-resolution mosaic. A quantitative performance comparison in terms of computation time and visual quality of the super-resolution mosaics through the three numerical techniques is presented.

Modeling of Food and Nutrition Surveillance in Primary Health Care

Directory of Open Access Journals (Sweden)

Santuzza Arreguy Silva VITORINO

Full Text Available ABSTRACT Objective: To describe the modeling stages of food and nutrition surveillance in the Primary Health Care of the Unified Health Care System, considering its activities, objectives, and goals Methods: Document analysis and semi-structured interviews were used for identifying the components, describe the intervention, and identify potential assessment users. Results: The results include identification of the objectives and goals of the intervention, the required inputs, activities, and expected effects. The intervention was then modeled based on these data. The use of the theoretical logic model optimizes times, resources, definition of the indicators that require monitoring, and the aspects that require assessment, identifying more clearly the contribution of the intervention to the results Conclusion: Modeling enabled the description of food and nutrition surveillance based on its components and may guide the development of viable plans to monitor food and nutrition surveillance actions so that modeling can be established as a local intersectoral planning instrument.

LCC: Light Curves Classifier

Science.gov (United States)

Vo, Martin

2017-08-01

Light Curves Classifier uses data mining and machine learning to obtain and classify desired objects. This task can be accomplished by attributes of light curves or any time series, including shapes, histograms, or variograms, or by other available information about the inspected objects, such as color indices, temperatures, and abundances. After specifying features which describe the objects to be searched, the software trains on a given training sample, and can then be used for unsupervised clustering for visualizing the natural separation of the sample. The package can be also used for automatic tuning parameters of used methods (for example, number of hidden neurons or binning ratio). Trained classifiers can be used for filtering outputs from astronomical databases or data stored locally. The Light Curve Classifier can also be used for simple downloading of light curves and all available information of queried stars. It natively can connect to OgleII, OgleIII, ASAS, CoRoT, Kepler, Catalina and MACHO, and new connectors or descriptors can be implemented. In addition to direct usage of the package and command line UI, the program can be used through a web interface. Users can create jobs for ”training” methods on given objects, querying databases and filtering outputs by trained filters. Preimplemented descriptors, classifier and connectors can be picked by simple clicks and their parameters can be tuned by giving ranges of these values. All combinations are then calculated and the best one is used for creating the filter. Natural separation of the data can be visualized by unsupervised clustering.

Intelligent Surveillance Robot with Obstacle Avoidance Capabilities Using Neural Network

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Widodo Budiharto

2015-01-01

Full Text Available For specific purpose, vision-based surveillance robot that can be run autonomously and able to acquire images from its dynamic environment is very important, for example, in rescuing disaster victims in Indonesia. In this paper, we propose architecture for intelligent surveillance robot that is able to avoid obstacles using 3 ultrasonic distance sensors based on backpropagation neural network and a camera for face recognition. 2.4 GHz transmitter for transmitting video is used by the operator/user to direct the robot to the desired area. Results show the effectiveness of our method and we evaluate the performance of the system.

SAVY-4000 Field Surveillance Plan Update for 2017

Energy Technology Data Exchange (ETDEWEB)

Kelly, Elizabeth J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Stone, Timothy Amos [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Smith, Paul Herrick [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Reeves, Kirk Patrick [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Veirs, Douglas Kirk [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Prochnow, David Adrian [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-03-20

The Packaging Surveillance Program section of the Department of Energy (DOE) Manual 441.1-­1, Nuclear Material Packaging Manual (DOE 2008), requires DOE contractors to “ensure that a surveillance program is established and implemented to ensure the nuclear material storage package continues to meet its design criteria.”This 2017 update reflects changes to the surveillance plan resulting from surveillance findings as documented in Reeves et al. 2016. These findings include observations of corrosion in SAVY and Hagan containers and the indication (in one SAVY container) of possible filter membrane thermal degradation. This surveillance plan update documents the rationale for selecting surveillance containers, specifies the containers for 2017 surveillance, and identifies a minimum set of containers for 2018 surveillance. This update contains important changes to the previous surveillance plans.

15 CFR 4.8 - Classified Information.

Science.gov (United States)

2010-01-01

... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Classified Information. 4.8 Section 4... INFORMATION Freedom of Information Act § 4.8 Classified Information. In processing a request for information..., the information shall be reviewed to determine whether it should remain classified. Ordinarily the...

Detection of microaneurysms in retinal images using an ensemble classifier

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M.M. Habib

2017-01-01

Full Text Available This paper introduces, and reports on the performance of, a novel combination of algorithms for automated microaneurysm (MA detection in retinal images. The presence of MAs in retinal images is a pathognomonic sign of Diabetic Retinopathy (DR which is one of the leading causes of blindness amongst the working age population. An extensive survey of the literature is presented and current techniques in the field are summarised. The proposed technique first detects an initial set of candidates using a Gaussian Matched Filter and then classifies this set to reduce the number of false positives. A Tree Ensemble classifier is used with a set of 70 features (the most commons features in the literature. A new set of 32 MA groundtruth images (with a total of 256 labelled MAs based on images from the MESSIDOR dataset is introduced as a public dataset for benchmarking MA detection algorithms. We evaluate our algorithm on this dataset as well as another public dataset (DIARETDB1 v2.1 and compare it against the best available alternative. Results show that the proposed classifier is superior in terms of eliminating false positive MA detection from the initial set of candidates. The proposed method achieves an ROC score of 0.415 compared to 0.2636 achieved by the best available technique. Furthermore, results show that the classifier model maintains consistent performance across datasets, illustrating the generalisability of the classifier and that overfitting does not occur.

Will smart surveillance systems listen, understand and speak Slovene?

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Simon Dobrišek

2013-12-01

Full Text Available The paper deals with the spoken language technologies that could enable the so-called smart (intelligent surveillance systems to listen, understand and speak Slovenian in the near future. Advanced computational methods of artificial perception and pattern recognition enable such systems to be at least to some extent aware of the environment, the presence of people and other phenomena that could be subject to surveillance. Speech is one such phenomenon that has the potential to be a key source of information in certain security situations. Technologies that enable automatic speech and speaker recognition as well as their psychophysical state by computer analysis of acoustic speech signals provide an entirely new dimension to the development of smart surveillance systems. Automatic recognition of spoken threats, screaming and crying for help, as well as a suspicious psycho-physical state of a speaker provide such systems to some extent with intelligent behaviour. The paper investigates the current state of development of these technologies and the requirements and possibilities of these systems to be used for the Slovenian spoken language, as well as different possible security application scenarios. It also addresses the broader legal and ethical issues raised by the development and use of such technologies, especially as audio surveillance is one of the most sensitive issues of privacy protection.

Legionella spp. and legionellosis in southeastern Italy: disease epidemiology and environmental surveillance in community and health care facilities

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Barbuti Giovanna

2010-11-01

Full Text Available Abstract Background Following the publication of the Italian Guidelines for the control and prevention of legionellosis an environmental and clinical surveillance has been carried out in Southeastern Italy. The aim of the study is to identify the risk factors for the disease, so allowing better programming of the necessary prevention measures. Methods During the period January 2000 - December 2009 the environmental surveillance was carried out by water sampling of 129 health care facilities (73 public and 56 private hospitals and 533 buildings within the community (63 private apartments, 305 hotels, 19 offices, 4 churches, 116 gyms, 3 swimming pools and 23 schools. Water sampling and microbiological analysis were carried out following the Italian Guidelines. From January 2005, all facilities were subject to risk analysis through the use of a standardized report; the results were classified as good (G, medium (M and bad (B. As well, all the clinical surveillance forms for legionellosis, which must be compiled by physicians and sent to the Regional Centre for Epidemiology (OER, were analyzed. Results Legionella spp. was found in 102 (79.1% health care facilities and in 238 (44.7% community buildings. The percentages for the contamination levels 10,000 cfu/L were respectively 33.1%, 53.4% and 13.5% for samples from health care facilities and 33.5%, 43.3% and 23.2% for samples from the community. Both in hospital and community environments, Legionella pneumophila serogroup (L. pn sg 2-14 was the most frequently isolate (respectively 54.8% and 40.8% of positive samples, followed by L. pn sg 1 (respectively 31.3% and 33%. The study showed a significant association between M or B score at the risk analysis and Legionella spp. positive microbiological test results (p Conclusions Our experience suggests that risk analysis and environmental microbiological surveillance should be carried out more frequently to control the environmental spread of Legionella

Wavelet classifier used for diagnosing shock absorbers in cars

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Janusz GARDULSKI

2007-01-01

Full Text Available The paper discusses some commonly used methods of hydraulic absorbertesting. Disadvantages of the methods are described. A vibro-acoustic method is presented and recommended for practical use on existing test rigs. The method is based on continuous wavelet analysis combined with neural classifier and 25-neuron, one-way, three-layer back propagation network. The analysis satisfies the intended aim.

The use of hyperspectral data for tree species discrimination: Combining binary classifiers

CSIR Research Space (South Africa)

Dastile, X

2010-11-01

Full Text Available classifier Classification system 7 class 1 class 2 new sample For 5-nearest neighbour classification: assign new sample to class 1. RU SASA 2010 ? Given learning task {(x1,t1),(x 2,t2),?,(x p,tp)} (xi ? Rn feature vectors, ti ? {?1,?, ?c...). A review on the combination of binary classifiers in multiclass problems. Springer science and Business Media B.V [7] Dietterich T.G and Bakiri G.(1995). Solving Multiclass Learning Problem via Error-Correcting Output Codes. AI Access Foundation...

Risk based surveillance for vector borne diseases

DEFF Research Database (Denmark)

Bødker, Rene

of samples and hence early detection of outbreaks. Models for vector borne diseases in Denmark have demonstrated dramatic variation in outbreak risk during the season and between years. The Danish VetMap project aims to make these risk based surveillance estimates available on the veterinarians smart phones...... in Northern Europe. This model approach may be used as a basis for risk based surveillance. In risk based surveillance limited resources for surveillance are targeted at geographical areas most at risk and only when the risk is high. This makes risk based surveillance a cost effective alternative...... sample to a diagnostic laboratory. Risk based surveillance models may reduce this delay. An important feature of risk based surveillance models is their ability to continuously communicate the level of risk to veterinarians and hence increase awareness when risk is high. This is essential for submission...

Emerging infectious diseases in free-ranging wildlife-Australian zoo based wildlife hospitals contribute to national surveillance.

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Keren Cox-Witton

Full Text Available Emerging infectious diseases are increasingly originating from wildlife. Many of these diseases have significant impacts on human health, domestic animal health, and biodiversity. Surveillance is the key to early detection of emerging diseases. A zoo based wildlife disease surveillance program developed in Australia incorporates disease information from free-ranging wildlife into the existing national wildlife health information system. This program uses a collaborative approach and provides a strong model for a disease surveillance program for free-ranging wildlife that enhances the national capacity for early detection of emerging diseases.

Power and Surveillance in Video Games

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Héctor Puente Bienvenido

2014-08-01

Full Text Available In this article we explore the history of video games (focusing on multiplayer ones, from the perspective of power relationships and the ways in which authority has been excesiced by the game industry and game players over time. From a hierarchical system of power and domain to the increasing flatness of the current structure, we address the systems of control and surveillance. We will finish our display assessing the emergent forms of production and relationships between players and developers.

CLASSIFICATION OF TRAFFIC RELATED SHORT TEXTS TO ANALYSE ROAD PROBLEMS IN URBAN AREAS

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A. M. M. Saldana-Perez

2017-09-01

Full Text Available The Volunteer Geographic Information (VGI can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media’s publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.

Sentiment analysis of Arabic tweets using text mining techniques

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Al-Horaibi, Lamia; Khan, Muhammad Badruddin

2016-07-01

Sentiment analysis has become a flourishing field of text mining and natural language processing. Sentiment analysis aims to determine whether the text is written to express positive, negative, or neutral emotions about a certain domain. Most sentiment analysis researchers focus on English texts, with very limited resources available for other complex languages, such as Arabic. In this study, the target was to develop an initial model that performs satisfactorily and measures Arabic Twitter sentiment by using machine learning approach, Naïve Bayes and Decision Tree for classification algorithms. The datasets used contains more than 2,000 Arabic tweets collected from Twitter. We performed several experiments to check the performance of the two algorithms classifiers using different combinations of text-processing functions. We found that available facilities for Arabic text processing need to be made from scratch or improved to develop accurate classifiers. The small functionalities developed by us in a Python language environment helped improve the results and proved that sentiment analysis in the Arabic domain needs lot of work on the lexicon side.

Monitoring data quality in syndromic surveillance: Learnings from a resource limited setting

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E Venkatarao

2012-01-01

Full Text Available Background: India is in the process of integrating all disease surveillance systems with the support of a World Bank funded program called the Integrated Disease Surveillance System. In this context the objective of the study was to evaluate the components of the Orissa Multi Disease Surveillance System. Materials and Methods: Multistage sampling was carried out, starting with four districts, followed by sequentially sampling two blocks; and in each block, two sectors and two health sub-centers were selected, all based on the best and worst performances. Two study instruments were developed for data validation, for assessing the components of the surveillance and diagnostic algorithm. The Organizational Ethics Group reviewed and approved the study. Results: In all 178 study subjects participated in the survey. The case definition of suspected meningitis in disease surveillance was found to be difficult, with only 29.94%, who could be correctly identified. Syndromic diagnosis following the diagnostic algorithm was difficult for suspected malaria (28.1%, ′unusual syndrome′ (28.1%, and simple diarrhea (62%. Only 17% could correctly answer questions on follow-up cases, but only 50% prioritized diseases. Our study showed that 54% cross-checked the data before compilation. Many (22% faltered on timeliness even during emergencies. The constraints identified were logistics (56% and telecommunication (41%. The reason for participation in surveillance was job responsibility (34.83%. Conclusions: Most of the deficiencies arose from human errors when carrying out day-to-day processes of surveillance activities, hence, should be improved by retraining. Enhanced laboratory support and electronic transmission would improve data quality and timeliness. Validity of some of the case definitions need to be rechecked. Training Programs should focus on motivating the surveillance personnel.

Veterinary syndromic surveillance in practice: costs and benefits for governmental organizations

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Fernanda C. Dórea

2015-12-01

Full Text Available Background: We describe a veterinary syndromic surveillance system developed in Sweden based on laboratory test requests. Materials and methods: The system is a desktop application built using free software. Results: Development took 1 year. During the first year of operation, utility was demonstrated by the detection of statistically significant increases in the number of laboratory submissions. The number of false alarms was considered satisfactory in order to achieve the desired sensitivity. Discussion: Besides the demonstrated benefit for disease surveillance, the system contributed to improving data quality and communication between the diagnostic departments and the epidemiology department.

Protocol for hospital based-surveillance of cerebral palsy (CP) in Hanoi using the Paediatric Active Enhanced Disease Surveillance mechanism (PAEDS-Vietnam): a study towards developing hospital-based disease surveillance in Vietnam.

Science.gov (United States)

Khandaker, Gulam; Van Bang, Nguyen; Dũng, Trịnh Quang; Giang, Nguyen Thi Huong; Chau, Cao Minh; Van Anh, Nguyen Thi; Van Thuong, Nguyen; Badawi, Nadia; Elliott, Elizabeth J

2017-11-09

The epidemiology, pathogenesis, management and outcomes of cerebral palsy (CP) in low-income and middle-income countries including Vietnam are unknown because of the lack of mechanisms for standardised collection of data. In this paper, we outline the protocol for developing a hospital-based surveillance system modelled on the Paediatric Active Enhanced Disease Surveillance (PAEDS) system in Australia. Using PAEDS-Vietnam we will define the aetiology, motor function and its severity, associated impairments, and nutritional and rehabilitation status of children with CP in Hanoi, Vietnam. These essential baseline data will inform future health service planning, health professional education and training, and family support. This is a hospital-based prospective surveillance of children with CP presenting to the rehabilitation, neurology and general paediatric services at the National Children's Hospital and St Paul Hospital in Hanoi. We will use active, prospective daily case-finding for all children with CP aged CP, known risk factors for CP, and nutrition, immunisation, education and rehabilitation status. This study was approved by the Hanoi Medical University Institutional Review Board (decision no 1722) and The University of Sydney Human Research Ethics Committee (approval no 2016/456). Establishment of PAEDS-Vietnam will enable hospital-based surveillance of CP for the first time in Vietnam. It will identify preventable causes of CP, patient needs and service gaps, and facilitate early diagnosis and intervention. Study findings will be disseminated through local and international conferences and peer-reviewed publications. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Value of syndromic surveillance within the Armed Forces for early warning during a dengue fever outbreak in French Guiana in 2006

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Jefferson Henry

2008-07-01

Full Text Available Abstract Background A dengue fever outbreak occured in French Guiana in 2006. The objectives were to study the value of a syndromic surveillance system set up within the armed forces, compared to the traditional clinical surveillance system during this outbreak, to highlight issues involved in comparing military and civilian surveillance systems and to discuss the interest of syndromic surveillance for public health response. Methods Military syndromic surveillance allows the surveillance of suspected dengue fever cases among the 3,000 armed forces personnel. Within the same population, clinical surveillance uses several definition criteria for dengue fever cases, depending on the epidemiological situation. Civilian laboratory surveillance allows the surveillance of biologically confirmed cases, within the 200,000 inhabitants. Results It was shown that syndromic surveillance detected the dengue fever outbreak several weeks before clinical surveillance, allowing quick and effective enhancement of vector control within the armed forces. Syndromic surveillance was also found to have detected the outbreak before civilian laboratory surveillance. Conclusion Military syndromic surveillance allowed an early warning for this outbreak to be issued, enabling a quicker public health response by the armed forces. Civilian surveillance system has since introduced syndromic surveillance as part of its surveillance strategy. This should enable quicker public health responses in the future.

Security Enrichment in Intrusion Detection System Using Classifier Ensemble

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Uma R. Salunkhe

2017-01-01

Full Text Available In the era of Internet and with increasing number of people as its end users, a large number of attack categories are introduced daily. Hence, effective detection of various attacks with the help of Intrusion Detection Systems is an emerging trend in research these days. Existing studies show effectiveness of machine learning approaches in handling Intrusion Detection Systems. In this work, we aim to enhance detection rate of Intrusion Detection System by using machine learning technique. We propose a novel classifier ensemble based IDS that is constructed using hybrid approach which combines data level and feature level approach. Classifier ensembles combine the opinions of different experts and improve the intrusion detection rate. Experimental results show the improved detection rates of our system compared to reference technique.

The Role of Hackers in Countering Surveillance and Promoting Democracy

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Sebastian Kubitschko

2015-09-01

Full Text Available Practices related to media technologies and infrastructures (MTI are an increasingly important part of democratic constellations in general and of surveillance tactics in particular. This article does not seek to discuss surveillance per se, but instead to open a new line of inquiry by presenting qualitative research on the Chaos Computer Club (CCC—one of the world’s largest and Europe’s oldest hacker organizations. Despite the longstanding conception of hacking as infused with political significance, the scope and style of hackers’ engagement with emerging issues related to surveillance remains poorly understood. The rationale of this paper is to examine the CCC as a civil society organization that counter-acts contemporary assemblages of surveillance in two ways: first, by de-constructing existing technology and by supporting, building, maintaining and using alternative media technologies and infrastructures that enable more secure and anonymous communication; and second, by articulating their expertise related to contemporary MTI to a wide range of audiences, publics and actors. Highlighting the significance of “privacy” for the health of democracy, I argue that the hacker organization is co-determining “interstitial spaces within information processing practices” (Cohen, 2012, p. 1931, and by doing so is acting on indispensable structural features of contemporary democratic constellations.

Kalman Filter Based Tracking in an Video Surveillance System

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SULIMAN, C.

2010-05-01

Full Text Available In this paper we have developed a Matlab/Simulink based model for monitoring a contact in a video surveillance sequence. For the segmentation process and corect identification of a contact in a surveillance video, we have used the Horn-Schunk optical flow algorithm. The position and the behavior of the correctly detected contact were monitored with the help of the traditional Kalman filter. After that we have compared the results obtained from the optical flow method with the ones obtained from the Kalman filter, and we show the correct functionality of the Kalman filter based tracking. The tests were performed using video data taken with the help of a fix camera. The tested algorithm has shown promising results.

The surveillance error grid.

Science.gov (United States)

Klonoff, David C; Lias, Courtney; Vigersky, Robert; Clarke, William; Parkes, Joan Lee; Sacks, David B; Kirkman, M Sue; Kovatchev, Boris

2014-07-01

Currently used error grids for assessing clinical accuracy of blood glucose monitors are based on out-of-date medical practices. Error grids have not been widely embraced by regulatory agencies for clearance of monitors, but this type of tool could be useful for surveillance of the performance of cleared products. Diabetes Technology Society together with representatives from the Food and Drug Administration, the American Diabetes Association, the Endocrine Society, and the Association for the Advancement of Medical Instrumentation, and representatives of academia, industry, and government, have developed a new error grid, called the surveillance error grid (SEG) as a tool to assess the degree of clinical risk from inaccurate blood glucose (BG) monitors. A total of 206 diabetes clinicians were surveyed about the clinical risk of errors of measured BG levels by a monitor. The impact of such errors on 4 patient scenarios was surveyed. Each monitor/reference data pair was scored and color-coded on a graph per its average risk rating. Using modeled data representative of the accuracy of contemporary meters, the relationships between clinical risk and monitor error were calculated for the Clarke error grid (CEG), Parkes error grid (PEG), and SEG. SEG action boundaries were consistent across scenarios, regardless of whether the patient was type 1 or type 2 or using insulin or not. No significant differences were noted between responses of adult/pediatric or 4 types of clinicians. Although small specific differences in risk boundaries between US and non-US clinicians were noted, the panel felt they did not justify separate grids for these 2 types of clinicians. The data points of the SEG were classified in 15 zones according to their assigned level of risk, which allowed for comparisons with the classic CEG and PEG. Modeled glucose monitor data with realistic self-monitoring of blood glucose errors derived from meter testing experiments plotted on the SEG when compared to

Towards one health disease surveillance: the Southern African Centre for Infectious Disease Surveillance approach.

Science.gov (United States)

Karimuribo, Esron D; Sayalel, Kuya; Beda, Eric; Short, Nick; Wambura, Philemon; Mboera, Leonard G; Kusiluka, Lughano J M; Rweyemamu, Mark M

2012-06-20

Africa has the highest burden of infectious diseases in the world and yet the least capacity for its risk management. It has therefore become increasingly important to search for 'fit-for- purpose' approaches to infectious disease surveillance and thereby targeted disease control. The fact that the majority of human infectious diseases are originally of animal origin means we have to consider One Health (OH) approaches which require inter-sectoral collaboration for custom-made infectious disease surveillance in the endemic settings of Africa. A baseline survey was conducted to assess the current status and performance of human and animal health surveillance systems and subsequently a strategy towards OH surveillance system was developed. The strategy focused on assessing the combination of participatory epidemiological approaches and the deployment of mobile technologies to enhance the effectiveness of disease alerts and surveillance at the point of occurrence, which often lies in remote areas. We selected three study sites, namely the Ngorongoro, Kagera River basin and Zambezi River basin ecosystems. We have piloted and introduced the next-generation Android mobile phones running the EpiCollect application developed by Imperial College to aid geo-spatial and clinical data capture and transmission of this data from the field to the remote Information Technology (IT) servers at the research hubs for storage, analysis, feedback and reporting. We expect that the combination of participatory epidemiology and technology will significantly improve OH disease surveillance in southern Africa.

Healthcare associated infections in neonatal intensive care unit and its correlation with environmental surveillance

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Sanjay Kumar

2018-03-01

Full Text Available Healthcare-associated infections (HAI are frequent complications in neonatal intensive care units (NICU with varying risk factors and bacteriological profile. There is paucity of literature comparing the bacteriological profile of organisms causing HAI with the environmental surveillance isolates. Therefore, this study aimed to evaluate demographic profile, risk factors and outcome of HAI in NICU and correlate with environmental surveillance.Three hundred newborns with signs and symptoms of sepsis were enrolled in the study group and their profile, risk factors and outcome were compared with the control group. Univariate analysis and multivariable logistic regression were performed. Environmental surveillance results were compared to the bacteriological profile of HAIs.We identified lower gestational age, male gender and apgar score less than 7 at 5 min, use of peripheral vascular catheter & ventilator along with their duration as significant risk factors. Mortality rate was 29% in the study group (p < 0.05. The HAI site distribution showed blood-stream infections (73% to be the most common followed by pneumonia (12% and meningitis (10%. Gram positive cocci were the most common isolates in HAI as well as environmental surveillance.The bacteriological profile of HAI correlates with the environmental surveillance report thus insisting for periodic surveillance and thereby avoiding irrational antibiotic usage. Keywords: Healthcare associated infection, Neonatal intensive care unit, Environmental surveillance

FPGA-Based Real-Time Motion Detection for Automated Video Surveillance Systems

Directory of Open Access Journals (Sweden)

Sanjay Singh

2016-03-01

Full Text Available Design of automated video surveillance systems is one of the exigent missions in computer vision community because of their ability to automatically select frames of interest in incoming video streams based on motion detection. This research paper focuses on the real-time hardware implementation of a motion detection algorithm for such vision based automated surveillance systems. A dedicated VLSI architecture has been proposed and designed for clustering-based motion detection scheme. The working prototype of a complete standalone automated video surveillance system, including input camera interface, designed motion detection VLSI architecture, and output display interface, with real-time relevant motion detection capabilities, has been implemented on Xilinx ML510 (Virtex-5 FX130T FPGA platform. The prototyped system robustly detects the relevant motion in real-time in live PAL (720 × 576 resolution video streams directly coming from the camera.

Syndromic surveillance: hospital emergency department participation during the Kentucky Derby Festival.

Science.gov (United States)

Carrico, Ruth; Goss, Linda

2005-01-01

Electronic syndromic surveillance may have value in detecting emerging pathogens or a biological weapons release. Hospitals that have an agile process to evaluate chief complaints of patients seeking emergency care may be able to more quickly identify subtle changes in the community's health. An easily adaptable prototype system was developed to monitor emergency department patient visits during the Kentucky Derby Festival in Louisville, Kentucky, from April 16-May 14, 2002. Use of the system was continued during the same festival periods in 2003 and 2004. Twelve area hospitals in Louisville, Kentucky, participated in a prospective analysis of the chief symptoms of patients who sought care in the emergency department during the Kentucky Derby Festival during 2002. Six hospitals were classified as computer record groups (CRG) and used their existing computerized record capabilities. The other 6 hospitals used a personal digital assistant (PDA) with customized software (PDA group). Data were evaluated by the health department epidemiologist using SaTScan, a modified version of a cancer cluster detection program, to look for clusters of cases above baseline over time and by Zip code. All 12 hospitals were able to collect and provide data elements during the study period. The 6 CRG hospitals were able to perform daily data transmission; however, 3 CRG hospitals were unable to interpret their data because it was transmitted in pure text format. In contrast, data from all 6 PDA group hospitals were interpretable. Real-time data analysis was compared with post-event data, and it was found that the real-time evaluation correctly identified no unusual disease activity during the study period. The 12 hospitals participating in this study demonstrated that community-wide surveillance using computerized data was possible and that the 6 study hospitals using a PDA could quickly interpret emergency department patients' chief complaints. The emergency department chief complaints

Drug overdose surveillance using hospital discharge data.

Science.gov (United States)

Slavova, Svetla; Bunn, Terry L; Talbert, Jeffery

2014-01-01

We compared three methods for identifying drug overdose cases in inpatient hospital discharge data on their ability to classify drug overdoses by intent and drug type(s) involved. We compared three International Classification of Diseases, Ninth Revision, Clinical Modification code-based case definitions using Kentucky hospital discharge data for 2000-2011. The first definition (Definition 1) was based on the external-cause-of-injury (E-code) matrix. The other two definitions were based on the Injury Surveillance Workgroup on Poisoning (ISW7) consensus recommendations for national and state poisoning surveillance using the principal diagnosis or first E-code (Definition 2) or any diagnosis/E-code (Definition 3). Definition 3 identified almost 50% more drug overdose cases than did Definition 1. The increase was largely due to cases with a first-listed E-code describing a drug overdose but a principal diagnosis that was different from drug overdose (e.g., mental disorders, or respiratory or circulatory system failure). Regardless of the definition, more than 53% of the hospitalizations were self-inflicted drug overdoses; benzodiazepines were involved in about 30% of the hospitalizations. The 2011 age-adjusted drug overdose hospitalization rate in Kentucky was 146/100,000 population using Definition 3 and 107/100,000 population using Definition 1. The ISW7 drug overdose definition using any drug poisoning diagnosis/E-code (Definition 3) is potentially the highest sensitivity definition for counting drug overdose hospitalizations, including by intent and drug type(s) involved. As the states enact policies and plan for adequate treatment resources, standardized drug overdose definitions are critical for accurate reporting, trend analysis, policy evaluation, and state-to-state comparison.

Drug Overdose Surveillance Using Hospital Discharge Data

Science.gov (United States)

Bunn, Terry L.; Talbert, Jeffery

2014-01-01

Objectives We compared three methods for identifying drug overdose cases in inpatient hospital discharge data on their ability to classify drug overdoses by intent and drug type(s) involved. Methods We compared three International Classification of Diseases, Ninth Revision, Clinical Modification code-based case definitions using Kentucky hospital discharge data for 2000–2011. The first definition (Definition 1) was based on the external-cause-of-injury (E-code) matrix. The other two definitions were based on the Injury Surveillance Workgroup on Poisoning (ISW7) consensus recommendations for national and state poisoning surveillance using the principal diagnosis or first E-code (Definition 2) or any diagnosis/E-code (Definition 3). Results Definition 3 identified almost 50% more drug overdose cases than did Definition 1. The increase was largely due to cases with a first-listed E-code describing a drug overdose but a principal diagnosis that was different from drug overdose (e.g., mental disorders, or respiratory or circulatory system failure). Regardless of the definition, more than 53% of the hospitalizations were self-inflicted drug overdoses; benzodiazepines were involved in about 30% of the hospitalizations. The 2011 age-adjusted drug overdose hospitalization rate in Kentucky was 146/100,000 population using Definition 3 and 107/100,000 population using Definition 1. Conclusion The ISW7 drug overdose definition using any drug poisoning diagnosis/E-code (Definition 3) is potentially the highest sensitivity definition for counting drug overdose hospitalizations, including by intent and drug type(s) involved. As the states enact policies and plan for adequate treatment resources, standardized drug overdose definitions are critical for accurate reporting, trend analysis, policy evaluation, and state-to-state comparison. PMID:25177055

Gearbox Condition Monitoring Using Advanced Classifiers

Directory of Open Access Journals (Sweden)

P. Večeř

2010-01-01

Full Text Available New efficient and reliable methods for gearbox diagnostics are needed in automotive industry because of growing demand for production quality. This paper presents the application of two different classifiers for gearbox diagnostics – Kohonen Neural Networks and the Adaptive-Network-based Fuzzy Interface System (ANFIS. Two different practical applications are presented. In the first application, the tested gearboxes are separated into two classes according to their condition indicators. In the second example, ANFIS is applied to label the tested gearboxes with a Quality Index according to the condition indicators. In both applications, the condition indicators were computed from the vibration of the gearbox housing. 

Monitoring influenza activity in the United States: a comparison of traditional surveillance systems with Google Flu Trends.

Directory of Open Access Journals (Sweden)

Justin R Ortiz

2011-04-01

Full Text Available Google Flu Trends was developed to estimate US influenza-like illness (ILI rates from internet searches; however ILI does not necessarily correlate with actual influenza virus infections.Influenza activity data from 2003-04 through 2007-08 were obtained from three US surveillance systems: Google Flu Trends, CDC Outpatient ILI Surveillance Network (CDC ILI Surveillance, and US Influenza Virologic Surveillance System (CDC Virus Surveillance. Pearson's correlation coefficients with 95% confidence intervals (95% CI were calculated to compare surveillance data. An analysis was performed to investigate outlier observations and determine the extent to which they affected the correlations between surveillance data. Pearson's correlation coefficient describing Google Flu Trends and CDC Virus Surveillance over the study period was 0.72 (95% CI: 0.64, 0.79. The correlation between CDC ILI Surveillance and CDC Virus Surveillance over the same period was 0.85 (95% CI: 0.81, 0.89. Most of the outlier observations in both comparisons were from the 2003-04 influenza season. Exclusion of the outlier observations did not substantially improve the correlation between Google Flu Trends and CDC Virus Surveillance (0.82; 95% CI: 0.76, 0.87 or CDC ILI Surveillance and CDC Virus Surveillance (0.86; 95%CI: 0.82, 0.90.This analysis demonstrates that while Google Flu Trends is highly correlated with rates of ILI, it has a lower correlation with surveillance for laboratory-confirmed influenza. Most of the outlier observations occurred during the 2003-04 influenza season that was characterized by early and intense influenza activity, which potentially altered health care seeking behavior, physician testing practices, and internet search behavior.

Participatory Surveillance and Photo Sharing Practices

DEFF Research Database (Denmark)

Albrechtslund, Anders; Damkjaer, Maja Sonne; Bøge, Ask Risom

2019-01-01

-material perspective on photo-sharing practices. Information, Communication & Society, 19(4), 475–488. Sontag, S. (1977). On Photography. Picador. Steeves, V., & Jones, O. (2010). Editorial: Surveillance, Children and Childhood. Surveillance & Society, 7(3/4), 187–191....... that parents do not generally plan to store or organize their photos, and even less their children’s photos. This seems to indicate a shift from a pre-digital perception of photos as objects to be packaged, accumulated, framed etc. which can age and disappear (see Sontag, 1977) to something perceived less....... References: Albrechtslund, A. (2008). Online Social Networking as Participatory Surveillance. First Monday, 13(3). Fotel, T., & Thomsen, T. U. (2002). The Surveillance of Children’s Mobility. Surveillance & Society, 1(4), 535-554. Lobinger, K. (2016). Photographs as things–photographs of things. A texto...

A Novel Surveillance System Applied in Civil Airport

Directory of Open Access Journals (Sweden)

Sun Hua Bo

2016-01-01

Full Text Available Conventional security monitoring of civil airport usually uses a fixed camera to acquire images. There are several problems with performance including difficulties introduced in the information transmission, storage, and analysis of the process. Insect compound eyes offer unique advantages for moving target capture and these have attracted the attention of many researchers in recent years. This paper contributes to this research by proposing a new surveillance system applied in civil airport. We discuss the finished bionic structure of the system, the development of the bionic control circuit, and introduce the proposed mathematical model of bionic compound eyes for data acquisition and image mosaic. Image matching for large view is also illustrated with different conditions. This mode and algorithm effectively achieve safety surveillance of airport with large field of view and high real-time processing.

Classifying Sluice Occurrences in Dialogue

DEFF Research Database (Denmark)

Baird, Austin; Hamza, Anissa; Hardt, Daniel

2018-01-01

perform manual annotation with acceptable inter-coder agreement. We build classifier models with Decision Trees and Naive Bayes, with accuracy of 67%. We deploy a classifier to automatically classify sluice occurrences in OpenSubtitles, resulting in a corpus with 1.7 million occurrences. This will support....... Despite this, the corpus can be of great use in research on sluicing and development of systems, and we are making the corpus freely available on request. Furthermore, we are in the process of improving the accuracy of sluice identification and annotation for the purpose of created a subsequent version...

Cost effectiveness of surveillance for GI cancers.

Science.gov (United States)

Omidvari, Amir-Houshang; Meester, Reinier G S; Lansdorp-Vogelaar, Iris

2016-12-01

Gastrointestinal (GI) diseases are among the leading causes of death in the world. To reduce the burden of GI diseases, surveillance is recommended for some diseases, including for patients with inflammatory bowel diseases, Barrett's oesophagus, precancerous gastric lesions, colorectal adenoma, and pancreatic neoplasms. This review aims to provide an overview of the evidence on cost-effectiveness of surveillance of individuals with GI conditions predisposing them to cancer, specifically focussing on the aforementioned conditions. We searched the literature and reviewed 21 studies. Despite heterogeneity of studies in terms of settings, study populations, surveillance strategies and outcomes, most reviewed studies suggested at least some surveillance of patients with these GI conditions to be cost-effective. For some high-risk conditions frequent surveillance with 3-month intervals was warranted, while for other conditions, surveillance may only be cost-effective every 10 years. Further studies based on more robust effectiveness evidence are needed to inform and optimise surveillance programmes for GI cancers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Public involvement in environmental surveillance at Hanford

International Nuclear Information System (INIS)

Hanf, R.W. Jr.; Patton, G.W.; Woodruff, R.K.; Poston, T.M.

1994-08-01

Environmental surveillance at the Hanford Site began during the mid-1940s following the construction and start-up of the nation's first plutonium production reactor. Over the past approximately 45 years, surveillance operations on and off the Site have continued, with virtually all sampling being conducted by Hanford Site workers. Recently, the US Department of Energy Richland Operations Office directed that public involvement in Hanford environmental surveillance operations be initiated. Accordingly, three special radiological air monitoring stations were constructed offsite, near hanford's perimeter. Each station is managed and operated by two local school teaches. These three stations are the beginning of a community-operated environmental surveillance program that will ultimately involve the public in most surveillance operations around the Site. The program was designed to stimulate interest in Hanford environmental surveillance operations, and to help the public better understand surveillance results. The program has also been used to enhance educational opportunities at local schools

Naive Bayes as opinion classifier to evaluate students satisfaction based on student sentiment in Twitter Social Media

Science.gov (United States)

Candra Permana, Fahmi; Rosmansyah, Yusep; Setiawan Abdullah, Atje

2017-10-01

Students activity on social media can provide implicit knowledge and new perspectives for an educational system. Sentiment analysis is a part of text mining that can help to analyze and classify the opinion data. This research uses text mining and naive Bayes method as opinion classifier, to be used as an alternative methods in the process of evaluating studentss satisfaction for educational institution. Based on test results, this system can determine the opinion classification in Bahasa Indonesia using naive Bayes as opinion classifier with accuracy level of 84% correct, and the comparison between the existing system and the proposed system to evaluate students satisfaction in learning process, there is only a difference of 16.49%.

Environmental surveillance master sampling schedule

Energy Technology Data Exchange (ETDEWEB)

Bisping, L.E.

1993-01-01

Environmental surveillance of the Hanford Site and surrounding areas is conducted by the Pacific Northwest Laboratory (PNL) for the US Department of Energy (DOE). Samples are routinely collected and analyzed to determine the quality of air, surface water, ground water, soil, sediment, wildlife, vegetation, foodstuffs, and farm products at Hanford Site and surrounding communities. This document contains the planned schedule for routine sample collection for the Surface Environmental Surveillance Project (SESP) and Drinking Water Project, and Ground-Water Surveillance Project.

Robust Behavior Recognition in Intelligent Surveillance Environments

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Ganbayar Batchuluun

2016-06-01

Full Text Available Intelligent surveillance systems have been studied by many researchers. These systems should be operated in both daytime and nighttime, but objects are invisible in images captured by visible light camera during the night. Therefore, near infrared (NIR cameras, thermal cameras (based on medium-wavelength infrared (MWIR, and long-wavelength infrared (LWIR light have been considered for usage during the nighttime as an alternative. Due to the usage during both daytime and nighttime, and the limitation of requiring an additional NIR illuminator (which should illuminate a wide area over a great distance for NIR cameras during the nighttime, a dual system of visible light and thermal cameras is used in our research, and we propose a new behavior recognition in intelligent surveillance environments. Twelve datasets were compiled by collecting data in various environments, and they were used to obtain experimental results. The recognition accuracy of our method was found to be 97.6%, thereby confirming the ability of our method to outperform previous methods.

Food and water radioactivity surveillance system in Romania

International Nuclear Information System (INIS)

Cucu, A.; Gheorghe, R.; May, C.; Barbu, R.

2008-01-01

Full text: Justification: Food and water radioactivity content are closely related both to natural radioactivity and also generated by contamination due to anthropic nuclear activities. Consequently, in accordance with the European Union acquis and World Health Organization recommendation, surveillance systems were operationalized in many European countries. According to the national Romanian derived legislation the public health authorities are responsible for organizing and coordination of the national surveillance system for water and food radioactivity and their health related effects. Objectives: Description of the levels and type of radioactivity of drinking water and main foodstuffs and their contribution to the Romanian population exposure in order to elaborate appropriate public health interventions. Method: The gross parameters, alpha and beta, have been used for screening surveillance of drinking water sources indeed for potable purposes in order to identify those that could exceed the total indicative dose of 0.1 mSv/year. The food surveillance was focused on the main foodstuffs including milk, meat, fish, eggs, bread, potatoes, root vegetables (mainly carrots), leafy vegetables (mainly cabbage), fruits, and canteen menu, controlled for presence and level of radioactivity for 137 Cs, 90 Sr, 226 Ra, 210 Po and 40 K. Nuclear facility related monitoring for areas as nuclear power plant Cernavoda (type HWR-CANDU) and for regions with activities of extraction and fabrication of uranium fuel includes monitoring of radioactivity for: environmental deposit levels, surface waters, spontaneous vegetation, drinking water and foodstuffs. Results: 1) The water radioactivity surveillance results, mapped by administrative borders of the national territory, reveal that parameters of drinking water complies both with Drinking Water Directive 98/83 EC and WHO recommandation/2004; 2) For food stuff radioactivity: a) Mean registered values fully comply with reference for

Elementary Surveillance (ELS) and Enhanced Surveillance (EHS) Validation via Mode S Secondary Radar Surveillance

National Research Council Canada - National Science Library

Grappel, Robert D; Harris, Garrett S; Kozar, Mark J; Wiken, Randall T

2008-01-01

...) and Enhanced Surveillance (ERS) data link applications. The intended audience for this report is an engineering staff assigned the task of implementing a monitoring system used to determine ELS and EHS compliance...

Laser surveillance system (LASSY)

International Nuclear Information System (INIS)

Boeck, H.

1991-09-01

Laser Surveillance System (LASSY) is a beam of laser light which scans a plane above the water or under-water in a spent-fuel pond. The system can detect different objects and estimates its coordinates and distance as well. LASSY can operate in stand-alone configuration or in combination with a video surveillance to trigger signal to a videorecorder. The recorded information on LASSY computer's disk comprises date, time, start and stop angle of detected alarm, the size of the disturbance indicated in number of deviated points and some other information. The information given by the laser system cannot be fully substituted by TV camera pictures since the scanning beam creates a horizontal surveillance plan. The engineered prototype laser system long-term field test has been carried out in Soluggia (Italy) and has shown its feasibility and reliability under the conditions of real spent fuel storage pond. The verification of the alarm table on the LASSY computer with the recorded video pictures of TV surveillance system confirmed that all alarm situations have been detected. 5 refs

Surveillance of antimicrobial resistance at a tertiary hospital in Tanzania

Directory of Open Access Journals (Sweden)

Mashurano Marcellina

2004-10-01

Full Text Available Abstract Background Antimicrobial resistance is particularly harmful to infectious disease management in low-income countries since expensive second-line drugs are not readily available. The objective of this study was to implement and evaluate a computerized system for surveillance of antimicrobial resistance at a tertiary hospital in Tanzania. Methods A computerized surveillance system for antimicrobial susceptibility (WHONET was implemented at the national referral hospital in Tanzania in 1998. The antimicrobial susceptibilities of all clinical bacterial isolates received during an 18 months' period were recorded and analyzed. Results The surveillance system was successfully implemented at the hospital. This activity increased the focus on antimicrobial resistance issues and on laboratory quality assurance issues. The study identified specific nosocomial problems in the hospital and led to the initiation of other prospective studies on prevalence and antimicrobial susceptibility of bacterial infections. Furthermore, the study provided useful data on antimicrobial patterns in bacterial isolates from the hospital. Gram-negative bacteria displayed high rates of resistance to common inexpensive antibiotics such as ampicillin, tetracycline and trimethoprim-sulfamethoxazole, leaving fluoroquinolones as the only reliable oral drugs against common Gram-negative bacilli. Gentamicin and third generation cephalosporins remain useful for parenteral therapy. Conclusion The surveillance system is a low-cost tool to generate valuable information on antimicrobial resistance, which can be used to prepare locally applicable recommendations on antimicrobial use. The system pinpoints relevant nosocomial problems and can be used to efficiently plan further research. The surveillance system also functions as a quality assurance tool, bringing attention to methodological issues in identification and susceptibility testing.

Visibility and surveillance regime in the age of Digital Identity

Directory of Open Access Journals (Sweden)

María Alejandra López Gabrielidis

2015-12-01

Full Text Available This article addresses the link between the hypervisibility regime in which the contemporary subject is immersed in and the new forms of surveillance. Based on an analysis of the work of Hito Steyerl How Not to be Seen: A Fucking Didactic Educational .MOV File (2013 we explore the changes suffered by the traditional form of surveillance with a special highlight on the current features of the cyber-surveillance device. The 21st century is witnessing a socio-technical phenomenon which transforms the subject into an image-data, as a result of what Paul Virilio calls the industrialization and proliferation of “visual machines” (photographic cameras, microscopes, telescopes, drones, the social online habits which tend to self-capture and self-diffusion, and the processes of datification. Nowadays, the subject assumes an active role in the surveillance mechanisms and, hence, is partly responsible of the control that is practiced over him. In this video, Hito Steyerl teaches us about camouflage techniques, confusion and low resolution uses, in order to be less visible before the eyes of the power. However, the excess of visibility and exposure of the subject seems to be a highly difficult situation to counteract in the technical conditions that we live in. As we propose in the last section of the article, in order to solve the surveillance problems in the digital age it is necessary to redefine the concept of privacy starting from the concept of digital identity, with all its implications. Consequently, we must lead the way into new forms of legal authority over data.

A Novel Cascade Classifier for Automatic Microcalcification Detection.

Directory of Open Access Journals (Sweden)

Seung Yeon Shin

Full Text Available In this paper, we present a novel cascaded classification framework for automatic detection of individual and clusters of microcalcifications (μC. Our framework comprises three classification stages: i a random forest (RF classifier for simple features capturing the second order local structure of individual μCs, where non-μC pixels in the target mammogram are efficiently eliminated; ii a more complex discriminative restricted Boltzmann machine (DRBM classifier for μC candidates determined in the RF stage, which automatically learns the detailed morphology of μC appearances for improved discriminative power; and iii a detector to detect clusters of μCs from the individual μC detection results, using two different criteria. From the two-stage RF-DRBM classifier, we are able to distinguish μCs using explicitly computed features, as well as learn implicit features that are able to further discriminate between confusing cases. Experimental evaluation is conducted on the original Mammographic Image Analysis Society (MIAS and mini-MIAS databases, as well as our own Seoul National University Bundang Hospital digital mammographic database. It is shown that the proposed method outperforms comparable methods in terms of receiver operating characteristic (ROC and precision-recall curves for detection of individual μCs and free-response receiver operating characteristic (FROC curve for detection of clustered μCs.

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha

2013-11-25

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Fuzzy prototype classifier based on items and its application in recommender system

Directory of Open Access Journals (Sweden)

Mei Cai

2017-01-01

Full Text Available Currently, recommender systems (RS are incorporating implicit information from social circle of the Internet. The implicit social information in human mind is not easy to reflect in appropriate decision making techniques. This paper consists of 2 contributions. First, we develop an item-based prototype classifier (IPC in which a prototype represents a social circlers preferences as a pattern classification technique. We assume the social circle which distinguishes with others by the items their members like. The prototype structure of the classifier is defined by two2-dimensional matrices. We use information gain and OWA aggregator to construct a feature space. The item-based classifier assigns a new item to some prototypes with different prototypicalities. We reform a typical data setmIris data set in UCI Machine Learning Repository to verify our fuzzy prototype classifier. The second proposition of this paper is to give the application of IPC in recommender system to solve new item cold-start problems. We modify the dataset of MovieLens to perform experimental demonstrations of the proposed ideas.

Positive predictive value and effectiveness of measles case-based surveillance in Uganda, 2012-2015.

Directory of Open Access Journals (Sweden)

Fred Nsubuga

Full Text Available Disease surveillance is a critical component in the control and elimination of vaccine preventable diseases. The Uganda National Expanded Program on Immunization strives to have a sensitive surveillance system within the Integrated Disease Surveillance and Response (IDSR framework. We analyzed measles surveillance data to determine the effectiveness of the measles case-based surveillance system and estimate its positive predictive value in order to inform policy and practice.An IDSR alert was defined as ≥1 suspected measles case reported by a district in a week, through the electronic Health Management Information System. We defined an alert in the measles case-based surveillance system (CBS as ≥1 suspected measles case with a blood sample collected for confirmation during the corresponding week in a particular district. Effectiveness of CBS was defined as having ≥80% of IDSR alerts with a blood sample collected for laboratory confirmation. Positive predictive value was defined as the proportion of measles case-patients who also had a positive measles serological result (IgM +. We reviewed case-based surveillance data with laboratory confirmation and measles surveillance data from the electronic Health Management Information System from 2012-2015.A total of 6,974 suspected measles case-persons were investigated by the measles case-based surveillance between 2012 and 2015. Of these, 943 (14% were measles specific IgM positive. The median age of measles case-persons between 2013 and 2015 was 4.0 years. Between 2013 and 2015, 72% of the IDSR alerts reported in the electronic Health Management Information System, had blood samples collected for laboratory confirmation. This was however less than the WHO recommended standard of ≥80%. The PPV of CBS between 2013 and 2015 was 8.6%.In conclusion, the effectiveness of measles case-based surveillance was sub-optimal, while the PPV showed that true measles cases have significantly reduced in Uganda

Air surveillance

Energy Technology Data Exchange (ETDEWEB)

Patton, G.W.

1995-06-01

This section of the 1994 Hanford Site Environmental Report summarizes the air surveillance and monitoring programs currently in operation at that Hanford Site. Atmospheric releases of pollutants from Hanford to the surrounding region are a potential source of human exposure. For that reason, both radioactive and nonradioactive materials in air are monitored at a number of locations. The influence of Hanford emissions on local radionuclide concentrations was evaluated by comparing concentrations measured at distant locations within the region to concentrations measured at the Site perimeter. This section discusses sample collection, analytical methods, and the results of the Hanford air surveillance program. A complete listing of all analytical results summarized in this section is reported separately by Bisping (1995).

Air surveillance

International Nuclear Information System (INIS)

Patton, G.W.

1995-01-01

This section of the 1994 Hanford Site Environmental Report summarizes the air surveillance and monitoring programs currently in operation at that Hanford Site. Atmospheric releases of pollutants from Hanford to the surrounding region are a potential source of human exposure. For that reason, both radioactive and nonradioactive materials in air are monitored at a number of locations. The influence of Hanford emissions on local radionuclide concentrations was evaluated by comparing concentrations measured at distant locations within the region to concentrations measured at the Site perimeter. This section discusses sample collection, analytical methods, and the results of the Hanford air surveillance program. A complete listing of all analytical results summarized in this section is reported separately by Bisping (1995)

Classifying unstructed textual data using the Product Score Model: an alternative text mining algorithm

NARCIS (Netherlands)

He, Qiwei; Veldkamp, Bernard P.; Eggen, T.J.H.M.; Veldkamp, B.P.

2012-01-01

Unstructured textual data such as students’ essays and life narratives can provide helpful information in educational and psychological measurement, but often contain irregularities and ambiguities, which creates difficulties in analysis. Text mining techniques that seek to extract useful

Project Surveillance and Maintenance Plan

International Nuclear Information System (INIS)

1985-09-01

The Project Surveillance and Maintenance Plan (PSMP) describes the procedures that will be used by the US Department of Energy (DOE), or other agency as designated by the President to verify that inactive uranium tailings disposal facilities remain in compliance with licensing requirements and US Environmental Protection Agency (EPA) standards for remedial actions. The PSMP will be used as a guide for the development of individual Site Surveillance and Maintenance Plans (part of a license application) for each of the UMTRA Project sites. The PSMP is not intended to provide minimum requirements but rather to provide guidance in the selection of surveillance measures. For example, the plan acknowledges that ground-water monitoring may or may not be required and provides the [guidance] to make this decision. The Site Surveillance and Maintenance Plans (SSMPs) will form the basis for the licensing of the long-term surveillance and maintenance of each UMTRA Project site by the NRC. Therefore, the PSMP is a key milestone in the licensing process of all UMTRA Project sites. The Project Licensing Plan (DOE, 1984a) describes the licensing process. 11 refs., 22 figs., 8 tabs

The importance of waterborne disease outbreak surveillance in the United States

Directory of Open Access Journals (Sweden)

Gunther Franz Craun

2012-12-01

Full Text Available Analyses of the causes of disease outbreaks associated with contaminated drinking water in the United States have helped inform prevention efforts at the national, state, and local levels. This article describes the changing nature of disease outbreaks in public water systems during 1971-2008 and discusses the importance of a collaborative waterborne outbreak surveillance system established in 1971. Increasing reports of outbreaks throughout the early 1980s emphasized that microbial contaminants remained a health-risk challenge for suppliers of drinking water. Outbreak investigations identified the responsible etiologic agents and deficiencies in the treatment and distribution of drinking water, especially the high risk associated with unfiltered surface water systems. Surveillance information was important in establishing an effective research program that guided government regulations and industry actions to improve drinking water quality. Recent surveillance statistics suggest that prevention efforts based on these research findings have been effective in reducing outbreak risks especially for surface water systems.

Societies of Control: State techno-surveillance and Civic Resistance in Mexico

Directory of Open Access Journals (Sweden)

Paola Ricaurte Quijano

2014-08-01

Full Text Available The aim of this article is to discuss the global and local implications of State surveillance in the light of the theoretical approach around control societies. We hold that the systematic, continuous and total techno-surveillance is an undeniable fact that promotes and requires multivaried forms of civil resistance. To demonstrate our position, we conducted a brief count of the actions undertaken by the Mexican civil society against the laws that promote the use of technology as a monitoring tool in Mexico, and the presence of spyware in Mexican operators. Finally, we present the consequences of techno-surveillance for journalists, activists and human rights advocates. This article concludes that monitoring practices in control societies are implemented by means of socio-technical mechanisms which articulate the public with the private sphere and are carried out with the civilian consent. However, various forms of civic resistance emerge in the continuity of the private and the public, the virtual and the physical, the local and the global.

Discourses of healthcare professionals about health surveillance actions for Tuberculosis control

Directory of Open Access Journals (Sweden)

Fernando Mitano

Full Text Available Abstract OBJECTIVE To analyze the meanings produced in the Health Surveillance actions for tuberculosis control, carried out by healthcare professionals in Mozambique. METHOD Qualitative study using the theoretical and methodological framework of the French Discourse Analysis. RESULTS A total of 15 healthcare professionals with more than one year of experience in disease control actions participated in the study. Four discursive blocks have emerged from the analysis: tuberculosis diagnosis process; meeting, communication and discussion of treatment; local strategies for tuberculosis control; involvement of family and community leaders in the tuberculosis control. CONCLUSION The statements of the healthcare professionals suggest, as Health Surveillance actions, practices that include collecting sputum in the patient's home and sending it to the laboratory; deployment of the medical team with a microscope for tuberculosis testing; and testing for diseases that may be associated with tuberculosis. In this context, the actions of Health Surveillance for tuberculosis control involve valuing all actors: family, community leaders, patients and health professionals.

Twitter web-service for soft agent reporting in persistent surveillance systems

Science.gov (United States)

Rababaah, Haroun; Shirkhodaie, Amir

2010-04-01

Persistent surveillance is an intricate process requiring monitoring, gathering, processing, tracking, and characterization of many spatiotemporal events occurring concurrently. Data associated with events can be readily attained by networking of hard (physical) sensors. Sensors may have homogeneous or heterogeneous (hybrid) sensing modalities with different communication bandwidth requirements. Complimentary to hard sensors are human observers or "soft sensors" that can report occurrences of evolving events via different communication devices (e.g., texting, cell phones, emails, instant messaging, etc.) to the command control center. However, networking of human observers in ad-hoc way is rather a difficult task. In this paper, we present a Twitter web-service for soft agent reporting in persistent surveillance systems (called Web-STARS). The objective of this web-service is to aggregate multi-source human observations in hybrid sensor networks rapidly. With availability of Twitter social network, such a human networking concept can not only be realized for large scale persistent surveillance systems (PSS), but also, it can be employed with proper interfaces to expedite rapid events reporting by human observers. The proposed technique is particularly suitable for large-scale persistent surveillance systems with distributed soft and hard sensor networks. The efficiency and effectiveness of the proposed technique is measured experimentally by conducting several simulated persistent surveillance scenarios. It is demonstrated that by fusion of information from hard and soft agents improves understanding of common operating picture and enhances situational awareness.

Ebola Surveillance - Guinea, Liberia, and Sierra Leone.

Science.gov (United States)

McNamara, Lucy A; Schafer, Ilana J; Nolen, Leisha D; Gorina, Yelena; Redd, John T; Lo, Terrence; Ervin, Elizabeth; Henao, Olga; Dahl, Benjamin A; Morgan, Oliver; Hersey, Sara; Knust, Barbara

2016-07-08

Developing a surveillance system during a public health emergency is always challenging but is especially so in countries with limited public health infrastructure. Surveillance for Ebola virus disease (Ebola) in the West African countries heavily affected by Ebola (Guinea, Liberia, and Sierra Leone) faced numerous impediments, including insufficient numbers of trained staff, community reticence to report cases and contacts, limited information technology resources, limited telephone and Internet service, and overwhelming numbers of infected persons. Through the work of CDC and numerous partners, including the countries' ministries of health, the World Health Organization, and other government and nongovernment organizations, functional Ebola surveillance was established and maintained in these countries. CDC staff were heavily involved in implementing case-based surveillance systems, sustaining case surveillance and contact tracing, and interpreting surveillance data. In addition to helping the ministries of health and other partners understand and manage the epidemic, CDC's activities strengthened epidemiologic and data management capacity to improve routine surveillance in the countries affected, even after the Ebola epidemic ended, and enhanced local capacity to respond quickly to future public health emergencies. However, the many obstacles overcome during development of these Ebola surveillance systems highlight the need to have strong public health, surveillance, and information technology infrastructure in place before a public health emergency occurs. Intense, long-term focus on strengthening public health surveillance systems in developing countries, as described in the Global Health Security Agenda, is needed.The activities summarized in this report would not have been possible without collaboration with many U.S and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html).

Classifying Aging as a Disease in the context of ICD-11

Directory of Open Access Journals (Sweden)

Alex eZhavoronkov

2015-11-01

Full Text Available Aging is a complex continuous multifactorial process leading to loss of function and crystalizing into the many age-related diseases. Here, we explore the arguments for classifying aging as a disease in the context of the upcoming World Health Organization’s 11th International Statistical Classification of Diseases and Related Health Problems (ICD-11, expected to be finalized in 2018. We hypothesize that classifying aging as a disease will result in new approaches and business models for addressing aging as a treatable condition, which will lead to both economic and healthcare benefits for all stakeholders. Classification of aging as a disease may lead to more efficient allocation of resources by enabling funding bodies and other stakeholders to use quality-adjusted life years (QALYs and healthy-years equivalent (HYE as metrics when evaluating both research and clinical programs. We propose forming a Task Force to interface the WHO in order to develop a multidisciplinary framework for classifying aging as a disease.

A cascade of classifiers for extracting medication information from discharge summaries

Directory of Open Access Journals (Sweden)

Halgrim Scott

2011-07-01

Full Text Available Abstract Background Extracting medication information from clinical records has many potential applications, and recently published research, systems, and competitions reflect an interest therein. Much of the early extraction work involved rules and lexicons, but more recently machine learning has been applied to the task. Methods We present a hybrid system consisting of two parts. The first part, field detection, uses a cascade of statistical classifiers to identify medication-related named entities. The second part uses simple heuristics to link those entities into medication events. Results The system achieved performance that is comparable to other approaches to the same task. This performance is further improved by adding features that reference external medication name lists. Conclusions This study demonstrates that our hybrid approach outperforms purely statistical or rule-based systems. The study also shows that a cascade of classifiers works better than a single classifier in extracting medication information. The system is available as is upon request from the first author.

Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition

Directory of Open Access Journals (Sweden)

Md. Rabiul Islam

2014-01-01

Full Text Available The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

Use of classifier to determine coffee harvest time by detachment force

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Murilo M. de Barros

Full Text Available ABSTRACT Coffee quality is an essential aspect to increase its commercial value and for the Brazilian coffee business to remain prominent in the world market. Fruit maturity stage at harvest is an important factor that affects the quality and commercial value of the product. Therefore, the objective of this study was to develop a classifier using neural networks to distinguish green coffee fruits from mature coffee fruits, based on the detachment force. Fruit detachment force and the percentage value of the maturity stage were measured during a 75-day harvest window. Collections were carried out biweekly, resulting in five different moments within the harvest period. A classifier was developed using neural networks to distinguish green fruits from mature fruits in the harvest period analyzed. The results show that, in the first half of June, the supervised classified had the highest success percentage in differentiating green fruits from mature fruits, and this period was considered as ideal for a selective harvest under these experimental conditions.

Evaluation of Syndromic Surveillance Systems in 6 US State and Local Health Departments.

Science.gov (United States)

Thomas, Mathew J; Yoon, Paula W; Collins, James M; Davidson, Arthur J; Mac Kenzie, William R

strengthen syndromic surveillance by including broader access to and enhanced analysis of text-related data from electronic health records. Health departments may accelerate the development and use of syndromic surveillance systems, including the improvement of the predictive value and strengthening the early outbreak detection capability of these systems. These efforts support getting the right information to the right people at the right time, which is the overarching goal of CDC's Surveillance Strategy.

SAGES: a suite of freely-available software tools for electronic disease surveillance in resource-limited settings.

Directory of Open Access Journals (Sweden)

Sheri L Lewis

Full Text Available Public health surveillance is undergoing a revolution driven by advances in the field of information technology. Many countries have experienced vast improvements in the collection, ingestion, analysis, visualization, and dissemination of public health data. Resource-limited countries have lagged behind due to challenges in information technology infrastructure, public health resources, and the costs of proprietary software. The Suite for Automated Global Electronic bioSurveillance (SAGES is a collection of modular, flexible, freely-available software tools for electronic disease surveillance in resource-limited settings. One or more SAGES tools may be used in concert with existing surveillance applications or the SAGES tools may be used en masse for an end-to-end biosurveillance capability. This flexibility allows for the development of an inexpensive, customized, and sustainable disease surveillance system. The ability to rapidly assess anomalous disease activity may lead to more efficient use of limited resources and better compliance with World Health Organization International Health Regulations.

Soil and vegetation surveillance

Energy Technology Data Exchange (ETDEWEB)

Antonio, E.J.

1995-06-01

Soil sampling and analysis evaluates long-term contamination trends and monitors environmental radionuclide inventories. This section of the 1994 Hanford Site Environmental Report summarizes the soil and vegetation surveillance programs which were conducted during 1994. Vegetation surveillance is conducted offsite to monitor atmospheric deposition of radioactive materials in areas not under cultivation and onsite at locations adjacent to potential sources of radioactivity.

Surveillance and Social Memory: Remembering Princess Diana with CCTV

Directory of Open Access Journals (Sweden)

Nicole Falkenhayner

2016-09-01

Full Text Available Since the 1990s, surveillance camera images have experienced a function creep from their juridical uses into journalism and entertainment. In these contexts, the images have also become memory media. This article, for the first time, analyses CCTV images, meaning closed circuit surveillance camera images, as memory media and discusses the implications of our use of artefacts of control within a frame of mediated constructions of social memory. The article undertakes this work by analyzing remediations of the CCTV images of Diana Spencer and Dodi Al-Fayed in the Ritz Hotel in Paris on 30 August 1997 in television news and a documentary from 2007 and 2011, respectively. It is shown how social memory of Diana’s death is a contested site, in which the images play a specific role.

Privacy preserving surveillance and the tracking-paradox

OpenAIRE

Greiner, S.; Birnstill, Pascal; Krempel, Erik; Beckert, B.; Beyerer, Jürgen

2013-01-01

Increasing capabilities of intelligent video surveillance systems impose new threats to privacy while, at the same time, offering opportunities for reducing the privacy invasiveness of surveillance measures as well as their selectivity. We show that aggregating more data about observed people does not necessarily lead to less privacy, but can increase the selectivity of surveillance measures. In case of video surveillance in a company environment, if we enable the system to authenticate emplo...

Surveillance theory and its implications for law

NARCIS (Netherlands)

Timan, Tjerk; Galic, Masa; Koops, Bert-Jaap; Brownsword, Roger; Scotford, Eloise; Yeung, Karen

2017-01-01

This chapter provides an overview of key surveillance theories and their implications for law and regulation. It presents three stages of theories that characterise changes in thinking about surveillance in society and the disciplining, controlling, and entertaining functions of surveillance.

76 FR 34761 - Classified National Security Information

Science.gov (United States)

2011-06-14

... MARINE MAMMAL COMMISSION Classified National Security Information [Directive 11-01] AGENCY: Marine... Commission's (MMC) policy on classified information, as directed by Information Security Oversight Office... of Executive Order 13526, ``Classified National Security Information,'' and 32 CFR part 2001...

Medical surveillance of occupationally exposed workers

International Nuclear Information System (INIS)

2007-05-01

The guide covers medical surveillance of workers engaged in radiation work and their fitness for this work, protection of the foetus and infant during the worker's pregnancy or breastfeeding, and medical surveillance measures to be taken when the dose limit has been exceeded. The guide also covers recognition of practitioners responsible for medical surveillance of category A workers, medical certificates to be issued to workers, and preservation and transfer of medical records. The medical surveillance requirements specified in this Guide cover the use of radiation and nuclear energy. The guide also applies to exposure to natural radiation in accordance with section 28 of the Finnish Radiation Decree

Negotiating privacy in surveillant welfare relations

DEFF Research Database (Denmark)

Andersen, Lars Bo; Lauritsen, Peter; Bøge, Ask Risom

. However, while privacy is central to debates of surveillance, it has proven less productive as an analytical resource for studying surveillance in practice. Consequently, this paper reviews different conceptualisations of privacy in relation to welfare and surveillance and argues for strengthening...... the analytical capacity of the concept by rendering it a situated and relational concept. The argument is developed through a research and design project called Teledialogue meant to improve the relation between case managers and children placed at institutions or in foster families. Privacy in Teledialogue...... notion of privacy are discussed in relation to both research- and public debates on surveillance in a welfare setting....

Medical surveillance of occupationally exposed workers

Energy Technology Data Exchange (ETDEWEB)

2007-05-15

The guide covers medical surveillance of workers engaged in radiation work and their fitness for this work, protection of the foetus and infant during the worker's pregnancy or breastfeeding, and medical surveillance measures to be taken when the dose limit has been exceeded. The guide also covers recognition of practitioners responsible for medical surveillance of category A workers, medical certificates to be issued to workers, and preservation and transfer of medical records. The medical surveillance requirements specified in this Guide cover the use of radiation and nuclear energy. The guide also applies to exposure to natural radiation in accordance with section 28 of the Finnish Radiation Decree

Error minimizing algorithms for nearest eighbor classifiers

Energy Technology Data Exchange (ETDEWEB)

Porter, Reid B [Los Alamos National Laboratory; Hush, Don [Los Alamos National Laboratory; Zimmer, G. Beate [TEXAS A& M

2011-01-03

Stack Filters define a large class of discrete nonlinear filter first introd uced in image and signal processing for noise removal. In recent years we have suggested their application to classification problems, and investigated their relationship to other types of discrete classifiers such as Decision Trees. In this paper we focus on a continuous domain version of Stack Filter Classifiers which we call Ordered Hypothesis Machines (OHM), and investigate their relationship to Nearest Neighbor classifiers. We show that OHM classifiers provide a novel framework in which to train Nearest Neighbor type classifiers by minimizing empirical error based loss functions. We use the framework to investigate a new cost sensitive loss function that allows us to train a Nearest Neighbor type classifier for low false alarm rate applications. We report results on both synthetic data and real-world image data.

Advancements in web-database applications for rabies surveillance

Directory of Open Access Journals (Sweden)

Bélanger Denise

2011-08-01

Full Text Available Abstract Background Protection of public health from rabies is informed by the analysis of surveillance data from human and animal populations. In Canada, public health, agricultural and wildlife agencies at the provincial and federal level are responsible for rabies disease control, and this has led to multiple agency-specific data repositories. Aggregation of agency-specific data into one database application would enable more comprehensive data analyses and effective communication among participating agencies. In Québec, RageDB was developed to house surveillance data for the raccoon rabies variant, representing the next generation in web-based database applications that provide a key resource for the protection of public health. Results RageDB incorporates data from, and grants access to, all agencies responsible for the surveillance of raccoon rabies in Québec. Technological advancements of RageDB to rabies surveillance databases include 1 automatic integration of multi-agency data and diagnostic results on a daily basis; 2 a web-based data editing interface that enables authorized users to add, edit and extract data; and 3 an interactive dashboard to help visualize data simply and efficiently, in table, chart, and cartographic formats. Furthermore, RageDB stores data from citizens who voluntarily report sightings of rabies suspect animals. We also discuss how sightings data can indicate public perception to the risk of racoon rabies and thus aid in directing the allocation of disease control resources for protecting public health. Conclusions RageDB provides an example in the evolution of spatio-temporal database applications for the storage, analysis and communication of disease surveillance data. The database was fast and inexpensive to develop by using open-source technologies, simple and efficient design strategies, and shared web hosting. The database increases communication among agencies collaborating to protect human health from

Towards data justice? The ambiguity of anti-surveillance resistance in political activism

Directory of Open Access Journals (Sweden)

Lina Dencik

2016-11-01

Full Text Available The Snowden leaks, first published in June 2013, provided unprecedented insights into the operations of state-corporate surveillance, highlighting the extent to which everyday communication is integrated into an extensive regime of control that relies on the ‘datafication’ of social life. Whilst such data-driven forms of governance have significant implications for citizenship and society, resistance to surveillance in the wake of the Snowden leaks has predominantly centred on techno-legal responses relating to the development and use of encryption and policy advocacy around privacy and data protection. Based on in-depth interviews with a range of social justice activists, we argue that there is a significant level of ambiguity around this kind of anti-surveillance resistance in relation to broader activist practices, and critical responses to the Snowden leaks have been confined within particular expert communities. Introducing the notion of ‘data justice’, we therefore go on to make the case that resistance to surveillance needs to be (reconceptualized on terms that can address the implications of this data-driven form of governance in relation to broader social justice agendas. Such an approach is needed, we suggest, in light of a shift to surveillance capitalism in which the collection, use and analysis of our data increasingly comes to shape the opportunities and possibilities available to us and the kind of society we live in.

Aggregation Operator Based Fuzzy Pattern Classifier Design

DEFF Research Database (Denmark)

Mönks, Uwe; Larsen, Henrik Legind; Lohweg, Volker

2009-01-01

This paper presents a novel modular fuzzy pattern classifier design framework for intelligent automation systems, developed on the base of the established Modified Fuzzy Pattern Classifier (MFPC) and allows designing novel classifier models which are hardware-efficiently implementable....... The performances of novel classifiers using substitutes of MFPC's geometric mean aggregator are benchmarked in the scope of an image processing application against the MFPC to reveal classification improvement potentials for obtaining higher classification rates....

Identification of flooded area from satellite images using Hybrid Kohonen Fuzzy C-Means sigma classifier

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Krishna Kant Singh

2017-06-01

Full Text Available A novel neuro fuzzy classifier Hybrid Kohonen Fuzzy C-Means-σ (HKFCM-σ is proposed in this paper. The proposed classifier is a hybridization of Kohonen Clustering Network (KCN with FCM-σ clustering algorithm. The network architecture of HKFCM-σ is similar to simple KCN network having only two layers, i.e., input and output layer. However, the selection of winner neuron is done based on FCM-σ algorithm. Thus, embedding the features of both, a neural network and a fuzzy clustering algorithm in the classifier. This hybridization results in a more efficient, less complex and faster classifier for classifying satellite images. HKFCM-σ is used to identify the flooding that occurred in Kashmir area in September 2014. The HKFCM-σ classifier is applied on pre and post flooding Landsat 8 OLI images of Kashmir to detect the areas that were flooded due to the heavy rainfalls of September, 2014. The classifier is trained using the mean values of the various spectral indices like NDVI, NDWI, NDBI and first component of Principal Component Analysis. The error matrix was computed to test the performance of the method. The method yields high producer’s accuracy, consumer’s accuracy and kappa coefficient value indicating that the proposed classifier is highly effective and efficient.

Enhanced surveillance of Staphylococcus aureus bacteraemia to identify targets for infection prevention.

Science.gov (United States)

Morris, A K; Russell, C D

2016-06-01

Surveillance of Staphylococcus aureus bacteraemia (SAB) in Scotland is limited to the number of infections per 100,000 acute occupied bed-days and susceptibility to meticillin. To demonstrate the value of enhanced SAB surveillance to identify targets for infection prevention. Prospective cohort study of all patients identified with SAB over a five-year period in a single health board in Scotland. All patients were reviewed at the bedside by a clinical microbiologist. In all, 556 SAB episodes were identified: 261 (46.6%) were hospital-acquired; 209 (37.9%) were healthcare-associated; 80 (14.4%) were community-acquired; and in six (1.1%) the origin of infection was not hospital-acquired, but could not be separated into healthcare-associated or community-acquired. These were classified as non-hospital-acquired. Meticillin-resistant S. aureus (MRSA) bacteraemia was associated with hospital-acquired and healthcare-associated infections. In addition, there was a significantly higher 30-day mortality associated with hospital-acquired (31.4%) and healthcare-associated (16.3%) infections compared to community-acquired SAB (8.7%). Vascular access devices were associated with hospital-acquired SAB and peripheral venous cannulas were the source for most of these (43.9%). Community-acquired infections were associated with intravenous drug misuse, respiratory tract infections and skeletal and joint infections. Skin and soft tissue infections were more widely seen in healthcare-associated infections. The data indicate that enhanced surveillance of SAB by origin of infection and source of bacteraemia has implications for infection prevention, empirical antibiotic therapy, and health improvement interventions. Copyright © 2016 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.

Science.gov (United States)

Luo, Yuan; Cheng, Yu; Uzuner, Özlem; Szolovits, Peter; Starren, Justin

2018-01-01

We propose Segment Convolutional Neural Networks (Seg-CNNs) for classifying relations from clinical notes. Seg-CNNs use only word-embedding features without manual feature engineering. Unlike typical CNN models, relations between 2 concepts are identified by simultaneously learning separate representations for text segments in a sentence: preceding, concept1, middle, concept2, and succeeding. We evaluate Seg-CNN on the i2b2/VA relation classification challenge dataset. We show that Seg-CNN achieves a state-of-the-art micro-average F-measure of 0.742 for overall evaluation, 0.686 for classifying medical problem-treatment relations, 0.820 for medical problem-test relations, and 0.702 for medical problem-medical problem relations. We demonstrate the benefits of learning segment-level representations. We show that medical domain word embeddings help improve relation classification. Seg-CNNs can be trained quickly for the i2b2/VA dataset on a graphics processing unit (GPU) platform. These results support the use of CNNs computed over segments of text for classifying medical relations, as they show state-of-the-art performance while requiring no manual feature engineering. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Systematic review of electronic surveillance of infectious diseases with emphasis on antimicrobial resistance surveillance in resource-limited settings.

Science.gov (United States)

Rattanaumpawan, Pinyo; Boonyasiri, Adhiratha; Vong, Sirenda; Thamlikitkul, Visanu

2018-02-01

Electronic surveillance of infectious diseases involves rapidly collecting, collating, and analyzing vast amounts of data from interrelated multiple databases. Although many developed countries have invested in electronic surveillance for infectious diseases, the system still presents a challenge for resource-limited health care settings. We conducted a systematic review by performing a comprehensive literature search on MEDLINE (January 2000-December 2015) to identify studies relevant to electronic surveillance of infectious diseases. Study characteristics and results were extracted and systematically reviewed by 3 infectious disease physicians. A total of 110 studies were included. Most surveillance systems were developed and implemented in high-income countries; less than one-quarter were conducted in low-or middle-income countries. Information technologies can be used to facilitate the process of obtaining laboratory, clinical, and pharmacologic data for the surveillance of infectious diseases, including antimicrobial resistance (AMR) infections. These novel systems require greater resources; however, we found that using electronic surveillance systems could result in shorter times to detect targeted infectious diseases and improvement of data collection. This study highlights a lack of resources in areas where an effective, rapid surveillance system is most needed. The availability of information technology for the electronic surveillance of infectious diseases, including AMR infections, will facilitate the prevention and containment of such emerging infectious diseases. Copyright © 2018 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

ISS--an electronic syndromic surveillance system for infectious disease in rural China.

Directory of Open Access Journals (Sweden)

Weirong Yan

Full Text Available BACKGROUND: Syndromic surveillance system has great advantages in promoting the early detection of epidemics and reducing the necessities of disease confirmation, and it is especially effective for surveillance in resource poor settings. However, most current syndromic surveillance systems are established in developed countries, and there are very few reports on the development of an electronic syndromic surveillance system in resource-constrained settings. OBJECTIVE: This study describes the design and pilot implementation of an electronic surveillance system (ISS for the early detection of infectious disease epidemics in rural China, complementing the conventional case report surveillance system. METHODS: ISS was developed based on an existing platform 'Crisis Information Sharing Platform' (CRISP, combining with modern communication and GIS technology. ISS has four interconnected functions: 1 work group and communication group; 2 data source and collection; 3 data visualization; and 4 outbreak detection and alerting. RESULTS: As of Jan. 31(st 2012, ISS has been installed and pilot tested for six months in four counties in rural China. 95 health facilities, 14 pharmacies and 24 primary schools participated in the pilot study, entering respectively 74,256, 79,701, and 2330 daily records into the central database. More than 90% of surveillance units at the study sites are able to send daily information into the system. In the paper, we also presented the pilot data from health facilities in the two counties, which showed the ISS system had the potential to identify the change of disease patterns at the community level. CONCLUSIONS: The ISS platform may facilitate the early detection of infectious disease epidemic as it provides near real-time syndromic data collection, interactive visualization, and automated aberration detection. However, several constraints and challenges were encountered during the pilot implementation of ISS in rural China.

Gender and classifiers in concurrent systems: Refining the typology of nominal classification

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Sebastian Fedden

2017-04-01

Full Text Available Some languages have both gender and classifiers, contrary to what was once believed possible. We use these interesting languages as a unique window onto nominal classification. They provide the impetus for a new typology, based on the degree of orthogonality of the semantic systems and the degree of difference of the forms realizing them. This nine-way typology integrates traditional gender, traditional classifiers and – importantly – the many recently attested phenomena lying between. Besides progress specifically in understanding nominal classification, our approach provides clarity on the wider theoretical issue of single versus concurrent featural systems.

Surveillance and threat detection prevention versus mitigation

CERN Document Server

Kirchner, Richard

2014-01-01

Surveillance and Threat Detection offers readers a complete understanding of the terrorist/criminal cycle, and how to interrupt that cycle to prevent an attack. Terrorists and criminals often rely on pre-attack and pre-operational planning and surveillance activities that can last a period of weeks, months, or even years. Identifying and disrupting this surveillance is key to prevention of attacks. The systematic capture of suspicious events and the correlation of those events can reveal terrorist or criminal surveillance, allowing security professionals to employ appropriate countermeasures and identify the steps needed to apprehend the perpetrators. The results will dramatically increase the probability of prevention while streamlining protection assets and costs. Readers of Surveillance and Threat Detection will draw from real-world case studies that apply to their real-world security responsibilities. Ultimately, readers will come away with an understanding of how surveillance detection at a high-value, f...

Social Media Text Classification by Enhancing Well-Formed Text Trained Model

Directory of Open Access Journals (Sweden)

Phat Jotikabukkana

2016-09-01

Full Text Available Social media are a powerful communication tool in our era of digital information. The large amount of user-generated data is a useful novel source of data, even though it is not easy to extract the treasures from this vast and noisy trove. Since classification is an important part of text mining, many techniques have been proposed to classify this kind of information. We developed an effective technique of social media text classification by semi-supervised learning utilizing an online news source consisting of well-formed text. The computer first automatically extracts news categories, well-categorized by publishers, as classes for topic classification. A bag of words taken from news articles provides the initial keywords related to their category in the form of word vectors. The principal task is to retrieve a set of new productive keywords. Term Frequency-Inverse Document Frequency weighting (TF-IDF and Word Article Matrix (WAM are used as main methods. A modification of WAM is recomputed until it becomes the most effective model for social media text classification. The key success factor was enhancing our model with effective keywords from social media. A promising result of 99.50% accuracy was achieved, with more than 98.5% of Precision, Recall, and F-measure after updating the model three times.

Classification of Traffic Related Short Texts to Analyse Road Problems in Urban Areas

Science.gov (United States)

Saldana-Perez, A. M. M.; Moreno-Ibarra, M.; Tores-Ruiz, M.

2017-09-01

The Volunteer Geographic Information (VGI) can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media's publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.

Surveillance of nuclear power reactors

International Nuclear Information System (INIS)

Marini, J.

1983-01-01

Surveillance of nuclear power reactors is now a necessity imposed by such regulatory documents as USNRC Regulatory Guide 1.133. In addition to regulatory requirements, however, nuclear reactor surveillance offers plant operators significant economic advantages insofar as a single day's outage is very costly. The economic worth of a reactor surveillance system can be stated in terms of the improved plant availability provided through its capability to detect incidents before they occur and cause serious damage. Furthermore, the TMI accident has demonstrated the need for monitoring certain components to provide operators with clear information on their functional status. In response to the above considerations, Framatome has developed a line of products which includes: pressure vessel leakage detection systems, loose part detection systems, component vibration monitoring systems, and, crack detection and monitoring systems. Some of the surveillance systems developed by Framatome are described in this paper

Replicas Strategy and Cache Optimization of Video Surveillance Systems Based on Cloud Storage

Directory of Open Access Journals (Sweden)

Rongheng Li

2018-04-01

Full Text Available With the rapid development of video surveillance technology, especially the popularity of cloud-based video surveillance applications, video data begins to grow explosively. However, in the cloud-based video surveillance system, replicas occupy an amount of storage space. Also, the slow response to video playback constrains the performance of the system. In this paper, considering the characteristics of video data comprehensively, we propose a dynamic redundant replicas mechanism based on security levels that can dynamically adjust the number of replicas. Based on the location correlation between cameras, this paper also proposes a data cache strategy to improve the response speed of data reading. Experiments illustrate that: (1 our dynamic redundant replicas mechanism can save storage space while ensuring data security; (2 the cache mechanism can predict the playback behaviors of the users in advance and improve the response speed of data reading according to the location and time correlation of the front-end cameras; and (3 in terms of cloud-based video surveillance, our proposed approaches significantly outperform existing methods.

Priorities for antibiotic resistance surveillance in Europe

DEFF Research Database (Denmark)

Fluit, A. C.; van der Bruggen, J. T.; Aarestrup, Frank Møller

2006-01-01

Antibiotic resistance is an increasing global problem. Surveillance studies are needed to monitor resistance development, to guide local empirical therapy, and to implement timely and adequate countermeasures. To achieve this, surveillance studies must have standardised methodologies, be longitud......Antibiotic resistance is an increasing global problem. Surveillance studies are needed to monitor resistance development, to guide local empirical therapy, and to implement timely and adequate countermeasures. To achieve this, surveillance studies must have standardised methodologies...... to the various reservoirs of antibiotic-resistant bacteria, such as hospitalised patients, nursing homes, the community, animals and food. Two studies that could serve as examples of tailored programmes are the European Antimicrobial Resistance Surveillance System (EARSS), which collects resistance data during...... of antibiotic resistance....

Groundwater surveillance plan for the Oak Ridge Reservation

International Nuclear Information System (INIS)

Forstrom, J.M.; Smith, E.D.; Winters, S.L.; McMaster, W.M.

1994-07-01

US Department of Energy (DOE) Order 5400.1 requires the preparation of environmental monitoring plans and implementation of environmental monitoring programs for all DOE facilities. The order identifies two distinct components of environmental monitoring, namely effluent monitoring and environmental surveillance. In general, effluent monitoring has the objectives of characterizing contaminants and demonstrating compliance with applicable standards and permit requirements, whereas environmental surveillance has the broader objective of monitoring the effects of DOE activities on on- and off-site environmental and natural resources. The purpose of this document is to support the Environmental Monitoring Plan for the Oak Ridge Reservation (ORR) by describing the groundwater component of the environmental surveillance program for the DOE facilities on the ORR. The distinctions between groundwater effluent monitoring and groundwater surveillance have been defined in the Martin Marietta Energy Systems, Inc., Groundwater Surveillance Strategy. As defined in the strategy, a groundwater surveillance program consists of two parts, plant perimeter surveillance and off-site water well surveillance. This document identifies the sampling locations, parameters, and monitoring frequencies for both of these activities on and around the ORR and describes the rationale for the program design. The program was developed to meet the objectives of DOE Order 5400.1 and related requirements in DOE Order 5400.5 and to conform with DOE guidance on environmental surveillance and the Energy Systems Groundwater Surveillance Strategy

Microprocessor-based integrated LMFBR core surveillance

International Nuclear Information System (INIS)

Gmeiner, L.

1984-06-01

This report results from a joint study of KfK and INTERATOM. The aim of this study is to explore the advantages of microprocessors and microelectronics for a more sophisticated core surveillance, which is based on the integration of separate surveillance techniques. Due to new developments in microelectronics and related software an approach to LMFBR core surveillance can be conceived that combines a number of measurements into a more intelligent decision-making data processing system. The following techniques are considered to contribute essentially to an integrated core surveillance system: - subassembly state and thermal hydraulics performance monitoring, - temperature noise analysis, - acoustic core surveillance, - failure characterization and failure prediction based on DND- and cover gas signals, and - flux tilting techniques. Starting from a description of these techniques it is shown that by combination and correlation of these individual techniques a higher degree of cost-effectiveness, reliability and accuracy can be achieved. (orig./GL) [de

Evaluating surveillance strategies for the early detection of low pathogenicity avian influenza infections.

Directory of Open Access Journals (Sweden)

Arianna Comin

Full Text Available In recent years, the early detection of low pathogenicity avian influenza (LPAI viruses in poultry has become increasingly important, given their potential to mutate into highly pathogenic viruses. However, evaluations of LPAI surveillance have mainly focused on prevalence and not on the ability to act as an early warning system. We used a simulation model based on data from Italian LPAI epidemics in turkeys to evaluate different surveillance strategies in terms of their performance as early warning systems. The strategies differed in terms of sample size, sampling frequency, diagnostic tests, and whether or not active surveillance (i.e., routine laboratory testing of farms was performed, and were also tested under different epidemiological scenarios. We compared surveillance strategies by simulating within-farm outbreaks. The output measures were the proportion of infected farms that are detected and the farm reproduction number (R(h. The first one provides an indication of the sensitivity of the surveillance system to detect within-farm infections, whereas R(h reflects the effectiveness of outbreak detection (i.e., if detection occurs soon enough to bring an epidemic under control. Increasing the sampling frequency was the most effective means of improving the timeliness of detection (i.e., it occurs earlier, whereas increasing the sample size increased the likelihood of detection. Surveillance was only effective in preventing an epidemic if actions were taken within two days of sampling. The strategies were not affected by the quality of the diagnostic test, although performing both serological and virological assays increased the sensitivity of active surveillance. Early detection of LPAI outbreaks in turkeys can be achieved by increasing the sampling frequency for active surveillance, though very frequent sampling may not be sustainable in the long term. We suggest that, when no LPAI virus is circulating yet and there is a low risk of virus

WORKPLACE SURVEILLANCE: BIG BROTHER IS WATCHING YOU?

Directory of Open Access Journals (Sweden)

Corneliu BÎRSAN

2018-05-01

Full Text Available Only recently workplace surveillance has become a real concern of the international community. Very often we hear about employers who monitor and record the actions of their employees, in order to check for any breaches of company policies or procedures, to ensure that appropriate behaviour standards are being met and that company property, confidential information and intellectual property is not being damaged. Surveillance at workplace may include inter alia monitoring of telephone and internet use, opening of personal files stored on a professional computer, video surveillance. But what if this monitoring or recording breaches human rights? In order to give practical examples for these means, we shall proceed to a chronological analysis of the most relevant cases dealt by the European Court of Human Rights along the time, in which the Strasbourg judges decided that the measures taken by the employers exceed the limits given by Article 8 of the Convention. After providing the most relevant examples from the Court’s case-law in this field, we shall analyse the outcome of the recent Grand Chamber Barbulescu v. Romania judgment. The purpose of this study is to offer to the interested legal professionals and to the domestic authorities of the Member States the information in order to adequately protect the right of each individual to respect for his or her private life and correspondence under the European Convention on Human Rights.

Electronic Integrated Disease Surveillance System and Pathogen Asset Control System

Directory of Open Access Journals (Sweden)

Tom G. Wahl

2012-06-01

Full Text Available Electronic Integrated Disease Surveillance System (EIDSS has been used to strengthen and support monitoring and prevention of dangerous diseases within One Health concept by integrating veterinary and human surveillance, passive and active approaches, case-based records including disease-specific clinical data based on standardised case definitions and aggregated data, laboratory data including sample tracking linked to each case and event with test results and epidemiological investigations. Information was collected and shared in secure way by different means: through the distributed nodes which are continuously synchronised amongst each other, through the web service, through the handheld devices. Electronic Integrated Disease Surveillance System provided near real time information flow that has been then disseminated to the appropriate organisations in a timely manner. It has been used for comprehensive analysis and visualisation capabilities including real time mapping of case events as these unfold enhancing decision making. Electronic Integrated Disease Surveillance System facilitated countries to comply with the IHR 2005 requirements through a data transfer module reporting diseases electronically to the World Health Organisation (WHO data center as well as establish authorised data exchange with other electronic system using Open Architecture approach. Pathogen Asset Control System (PACS has been used for accounting, management and control of biological agent stocks. Information on samples and strains of any kind throughout their entire lifecycle has been tracked in a comprehensive and flexible solution PACS. Both systems have been used in a combination and individually. Electronic Integrated Disease Surveillance System and PACS are currently deployed in the Republics of Kazakhstan, Georgia and Azerbaijan as a part of the Cooperative Biological Engagement Program (CBEP sponsored by the US Defense Threat Reduction Agency (DTRA.

Post-tensioning system surveillance program

International Nuclear Information System (INIS)

Drew, G.E.

1979-01-01

Nuclear power plant containment structure post-tensioning system tendon surveillance program is described in detail. Data collected over three yearly post-tensioning system Surveillance Programs is presented and evaluated to correlate anticipated stress losses with actual losses. In addition corrosion protected system performance is analyzed

Integrating air-related health surveillance into air quality management: perceptions and practicalities

CSIR Research Space (South Africa)

Wright, C

2012-06-01

Full Text Available Health surveillance is presently not an integral part of air quality management in South Africa, although ambient air pollution standards are derived from health effects of personal exposure. In a survey to air quality officials and environmental...

ARABIC TEXT CLASSIFICATION USING NEW STEMMER FOR FEATURE SELECTION AND DECISION TREES

Directory of Open Access Journals (Sweden)

SAID BAHASSINE

2017-06-01

Full Text Available Text classification is the process of assignment of unclassified text to appropriate classes based on their content. The most prevalent representation for text classification is the bag of words vector. In this representation, the words that appear in documents often have multiple morphological structures, grammatical forms. In most cases, this morphological variant of words belongs to the same category. In the first part of this paper, anew stemming algorithm was developed in which each term of a given document is represented by its root. In the second part, a comparative study is conducted of the impact of two stemming algorithms namely Khoja’s stemmer and our new stemmer (referred to hereafter by origin-stemmer on Arabic text classification. This investigation was carried out using chi-square as a feature of selection to reduce the dimensionality of the feature space and decision tree classifier. In order to evaluate the performance of the classifier, this study used a corpus that consists of 5070 documents independently classified into six categories: sport, entertainment, business, Middle East, switch and world on WEKA toolkit. The recall, f-measure and precision measures are used to compare the performance of the obtained models. The experimental results show that text classification using rout stemmer outperforms classification using Khoja’s stemmer. The f-measure was 92.9% in sport category and 89.1% in business category.

Composite Classifiers for Automatic Target Recognition

National Research Council Canada - National Science Library

Wang, Lin-Cheng

1998-01-01

...) using forward-looking infrared (FLIR) imagery. Two existing classifiers, one based on learning vector quantization and the other on modular neural networks, are used as the building blocks for our composite classifiers...

Enteric disease surveillance under the AFHSC-GEIS: Current efforts, landscape analysis and vision forward

Directory of Open Access Journals (Sweden)

Kasper Matthew R

2011-03-01

Full Text Available Abstract The mission of the Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System (AFHSC-GEIS is to support global public health and to counter infectious disease threats to the United States Armed Forces, including newly identified agents or those increasing in incidence. Enteric diseases are a growing threat to U.S. forces, which must be ready to deploy to austere environments where the risk of exposure to enteropathogens may be significant and where routine prevention efforts may be impractical. In this report, the authors review the recent activities of AFHSC-GEIS partner laboratories in regards to enteric disease surveillance, prevention and response. Each partner identified recent accomplishments, including support for regional networks. AFHSC/GEIS partners also completed a Strengths, Weaknesses, Opportunities and Threats (SWOT survey as part of a landscape analysis of global enteric surveillance efforts. The current strengths of this network include excellent laboratory infrastructure, equipment and personnel that provide the opportunity for high-quality epidemiological studies and test platforms for point-of-care diagnostics. Weaknesses include inconsistent guidance and a splintered reporting system that hampers the comparison of data across regions or longitudinally. The newly chartered Enterics Surveillance Steering Committee (ESSC is intended to provide clear mission guidance, a structured project review process, and central data management and analysis in support of rationally directed enteric disease surveillance efforts.

Mass gatherings: A one-stop opportunity to complement global disease surveillance

Directory of Open Access Journals (Sweden)

Habida Elachola

2016-01-01

Full Text Available Emerging infections including those resulting from the bioterrorist use of infectious agents have indicated the need for global health surveillance. This paper reviews multiple surveillance opportunities presented by mass gatherings (MGs that align with fundamental questions in epidemiology (why, what, who, where, when and how. Some MGs bring together large, diverse population groups coming from countries with high prevalence of communicable diseases and disparate surveillance capacities. MGs have the potential to exacerbate the transmission dynamics of infectious diseases due to various factors including the high population density and rigor of events, increase in number of people with underlying diseases that predisposes them to disease acquisition, mixing of people from countries or regions with and without efficient disease control efforts, and varying endemicity or existence of communicable diseases in home countries. MGs also have the potential to increase the opportunities for mechanical and even heat-related injuries, morbidity or deaths from accidents, alcohol use, deliberate terrorist attacks with biological agents and/or with explosives and from exacerbation of pre-existing conditions. Responding to these wider range of events may require the use of novel bio-surveillance systems designed to collect data from different sources including electronic and non-electronic medical records from emergency departments and hospitalisations, laboratories, medical examiners, emergency call centres, veterinary, food processors, drinking water systems and even other non-traditional sources such as over-the-counter drug sales and crowd photographs. Well-structured, interoperable real-time surveillance and reporting systems should be integral to MG planning. The increase in magnitude of participants exceeding millions and diversity of people attending MGs can be proactively used to conduct active surveillance of communicable and non

The Great East Japan Earthquake: a need to plan for post-disaster surveillance in developed countries

Directory of Open Access Journals (Sweden)

Jeffrey Partridge

2011-12-01

Full Text Available After a devastating earthquake and tsunami struck north-eastern Japan in March 2011, the public health system, including the infectious disease surveillance system, was severely compromised. While models for post-disaster surveillance exist, they focus predominantly on developing countries during the early recovery phase. Such models do not necessarily apply to developed countries, which differ considerably in their baseline surveillance systems. Furthermore, there is a need to consider the process by which a surveillance system recovers post-disaster. The event in Japan has highlighted a need to address these concerns surrounding post-disaster surveillance in developed countries.In May 2011, the World Health Organization convened a meeting where post-disaster surveillance was discussed by experts and public health practitioners. In this paper, we describe a post-disaster surveillance approach that was discussed at the meeting, based on what had actually occurred and what may have been, or would be, ideal. Briefly, we describe the evolution of a surveillance system as it returns to the pre-existing system, starting from an event-based approach during the emergency relief phase, a syndromic approach during the early recovery phase, an enhanced sentinel approach during the late recovery phase and a return to baseline during the development phase. Our aim is not to recommend a specific model but to encourage other developed countries to initiate their own discussions on post-disaster surveillance and develop plans according to their needs and capacities. As natural disasters will continue to occur, we hope that developing such plans during the “inter-disaster” period will help mitigate the surveillance challenges that will arise post-disaster.

Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield.

Science.gov (United States)

Hassanpour, Saeed; Langlotz, Curtis P; Amrhein, Timothy J; Befera, Nicholas T; Lungren, Matthew P

2017-04-01

The purpose of this study is to evaluate the performance of a natural language processing (NLP) system in classifying a database of free-text knee MRI reports at two separate academic radiology practices. An NLP system that uses terms and patterns in manually classified narrative knee MRI reports was constructed. The NLP system was trained and tested on expert-classified knee MRI reports from two major health care organizations. Radiology reports were modeled in the training set as vectors, and a support vector machine framework was used to train the classifier. A separate test set from each organization was used to evaluate the performance of the system. We evaluated the performance of the system both within and across organizations. Standard evaluation metrics, such as accuracy, precision, recall, and F1 score (i.e., the weighted average of the precision and recall), and their respective 95% CIs were used to measure the efficacy of our classification system. The accuracy for radiology reports that belonged to the model's clinically significant concept classes after training data from the same institution was good, yielding an F1 score greater than 90% (95% CI, 84.6-97.3%). Performance of the classifier on cross-institutional application without institution-specific training data yielded F1 scores of 77.6% (95% CI, 69.5-85.7%) and 90.2% (95% CI, 84.5-95.9%) at the two organizations studied. The results show excellent accuracy by the NLP machine learning classifier in classifying free-text knee MRI reports, supporting the institution-independent reproducibility of knee MRI report classification. Furthermore, the machine learning classifier performed well on free-text knee MRI reports from another institution. These data support the feasibility of multiinstitutional classification of radiologic imaging text reports with a single machine learning classifier without requiring institution-specific training data.

Internet and Surveillance

DEFF Research Database (Denmark)

The Internet has been transformed in the past years from a system primarily oriented on information provision into a medium for communication and community-building. The notion of “Web 2.0”, social software, and social networking sites such as Facebook, Twitter and MySpace have emerged in this co......The Internet has been transformed in the past years from a system primarily oriented on information provision into a medium for communication and community-building. The notion of “Web 2.0”, social software, and social networking sites such as Facebook, Twitter and MySpace have emerged...... institutions have a growing interest in accessing this personal data. Here, contributors explore this changing landscape by addressing topics such as commercial data collection by advertising, consumer sites and interactive media; self-disclosure in the social web; surveillance of file-sharers; privacy...... in the age of the internet; civil watch-surveillance on social networking sites; and networked interactive surveillance in transnational space. This book is a result of a research action launched by the intergovernmental network COST (European Cooperation in Science and Technology)....

Text Classification and Distributional features techniques in Datamining and Warehousing

OpenAIRE

Bethu, Srikanth; Babu, G Charless; Vinoda, J; Priyadarshini, E; rao, M Raghavendra

2013-01-01

Text Categorization is traditionally done by using the term frequency and inverse document frequency.This type of method is not very good because, some words which are not so important may appear in the document .The term frequency of unimportant words may increase and document may be classified in the wrong category.For reducing the error of classifying of documents in wrong category. The Distributional features are introduced. In the Distribuional Features, the Distribution of the words in ...

Classifying Coding DNA with Nucleotide Statistics

Directory of Open Access Journals (Sweden)

Nicolas Carels

2009-10-01

Full Text Available In this report, we compared the success rate of classification of coding sequences (CDS vs. introns by Codon Structure Factor (CSF and by a method that we called Universal Feature Method (UFM. UFM is based on the scoring of purine bias (Rrr and stop codon frequency. We show that the success rate of CDS/intron classification by UFM is higher than by CSF. UFM classifies ORFs as coding or non-coding through a score based on (i the stop codon distribution, (ii the product of purine probabilities in the three positions of nucleotide triplets, (iii the product of Cytosine (C, Guanine (G, and Adenine (A probabilities in the 1st, 2nd, and 3rd positions of triplets, respectively, (iv the probabilities of G in 1st and 2nd position of triplets and (v the distance of their GC3 vs. GC2 levels to the regression line of the universal correlation. More than 80% of CDSs (true positives of Homo sapiens (>250 bp, Drosophila melanogaster (>250 bp and Arabidopsis thaliana (>200 bp are successfully classified with a false positive rate lower or equal to 5%. The method releases coding sequences in their coding strand and coding frame, which allows their automatic translation into protein sequences with 95% confidence. The method is a natural consequence of the compositional bias of nucleotides in coding sequences.

A systematic comparison of supervised classifiers.

Directory of Open Access Journals (Sweden)

Diego Raphael Amancio

Full Text Available Pattern recognition has been employed in a myriad of industrial, commercial and academic applications. Many techniques have been devised to tackle such a diversity of applications. Despite the long tradition of pattern recognition research, there is no technique that yields the best classification in all scenarios. Therefore, as many techniques as possible should be considered in high accuracy applications. Typical related works either focus on the performance of a given algorithm or compare various classification methods. In many occasions, however, researchers who are not experts in the field of machine learning have to deal with practical classification tasks without an in-depth knowledge about the underlying parameters. Actually, the adequate choice of classifiers and parameters in such practical circumstances constitutes a long-standing problem and is one of the subjects of the current paper. We carried out a performance study of nine well-known classifiers implemented in the Weka framework and compared the influence of the parameter configurations on the accuracy. The default configuration of parameters in Weka was found to provide near optimal performance for most cases, not including methods such as the support vector machine (SVM. In addition, the k-nearest neighbor method frequently allowed the best accuracy. In certain conditions, it was possible to improve the quality of SVM by more than 20% with respect to their default parameter configuration.

National Cardiac Device Surveillance Program Database

Data.gov (United States)

Department of Veterans Affairs — The National Cardiac Device Surveillance Program Database supports the Eastern Pacemaker Surveillance Center (EPSC) staff in its function of monitoring some 11,000...

Preferential sampling in veterinary parasitological surveillance

Directory of Open Access Journals (Sweden)

Lorenzo Cecconi

2016-04-01

Full Text Available In parasitological surveillance of livestock, prevalence surveys are conducted on a sample of farms using several sampling designs. For example, opportunistic surveys or informative sampling designs are very common. Preferential sampling refers to any situation in which the spatial process and the sampling locations are not independent. Most examples of preferential sampling in the spatial statistics literature are in environmental statistics with focus on pollutant monitors, and it has been shown that, if preferential sampling is present and is not accounted for in the statistical modelling and data analysis, statistical inference can be misleading. In this paper, working in the context of veterinary parasitology, we propose and use geostatistical models to predict the continuous and spatially-varying risk of a parasite infection. Specifically, breaking with the common practice in veterinary parasitological surveillance to ignore preferential sampling even though informative or opportunistic samples are very common, we specify a two-stage hierarchical Bayesian model that adjusts for preferential sampling and we apply it to data on Fasciola hepatica infection in sheep farms in Campania region (Southern Italy in the years 2013-2014.

Collecting syndromic surveillance data by mobile phone in rural India: implementation and feasibility

Directory of Open Access Journals (Sweden)

Vishal Diwan

2015-04-01

Full Text Available Background: Infectious disease surveillance has long been a challenge for countries like India, where 75% of the health care services are private and consist of both formal and informal health care providers. Infectious disease surveillance data are regularly collected from governmental and qualified private facilities, but not from the informal sector. This study describes a mobile-based syndromic surveillance system and its application in a resource-limited setting, collecting data on patients’ symptoms from formal and informal health care providers. Design: The study includes three formal and six informal health care providers from two districts of Madhya Pradesh, India. Data collectors were posted in the clinics during the providers’ working hours and entered patient information and infectious disease symptoms on the mobile-based syndromic surveillance system. Results: Information on 20,424 patients was collected in the mobile-based surveillance system. The five most common (overlapping symptoms were fever (48%, cough (38%, body ache (38%, headache (37%, and runny nose (22%. During the same time period, the government's disease surveillance program reported around 22,000 fever cases in one district as a whole. Our data – from a very small fraction of all health care providers – thus highlight an enormous underreporting in the official surveillance data, which we estimate here to capture less than 1% of the fever cases. Additionally, we found that patients from more than 600 villages visited the nine providers included in our study. Conclusions: The study demonstrated that a mobile-based system can be used for disease surveillance from formal and informal providers in resource-limited settings. People who have not used smartphones or even computers previously can, in a short timeframe, be trained to fill out surveillance forms and submit them from the device. Technology, including network connections, works sufficiently for disease

The value of information: Current challenges in surveillance implementation.

Science.gov (United States)

Stärk, Katharina D C; Häsler, Barbara

2015-11-01

Animal health surveillance is a complex activity that involves multiple stakeholders and provides decision support across sectors. Despite progress in the design of surveillance systems, some technical challenges remain, specifically for emerging hazards. Surveillance can also be impacted by political interests and costly consequences of case reporting, particularly in relation to international trade. Constraints on surveillance can therefore be of technical, economic and political nature. From an economic perspective, both surveillance and intervention are resource-using activities that are part of a mitigation strategy. Surveillance provides information for intervention decisions and thereby helps to offset negative effects of animal disease and to reduce the decision uncertainty associated with choices on disease control. It thus creates monetary and non-monetary benefits, both of which may be challenging to quantify. The technical relationships between surveillance, intervention and loss avoidance have not been established for most hazards despite being important consideration for investment decisions. Therefore, surveillance cannot just be maximised to minimise intervention costs. Economic appraisals of surveillance need to be done on a case by case basis for any hazard considering both surveillance and intervention performance, the losses avoided and the values attached to them. This can be achieved by using an evaluation approach which provides a systematic investigation of the worth or merit of surveillance activities. Evaluation is driven by a specific evaluation question which for surveillance systems commonly considers effectiveness, efficiency, implementation and/or compliance issues. More work is needed to provide guidance on the appropriate selection of evaluation attributes and general good practice in surveillance evaluation. Due to technical challenges, economic constraints and variable levels of capacity, the implementation of surveillance systems

Rationale for and protocol of a multi-national population-based bacteremia surveillance collaborative

Directory of Open Access Journals (Sweden)

Church Deirdre L

2009-07-01

Full Text Available Abstract Background Bloodstream infections are frequent causes of human illness and cause major morbidity and death. In order to best define the epidemiology of these infections and to track changes in occurrence, adverse outcome, and resistance rates over time, population based methodologies are optimal. However, few population-based surveillance systems exist worldwide, and because of differences in methodology inter-regional comparisons are limited. In this report we describe the rationale and propose first practical steps for developing an international collaborative approach to the epidemiologic study and surveillance for bacteremia. Findings The founding collaborative participants represent six regions in four countries in three continents with a combined annual surveillance population of more than 8 million residents. Conclusion Future studies from this collaborative should lead to a better understanding of the epidemiology of bloodstream infections.

Using a data fusion-based activity recognition framework to determine surveillance system requirements

CSIR Research Space (South Africa)

Le Roux, WH

2007-07-01

Full Text Available A technique is proposed to extract system requirements for a maritime area surveillance system, based on an activity recognition framework originally intended for the characterisation, prediction and recognition of intentional actions for threat...

2012 Sexually Transmitted Diseases Surveillance

Science.gov (United States)

... Data Appendix Tables A1 - A4 STD Surveillance Case Definitions Contributors Related Links STD Home STD Data & Statistics NCHHSTP Atlas Interactive STD Data - 1996-2013 STD Health Equity HIV/AIDS Surveillance & Statistics Follow STD STD on Twitter STD on Facebook File Formats Help: How do I view different ...

Weighing in on Surveillance: Perception of the Impact of Surveillance on Female Ballet Dancers' Health

Science.gov (United States)

Dryburgh, Anne; Fortin, Sylvie

2010-01-01

The aim of this qualitative study was to investigate professional ballet dancers' perceptions of the impact of surveillance on their psychological and physical health. The theoretical framework was inspired by Foucault's writing, particularly his concepts of surveillance, power, discipline and docile bodies. Fifteen professional ballet dancers…

36 CFR 1256.46 - National security-classified information.

Science.gov (United States)

2010-07-01

... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false National security-classified... Restrictions § 1256.46 National security-classified information. In accordance with 5 U.S.C. 552(b)(1), NARA... properly classified under the provisions of the pertinent Executive Order on Classified National Security...

Class-specific Error Bounds for Ensemble Classifiers

Energy Technology Data Exchange (ETDEWEB)

Prenger, R; Lemmond, T; Varshney, K; Chen, B; Hanley, W

2009-10-06

The generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. This bound suggests that increasing the strength and/or decreasing the correlation of an ensemble's base classifiers may yield improved performance under the assumption of equal error costs. However, this and other existing bounds do not directly address application spaces in which error costs are inherently unequal. For applications involving binary classification, Receiver Operating Characteristic (ROC) curves, performance curves that explicitly trade off false alarms and missed detections, are often utilized to support decision making. To address performance optimization in this context, we have developed a lower bound for the entire ROC curve that can be expressed in terms of the class-specific strength and correlation of the base classifiers. We present empirical analyses demonstrating the efficacy of these bounds in predicting relative classifier performance. In addition, we specify performance regions of the ROC curve that are naturally delineated by the class-specific strengths of the base classifiers and show that each of these regions can be associated with a unique set of guidelines for performance optimization of binary classifiers within unequal error cost regimes.

Surveillance of WWER-440 fuel performance

International Nuclear Information System (INIS)

Simko, J.; Urban, P.

1999-01-01

In this lecture next problems of surveillance of WWER-440 fuel performance are presented: surveillance of WWER-440 fuel performance at Mochovce NPP; basic data of WWER-440 reactor; in-core reactor measuring system 'SVRK'; basic level of SVRK; information output of basic level of SVRK; surveillance of fuel performance; table of permissible operation conditions of the reactor; limitation of the unit 1 power at the beginning of the operation; cyclic changes of power; future perspectives

Deconvolution When Classifying Noisy Data Involving Transformations

KAUST Repository

Carroll, Raymond

2012-09-01

In the present study, we consider the problem of classifying spatial data distorted by a linear transformation or convolution and contaminated by additive random noise. In this setting, we show that classifier performance can be improved if we carefully invert the data before the classifier is applied. However, the inverse transformation is not constructed so as to recover the original signal, and in fact, we show that taking the latter approach is generally inadvisable. We introduce a fully data-driven procedure based on cross-validation, and use several classifiers to illustrate numerical properties of our approach. Theoretical arguments are given in support of our claims. Our procedure is applied to data generated by light detection and ranging (Lidar) technology, where we improve on earlier approaches to classifying aerosols. This article has supplementary materials online.

Deconvolution When Classifying Noisy Data Involving Transformations.

Science.gov (United States)

Carroll, Raymond; Delaigle, Aurore; Hall, Peter

2012-09-01

In the present study, we consider the problem of classifying spatial data distorted by a linear transformation or convolution and contaminated by additive random noise. In this setting, we show that classifier performance can be improved if we carefully invert the data before the classifier is applied. However, the inverse transformation is not constructed so as to recover the original signal, and in fact, we show that taking the latter approach is generally inadvisable. We introduce a fully data-driven procedure based on cross-validation, and use several classifiers to illustrate numerical properties of our approach. Theoretical arguments are given in support of our claims. Our procedure is applied to data generated by light detection and ranging (Lidar) technology, where we improve on earlier approaches to classifying aerosols. This article has supplementary materials online.

Just-in-time classifiers for recurrent concepts.

Science.gov (United States)

Alippi, Cesare; Boracchi, Giacomo; Roveri, Manuel

2013-04-01

Just-in-time (JIT) classifiers operate in evolving environments by classifying instances and reacting to concept drift. In stationary conditions, a JIT classifier improves its accuracy over time by exploiting additional supervised information coming from the field. In nonstationary conditions, however, the classifier reacts as soon as concept drift is detected; the current classification setup is discarded and a suitable one activated to keep the accuracy high. We present a novel generation of JIT classifiers able to deal with recurrent concept drift by means of a practical formalization of the concept representation and the definition of a set of operators working on such representations. The concept-drift detection activity, which is crucial in promptly reacting to changes exactly when needed, is advanced by considering change-detection tests monitoring both inputs and classes distributions.

Deconvolution When Classifying Noisy Data Involving Transformations

KAUST Repository

Carroll, Raymond; Delaigle, Aurore; Hall, Peter

2012-01-01

In the present study, we consider the problem of classifying spatial data distorted by a linear transformation or convolution and contaminated by additive random noise. In this setting, we show that classifier performance can be improved if we carefully invert the data before the classifier is applied. However, the inverse transformation is not constructed so as to recover the original signal, and in fact, we show that taking the latter approach is generally inadvisable. We introduce a fully data-driven procedure based on cross-validation, and use several classifiers to illustrate numerical properties of our approach. Theoretical arguments are given in support of our claims. Our procedure is applied to data generated by light detection and ranging (Lidar) technology, where we improve on earlier approaches to classifying aerosols. This article has supplementary materials online.

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African Journals Online (AJOL)

Adopting a surveillance system for antibacterial use has therefore become a more realistic ..... Financial support was obtained from the African Poverty Related Infection ... classification and Defined Daily Dose system methodology in Canada.

Comparative assessment of passive surveillance in disease-free and endemic situation: Example of Brucella melitensis surveillance in Switzerland and in Bosnia and Herzegovina

Directory of Open Access Journals (Sweden)

Haracic Sabina

2008-12-01

Full Text Available Abstract Background Globalization and subsequent growth in international trade in animals and animal products has increased the importance of international disease reporting. Efficient and reliable surveillance systems are needed in order to document the disease status of a population at a given time. In this context, passive surveillance plays an important role in early warning systems. However, it is not yet routinely integrated in the assessment of disease surveillance systems because different factors like the disease awareness (DA of people reporting suspect cases influence the detection performance of passive surveillance. In this paper, we used scenario tree methodology in order to evaluate and compare the quality and benefit of abortion testing (ABT for Brucella melitensis (Bm between the disease free situation in Switzerland (CH and a hypothetical disease free situation in Bosnia and Herzegovina (BH, taking into account DA levels assumed for the current endemic situation in BH. Results The structure and input parameters of the scenario tree were identical for CH and BH with the exception of population data in small ruminants and the DA in farmers and veterinarians. The sensitivity analysis of the stochastic scenario tree model showed that the small ruminant population structure and the DA of farmers were important influential parameters with regard to the unit sensitivity of ABT in both CH and BH. The DA of both farmers and veterinarians was assumed to be higher in BH than in CH due to the current endemic situation in BH. Although the same DA cannot necessarily be assumed for the modelled hypothetical disease free situation as for the actual endemic situation, it shows the importance of the higher vigilance of people reporting suspect cases on the probability that an average unit processed in the ABT-component would test positive. Conclusion The actual sensitivity of passive surveillance approaches heavily depends on the context in

Patentna zaštita poverljivih pronalazaka / Patent protection of classified invention

Directory of Open Access Journals (Sweden)

Obrad T. Čabarkapa

2008-10-01

Full Text Available Svaki pronalazak za koji se utvrdi da je značajan za odbranu i bezbednost Republike Srbije smatra se poverljivim. Za patentnu zaštitu poverljivih pronalazaka podnosi se prijava organu nadležnom za poslove odbrane, koji ima isključivo pravo da raspolaže poverljivim pronalascima1. U organizacijskoj jedinici nadležnoj za poslove naučne i inovacione delatnosti2 realizuje postupak ispitivanja poverljivih prijava patenata. Da bi se donela ocena o poverljivosti prijavljenog pronalaska neophodno je realizovati određene faze u postupku ispitivanja prijave. Poverljivi pronalazak se ne objavljuje, a pronalazač, nakon priznavanja patenta, u skladu sa zakonskim propisima, ima određena moralna i materijalna prava. / Every invention established to be of significance for defense or security of the Republic of Serbia is considered to be a classified invention. For the purpose of patent protection of classified inventions, a confidential application must be submitted to a relevant defense authority having the exclusive right to deal with classified inventions3. An organizational unit competent for scientific and innovation issues carries out the examination of classified patent applications. In order to evaluate classification of the submitted invention, regarding its significance for defense or security of the country as well as to make the final decision on the application, the examination procedure should be carried out through several phases. A classified invention is not to be published and once the patent has been approved, the inventor enjoys moral and material rights in accordance with law.

Urine Telomerase for Diagnosis and Surveillance of Bladder Cancer

Directory of Open Access Journals (Sweden)

Angela Lamarca

2012-01-01

Full Text Available Bladder cancer has increased incidence during last decades. For those patients with nonmuscle involved tumors, noninvasive diagnosis test and surveillance methods must be designed to avoid current cystoscopies that nowadays are done regularly in a lot of patients. Novel urine biomarkers have been developed during last years. Telomerase is important in cancer biology, improving the division capacity of cancer cells. Even urinary telomerase could be a potentially useful urinary tumor marker; its use for diagnosis of asymptomatic and symptomatic patients or its impact during surveillance is still unknown. Moreover, there will need to be uniformity and standardization in the assays before it can become useful in clinical practice. It does not seem to exist a real difference between the most classical assays for the detection of urine telomerase (TRAP and hTERT. However, the new detection methods with modified TeloTAGGG telomerase or with gold nanoparticles must also be taken into consideration for the correct development of this diagnosis method. Maybe the target population would be the high-risk groups within screening programs. To date there is no enough evidence to use it alone and to eliminate cystoscopies from the diagnosis and surveillance of these patients. The combination with cytology or FISH is still preferred.

LOCALIZATION AND RECOGNITION OF DYNAMIC HAND GESTURES BASED ON HIERARCHY OF MANIFOLD CLASSIFIERS

Directory of Open Access Journals (Sweden)

M. Favorskaya

2015-05-01

Full Text Available Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case. Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset “Multi-modal Gesture Recognition Challenge 2013: Dataset and Results” including 393 dynamic hand-gestures was chosen. The proposed method yielded 84–91% recognition accuracy, in average, for restricted set of dynamic gestures.

Organization of surveillance in GI practice.

Science.gov (United States)

Senore, Carlo; Bellisario, Cristina; Hassan, Cesare

2016-12-01

Several reports documented an inefficient utilisation of available resources, as well as a suboptimal compliance with surveillance recommendations. Although, evidence suggests that organisational issues can influence the quality of care delivered, surveillance protocols are usually based on non-organized approaches. We conducted a literature search (publication date: 01/2000-06/2016) on PubMed and Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects and Cochrane Central Register of Controlled Trials for guidelines, or consensus statements, for surveys of practice, reporting information about patients, or providers attitudes and behaviours, for intervention studies to enhance compliance with guidelines. Related articles were also scrutinised. Based on the clinical relevance and burden on endoscopy services this review was focused on surveillance for Barrett's oesophagus, IBD and post-polypectomy surveillance of colonic adenomas. Existing guidelines are generally recognising structure and process requirements influencing delivery of surveillance interventions, while less attention had been devoted to transitions and interfaces in the care process. Available evidence from practice surveys is suggesting the need to design organizational strategies aimed to enable patients to attend and providers to deliver timely and appropriate care. Well designed studies assessing the effectiveness of specific interventions in this setting are however lacking. Indirect evidence from screening settings would suggest that the implementation of automated standardized recall systems, utilisation of clinical registries, removing financial barriers, could improve appropriateness of use and compliance with recommendations. Lack of sound evidence regarding utility and methodology of surveillance can contribute to explain the observed variability in providers and patients attitudes and in compliance with the recommended surveillance. Copyright © 2016 Elsevier

Study of operational conditions in medical radiodiagnostic services - ionizing radiation surveillance program in Sao Paulo State, Brazil

International Nuclear Information System (INIS)

Aldred, Marta Aurelia; Eduardo, Maria Bernardete de Paula; Carvalho, Marisa Lima

1996-01-01

A radiation surveillance program was created in Sao Paulo State (Brazil) in 1994 to identify the risks in health care services. A total number of 259 centres were visited and 411 radiodiagnostic rooms were inspected. During the survey an 'inspection form' of 32 items was filled in. Analysis of the answers classified 24% of services as high risk, 22% of rooms showed irregular installations, 25% of X-ray equipment presented problems and 22% of personnel used inadequate procedures. Additional and regular surveys were programmed for the services considered of high risk in order to reduce it

MAMMOGRAMS ANALYSIS USING SVM CLASSIFIER IN COMBINED TRANSFORMS DOMAIN

Directory of Open Access Journals (Sweden)

B.N. Prathibha

2011-02-01

Full Text Available Breast cancer is a primary cause of mortality and morbidity in women. Reports reveal that earlier the detection of abnormalities, better the improvement in survival. Digital mammograms are one of the most effective means for detecting possible breast anomalies at early stages. Digital mammograms supported with Computer Aided Diagnostic (CAD systems help the radiologists in taking reliable decisions. The proposed CAD system extracts wavelet features and spectral features for the better classification of mammograms. The Support Vector Machines classifier is used to analyze 206 mammogram images from Mias database pertaining to the severity of abnormality, i.e., benign and malign. The proposed system gives 93.14% accuracy for discrimination between normal-malign and 87.25% accuracy for normal-benign samples and 89.22% accuracy for benign-malign samples. The study reveals that features extracted in hybrid transform domain with SVM classifier proves to be a promising tool for analysis of mammograms.

CCTV Coverage Index Based on Surveillance Resolution and Its Evaluation Using 3D Spatial Analysis

Directory of Open Access Journals (Sweden)

Kyoungah Choi

2015-09-01

Full Text Available We propose a novel approach to evaluating how effectively a closed circuit television (CCTV system can monitor a targeted area. With 3D models of the target area and the camera parameters of the CCTV system, the approach produces surveillance coverage index, which is newly defined in this study as a quantitative measure for surveillance performance. This index indicates the proportion of the space being monitored with a sufficient resolution to the entire space of the target area. It is determined by computing surveillance resolution at every position and orientation, which indicates how closely a specific object can be monitored with a CCTV system. We present full mathematical derivation for the resolution, which depends on the location and orientation of the object as well as the geometric model of a camera. With the proposed approach, we quantitatively evaluated the surveillance coverage of a CCTV system in an underground parking area. Our evaluation process provided various quantitative-analysis results, compelling us to examine the design of the CCTV system prior to its installation and understand the surveillance capability of an existing CCTV system.

Crypto and empire: the contradictions of counter-surveillance advocacy

NARCIS (Netherlands)

Gürses, S.; Kundnani, A.; Van Hoboken, J.

2016-01-01

Since Edward Snowden’s revelations of US and UK surveillance programs, privacy advocates, progressive security engineers, and policy makers have been seeking to win majority support for countering surveillance. The problem is framed as the replacement of targeted surveillance with mass surveillance

Evaluating the use of cell phone messaging for community Ebola syndromic surveillance in high risked settings in Southern Sierra Leone.

Science.gov (United States)

Jia, Kangbai; Mohamed, Koroma

2015-09-01

Most underdeveloped countries do not meet core disease outbreak surveillance because of the lack of human resources, laboratory and infrastructural facilities. The use of cell phone technology for disease outbreak syndromic surveillance is a new phenomenon in Sierra Leone despite its successes in other developing countries like Sri Lanka. In this study we set to evaluate the effectiveness of using cell phone technology for Ebola hemorrhagic fever syndromic surveillance in a high risked community in Sierra Leone. This study evaluated the effectiveness of using cell phone messaging (text and calls) for community Ebola hemorrhagic fever syndromic surveillance in high risked community in southern Sierra Leone. All cell phone syndromic surveillance data used for this study was reported as cell phone alert messages-texts and voice calls; by the Moyamba District Health Management Team for both Ebola hemorrhagic fever suspect and mortalities. We conducted a longitudinal data analysis of the monthly cumulative confirmed Ebola hemorrhagic fever cases and mortalities collected by both the traditional sentinel and community cell phone syndromic surveillance from August 2014 to October 2014. A total of 129 and 49 Ebola hemorrhagic fever suspect and confirmed cases respectively were recorded using the community Ebola syndromic surveillance cell phone alert system by the Moyamba District Health Management Team in October 2014. The average number of Ebola hemorrhagic fever suspects and confirmed cases for October 2014 were 4.16 (Std.dev 3.76) and 1.58 (Std.dev 1.43) respectively. Thirty-four percent (n=76) of the community Ebola syndromic surveillance cell phone alerts that were followed-up within 24 hours reported Ebola hemorrhagic fever suspect cases while 65.92% (n=147) reported mortality. Our study suggests some form of underreporting by the traditional sentinel Ebola hemorrhagic fever disease surveillance system in Moyamba District southern Sierra Leone for August

Ultrasound surveillance for radiation-induced thyroid carcinoma in adult survivors of childhood cancer.

Science.gov (United States)

Brignardello, Enrico; Felicetti, Francesco; Castiglione, Anna; Gallo, Marco; Maletta, Francesca; Isolato, Giuseppe; Biasin, Eleonora; Fagioli, Franca; Corrias, Andrea; Palestini, Nicola

2016-03-01

The optimal surveillance strategy to screen for thyroid carcinoma childhood cancer survivors (CCS) at increased risk is still debated. In our clinical practice, beside neck palpation we routinely perform thyroid ultrasound (US). Here we describe the results obtained using this approach. We considered all CCS referred to our long term clinic from November 2001 to September 2014. One hundred and ninety-seven patients who had received radiation therapy involving the thyroid gland underwent US surveillance. Thyroid US started 5 years after radiotherapy and repeated every 3 years, if negative. Among 197 CCS previously irradiated to the thyroid gland, 74 patients (37.5%) developed thyroid nodules, and fine-needle aspiration was performed in 35. In 11 patients the cytological examination was suspicious or diagnostic for malignancy (TIR 4/5), whereas a follicular lesion was diagnosed in nine. Patients with TIR 4/5 cytology were operated and in all cases thyroid cancer diagnosis was confirmed. The nine patients with TIR 3 cytology also underwent surgery and a carcinoma was diagnosed in three of them. Prevalence of thyroid cancer was 7.1%. Tumour size ranged between 4 and 25 mm, but six (43%) were classified T3 because of extra-thyroidal extension. Six patients had nodal metastases; in eight patients the tumour was multifocal. At the time of the study all patients are disease free, without evidence of surgery complications. Applying our US surveillance protocol, the prevalence of radiation-induced thyroid cancer is high. Histological features of the thyroid cancers diagnosed in our cohort suggest that most of them were clinically relevant tumours. Copyright © 2015 Elsevier Ltd. All rights reserved.

Autoregressive Integrated Adaptive Neural Networks Classifier for EEG-P300 Classification

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Demi Soetraprawata

2013-06-01

Full Text Available Brain Computer Interface has a potency to be applied in mechatronics apparatus and vehicles in the future. Compared to the other techniques, EEG is the most preferred for BCI designs. In this paper, a new adaptive neural network classifier of different mental activities from EEG-based P300 signals is proposed. To overcome the over-training that is caused by noisy and non-stationary data, the EEG signals are filtered and extracted using autoregressive models before passed to the adaptive neural networks classifier. To test the improvement in the EEG classification performance with the proposed method, comparative experiments were conducted using Bayesian Linear Discriminant Analysis. The experiment results show that the all subjects achieve a classification accuracy of 100%.

WEB-BASED ADAPTIVE TESTING SYSTEM (WATS FOR CLASSIFYING STUDENTS ACADEMIC ABILITY

Directory of Open Access Journals (Sweden)

Jaemu LEE,

2012-08-01

Full Text Available Computer Adaptive Testing (CAT has been highlighted as a promising assessment method to fulfill two testing purposes: estimating student academic ability and classifying student academic level. In this paper, we introduced the Web-based Adaptive Testing System (WATS developed to support a cost effective assessment for classifying students’ ability into different academic levels. Instead of using a traditional paper and pencil test, the WATS is expected to serve as an alternate method to promptly diagnosis and identify underachieving students through Web-based testing. The WATS can also help provide students with appropriate learning contents and necessary academic support in time. In this paper, theoretical background and structure of WATS, item construction process based upon item response theory, and user interfaces of WATS were discussed.

EVALUATING A COMPUTER BASED SKILLS ACQUISITION TRAINER TO CLASSIFY BADMINTON PLAYERS

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Minh Vu Huynh

2011-09-01

Full Text Available The aim of the present study was to compare the statistical ability of both neural networks and discriminant function analysis on the newly developed SATB program. Using these statistical tools, we identified the accuracy of the SATB in classifying badminton players into different skill level groups. Forty-one participants, classified as advanced, intermediate, or beginner skilled level, participated in this study. Results indicated neural networks are more effective in predicting group membership, and displayed higher predictive validity when compared to discriminant analysis. Using these outcomes, in conjunction with the physiological and biomechanical variables of the participants, we assessed the authenticity and accuracy of the SATB and commented on the overall effectiveness of the visual based training approach to training badminton athletes

Comparing classifiers for pronunciation error detection

NARCIS (Netherlands)

Strik, H.; Truong, K.; Wet, F. de; Cucchiarini, C.

2007-01-01

Providing feedback on pronunciation errors in computer assisted language learning systems requires that pronunciation errors be detected automatically. In the present study we compare four types of classifiers that can be used for this purpose: two acoustic-phonetic classifiers (one of which employs

Classifier Fusion With Contextual Reliability Evaluation.

Science.gov (United States)

Liu, Zhunga; Pan, Quan; Dezert, Jean; Han, Jun-Wei; He, You

2018-05-01

Classifier fusion is an efficient strategy to improve the classification performance for the complex pattern recognition problem. In practice, the multiple classifiers to combine can have different reliabilities and the proper reliability evaluation plays an important role in the fusion process for getting the best classification performance. We propose a new method for classifier fusion with contextual reliability evaluation (CF-CRE) based on inner reliability and relative reliability concepts. The inner reliability, represented by a matrix, characterizes the probability of the object belonging to one class when it is classified to another class. The elements of this matrix are estimated from the -nearest neighbors of the object. A cautious discounting rule is developed under belief functions framework to revise the classification result according to the inner reliability. The relative reliability is evaluated based on a new incompatibility measure which allows to reduce the level of conflict between the classifiers by applying the classical evidence discounting rule to each classifier before their combination. The inner reliability and relative reliability capture different aspects of the classification reliability. The discounted classification results are combined with Dempster-Shafer's rule for the final class decision making support. The performance of CF-CRE have been evaluated and compared with those of main classical fusion methods using real data sets. The experimental results show that CF-CRE can produce substantially higher accuracy than other fusion methods in general. Moreover, CF-CRE is robust to the changes of the number of nearest neighbors chosen for estimating the reliability matrix, which is appealing for the applications.

Hierarchical mixtures of naive Bayes classifiers

NARCIS (Netherlands)

Wiering, M.A.

2002-01-01

Naive Bayes classifiers tend to perform very well on a large number of problem domains, although their representation power is quite limited compared to more sophisticated machine learning algorithms. In this pa- per we study combining multiple naive Bayes classifiers by using the hierar- chical

Surveillance Pleasures

DEFF Research Database (Denmark)

Albrechtslund, Anders

The notorious intensification and digitalization of surveillance technologies and practices in today’s society has brought about numerous changes. These changes have been widely noticed, described and discussed across many academic disciplines. However, the contexts of entertainment, play...

Sistemas de vigilancia de la salud pública: no pidamos peras al olmo Public health surveillance systems: let's not ask for the impossible

Directory of Open Access Journals (Sweden)

S. de Mateo

2003-07-01

Full Text Available La publicación del Decreto por el que se creó la Red Nacional de Vigilancia Epidemiológica, hace ya siete años, da pie para reflexionar sobre los sistemas de vigilancia de la salud pública en nuestro país e incidir en aquellos aspectos que facilitan o impiden que estos sistemas cumplan con su objetivo fundamental de proporcionar una información que sirva para facilitar el control de las enfermedades. Muchas de las situaciones vividas en el ámbito de la salud en estos últimos años, calificadas de «crisis sanitarias» por los medios de comunicación, han sido consideradas como riesgos inaceptables por la población, que los sistemas sanitarios deberían haber evitado y, entre los fallos evidenciados, siempre se alude a defectos de los sistemas de vigilancia. Algunos de estos defectos provienen de las propias limitaciones de los instrumentos utilizados para la medición y clasificación de los problemas de salud, pero también existen otros derivados de una concepción no adecuada de la vigilancia y que impiden valorar el verdadero impacto de los problemas de salud. Comentar unos y otros no solucionará los problemas de la vigilancia, pero sí puede servir para que muchas personas no sigan pidiendo a nuestros sistemas de vigilancia aquello que no pueden ofrecer.The publication of the Decree creating the National Epidemiological Surveillance Network, 7 years ago now, invites us to reflect on public health surveillance systems in our country and to highlight those aspects that help or obstruct these systems in meeting their basic objective of providing information that can be used to facilitate disease control. Many of the events that have taken place in the health arena in recent years, labeled as «health crises» by the communications media, have been considered by the population as unacceptable risks that the health system should have avoided; defects in surveillance systems are one of the errors always mentioned in this respect. Some

Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data.

Science.gov (United States)

Kagashe, Ireneus; Yan, Zhijun; Suheryani, Imran

2017-09-12

Uptake of medicinal drugs (preventive or treatment) is among the approaches used to control disease outbreaks, and therefore, it is of vital importance to be aware of the counts or frequencies of most commonly used drugs and trending topics about these drugs from consumers for successful implementation of control measures. Traditional survey methods would have accomplished this study, but they are too costly in terms of resources needed, and they are subject to social desirability bias for topics discovery. Hence, there is a need to use alternative efficient means such as Twitter data and machine learning (ML) techniques. Using Twitter data, the aim of the study was to (1) provide a methodological extension for efficiently extracting widely consumed drugs during seasonal influenza and (2) extract topics from the tweets of these drugs and to infer how the insights provided by these topics can enhance seasonal influenza surveillance. From tweets collected during the 2012-13 flu season, we first identified tweets with mentions of drugs and then constructed an ML classifier using dependency words as features. The classifier was used to extract tweets that evidenced consumption of drugs, out of which we identified the mostly consumed drugs. Finally, we extracted trending topics from each of these widely used drugs' tweets using latent Dirichlet allocation (LDA). Our proposed classifier obtained an F 1 score of 0.82, which significantly outperformed the two benchmark classifiers (ie, Pstrategies for mitigating the severity of seasonal influenza outbreaks. The proposed methods can be extended to the outbreaks of other diseases. ©Ireneus Kagashe, Zhijun Yan, Imran Suheryani. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 12.09.2017.

Vector Borne Infections in Italy: Results of the Integrated Surveillance System for West Nile Disease in 2013

Directory of Open Access Journals (Sweden)

Christian Napoli

2015-01-01

Full Text Available The epidemiology of West Nile disease (WND is influenced by multiple ecological factors and, therefore, integrated surveillance systems are needed for early detecting the infection and activating consequent control actions. As different animal species have different importance in the maintenance and in the spread of the infection, a multispecies surveillance approach is required. An integrated and comprehensive surveillance system is in place in Italy aiming at early detecting the virus introduction, monitoring the possible infection spread, and implementing preventive measures for human health. This paper describes the integrated surveillance system for WND in Italy, which incorporates data from veterinary and human side in order to evaluate the burden of infection in animals and humans and provide the public health authorities at regional and national levels with the information needed for a fine tune response.

A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks

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Tao Geng

2008-01-01

Full Text Available A novel 4-class single-trial brain computer interface (BCI based on two (rather than four or more binary linear discriminant analysis (LDA classifiers is proposed, which is called a “parallel BCI.” Unlike other BCIs where mental tasks are executed and classified in a serial way one after another, the parallel BCI uses properly designed parallel mental tasks that are executed on both sides of the subject body simultaneously, which is the main novelty of the BCI paradigm used in our experiments. Each of the two binary classifiers only classifies the mental tasks executed on one side of the subject body, and the results of the two binary classifiers are combined to give the result of the 4-class BCI. Data was recorded in experiments with both real movement and motor imagery in 3 able-bodied subjects. Artifacts were not detected or removed. Offline analysis has shown that, in some subjects, the parallel BCI can generate a higher accuracy than a conventional 4-class BCI, although both of them have used the same feature selection and classification algorithms.

Automated real time constant-specificity surveillance for disease outbreaks

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Brownstein John S

2007-06-01

Full Text Available Abstract Background For real time surveillance, detection of abnormal disease patterns is based on a difference between patterns observed, and those predicted by models of historical data. The usefulness of outbreak detection strategies depends on their specificity; the false alarm rate affects the interpretation of alarms. Results We evaluate the specificity of five traditional models: autoregressive, Serfling, trimmed seasonal, wavelet-based, and generalized linear. We apply each to 12 years of emergency department visits for respiratory infection syndromes at a pediatric hospital, finding that the specificity of the five models was almost always a non-constant function of the day of the week, month, and year of the study (p Conclusion Modeling the variance of visit patterns enables real-time detection with known, constant specificity at all times. With constant specificity, public health practitioners can better interpret the alarms and better evaluate the cost-effectiveness of surveillance systems.

Novel Two-Step Classifier for Torsades de Pointes Risk Stratification from Direct Features

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Jaimit Parikh

2017-11-01

Full Text Available While pre-clinical Torsades de Pointes (TdP risk classifiers had initially been based on drug-induced block of hERG potassium channels, it is now well established that improved risk prediction can be achieved by considering block of non-hERG ion channels. The current multi-channel TdP classifiers can be categorized into two classes. First, the classifiers that take as input the values of drug-induced block of ion channels (direct features. Second, the classifiers that are built on features extracted from output of the drug-induced multi-channel blockage simulations in the in-silico models (derived features. The classifiers built on derived features have thus far not consistently provided increased prediction accuracies, and hence casts doubt on the value of such approaches given the cost of including biophysical detail. Here, we propose a new two-step method for TdP risk classification, referred to as Multi-Channel Blockage at Early After Depolarization (MCB@EAD. In the first step, we classified the compound that produced insufficient hERG block as non-torsadogenic. In the second step, the role of non-hERG channels to modulate TdP risk are considered by constructing classifiers based on direct or derived features at critical hERG block concentrations that generates EADs in the computational cardiac cell models. MCB@EAD provides comparable or superior TdP risk classification of the drugs from the direct features in tests against published methods. TdP risk for the drugs highly correlated to the propensity to generate EADs in the model. However, the derived features of the biophysical models did not improve the predictive capability for TdP risk assessment.

Achievable Rate Estimation of IEEE 802.11ad Visual Big-Data Uplink Access in Cloud-Enabled Surveillance Applications.

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Joongheon Kim

Full Text Available This paper addresses the computation procedures for estimating the impact of interference in 60 GHz IEEE 802.11ad uplink access in order to construct visual big-data database from randomly deployed surveillance camera sensing devices. The acquired large-scale massive visual information from surveillance camera devices will be used for organizing big-data database, i.e., this estimation is essential for constructing centralized cloud-enabled surveillance database. This performance estimation study captures interference impacts on the target cloud access points from multiple interference components generated by the 60 GHz wireless transmissions from nearby surveillance camera devices to their associated cloud access points. With this uplink interference scenario, the interference impacts on the main wireless transmission from a target surveillance camera device to its associated target cloud access point with a number of settings are measured and estimated under the consideration of 60 GHz radiation characteristics and antenna radiation pattern models.

Environmental health surveillance system; Kankyo hoken surveillance system

Energy Technology Data Exchange (ETDEWEB)

Ono, M. [National Inst. for Environmental Studies, Tsukuba (Japan)

1998-02-01

The Central Environmental Pollution Prevention Council pointed out the necessity to establish an environmental health surveillance system (hereinafter referred to as System) in its report `on the first type district specified by the Environmental Pollution Caused Health Damages Compensation Act,` issued in 1986. A study team, established in Environment Agency, has been discussing to establish System since 1986. This paper outlines System, and some of the pilot surveillance results. It is not aimed at elucidation of the cause-effect relationships between health and air pollution but at discovery of problems, in which the above relationships in a district population are monitored periodically and continuously from long-term and prospective viewpoints, in order to help take necessary measures in the early stage. System is now collecting the data of the chronic obstructive lung diseases on a nation-wide scale through health examinations of 3-year-old and preschool children and daily air pollution monitoring. 6 refs., 3 figs., 1 tab.

Effective surveillance for homeland security balancing technology and social issues

CERN Document Server

Flammini, Francesco; Franceschetti, Giorgio

2013-01-01

Effective Surveillance for Homeland Security: Balancing Technology and Social Issues provides a comprehensive survey of state-of-the-art methods and tools for the surveillance and protection of citizens and critical infrastructures against natural and deliberate threats. Focusing on current technological challenges involving multi-disciplinary problem analysis and systems engineering approaches, it provides an overview of the most relevant aspects of surveillance systems in the framework of homeland security. Addressing both advanced surveillance technologies and the related socio-ethical issues, the book consists of 21 chapters written by international experts from the various sectors of homeland security. Part I, Surveillance and Society, focuses on the societal dimension of surveillance-stressing the importance of societal acceptability as a precondition to any surveillance system. Part II, Physical and Cyber Surveillance, presents advanced technologies for surveillance. It considers developing technologie...

Evaluation of community-based surveillance for Guinea worm, South ...

African Journals Online (AJOL)

2012-08-03

Aug 3, 2012 ... deleted at the Data Manager Level in Loki. Conclusion. Community-based surveillance for guinea worm is a good example of a surveillance system on which an integrated disease surveillance system can be based in countries with poor surveillance like South Sudan. This makes its potential value to ...

Surveillance of Rift Valley Fever in Iran between 2001 and 2011

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Sadegh CHINIKAR

2013-06-01

Full Text Available Rift Valley fever virus (RVFV is an acute zoonotic viral disease that mostly affects ruminants with an occasional spillover as human infection. Following the outbreak of RVF in Saudi Arabia in 2000, surveillance of both animal and human population in Iran increased until 2011. During this period 1206 ovine, 405 caprine, 325 bovine and 28 camel samples were tested for RVFV in nine provinces in Iran. None of these samples tested IgG positive. Moreover, amongst 37 clinically suspected human cases of patients with RVF symptoms, none of these samples tested positive for RVFV. Despite the fact that no positive cases in human or animal populations were identified in Iran, surveillance and monitoring of viral haemorrhagic fevers including RVFV will continue.

Surveillance of Rift Valley Fever in Iran between 2001 and 2011

Directory of Open Access Journals (Sweden)

Sadegh CHINIKAR

2013-04-01

Full Text Available Rift Valley fever virus (RVFV is an acute zoonotic viral disease that mostly affects ruminants with an occasional spillover as human infection. Following the outbreak of RVF in Saudi Arabia in 2000, surveillance of both animal and human population in Iran increased until 2011. During this period 1206 ovine, 405 caprine, 325 bovine and 28 camel samples were tested for RVFV in nine provinces in Iran. None of these samples tested IgG positive. Moreover, amongst 37 clinically suspected human cases of patients with RVF symptoms, none of these samples tested positive for RVFV. Despite the fact that no positive cases in human or animal populations were identified in Iran, surveillance and monitoring of viral haemorrhagic fevers including RVFV will continue.

3013/9975 Surveillance Program Interim Summary Report

Energy Technology Data Exchange (ETDEWEB)

Dunn, K.; Hackney, B.; McClard, J.

2011-06-22

The K-Area Materials Storage (KAMS) Documented Safety Analysis (DSA) requires a surveillance program to monitor the safety performance of 3013 containers and 9975 shipping packages stored in KAMS. The SRS surveillance program [Reference 1] outlines activities for field surveillance and laboratory tests that demonstrate the packages meet the functional performance requirements described in the DSA. The SRS program also supports the complexwide Integrated Surveillance Program (ISP) [Reference 2] for 3013 containers. The purpose of this report is to provide a summary of the SRS portion of the surveillance program activities through fiscal year 2010 (FY10) and formally communicate the interpretation of these results by the Surveillance Program Authority (SPA). Surveillance for the initial 3013 container random sampling of the Innocuous bin and the Pressure bin has been completed and there has been no indication of corrosion or significant pressurization. The maximum pressure observed was less than 50 psig, which is well below the design pressure of 699 psig for the 3013 container [Reference 3]. The data collected during surveillance of these bins has been evaluated by the Materials Identification and Surveillance (MIS) Working Group and no additional surveillance is necessary for these bins at least through FY13. A decision will be made whether additional surveillance of these bins is needed during future years of storage and as additional containers are generated. Based on the data collected to date, the SPA concludes that 3013 containers in these bins can continue to be safely stored in KAMS. This year, 13 destructive examinations (DE) were performed on random samples from the Pressure & Corrosion bin. To date, DE has been completed for approximately 30% of the random samples from the Pressure & Corrosion bin. In addition, DE has been performed on 6 engineering judgment (EJ) containers, for a total of 17 to date. This includes one container that exceeded the 3013

Logarithmic learning for generalized classifier neural network.

Science.gov (United States)

Ozyildirim, Buse Melis; Avci, Mutlu

2014-12-01

Generalized classifier neural network is introduced as an efficient classifier among the others. Unless the initial smoothing parameter value is close to the optimal one, generalized classifier neural network suffers from convergence problem and requires quite a long time to converge. In this work, to overcome this problem, a logarithmic learning approach is proposed. The proposed method uses logarithmic cost function instead of squared error. Minimization of this cost function reduces the number of iterations used for reaching the minima. The proposed method is tested on 15 different data sets and performance of logarithmic learning generalized classifier neural network is compared with that of standard one. Thanks to operation range of radial basis function included by generalized classifier neural network, proposed logarithmic approach and its derivative has continuous values. This makes it possible to adopt the advantage of logarithmic fast convergence by the proposed learning method. Due to fast convergence ability of logarithmic cost function, training time is maximally decreased to 99.2%. In addition to decrease in training time, classification performance may also be improved till 60%. According to the test results, while the proposed method provides a solution for time requirement problem of generalized classifier neural network, it may also improve the classification accuracy. The proposed method can be considered as an efficient way for reducing the time requirement problem of generalized classifier neural network. Copyright © 2014 Elsevier Ltd. All rights reserved.

Surveillance of wild birds for avian influenza virus.

Science.gov (United States)

Hoye, Bethany J; Munster, Vincent J; Nishiura, Hiroshi; Klaassen, Marcel; Fouchier, Ron A M

2010-12-01

Recent demand for increased understanding of avian influenza virus in its natural hosts, together with the development of high-throughput diagnostics, has heralded a new era in wildlife disease surveillance. However, survey design, sampling, and interpretation in the context of host populations still present major challenges. We critically reviewed current surveillance to distill a series of considerations pertinent to avian influenza virus surveillance in wild birds, including consideration of what, when, where, and how many to sample in the context of survey objectives. Recognizing that wildlife disease surveillance is logistically and financially constrained, we discuss pragmatic alternatives for achieving probability-based sampling schemes that capture this host-pathogen system. We recommend hypothesis-driven surveillance through standardized, local surveys that are, in turn, strategically compiled over broad geographic areas. Rethinking the use of existing surveillance infrastructure can thereby greatly enhance our global understanding of avian influenza and other zoonotic diseases.

Somatic surveillance: corporeal control through information networks

OpenAIRE

Monahan, Torin; Wall, Tyler

2007-01-01

Somatic surveillance is the increasingly invasive technological monitoring of and intervention into body functions. Within this type of surveillance regime, bodies are recast as nodes on vast information networks, enabling corporeal control through remote network commands, automated responses, or self-management practices. In this paper, we investigate three developments in somatic surveillance: nanotechnology systems for soldiers on the battlefield, commercial body-monitoring systems for hea...

The use of information and communication technologies for the purposes of surveilance in working organizations: The case of Serbia

Directory of Open Access Journals (Sweden)

Petrović Dalibor

2017-01-01

Full Text Available This paper deals with the use of information and communication technologies for the purposes of surveillance in working organizations in general and in Serbia as well. Until now, explosive development of information and communication technologies provided unprecedented possibilities for employee's surveillance. In line with that, fundamental questions that lie in the core of this paper are, firstly, in which way and extent new surveillance technologies empower employers as owners of the complete production process, and secondly, whether usage of new surveillance technologies will fulfill the long-lasting capitalists desire to make workforce a predictable component of the working process. Beside defining theoretical framework and analyzing different aspects of work surveillance, we have conducted an empirical research in the form of 15 in-depth interviews with people employed in different types of Serbian working organizations. The results of our research showed that surveillance practice is widespread in both international and domestic working organizations. What is even more surprising, the employees, with the exception of rare and sporadic resistant strategies, quite readily accept surveillance as a natural fact without any idea that their working and human rights have been violated.

Strengthening Injury Surveillance System in Iran

Directory of Open Access Journals (Sweden)

Motevalian Seyed Abbas

2012-02-01

Full Text Available 【Abstract】Objective: To strengthen the current Injury Surveillance System (IS System in order to better monitor injury conditions, improve protection ways and promote safety. Methods: At first we carried out a study to evaluate the frameworks of IS System in the developed countries. Then all the available documents from World Health Organization, Eastern Mediterranean Regional Organization, as well as Minister of Health and Medical Education concerning Iran were reviewed. Later a national stakeholder抯 consultation was held to collect opinions and views. A national workshop was also intended for provincial representatives from 41 universities to identify the barriers and limitations of the existing program and further to strengthen injury surveillance. Results: The evaluation of the current IS System revealed many problems, mainly presented as lack of accurate pre- and post-hospital death registry, need of precise injury data registry in outpatient medical centers, incomplete injury data registry in hospitals and lack of accuracy in definition of variables in injury registry. The five main characteristics of current IS System including flexibility, acceptability, simplicity, usefulness and timeliness were evaluated as moderate by experts. Conclusions: Major revisions must be considered in the current IS System in Iran. The following elements should be added to the questionnaire: identifier, manner of arrival to the hospital, situation of the injured patient, consumption of alcohol and opioids, other involved participants in the accident, intention, severity and site of injury, side effects of surgery and medication, as well as one month follow-up results. Data should be collected from 10% of all hospitals in Iran and analyzed every 3 months. Simultaneously data should be online to be retrieved by researches. Key words: Wounds and injuries; Population surveillance; Registries; Iran

Construction accident narrative classification: An evaluation of text mining techniques.

Science.gov (United States)

Goh, Yang Miang; Ubeynarayana, C U

2017-11-01

Learning from past accidents is fundamental to accident prevention. Thus, accident and near miss reporting are encouraged by organizations and regulators. However, for organizations managing large safety databases, the time taken to accurately classify accident and near miss narratives will be very significant. This study aims to evaluate the utility of various text mining classification techniques in classifying 1000 publicly available construction accident narratives obtained from the US OSHA website. The study evaluated six machine learning algorithms, including support vector machine (SVM), linear regression (LR), random forest (RF), k-nearest neighbor (KNN), decision tree (DT) and Naive Bayes (NB), and found that SVM produced the best performance in classifying the test set of 251 cases. Further experimentation with tokenization of the processed text and non-linear SVM were also conducted. In addition, a grid search was conducted on the hyperparameters of the SVM models. It was found that the best performing classifiers were linear SVM with unigram tokenization and radial basis function (RBF) SVM with uni-gram tokenization. In view of its relative simplicity, the linear SVM is recommended. Across the 11 labels of accident causes or types, the precision of the linear SVM ranged from 0.5 to 1, recall ranged from 0.36 to 0.9 and F1 score was between 0.45 and 0.92. The reasons for misclassification were discussed and suggestions on ways to improve the performance were provided. Copyright © 2017 Elsevier Ltd. All rights reserved.

Real-Time Surveillance of Infectious Diseases: Taiwan's Experience.

Science.gov (United States)

Jian, Shu-Wan; Chen, Chiu-Mei; Lee, Cheng-Yi; Liu, Ding-Ping

Integration of multiple surveillance systems advances early warning and supports better decision making during infectious disease events. Taiwan has a comprehensive network of laboratory, epidemiologic, and early warning surveillance systems with nationwide representation. Hospitals and clinical laboratories have deployed automatic reporting mechanisms since 2014 and have effectively improved timeliness of infectious disease and laboratory data reporting. In June 2016, the capacity of real-time surveillance in Taiwan was externally assessed and was found to have a demonstrated and sustainable capability. We describe Taiwan's disease surveillance system and use surveillance efforts for influenza and Zika virus as examples of surveillance capability. Timely and integrated influenza information showed a higher level and extended pattern of influenza activity during the 2015-16 season, which ensured prompt information dissemination and the coordination of response operations. Taiwan also has well-developed disease detection systems and was the first country to report imported cases of Zika virus from Miami Beach and Singapore. This illustrates a high level of awareness and willingness among health workers to report emerging infectious diseases, and highlights the robust and sensitive nature of Taiwan's surveillance system. These 2 examples demonstrate the flexibility of the surveillance systems in Taiwan to adapt to emerging infectious diseases and major communicable diseases. Through participation in the GHSA, Taiwan can more actively collaborate with national counterparts and use its expertise to strengthen global and regional surveillance capacity in the Asia Pacific and in Southeast Asia, in order to advance a world safe and secure from infectious disease.

A Modified FCM Classifier Constrained by Conditional Random Field Model for Remote Sensing Imagery

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WANG Shaoyu

2016-12-01

Full Text Available Remote sensing imagery has abundant spatial correlation information, but traditional pixel-based clustering algorithms don't take the spatial information into account, therefore the results are often not good. To this issue, a modified FCM classifier constrained by conditional random field model is proposed. Adjacent pixels' priori classified information will have a constraint on the classification of the center pixel, thus extracting spatial correlation information. Spectral information and spatial correlation information are considered at the same time when clustering based on second order conditional random field. What's more, the global optimal inference of pixel's classified posterior probability can be get using loopy belief propagation. The experiment shows that the proposed algorithm can effectively maintain the shape feature of the object, and the classification accuracy is higher than traditional algorithms.

DECISION TREE CLASSIFIERS FOR STAR/GALAXY SEPARATION

International Nuclear Information System (INIS)

Vasconcellos, E. C.; Ruiz, R. S. R.; De Carvalho, R. R.; Capelato, H. V.; Gal, R. R.; LaBarbera, F. L.; Frago Campos Velho, H.; Trevisan, M.

2011-01-01

We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 ≤ r ≤ 21 (85.2%) and r ≥ 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 ≤ r ≤ 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (>80%) while simultaneously achieving low contamination (∼2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 ≤ r ≤ 21.

Standardized rendering from IR surveillance motion imagery

Science.gov (United States)

Prokoski, F. J.

2014-06-01

Government agencies, including defense and law enforcement, increasingly make use of video from surveillance systems and camera phones owned by non-government entities.Making advanced and standardized motion imaging technology available to private and commercial users at cost-effective prices would benefit all parties. In particular, incorporating thermal infrared into commercial surveillance systems offers substantial benefits beyond night vision capability. Face rendering is a process to facilitate exploitation of thermal infrared surveillance imagery from the general area of a crime scene, to assist investigations with and without cooperating eyewitnesses. Face rendering automatically generates greyscale representations similar to police artist sketches for faces in surveillance imagery collected from proximate locations and times to a crime under investigation. Near-realtime generation of face renderings can provide law enforcement with an investigation tool to assess witness memory and credibility, and integrate reports from multiple eyewitnesses, Renderings can be quickly disseminated through social media to warn of a person who may pose an immediate threat, and to solicit the public's help in identifying possible suspects and witnesses. Renderings are pose-standardized so as to not divulge the presence and location of eyewitnesses and surveillance cameras. Incorporation of thermal infrared imaging into commercial surveillance systems will significantly improve system performance, and reduce manual review times, at an incremental cost that will continue to decrease. Benefits to criminal justice would include improved reliability of eyewitness testimony and improved accuracy of distinguishing among minority groups in eyewitness and surveillance identifications.

Challenges of implementing an Integrated Disease Surveillance and ...

African Journals Online (AJOL)

Tanzania adopted an Integrated Disease Surveillance and Response (IDSR) strategy in 1998 in order to strengthen its infectious disease surveillance system. During that time, the country had 5 separate surveillance systems to monitor infectious disease trends and disease control programmes. The systems included the ...

Mobile Phone-Based mHealth Approaches for Public Health Surveillance in Sub-Saharan Africa: A Systematic Review

Directory of Open Access Journals (Sweden)

Johanna Brinkel

2014-11-01

Full Text Available Whereas mobile phone-based surveillance has the potential to provide real-time validated data for disease clustering and prompt respond and investigation, little evidence is available on current practice in sub-Sahara Africa. The objective of this review was to examine mobile phone-based mHealth interventions for Public Health surveillance in the region. We conducted electronic search in MEDLINE, EMBASE, IEE Xplore, African Index Medicus (AIM, BioMed Central, PubMed Central (PMC, the Public Library of Science (PLoS and IRIS for publications used in the review. In all, a total of nine studies were included which focused on infectious disease surveillance of malaria (n = 3, tuberculosis (n = 1 and influenza-like illnesses (n = 1 as well as on non-infectious disease surveillance of child malnutrition (n = 2, maternal health (n = 1 and routine surveillance of various diseases and symptoms (n = 1. Our review revealed that mobile phone-based surveillance projects in the sub-Saharan African countries are on small scale, fragmented and not well documented. We conclude by advocating for a strong drive for more research in the applied field as well as a better reporting of lessons learned in order to create an epistemic community to help build a more evidence-based field of practice in mHealth surveillance in the region.

Evaluation of the cost-effectiveness of bovine brucellosis surveillance in a disease-free country using stochastic scenario tree modelling.

Directory of Open Access Journals (Sweden)

Viviane Hénaux

Full Text Available Surveillance systems of exotic infectious diseases aim to ensure transparency about the country-specific animal disease situation (i.e. demonstrate disease freedom and to identify any introductions. In a context of decreasing resources, evaluation of surveillance efficiency is essential to help stakeholders make relevant decisions about prioritization of measures and funding allocation. This study evaluated the efficiency (sensitivity related to cost of the French bovine brucellosis surveillance system using stochastic scenario tree models. Cattle herds were categorized into three risk groups based on the annual number of purchases, given that trading is considered as the main route of brucellosis introduction in cattle herds. The sensitivity in detecting the disease and the costs of the current surveillance system, which includes clinical (abortion surveillance, programmed serological testing and introduction controls, were compared to those of 19 alternative surveillance scenarios. Surveillance costs included veterinary fees and laboratory analyses. The sensitivity over a year of the current surveillance system was predicted to be 91±7% at a design prevalence of 0.01% for a total cost of 14.9±1.8 million €. Several alternative surveillance scenarios, based on clinical surveillance and random or risk-based serological screening in a sample (20% of the population, were predicted to be at least as sensitive but for a lower cost. Such changes would reduce whole surveillance costs by 20 to 61% annually, and the costs for farmers only would be decreased from about 12.0 million € presently to 5.3-9.0 million € (i.e. 25-56% decrease. Besides, fostering the evolution of the surveillance system in one of these directions would be in agreement with the European regulations and farmers perceptions on brucellosis risk and surveillance.

Classifying cognitive profiles using machine learning with privileged information in Mild Cognitive Impairment

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Hanin Hamdan Alahmadi

2016-11-01

Full Text Available Early diagnosis of dementia is critical for assessing disease progression and potential treatment. State-or-the-art machine learning techniques have been increasingly employed to take on this diagnostic task. In this study, we employed Generalised Matrix Learning Vector Quantization (GMLVQ classifiers to discriminate patients with Mild Cognitive Impairment (MCI from healthy controls based on their cognitive skills. Further, we adopted a ``Learning with privileged information'' approach to combine cognitive and fMRI data for the classification task. The resulting classifier operates solely on the cognitive data while it incorporates the fMRI data as privileged information (PI during training. This novel classifier is of practical use as the collection of brain imaging data is not always possible with patients and older participants.MCI patients and healthy age-matched controls were trained to extract structure from temporal sequences. We ask whether machine learning classifiers can be used to discriminate patients from controls based on the learning performance and whether differences between these groups relate to individual cognitive profiles. To this end, we tested participants in four cognitive tasks: working memory, cognitive inhibition, divided attention, and selective attention. We also collected fMRI data before and after training on the learning task and extracted fMRI responses and connectivity as features for machine learning classifiers. Our results show that the PI guided GMLVQ classifiers outperform the baseline classifier that only used the cognitive data. In addition, we found that for the baseline classifier, divided attention is the only relevant cognitive feature. When PI was incorporated, divided attention remained the most relevant feature while cognitive inhibition became also relevant for the task. Interestingly, this analysis for the fMRI GMLVQ classifier suggests that (1 when overall fMRI signal for structured stimuli is

Lung Nodule Detection in CT Images using Neuro Fuzzy Classifier

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M. Usman Akram

2013-07-01

Full Text Available Automated lung cancer detection using computer aided diagnosis (CAD is an important area in clinical applications. As the manual nodule detection is very time consuming and costly so computerized systems can be helpful for this purpose. In this paper, we propose a computerized system for lung nodule detection in CT scan images. The automated system consists of two stages i.e. lung segmentation and enhancement, feature extraction and classification. The segmentation process will result in separating lung tissue from rest of the image, and only the lung tissues under examination are considered as candidate regions for detecting malignant nodules in lung portion. A feature vector for possible abnormal regions is calculated and regions are classified using neuro fuzzy classifier. It is a fully automatic system that does not require any manual intervention and experimental results show the validity of our system.

Microprocessor-based integrated LMFBR core surveillance. Pt. 2

International Nuclear Information System (INIS)

Elies, V.

1985-12-01

This report is the result of the KfK part of a joint study of KfK and INTERATOM. The aim of this study is to explore the advantages of microprocessors and microelectronics for a more sophisticated core surveillance, which is based on the integration of separate surveillance techniques. After a description of the experimental results gained with the different surveillance techniques so far, it is shown which kinds of correlation can be done using the evaluation results obtained from the single surveillance systems. The main part of this report contains the systems analysis of a microcomputer-based system integrating different surveillance methods. After an analysis of the hardware requirements a hardware structure for the integrated system is proposed. The software structure is then described for the subsystem performing the different surveillance algorithms as well as for the system which does the correlation thus deriving additional information from the single results. (orig.) [de

Reliability demonstration of imaging surveillance systems

International Nuclear Information System (INIS)

Sheridan, T.F.; Henderson, J.T.; MacDiarmid, P.R.

1979-01-01

Security surveillance systems which employ closed circuit television are being deployed with increasing frequency for the protection of property and other valuable assets. A need exists to demonstrate the reliability of such systems before their installation to assure that the deployed systems will operate when needed with only the scheduled amount of maintenance and support costs. An approach to the reliability demonstration of imaging surveillance systems which employ closed circuit television is described. Failure definitions based on industry television standards and imaging alarm assessment criteria for surveillance systems are discussed. Test methods which allow 24 hour a day operation without the need for numerous test scenarios, test personnel and elaborate test facilities are presented. Existing reliability demonstration standards are shown to apply which obviate the need for elaborate statistical tests. The demonstration methods employed are shown to have applications in other types of imaging surveillance systems besides closed circuit television

Surveillance of working conditions and the work environment: development of a national hazard surveillance tool in New Zealand.

Science.gov (United States)

Lilley, Rebbecca; Feyer, Anne-Marie; Firth, Hilda; Cunningham, Chris; Paul, Charlotte

2010-02-01

Changes to work and the impact of these changes on worker health and safety have been significant. A core surveillance data set is needed to understand the impact of working conditions and work environments. Yet, there is little harmony amongst international surveys and a critical lack of guidance identifying the best directions for surveillance efforts. This paper describes the establishment of an instrument suitable for use as a hazard surveillance tool for New Zealand workers. An iterative process of critical review was undertaken to create a dimensional framework and select specific measures from existing instruments. Pilot testing to ascertain participant acceptability of the questions was undertaken. The final questionnaire includes measures of socio-demographic characteristics, occupational history, work organisation, physicochemical, ergonomic and psychosocial hazards. Outcome measures were also included. A robust New Zealand hazard surveillance questionnaire comprehensively covering the key measures of work organisation and work environments that impact upon worker health and safety outcomes was developed. Recommended measures of work organisation, work environment and health outcomes that should be captured in work environment surveillance are made.

Thai Finger-Spelling Recognition Using a Cascaded Classifier Based on Histogram of Orientation Gradient Features

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Kittasil Silanon

2017-01-01

Full Text Available Hand posture recognition is an essential module in applications such as human-computer interaction (HCI, games, and sign language systems, in which performance and robustness are the primary requirements. In this paper, we proposed automatic classification to recognize 21 hand postures that represent letters in Thai finger-spelling based on Histogram of Orientation Gradient (HOG feature (which is applied with more focus on the information within certain region of the image rather than each single pixel and Adaptive Boost (i.e., AdaBoost learning technique to select the best weak classifier and to construct a strong classifier that consists of several weak classifiers to be cascaded in detection architecture. We collected 21 static hand posture images from 10 subjects for testing and training in Thai letters finger-spelling. The parameters for the training process have been adjusted in three experiments, false positive rates (FPR, true positive rates (TPR, and number of training stages (N, to achieve the most suitable training model for each hand posture. All cascaded classifiers are loaded into the system simultaneously to classify different hand postures. A correlation coefficient is computed to distinguish the hand postures that are similar. The system achieves approximately 78% accuracy on average on all classifier experiments.

32 CFR 2400.28 - Dissemination of classified information.

Science.gov (United States)

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Dissemination of classified information. 2400.28... SECURITY PROGRAM Safeguarding § 2400.28 Dissemination of classified information. Heads of OSTP offices... originating official may prescribe specific restrictions on dissemination of classified information when...

Massively Multi-core Acceleration of a Document-Similarity Classifier to Detect Web Attacks

Energy Technology Data Exchange (ETDEWEB)

Ulmer, C; Gokhale, M; Top, P; Gallagher, B; Eliassi-Rad, T

2010-01-14

This paper describes our approach to adapting a text document similarity classifier based on the Term Frequency Inverse Document Frequency (TFIDF) metric to two massively multi-core hardware platforms. The TFIDF classifier is used to detect web attacks in HTTP data. In our parallel hardware approaches, we design streaming, real time classifiers by simplifying the sequential algorithm and manipulating the classifier's model to allow decision information to be represented compactly. Parallel implementations on the Tilera 64-core System on Chip and the Xilinx Virtex 5-LX FPGA are presented. For the Tilera, we employ a reduced state machine to recognize dictionary terms without requiring explicit tokenization, and achieve throughput of 37MB/s at slightly reduced accuracy. For the FPGA, we have developed a set of software tools to help automate the process of converting training data to synthesizable hardware and to provide a means of trading off between accuracy and resource utilization. The Xilinx Virtex 5-LX implementation requires 0.2% of the memory used by the original algorithm. At 166MB/s (80X the software) the hardware implementation is able to achieve Gigabit network throughput at the same accuracy as the original algorithm.

An assessment of self-reported physical activity instruments in young people for population surveillance: Project ALPHA

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Pearson Natalie

2011-01-01

Full Text Available Abstract Background The assessment of physical activity is an essential part of understanding patterns and influences of behaviour, designing interventions, and undertaking population surveillance and monitoring, but it is particularly problematic when using self-report instruments with young people. This study reviewed available self-report physical activity instruments developed for use with children and adolescents to assess their suitability and feasibility for use in population surveillance systems, particularly in Europe. Methods Systematic searches and review, supplemented by expert panel assessment. Results Papers (n = 437 were assessed as potentially relevant; 89 physical activity measures were identified with 20 activity-based measures receiving detailed assessment. Three received support from the majority of the expert group: Physical Activity Questionnaire for Children/Adolescents (PAQ-C/PAQ-A, Youth Risk Behaviour Surveillance Survey (YRBS, and the Teen Health Survey. Conclusions Population surveillance of youth physical activity is strongly recommended and those involved in developing and undertaking this task should consider the three identified shortlisted instruments and evaluate their appropriateness for application within their national context. Further development and testing of measures suitable for population surveillance with young people is required.

Surveillance Duplex Ultrasonography of Stent Grafts for Popliteal Aneurysms.

Science.gov (United States)

Pineda, Danielle M; Troutman, Douglas A; Dougherty, Matthew J; Calligaro, Keith D

2016-05-01

Stent grafts, also known as covered stents, have become an increasingly acceptable treatment for popliteal artery aneurysms. However, endovascular exclusion confers lower primary patency compared to traditional open bypass and exclusion. The purpose of this study was to evaluate whether duplex ultrasonography (DU) can reliably diagnose failing stent grafts placed for popliteal artery aneurysms prior to occlusion. Between June 5, 2007, and March 11, 2014, 21 stent grafts (Viabahn; Gore, Flagstaff, Arizona) were placed in 19 patients for popliteal artery aneurysms. All patients had at least 1 follow-up duplex scan postoperatively. Mean follow-up was 28.9 months (9-93 months). Postoperative DU surveillance was performed in our Intersocietal Accreditation Commission noninvasive vascular laboratory at 1 week postprocedure and every 6 months thereafter. Duplex ultrasonography measured peak systolic velocities (PSVs) and ratio of adjacent PSVs (Vr) every 5 cm within the stent graft and adjacent arteries. We retrospectively classified the following factors as "abnormal DU findings": focal PSV > 300 cm/s, uniform PSVs 3.0. These DU criteria were derived from laboratory-specific data that we previously published on failing stent grafts placed for lower extremity occlusive disease. Four of the 21 stent grafts presented with symptomatic graft thrombosis within 6 months of a normal DU. Three of these 4 patients presented with rest pain and underwent thrombectomy (2) or vein bypass (1), and 1 elected for nonintervention for claudication. Our results suggest that surveillance DU using criteria established for grafts placed for occlusive disease may not be useful for predicting stent graft failure in popliteal artery aneurysms. © The Author(s) 2016.

Revising rates of asymptomatic Zika virus infection based on sentinel surveillance data from French Overseas Territories

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Lorenzo Subissi

2017-12-01

Full Text Available French Polynesia and the French Territories of the Americas (FTAs have experienced outbreaks of Zika virus (ZIKV infection. These territories used similar sentinel syndromic surveillance to follow the epidemics. However, the surveillance system only takes into account consulting patients diagnosed with ZIKV disease, while non-consulting cases, as well as asymptomatic cases, are not taken into account. In the French territories under study, the ratio of consulting to non-consulting patients was found to likely be as low as 1/3 to 1/4, and rough estimates of the ZIKV asymptomatic infections indicated a lower rate than previously reported (i.e., not more than half. Keywords: Zika virus, Sentinel surveillance, Asymptomatic infections, Pacific islands, Caribbean region, Vector-borne infections

Surveillance extension experience at WWER-440 type reactors

International Nuclear Information System (INIS)

Gillemot, F.; Uri, G.; Oszwald, F.; Trampus, P.

1993-01-01

In WWER-440 reactors, the surveillance specimens are located in accelerated irradiation positions. After 5 years, all specimens are withdrawn and the operational changes are not monitored. At Paks NPP a new surveillance program extension has been settled in order to avoid these original program disadvantages and generate further data for plant lifetime management. This paper includes: research performed to prepare the surveillance extension programme, the evaluation method for the surveillance extension, and first results (Charpy and tensile tests). (authors). 6 refs., 12 figs., 3 tabs

Surveillance extension experience at WWER-440 type reactors

Energy Technology Data Exchange (ETDEWEB)

Gillemot, F; Uri, G [Budapesti Mueszaki Egyetem, Budapest (Hungary); Oszwald, F; Trampus, P

1994-12-31

In WWER-440 reactors, the surveillance specimens are located in accelerated irradiation positions. After 5 years, all specimens are withdrawn and the operational changes are not monitored. At Paks NPP a new surveillance program extension has been settled in order to avoid these original program disadvantages and generate further data for plant lifetime management. This paper includes: research performed to prepare the surveillance extension programme, the evaluation method for the surveillance extension, and first results (Charpy and tensile tests). (authors). 6 refs., 12 figs., 3 tabs.

Ambient Surveillance by Probabilistic-Possibilistic Perception

NARCIS (Netherlands)

Bittermann, M.S.; Ciftcioglu, O.

2013-01-01

A method for quantifying ambient surveillance is presented, which is based on probabilistic-possibilistic perception. The human surveillance of a scene through observing camera sensed images on a monitor is modeled in three steps. First immersion of the observer is simulated by modeling perception

Approaches to canine health surveillance.

Science.gov (United States)

O'Neill, Dan G; Church, David B; McGreevy, Paul D; Thomson, Peter C; Brodbelt, Dave C

2014-01-01

Effective canine health surveillance systems can be used to monitor disease in the general population, prioritise disorders for strategic control and focus clinical research, and to evaluate the success of these measures. The key attributes for optimal data collection systems that support canine disease surveillance are representativeness of the general population, validity of disorder data and sustainability. Limitations in these areas present as selection bias, misclassification bias and discontinuation of the system respectively. Canine health data sources are reviewed to identify their strengths and weaknesses for supporting effective canine health surveillance. Insurance data benefit from large and well-defined denominator populations but are limited by selection bias relating to the clinical events claimed and animals covered. Veterinary referral clinical data offer good reliability for diagnoses but are limited by referral bias for the disorders and animals included. Primary-care practice data have the advantage of excellent representation of the general dog population and recording at the point of care by veterinary professionals but may encounter misclassification problems and technical difficulties related to management and analysis of large datasets. Questionnaire surveys offer speed and low cost but may suffer from low response rates, poor data validation, recall bias and ill-defined denominator population information. Canine health scheme data benefit from well-characterised disorder and animal data but reflect selection bias during the voluntary submissions process. Formal UK passive surveillance systems are limited by chronic under-reporting and selection bias. It is concluded that active collection systems using secondary health data provide the optimal resource for canine health surveillance.

Environmental surveillance master sampling schedule

International Nuclear Information System (INIS)

Bisping, L.E.

1995-02-01

Environmental surveillance of the Hanford Site and surrounding areas is conducted by the Pacific Northwest Laboratory (PNL) for the U.S. Department of Energy (DOE). This document contains the planned 1994 schedules for routine collection of samples for the Surface Environmental Surveillance Project (SESP), Drinking Water Project, and Ground-Water Surveillance Project. Samples are routinely collected for the SESP and analyzed to determine the quality of air, surface water, soil, sediment, wildlife, vegetation, foodstuffs, and farm products at Hanford Site and surrounding communities. The responsibility for monitoring onsite drinking water falls outside the scope of the SESP. PNL conducts the drinking water monitoring project concurrent with the SESP to promote efficiency and consistency, utilize expertise developed over the years, and reduce costs associated with management, procedure development, data management, quality control, and reporting. The ground-water sampling schedule identifies ground-water sampling .events used by PNL for environmental surveillance of the Hanford Site. Sampling is indicated as annual, semi-annual, quarterly, or monthly in the sampling schedule. Some samples are collected and analyzed as part of ground-water monitoring and characterization programs at Hanford (e.g. Resources Conservation and Recovery Act (RCRA), Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), or Operational). The number of samples planned by other programs are identified in the sampling schedule by a number in the analysis column and a project designation in the Cosample column. Well sampling events may be merged to avoid redundancy in cases where sampling is planned by both-environmental surveillance and another program

Environmental surveillance master sampling schedule

Energy Technology Data Exchange (ETDEWEB)

Bisping, L.E.

1995-02-01

Environmental surveillance of the Hanford Site and surrounding areas is conducted by the Pacific Northwest Laboratory (PNL) for the U.S. Department of Energy (DOE). This document contains the planned 1994 schedules for routine collection of samples for the Surface Environmental Surveillance Project (SESP), Drinking Water Project, and Ground-Water Surveillance Project. Samples are routinely collected for the SESP and analyzed to determine the quality of air, surface water, soil, sediment, wildlife, vegetation, foodstuffs, and farm products at Hanford Site and surrounding communities. The responsibility for monitoring onsite drinking water falls outside the scope of the SESP. PNL conducts the drinking water monitoring project concurrent with the SESP to promote efficiency and consistency, utilize expertise developed over the years, and reduce costs associated with management, procedure development, data management, quality control, and reporting. The ground-water sampling schedule identifies ground-water sampling .events used by PNL for environmental surveillance of the Hanford Site. Sampling is indicated as annual, semi-annual, quarterly, or monthly in the sampling schedule. Some samples are collected and analyzed as part of ground-water monitoring and characterization programs at Hanford (e.g. Resources Conservation and Recovery Act (RCRA), Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), or Operational). The number of samples planned by other programs are identified in the sampling schedule by a number in the analysis column and a project designation in the Cosample column. Well sampling events may be merged to avoid redundancy in cases where sampling is planned by both-environmental surveillance and another program.

Multiclass Boosting with Adaptive Group-Based kNN and Its Application in Text Categorization

Directory of Open Access Journals (Sweden)

Lei La

2012-01-01

Full Text Available AdaBoost is an excellent committee-based tool for classification. However, its effectiveness and efficiency in multiclass categorization face the challenges from methods based on support vector machine (SVM, neural networks (NN, naïve Bayes, and k-nearest neighbor (kNN. This paper uses a novel multi-class AdaBoost algorithm to avoid reducing the multi-class classification problem to multiple two-class classification problems. This novel method is more effective. In addition, it keeps the accuracy advantage of existing AdaBoost. An adaptive group-based kNN method is proposed in this paper to build more accurate weak classifiers and in this way control the number of basis classifiers in an acceptable range. To further enhance the performance, weak classifiers are combined into a strong classifier through a double iterative weighted way and construct an adaptive group-based kNN boosting algorithm (AGkNN-AdaBoost. We implement AGkNN-AdaBoost in a Chinese text categorization system. Experimental results showed that the classification algorithm proposed in this paper has better performance both in precision and recall than many other text categorization methods including traditional AdaBoost. In addition, the processing speed is significantly enhanced than original AdaBoost and many other classic categorization algorithms.

3013/9975 Surveillance Program Interim Summary Report

International Nuclear Information System (INIS)

Dunn, K.; Hackney, B.; McClard, J.

2011-01-01

The K-Area Materials Storage (KAMS) Documented Safety Analysis (DSA) requires a surveillance program to monitor the safety performance of 3013 containers and 9975 shipping packages stored in KAMS. The SRS surveillance program (Reference 1) outlines activities for field surveillance and laboratory tests that demonstrate the packages meet the functional performance requirements described in the DSA. The SRS program also supports the complexwide Integrated Surveillance Program (ISP) (Reference 2) for 3013 containers. The purpose of this report is to provide a summary of the SRS portion of the surveillance program activities through fiscal year 2010 (FY10) and formally communicate the interpretation of these results by the Surveillance Program Authority (SPA). Surveillance for the initial 3013 container random sampling of the Innocuous bin and the Pressure bin has been completed and there has been no indication of corrosion or significant pressurization. The maximum pressure observed was less than 50 psig, which is well below the design pressure of 699 psig for the 3013 container (Reference 3). The data collected during surveillance of these bins has been evaluated by the Materials Identification and Surveillance (MIS) Working Group and no additional surveillance is necessary for these bins at least through FY13. A decision will be made whether additional surveillance of these bins is needed during future years of storage and as additional containers are generated. Based on the data collected to date, the SPA concludes that 3013 containers in these bins can continue to be safely stored in KAMS. This year, 13 destructive examinations (DE) were performed on random samples from the Pressure and Corrosion bin. To date, DE has been completed for approximately 30% of the random samples from the Pressure and Corrosion bin. In addition, DE has been performed on 6 engineering judgment (EJ) containers, for a total of 17 to date. This includes one container that exceeded the 3013

Was the French clinical surveillance system of bovine brucellosis influenced by the occurrence and surveillance of other abortive diseases?

Science.gov (United States)

Bronner, Anne; Morignat, Eric; Touratier, Anne; Gache, Kristel; Sala, Carole; Calavas, Didier

2015-03-01

The bovine brucellosis clinical surveillance system implemented in France aims to detect early any case of bovine brucellosis, a disease of which the country has been declared free since 2005. It relies on the mandatory notification of every bovine abortion. Following the spread of the Schmallenberg virus (SBV) in France in 2012 and 2013, and the implementation in 2012 of a clinical surveillance programme of Q fever based on abortion notifications in ten pilot départements, our objective was to study whether these two events influenced the brucellosis clinical surveillance system. The proportion of notifying farmers was analyzed over each semester from June 1, 2009 to June 30, 2013 according to the size and production type of herds, SBV status of départements and the implementation of the Q fever surveillance. Our analysis showed a slight increase in the proportion of notifying farmers as départements became infected by SBV, and after the implementation of Q fever surveillance (during the first semester of 2013). These variations might be explained by an increase in abortion occurrence (congenital deformities in newborns, due to SBV) and/or by an increase in farmers' and veterinarians' awareness (due to the spread of SBV and the implementation of the Q fever surveillance). These results highlight the difficulties in interpreting variations in the proportion of notifying farmers as a consequence of an increase in abortion occurrence. As bovine abortion surveillance can play an important role in the early warning for several diseases, there is a need to explore other ways to monitor abortions in cattle, such as syndromic surveillance using the dates of artificial insemination or calving data. Copyright © 2015 Elsevier B.V. All rights reserved.

“Jones-ing” for a Solution: Commercial Street Surveillance and Privacy Torts in Canada

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Stuart Hargreaves

2014-07-01

Full Text Available While street surveillance technologies such as Google Street View are deployed with no discriminatory intent, there is selective scrutiny applied to the published imagery by the anonymous crowd. Disproportionately directed at women and members of ethnic minority groups, this scrutiny means the social risks of street surveillance are not equal. This paper considers the possibility of invasion of privacy actions in tort brought against the commercial service provider as a possible solution. Analysis suggests that Canadian law has evolved in a way such that it is exceedingly difficult to make a claim for “privacy” in tort when the plaintiff is located in public space. This evolution exists in order to ensure that innocuous behavior not be rendered actionable. Furthermore, conceptual reasons exist to suggest that actions in tort are unlikely to be the best solution to the problems posed by commercial street surveillance. While any individual case of embarrassment or nuisance matters, broader “macro-harms” that impact entire communities reflect perhaps the most serious problem associated with the selective scrutiny of street surveillance imagery. Yet, it seems difficult to justify attaching liability for those harms to the commercial providers. While limits need to be placed on the operation of these street surveillance programmes, it is unlikely that invasion of privacy actions are the most effective way to achieve that goal.

Transition to CCTV surveillance for safeguards