Jiang, Hai; Liu, Jing; Cheng, Hao-Wen; Zhang, Yao
The increasing number of space debris has created an orbital debris environment that poses increasing impact risks to existing space systems and human space flights. For the safety of in-orbit spacecrafts, we should optimally schedule surveillance tasks for the existing facilities to allocate resources in a manner that most significantly improves the ability to predict and detect events involving affected spacecrafts. This paper analyzes two criteria that mainly affect the performance of a scheduling scheme and introduces an artificial intelligence algorithm into the scheduling of tasks of the space debris surveillance network. A new scheduling algorithm based on the particle swarm optimization algorithm is proposed, which can be implemented in two different ways: individual optimization and joint optimization. Numerical experiments with multiple facilities and objects are conducted based on the proposed algorithm, and simulation results have demonstrated the effectiveness of the proposed algorithm.
Cha, Daehyun; Hwang, Chansik
Previous vehicle surveillance researches on distributed sensor network focused on overcoming power limitation and communication bandwidth constraints in sensor node. In spite of this constraints, vehicle surveillance sensor node must have signal compression, feature extraction, target localization, noise cancellation and collaborative signal processing with low computation and communication energy dissipation. In this paper, we introduce an algorithm for light-weight wireless sensor node signal processing based on lifting scheme wavelet analysis feature extraction in distributed sensor network.
Full Text Available The topology inference is the study of spatial and temporal relationships among cameras within a video surveillance network. We propose a novel approach to understand activities based on the visual coverage of a video surveillance network. In our approach, an optimal camera placement scheme is firstly presented by using a binary integer programming algorithm in order to maximize the surveillance coverage. Then, each camera view is decomposed into regions based on the Histograms of Color Optical Flow (HCOF, according to the spatial-temporal distribution of activity patterns observed in a training set of video sequences. We conduct experiments by using hours of video sequences captured at an office building with seven camera views, all of which are sparse scenes with complex activities. The results of real scene experiment show that the features of histograms of color optic flow offer important contextual information for spatial and temporal topology inference of a camera network.
Amaku, Marcos; Grisi-Filho, José Henrique de Hildebrand; Negreiros, Rísia Lopes; Dias, Ricardo Augusto; Ferreira, Fernando; Ferreira Neto, José Soares; Cipullo, Rafael Ishibashi; Marques, Fernando Silveira; Ossada, Raul
The network of animal movements among livestock premises is an important topological structure for the spread of infectious diseases. The central focus of this study was to analyze strategies for selecting premises based on the friendship paradox ("your friends have more friends than you do") - in which premises that neighbor randomly selected premises are sampled for surveillance or control - to determine whether these strategies are viable alternatives for the surveillance and control of diseases in scenarios with insufficient data on animal movement. To test the effectiveness of these strategies, we performed three sets of simulations. In the first set, we examined the risk of spreading an infectious disease using the cattle movement network of the state of Mato Grosso, Brazil. All tested strategies based on the friendship paradox have comparable performance to the hub control strategy (controlling premises that sold more animals) and superior performance to random sampling in terms of both reducing the risk of purchasing infected animals and the number of premises that need to be controlled. In the second and third sets of simulations, we observed that the friendship paradox strategies were more sensitive than the random sampling strategy to detect cases and disease, respectively. The survey of the entire animal movement network to identify animal premises with a key role in trade is not always possible, either because the data are insufficient or because informal trade is significant. If surveying the network is not possible, all approaches based on knowledge of the network become useless. As an alternative, knowing that there is a hidden movement network that follows rules inherent to all networks, such as the friendship paradox, can be used to our advantage. Strategies based on the friendship paradox do not assume knowledge of the animal movement network and therefore may be viable alternatives for the surveillance or control of infectious diseases in the
Jeremy Sueker, J.; Blazes, David L.; Matthew C Johns; Patrick J Blair; Paul A Sjoberg; Tjaden, Jeffrey A.; Montgomery, Joel M.; Pavlin, Julie A; Schnabel, David C; Angelia A Eick; Tobias, Steven; Quintana, Miguel; Vest, Kelly G; Burke, Ronald L.; Lindler, Luther E.
Please cite this paper as: Jeremy Sueker et al. (2010) Influenza and respiratory disease surveillance: the US military’s global laboratory‐based network. Influenza and Other Respiratory Viruses 4(3), 155–161. The US Department of Defense influenza surveillance system now spans nearly 500 sites in 75 countries, including active duty US military and dependent populations as well as host‐country civilian and military personnel. This system represents a major part of the US Government’s contribut...
Morse, Stephen S
Zoonotic infections are important sources of human disease; most known emerging infections are zoonotic (e.g., HIV, Ebola virus, severe acute respiratory syndrome, Nipah virus, and enteropathogenic Escherichia coli) and originated as natural infections of other species that acquired opportunities to come in contact with humans. There are also serious infectious diseases classically considered zoonotic, such as influenza, rabies, bubonic plague, brucellosis, and leptospirosis. More recently, it has been recognized that wildlife constitutes a particularly important source of novel zoonoses. With all this microbial movement, surveillance is considered the first line of public health defense. The zoonotic origin of many human and livestock infections argues strongly for the synergistic value of a One Health approach, which provides the capability to identify pathogens crossing into new species and could provide earlier warning of potential epidemics. This article discusses public health surveillance and major recent surveillance initiatives and reviews progress toward implementing a One Health surveillance framework. Networks discussed include global intergovernmental organizations and recent combined efforts of these organizations; Web-based nongovernmental systems (e.g., ProMED, the Program for Monitoring Emerging Diseases); and networks of bilateral or multilateral government programs (e.g., the CDC's Global Disease Detection [GDD] platform; the U.S. Department of Defense's Global Emerging Infections Surveillance and Response System [GEIS]; regional and subregional networks; and the U.S. Agency for International Development's Emerging Pandemic Threats [EPT] program and its surveillance component, PREDICT). Syndromic surveillance also has potential to complement existing systems. New technologies are enabling revolutionary capabilities for global surveillance, but in addition to serious technical needs, both sustainability and data-sharing mechanisms remain
Jiang, H.; Cheng, H.; Zhang, Y.; Liu, J.
A growing number of space activities have created an orbital debris environment that poses increasing impact risks to existing space systems and human space flight. For the safety of in-orbit spacecraft, a lot of observation facilities are needed to catalog space objects, especially in low earth orbit. Surveillance of Low earth orbit objects are mainly rely on ground-based radar, due to the ability limitation of exist radar facilities, a large number of ground-based radar need to build in the next few years in order to meet the current space surveillance demands. How to optimize the embattling of ground-based radar surveillance network is a problem to need to be solved. The traditional method for embattling optimization of ground-based radar surveillance network is mainly through to the detection simulation of all possible stations with cataloged data, and makes a comprehensive comparative analysis of various simulation results with the combinational method, and then selects an optimal result as station layout scheme. This method is time consuming for single simulation and high computational complexity for the combinational analysis, when the number of stations increases, the complexity of optimization problem will be increased exponentially, and cannot be solved with traditional method. There is no better way to solve this problem till now. In this paper, target detection procedure was simplified. Firstly, the space coverage of ground-based radar was simplified, a space coverage projection model of radar facilities in different orbit altitudes was built; then a simplified objects cross the radar coverage model was established according to the characteristics of space objects orbit motion; after two steps simplification, the computational complexity of the target detection was greatly simplified, and simulation results shown the correctness of the simplified results. In addition, the detection areas of ground-based radar network can be easily computed with the
resistance surveillance, diarrhea etiology and antimicrobial resistance surveillance, sexually transmitted illness surveillance, and capacity building...vomiting, diarrhea , joint pains, general malaise. Of the samples analyzed, only 53.7% had an associated etiology: Malaria (47.0%, EBV (39.7...immunity to the disease. Many adults in those situations are reservoirs, facilitating continuing disease transmission to those without immunity. In Kenya
Full Text Available As a consequence of increasing safety concerns, camera surveillance has been widely adopted as a way to monitor public spaces. One of the major challenges of camera surveillance is to design an optimal method for camera network placement in order to ensure the greater possible coverage. In addition, this method must consider the landscape of the monitored environment to take into account the existing objects that may influence the deployment of such a network. In this paper, a new Voronoi-based 3D GIS oriented approach named “HybVOR” is proposed for surveillance camera network placement. The “HybVOR” approach aims to achieve a coverage near 100% through three main phases. First, a Voronoi Diagram from buildings’ footprints is generated and cameras are placed on the Voronoi Edges. Second, the level of coverage is assessed by calculating a viewshed based on a raster Digital Surface Model of the region of interest. Finally, the visibility of the main buildings’ entrances is evaluated based on a 3D vector model that contains these features. The effectiveness of the “HybVOR” approach is demonstrated through a case study that corresponds to an area of interest in Jeddah Seaport in the Kingdom of Saudi Arabia.
Reda Yaagoubi; Mabrouk El Yarmani; Abdullah Kamel; Walid Khemiri
As a consequence of increasing safety concerns, camera surveillance has been widely adopted as a way to monitor public spaces. One of the major challenges of camera surveillance is to design an optimal method for camera network placement in order to ensure the greater possible coverage. In addition, this method must consider the landscape of the monitored environment to take into account the existing objects that may influence the deployment of such a network. In this paper, a new Voronoi-bas...
Simon, Gaëlle; Larsen, Lars E.; Dürrwald, Ralf; Foni, Emanuela; Harder, Timm; Reeth, Van Kristien; Markowska-Daniel, Iwona; Reid, Scott M.; Dan, Adam; Maldonado, Jaime; Huovilainen, Anita; Billinis, Charalambos; Davidson, Irit; Agüero, Montserrat; Vila, Thaïs; Hervé, Séverine; Breum, Solvej Østergaard; Chiapponi, Chiara; Urbaniak, Kinga; Kyriakis, Constantinos S.; Brown, Ian H.; Loeffen, Willie; Meulen, Van der Karen; Schlegel, Michael; Bublot, Michel; Kellam, Paul; Watson, Simon; Lewis, Nicola S.; Pybus, Oliver G.; Webby, Richard; Chen, Hualan; Vincent, Amy L.
Swine influenza causes concern for global veterinary and public health officials. In continuing two previous networks that initiated the surveillance of swine influenza viruses (SIVs) circulating in European pigs between 2001 and 2008, a third European Surveillance Network for Influenza in Pigs (
VanderWaal, Kimberly L; Picasso, Catalina; Enns, Eva A; Craft, Meggan E; Alvarez, Julio; Fernandez, Federico; Gil, Andres; Perez, Andres; Wells, Scott
Movement of livestock between premises is one of the foremost factors contributing to the spread of infectious diseases of livestock. In part to address this issue, the origin and destination for all cattle movements in Uruguay are registered by law. This information has great potential to be used in assessing the risk of disease spread in the Uruguayan cattle population. Here, we analyze cattle movements from 2008 to 2013 using network analysis in order to understand the flows of animals in the Uruguayan cattle industry and to identify targets for surveillance and control measures. Cattle movements were represented as seasonal and annual networks in which farms represented nodes and nodes were linked based on the frequency and quantity of cattle moved. At the farm level, the distribution of the number of unique farms each farm is connected to through outgoing and incoming movements, as well as the number of animals moved, was highly right-skewed; the majority of farms had few to no contacts, whereas the 10% most highly connected farms accounted for 72-83% of animals moved annually. This extreme level of heterogeneity in movement patterns indicates that some farms may be disproportionately important for pathogen spread. Different production types exhibited characteristic patterns of farm-level connectivity, with some types, such a dairies, showing consistently higher levels of centrality. In addition, the observed networks were characterized by lower levels of connectivity and higher levels of heterogeneity than random networks of the same size and density, both of which have major implications for disease dynamics and control strategies. This represents the first in-depth analysis of farm-level livestock movements within South America, and highlights the importance of collecting livestock movement data in order to understand the vulnerability of livestock trade networks to invasion by infectious diseases.
Reid, Scott M.; Simon, Gaëlle; Larsen, Lars Erik
Objectives: The “European surveillance network for influenza in pigs (ESNIP) 3” continues a surveillance network previously established during concerted actions ESNIP 1 and ESNIP 2. Running from 2010-2013, ESNIP 3 represents the only organised surveillance network for influenza in pigs in Europe...... influenza virus (SIV) experimentally and in the field. Three work packages aim to increase knowledge of the epidemiology and evolution of SIV in European pigs to inform changes in disease trends and variation in contemporary viruses through organised field surveillance programmes. Results: An inventory...... will improve SI diagnosis by updating reagents employed in the recommended techniques to define minimum datasets for standardised epidemiological analyses. These approaches will aid pandemic preparedness and planning for human influenza whilst providing an evidence base for decisions relating to veterinary...
Wan, Xiang; Liu, Jiming; Cheung, William K; Tong, Tiejun
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.
Offering ready access to the security industry's cutting-edge digital future, Intelligent Network Video provides the first complete reference for all those involved with developing, implementing, and maintaining the latest surveillance systems. Pioneering expert Fredrik Nilsson explains how IP-based video surveillance systems provide better image quality, and a more scalable and flexible system at lower cost. A complete and practical reference for all those in the field, this volume:Describes all components relevant to modern IP video surveillance systemsProvides in-depth information about ima
Jose L Herrera
Full Text Available As infectious disease surveillance systems expand to include digital, crowd-sourced, and social network data, public health agencies are gaining unprecedented access to high-resolution data and have an opportunity to selectively monitor informative individuals. Contact networks, which are the webs of interaction through which diseases spread, determine whether and when individuals become infected, and thus who might serve as early and accurate surveillance sensors. Here, we evaluate three strategies for selecting sensors-sampling the most connected, random, and friends of random individuals-in three complex social networks-a simple scale-free network, an empirical Venezuelan college student network, and an empirical Montreal wireless hotspot usage network. Across five different surveillance goals-early and accurate detection of epidemic emergence and peak, and general situational awareness-we find that the optimal choice of sensors depends on the public health goal, the underlying network and the reproduction number of the disease (R0. For diseases with a low R0, the most connected individuals provide the earliest and most accurate information about both the onset and peak of an outbreak. However, identifying network hubs is often impractical, and they can be misleading if monitored for general situational awareness, if the underlying network has significant community structure, or if R0 is high or unknown. Taking a theoretical approach, we also derive the optimal surveillance system for early outbreak detection but find that real-world identification of such sensors would be nearly impossible. By contrast, the friends-of-random strategy offers a more practical and robust alternative. It can be readily implemented without prior knowledge of the network, and by identifying sensors with higher than average, but not the highest, epidemiological risk, it provides reasonably early and accurate information.
Girond, Florian; Randrianasolo, Laurence; Randriamampionona, Lea; Rakotomanana, Fanjasoa; Randrianarivelojosia, Milijaona; Ratsitorahina, Maherisoa; Brou, Télesphore Yao; Herbreteau, Vincent; Mangeas, Morgan; Zigiumugabe, Sixte; Hedje, Judith; Rogier, Christophe; Piola, Patrice
The use of a malaria early warning system (MEWS) to trigger prompt public health interventions is a key step in adding value to the epidemiological data routinely collected by sentinel surveillance systems. This study describes a system using various epidemic thresholds and a forecasting component with the support of new technologies to improve the performance of a sentinel MEWS. Malaria-related data from 21 sentinel sites collected by Short Message Service are automatically analysed to detect malaria trends and malaria outbreak alerts with automated feedback reports. Roll Back Malaria partners can, through a user-friendly web-based tool, visualize potential outbreaks and generate a forecasting model. The system already demonstrated its ability to detect malaria outbreaks in Madagascar in 2014. This approach aims to maximize the usefulness of a sentinel surveillance system to predict and detect epidemics in limited-resource environments.
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.
Full Text Available BACKGROUND: Syndromic surveillance systems have been developed in recent years and are now increasingly used by stakeholders to quickly answer questions and make important decisions. It is therefore essential to evaluate the quality and utility of such systems. This study was designed to assess a syndromic surveillance system based on emergency departments' (ED morbidity rates related to the health effects of heat waves. This study uses data collected during the 2006 heat wave in France. METHODS: Data recorded from 15 EDs in the Ile-de-France (Paris and surrounding area from June to August, 2006, were transmitted daily via the Internet to the French Institute for Public Health Surveillance. Items collected included diagnosis (ICD10, outcome, and age. Several aspects of the system have been evaluated (data quality, cost, flexibility, stability, and performance. Periods of heat wave are considered the most suitable time to evaluate the system. RESULTS: Data quality did not vary significantly during the period. Age, gender and outcome were completed in a comprehensive manner. Diagnoses were missing or uninformative for 37.5% of patients. Stability was recorded as being 99.49% for the period overall. The average cost per day over the study period was estimated to be euro287. Diagnoses of hyperthermia, malaise, dehydration, hyponatremia were correlated with increased temperatures. Malaise was most sensitive in younger and elderly adults but also the less specific. However, overall syndrome groups were more sensitive with comparable specificity than individual diagnoses. CONCLUSION: This system satisfactorily detected the health impact of hot days (observed values were higher than expected on more than 90% of days on which a heat alert was issued. Our findings should reassure stakeholders about the reliability of health impact assessments during or following such an event. These evaluations are essential to establish the validity of the results of
Enrique de la Hoz
Full Text Available Due to the low cost of CMOS IP-based cameras, wireless surveillance sensor networks have emerged as a new application of sensor networks able to monitor public or private areas or even country borders. Since these networks are bandwidth intensive and the radioelectric spectrum is limited, especially in unlicensed bands, it is mandatory to assign frequency channels in a smart manner. In this work, we propose the application of automated negotiation techniques for frequency assignment. Results show that these techniques are very suitable for the problem, being able to obtain the best solutions among the techniques with which we have compared them.
de la Hoz, Enrique; Gimenez-Guzman, Jose Manuel; Marsa-Maestre, Ivan; Orden, David
Due to the low cost of CMOS IP-based cameras, wireless surveillance sensor networks have emerged as a new application of sensor networks able to monitor public or private areas or even country borders. Since these networks are bandwidth intensive and the radioelectric spectrum is limited, especially in unlicensed bands, it is mandatory to assign frequency channels in a smart manner. In this work, we propose the application of automated negotiation techniques for frequency assignment. Results show that these techniques are very suitable for the problem, being able to obtain the best solutions among the techniques with which we have compared them.
Full Text Available Current video-surveillance systems typically consist of many video sources distributed over a wide area, transmitting live video streams to a central location for processing and monitoring. The target of this paper is to present an experience of implementation of a large-scale video-surveillance system based on a wireless mesh network infrastructure, discussing architecture, protocol, and implementation issues. More specifically, the paper proposes an architecture for a video-surveillance system, and mainly centers its focus on the routing protocol to be used in the wireless mesh network, evaluating its impact on performance at the receiver side. A wireless mesh network was chosen to support a video-surveillance application in order to reduce the overall system costs and increase scalability and performance. The paper analyzes the performance of the network in order to choose design parameters that will achieve the best trade-off between video encoding quality and the network traffic generated.
Full Text Available Current video-surveillance systems typically consist of many video sources distributed over a wide area, transmitting live video streams to a central location for processing and monitoring. The target of this paper is to present an experience of implementation of a large-scale video-surveillance system based on a wireless mesh network infrastructure, discussing architecture, protocol, and implementation issues. More specifically, the paper proposes an architecture for a video-surveillance system, and mainly centers its focus on the routing protocol to be used in the wireless mesh network, evaluating its impact on performance at the receiver side. A wireless mesh network was chosen to support a video-surveillance application in order to reduce the overall system costs and increase scalability and performance. The paper analyzes the performance of the network in order to choose design parameters that will achieve the best trade-off between video encoding quality and the network traffic generated.
Introduces a developing method of a real-time network multimedia server based on uClinux, the multimedia server can control management and data access to remote data surveillance camera. Applying it to large scale network surveillance system, users can access the distributed network surveillance server cluster system composed of the real-time data, then read and save (or write) them to large capacity storage devices, increasing the number of concurrent users type connection, improve the stability and reliability of network surveillance system.%介绍了一种基于uClinux的实时网络监控服务器开发方法，该服务器能对实时对远程网络终端、监控摄像头等进行控制管理和数据访问。将其应用到大型网络监控系统中，用户可访问由多台服务器组成的分布式网络监控服务器集群，实时读取数据然后将其存写到大容量存储设备中，增加并发式连接的用户数量，提高远程实时网络监控系统稳定性和可靠性。
The Réseau National Télé-informatique de surveillance et d'information sur les Maladies Transmissibles (RNTMT) (French communicable diseases computerised surveillance network) comprises a network of sentinel general practitioners (SGP). These benevolent volunteers are responsible for the weekly epidemiological surveillance. Since its creation, 1,700 SGPs have participated in the RNTMT, representing a total of more than 120,000 connections to the RNTMT telematic service center. The principal motivation of these benevolent SGPs was to 'actively participate in public health', although only a minority of them (17.6%) had any training in this field. Such a system, based on the benevolent and voluntary activity of SGPs, requires a good understanding of SGPs' attitudes towards epidemiological surveillance in general and the tool used, in order to quantitatively and qualitatively follow their participation and to provide regular and useful feedback to the surveillance actors.
Full Text Available The East African Integrated Disease Surveillance Network (EAIDSNet was formed in response to a growing frequency of cross-border malaria outbreaks in the 1990s and a growing recognition that fragmented disease interventions, coupled with weak laboratory capacity, were making it difficult to respond in a timely manner to the outbreaks of malaria and other infectious diseases. The East Africa Community (EAC partner states, with financial support from the Rockefeller Foundation, established EAIDSNet in 2000 to develop and strengthen the communication channels necessary for integrated cross-border disease surveillance and control efforts. The objective of this paper is to review the regional EAIDSNet initiative and highlight achievements and challenges in its implementation. Major accomplishments of EAIDSNet include influencing the establishment of a Department of Health within the EAC Secretariat to support a regional health agenda; successfully completing a regional field simulation exercise in pandemic influenza preparedness; and piloting a web-based portal for linking animal and human health disease surveillance. The strategic direction of EAIDSNet was shaped, in part, by lessons learned following a visit to the more established Mekong Basin Disease Surveillance (MBDS regional network. Looking to the future, EAIDSNet is collaborating with the East, Central and Southern Africa Health Community (ECSA-HC, EAC partner states, and the World Health Organization to implement the World Bank-funded East Africa Public Health Laboratory Networking Project (EAPHLNP. The network has also begun lobbying East African countries for funding to support EAIDSNet activities.
Meyer, William G; Pavlin, Julie A; Hospenthal, Duane; Murray, Clinton K; Jerke, Kurt; Hawksworth, Anthony; Metzgar, David; Myers, Todd; Walsh, Douglas; Wu, Max; Ergas, Rosa; Chukwuma, Uzo; Tobias, Steven; Klena, John; Nakhla, Isabelle; Talaat, Maha; Maves, Ryan; Ellis, Michael; Wortmann, Glenn; Blazes, David L; Lindler, Luther
International infectious disease surveillance has been conducted by the United States (U.S.) Department of Defense (DoD) for many years and has been consolidated within the Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System (AFHSC-GEIS) since 1998. This includes activities that monitor the presence of antimicrobial resistance among pathogens. AFHSC-GEIS partners work within DoD military treatment facilities and collaborate with host-nation civilian and military clinics, hospitals and university systems. The goals of these activities are to foster military force health protection and medical diplomacy. Surveillance activities include both community-acquired and health care-associated infections and have promoted the development of surveillance networks, centers of excellence and referral laboratories. Information technology applications have been utilized increasingly to aid in DoD-wide global surveillance for diseases significant to force health protection and global public health. This section documents the accomplishments and activities of the network through AFHSC-GEIS partners in 2009.
Sunil Kr Singh
Full Text Available With the emergence of ubiquitous computing, whole scenario of computing has been changed. It affected many inter disciplinary fields. This paper visions the impact of ubiquitous computing on video surveillance system. With increase in population and highly specific security areas, intelligent monitoring is the major requirement of modern world .The paper describes the evolution of surveillance system from analog to multi sensor ubiquitous system. It mentions the demand of context based architectures. It draws the benefit of merging of cloud computing to boost the surveillance system and at the same time reducing cost and maintenance. It analyzes some surveillance system architectures which are made for ubiquitous deployment. It provides major challenges and opportunities for the researchers to make surveillance system highly efficient and make them seamlessly embed in our environments.
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...
Martin, Vincent; Zhou, Xiaoyan; Marshall, Edith; Jia, Beibei; Fusheng, Guo; FrancoDixon, Mary Ann; DeHaan, Nicoline; Pfeiffer, Dirk U; Soares Magalhães, Ricardo J; Gilbert, Marius
Over the past two decades, the poultry sector in China went through a phase of tremendous growth as well as rapid intensification and concentration. Highly pathogenic avian influenza virus (HPAIV) subtype H5N1 was first detected in 1996 in Guangdong province, South China and started spreading throughout Asia in early 2004. Since then, control of the disease in China has relied heavily on wide-scale preventive vaccination combined with movement control, quarantine and stamping out. This strategy has been successful in drastically reducing the number of outbreaks during the past 5years. However, HPAIV H5N1 is still circulating and is regularly isolated in traditional live bird markets (LBMs) where viral infection can persist, which represent a public health hazard for people visiting them. The use of social network analysis in combination with epidemiological surveillance in South China has identified areas where the success of current strategies for HPAI control in the poultry production sector may benefit from better knowledge of poultry trading patterns and the LBM network configuration as well as their capacity for maintaining HPAIV H5N1 infection. We produced a set of LBM network maps and estimated the associated risk of HPAIV H5N1 within LBMs and along poultry market chains, providing new insights into how live poultry trade and infection are intertwined. More specifically, our study provides evidence that several biosecurity factors such as daily cage cleaning, daily cage disinfection or manure processing contribute to a reduction in HPAIV H5N1 presence in LBMs. Of significant importance is that the results of our study also show the association between social network indicators and the presence of HPAIV H5N1 in specific network configurations such as the one represented by the counties of origin of the birds traded in LBMs. This new information could be used to develop more targeted and effective control interventions.
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...
Lu, Xiao-Shan; Huang, Hai-Jun; Long, Jiancheng
New sensor technologies (e.g. surveillance cameras, loop detectors) enable the synthesis of disaggregated vehicle information from multiple locations. This article studies the camera location problem for traffic surveillance in urban road networks with multiple user classes. All users are differentiated by their own acceptance degree of camera monitoring and make their route choices in a logit-based stochastic user equilibrium manner. A bi-level programming model is proposed to formulate the problem and solved by the sensitivity analysis based branch and bound method. Numerical examples are presented to illustrate the model application and show the effectiveness of the solution method.
Wang, Xue; Wang, Sheng; Ma, Junjie; Sun, Xinyao
Wireless sensor networks involve a large number of sensor nodes with limited energy supply, which impacts the behavior of their application. In wireless multimedia sensor networks, sensor nodes are equipped with audio and visual information collection modules. Multimedia contents are ubiquitously retrieved in surveillance applications. To solve the energy problems during target surveillance with wireless multimedia sensor networks, an energy-aware sensor scheduling method is proposed in this paper. Sensor nodes which acquire acoustic signals are deployed randomly in the sensing fields. Target localization is based on the signal energy feature provided by multiple sensor nodes, employing particle swarm optimization (PSO). During the target surveillance procedure, sensor nodes are adaptively grouped in a totally distributed manner. Specially, the target motion information is extracted by a forecasting algorithm, which is based on the hidden Markov model (HMM). The forecasting results are utilized to awaken sensor node in the vicinity of future target position. According to the two properties, signal energy feature and residual energy, the sensor nodes decide whether to participate in target detection separately with a fuzzy control approach. Meanwhile, the local routing scheme of data transmission towards the observer is discussed. Experimental results demonstrate the efficiency of energy-aware scheduling of surveillance in wireless multimedia sensor network, where significant energy saving is achieved by the sensor awakening approach and data transmission paths are calculated with low computational complexity.
Bahamondes Maria V
Full Text Available Abstract Background Improving maternal health is one of the Millennium Development Goals for 2015. Recently some progress has been achieved in reducing mortality. On the other hand, in developed regions, maternal death is a relatively rare event compared to the number of cases of morbidity; hence studying maternal morbidity has become more relevant. Electronic surveillance systems may improve research by facilitating complete data reporting and reducing the time required for data collection and analysis. Therefore the purpose of this study was to describe the methods used in elaborating and implementing the National Network for the Surveillance of Severe Maternal Morbidity in Brazil. Methods The project consisted of a multicenter, cross-sectional study for the surveillance of severe maternal morbidity including near-miss, in Brazil. Results Following the development of a conceptual framework, centers were selected for inclusion in the network, consensus meetings were held among the centers, an electronic data collection system was identified, specific software and hardware tools were developed, research material was prepared, and the implementation process was initiated and analyzed. Conclusion The conceptual framework developed for this network was based on the experience acquired in various studies carried out in the area over recent years and encompasses maternal and perinatal health. It is innovative especially in the context of a developing country. The implementation of the project represents the first step towards this planned management. The system online elaborated for this surveillance network may be used in further studies in reproductive and perinatal health.
Hanrahan, Lawrence P.; Anderson, Henry A.; Busby, Brian; Bekkedal, Marni; Sieger, Thomas; Stephenson, Laura; Knobeloch, Lynda; Werner, Mark; Imm, Pamela; Olson, Joseph
In this article we describe the development of an information system for environmental childhood cancer surveillance. The Wisconsin Cancer Registry annually receives more than 25,000 incident case reports. Approximately 269 cases per year involve children. Over time, there has been considerable community interest in understanding the role the environment plays as a cause of these cancer cases. Wisconsin’s Public Health Information Network (WI-PHIN) is a robust web portal integrating both Health Alert Network and National Electronic Disease Surveillance System components. WI-PHIN is the information technology platform for all public health surveillance programs. Functions include the secure, automated exchange of cancer case data between public health–based and hospital-based cancer registrars; web-based supplemental data entry for environmental exposure confirmation and hypothesis testing; automated data analysis, visualization, and exposure–outcome record linkage; directories of public health and clinical personnel for role-based access control of sensitive surveillance information; public health information dissemination and alerting; and information technology security and critical infrastructure protection. For hypothesis generation, cancer case data are sent electronically to WI-PHIN and populate the integrated data repository. Environmental data are linked and the exposure–disease relationships are explored using statistical tools for ecologic exposure risk assessment. For hypothesis testing, case–control interviews collect exposure histories, including parental employment and residential histories. This information technology approach can thus serve as the basis for building a comprehensive system to assess environmental cancer etiology. PMID:15471739
Full Text Available In this work, a secure wireless sensor network (WSN for the surveillance, monitoring and protection of critical infrastructures was developed. To guarantee the security of the system, the main focus was the implementation of a unique security concept, which includes both security on the communication level, as well as mechanisms that ensure the functional safety during its operation. While there are many theoretical approaches in various subdomains of WSNs—like network structures, communication protocols and security concepts—the construction, implementation and real-life application of these devices is still rare. This work deals with these aforementioned aspects, including all phases from concept-generation to operation of a secure wireless sensor network. While the key focus of this paper lies on the security and safety features of the WSN, the detection, localization and classification capabilities resulting from the interaction of the nodes’ different sensor types are also described.
Hulihan, Mary M; Feuchtbaum, Lisa; Jordan, Lanetta; Kirby, Russell S; Snyder, Angela; Young, William; Greene, Yvonne; Telfair, Joseph; Wang, Ying; Cramer, William; Werner, Ellen M; Kenney, Kristy; Creary, Melissa; Grant, Althea M
The lack of an ongoing surveillance system for hemoglobinopathies in the United States impedes the ability of public health organizations to identify individuals with these conditions, monitor their health-care utilization and clinical outcomes, and understand the effect these conditions have on the health-care system. This article describes the results of a pilot program that supported the development of the infrastructure and data collection methods for a state-based surveillance system for selected hemoglobinopathies. The system was designed to identify and gather information on all people living with a hemoglobinopathy diagnosis (sickle cell diseases or thalassemias) in the participating states during 2004-2008. Novel, three-level case definitions were developed, and multiple data sets were used to collect information. In total, 31,144 individuals who had a hemoglobinopathy diagnosis during the study period were identified in California; 39,633 in Florida; 20,815 in Georgia; 12,680 in Michigan; 34,853 in New York, and 8,696 in North Carolina. This approach provides a possible model for the development of state-based hemoglobinopathy surveillance systems.
Full Text Available For the purpose of remote command and situation awareness, multiple unmanned aerial vehicles (UAVs cooperative surveillance with a ground station via multihop communications is presented in this paper. Considering limited communication capacities, a reliable UAV-to-UAV communication relay chain is dynamically established for connectivity maintenance and real-time surveillance information transmission. Firstly, a multiple UAVs cooperative surveillance framework is constructed with history detection information and surveillance payoff estimation. Secondly, four attributes are proposed to characterize differences among UAV alternatives in communication network containing a ground station, and a novel multiple relay UAVs selection scheme based on fuzzy optimum selection is developed to achieve tradeoff between surveillance mission and connectivity maintenance. Furthermore, satisfied with collision avoidance, limited communication and UAV kinematic constraints, the optimal UAV motion plan is obtained by decentralized receding horizon control, which is solved by particle swarm optimization with elite mechanism. Simulations demonstrate the effectiveness of the proposed methods in multi UAVs cooperative surveillance.
Roberts, Harold M
Google's AdWords processes information about what sorts of content users are browsing for about a quarter of all web site visits. The significance of AdWords' use of this vast amount of personal data lies not in its use for such obviously authoritarian purposes but instead as a network of grey surveillance with Google acting as the hub and the various publishers, advertisers, and users watching (and controlling) each other in distinct ways. Google's model of collective intelligence in its s...
There are close to 20,000 cataloged manmade objects in space, the large majority of which are not active, functioning satellites. These are tracked by phased array and mechanical radars and ground and space-based optical telescopes, collectively known as the Space Surveillance Network (SSN). A better SSN schedule of observations could, using exactly the same legacy sensor resources, improve space catalog accuracy through more complementary tracking, provide better responsiveness to real-time changes, better track small debris in low earth orbit (LEO) through efficient use of applicable sensors, efficiently track deep space (DS) frequent revisit objects, handle increased numbers of objects and new types of sensors, and take advantage of future improved communication and control to globally optimize the SSN schedule. We have developed a scheduling algorithm that takes as input the space catalog and the associated covariance matrices and produces a globally optimized schedule for each sensor site as to what objects to observe and when. This algorithm is able to schedule more observations with the same sensor resources and have those observations be more complementary, in terms of the precision with which each orbit metric is known, to produce a satellite observation schedule that, when executed, minimizes the covariances across the entire space object catalog. If used operationally, the results would be significantly increased accuracy of the space catalog with fewer lost objects with the same set of sensor resources. This approach inherently can also trade-off fewer high priority tasks against more lower-priority tasks, when there is benefit in doing so. Currently the project has completed a prototyping and feasibility study, using open source data on the SSN's sensors, that showed significant reduction in orbit metric covariances. The algorithm techniques and results will be discussed along with future directions for the research.
为了有效监测计算机网络面临的安全威胁,借鉴计算机免疫学中的克隆选择原理,研究一种动态的网络安全监测方法,模拟真实计算机网络环境下的抗原、自体和检测器等克隆选择原理中的关键要素,用数学方法描述检测器的动态演化过程,建立网络安全威胁监测的基本方法,实现了网络安全威胁的告警、网络安全风险评估和网络安全威胁的取证等网络安全监测流程.%In order to survey the security threats in the computer networks, a surveying method for network security based on clonal selection principle in computer immunology is proposed in this paper. Antigen, self-cell, detector, and etc in clonal selection principle are simulated in the real environment of computer networks. Dynamical evolution process of detector is described with math methods. Basic surveying method for network security threat is established. The flows of security threat alarm, security risk assessment and security threat forensics are realized.
Thiam, D; Niang, M; Dia, N; Sarr, F D; Goudiab, D; Senghor, M-L; Kiori, D; Faye, T; Espié, E; Ba, I O; Richard, V
Influenza surveillance in Senegal was initially restricted to the identification of circulating strains. The network has recently been enhanced (i) to include epidemiological data from Dakar and other regions and (ii) to extend virological surveillance to other respiratory viruses. Epidemiological data from the sentinel sites is transmitted daily by mobile phone. The data include those for other febrile syndromes similar to influenza-like illnesses (ILI), corresponding to integrated approach. Also, clinical samples are randomly selected and analyzed for influenza and other respiratory viruses. There were 180,192 declared visits to the 11 sentinel sites between week 11-2012 and week 52-2013; 24% of the visits were for fever syndromes and 25% of the cases of fever syndrome were ILI. Rhinoviruses were the most frequent cause of ILI (19%), before adenoviruses (18%), enteroviruses (18%) and influenza A viruses (13%). Co-circulation and co-infection were frequent and were responsible for ILI peaks. In conclusion, it is clear that the greatest advantage of this system is the ease with which it can be implemented, thanks to the availability of mobile phones and mobile phone networks. We recommend this solution for other African countries, because it performs very well and provides rapid benefits in terms of public health decision-making.
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....
Echevarría, Juan Emilio; Fernández García, Aurora; de Ory, Fernando
The Laboratory is a fundamental component on the surveillance of measles and rubella. Cases need to be properly confirmed to ensure an accurate estimation of the incidence. Strains should be genetically characterized to know the transmission pattern of these viruses and frequently, outbreaks and transmission chains can be totally discriminated only after that. Finally, the susceptibility of the population is estimated on the basis of sero-prevalence surveys. Detection of specific IgM response is the base of the laboratory diagnosis of these diseases. It should be completed with genomic detection by RT-PCR to reach an optimal efficiency, especially when sampling is performed early in the course of the disease. Genotyping is performed by genomic sequencing according to reference protocols of the WHO. Laboratory surveillance of measles and rubella in Spain is organized as a net of regional laboratories with different capabilities. The National Center of Microbiology as National Reference Laboratory (NRL), supports regional laboratories ensuring the availability of all required techniques in the whole country and watching for the quality of the results. The NRL is currently working in the implementation of new molecular techniques based on the analysis of genomic hypervariable regions for the strain characterization at sub-genotypic levels and use them in the surveillance.
Temte, Jonathan L; Barlow, Shari; Schemmel, Amber; Temte, Emily; Hahn, David L; Reisdorf, Erik; Shult, Peter; Tamerius, John
The goal of public health infectious disease surveillance systems is to provide accurate laboratory results in near-real time. When it comes to influenza surveillance, most current systems are encumbered with inherent delays encountered in the real-life chaos of medical practice. To combat this, we implemented and tested near-real-time surveillance using a rapid influenza detection test (RIDT) coupled with immediate, wireless transmission of results to public health entities. A network of 19 primary care clinics across Wisconsin were recruited, including 4 sites already involved in ongoing influenza surveillance and 15 sites that were new to surveillance activities. Each site was provided with a Quidel Sofia Influenza A+B RIDT analyzer attached to a wireless router. Influenza test results, along with patient age, were transmitted immediately to a cloud-based server, automatically compiled, and forwarded to the surveillance team daily. Weekly counts of positive influenza A and B cases were compared with positive polymerase chain reaction (PCR) detections from an independent surveillance system within the state. Following Institutional Review Board (IRB) and institutional approvals, we recruited 19 surveillance sites, installed equipment, and trained staff within 4 months. Of the 1119 cases tested between September 15, 2013 and June 28, 2014, 316 were positive for influenza. The system provided early detection of the influenza outbreak in Wisconsin. The influenza peak between January 12 and 25, 2014, as well as the epidemic curve, closely matched that derived from the established PCR laboratory network (r = 0.927; P surveillance. Results from the initial year strongly support this approach to highly accurate and timely influenza surveillance. © Copyright 2017 by the American Board of Family Medicine.
The traveler presented a paper at the Seventh ASTM-EURATOM Symposium on Reactor Dosimetry and co-chaired an oral session on Computer Codes and Methods. Papers of considerable interest to the NRC Surveillance Dosimetry Program involved statistically based adjustment procedures and uncertainties. The information exchange meetings with Czechoslovakia and Hungary were very enlightening. Lack of large computers have hindered their surveillance program. They depended very highly on information from their measurement programs which were somewhat limited because of the lack of sophisticated electronics. The Nuclear Research Institute at Rez had to rely on expensive mockups of power reactor configurations to test their fluence exposures. Computers, computer codes, and updated nuclear data would advance their technology rapidly, and they were not hesitant to admit this fact. Both eastern-bloc countries said that IBM is providing an IBM 3090 for educational purposes but research and development studies would have very limited access. They were very apologetic that their currencies were not convertible, and any exchange means that they could provide services or pay for US scientists in their respective countries, but funding for their scientists in the United States, or expenses that involved payment in dollars, must come from us.
Valicka, C.; Garcia, D.; Staid, A.; Watson, J.; Rintoul, M.; Hackebeil, G.; Ntaimo, L.
Advances in space technologies continue to reduce the cost of placing satellites in orbit. With more entities operating space vehicles, the number of orbiting vehicles and debris has reached unprecedented levels and the number continues to grow. Sensor operators responsible for maintaining the space catalog and providing space situational awareness face an increasingly complex and demanding scheduling requirements. Despite these trends, a lack of advanced tools continues to prevent sensor planners and operators from fully utilizing space surveillance resources. One key challenge involves optimally selecting sensors from a network of varying capabilities for missions with differing requirements. Another open challenge, the primary focus of our work, is building robust schedules that effectively plan for uncertainties associated with weather, ad hoc collections, and other target uncertainties. Existing tools and techniques are not amenable to rigorous analysis of schedule optimality and do not adequately address the presented challenges. Building on prior research, we have developed stochastic mixed-integer linear optimization models to address uncertainty due to weather's effect on collection quality. By making use of the open source Pyomo optimization modeling software, we have posed and solved sensor network scheduling models addressing both forms of uncertainty. We present herein models that allow for concurrent scheduling of collections with the same sensor configuration and for proactively scheduling against uncertain ad hoc collections. The suitability of stochastic mixed-integer linear optimization for building sensor network schedules under different run-time constraints will be discussed.
Henao, Olga L; Jones, Timothy F; Vugia, Duc J; Griffin, Patricia M
The Foodborne Diseases Active Surveillance Network (FoodNet) provides a foundation for food safety policy and illness prevention in the United States. FoodNet conducts active, population-based surveillance at 10 US sites for laboratory-confirmed infections of 9 bacterial and parasitic pathogens transmitted commonly through food and for hemolytic uremic syndrome. Through FoodNet, state and federal scientists collaborate to monitor trends in enteric illnesses, identify their sources, and implement special studies. FoodNet's major contributions include establishment of reliable, active population-based surveillance of enteric diseases; development and implementation of epidemiologic studies to determine risk and protective factors for sporadic enteric infections; population and laboratory surveys that describe the features of gastrointestinal illnesses, medical care-seeking behavior, frequency of eating various foods, and laboratory practices; and development of a surveillance and research platform that can be adapted to address emerging issues. The importance of FoodNet's ongoing contributions probably will grow as clinical, laboratory, and informatics technologies continue changing rapidly.
Michelini, Alberto; Margheriti, Lucia; Cattaneo, Marco; Cecere, Gianpaolo; D'Anna, Giuseppe; Delladio, Alberto; Moretti, Milena; Pintore, Stefano; Amato, Alessandro; Basili, Alberto; Bono, Andrea; Casale, Paolo; Danecek, Peter; Demartin, Martina; Faenza, Licia; Lauciani, Valentino; Mandiello, Alfonso Giovanni; Marchetti, Alessandro; Marcocci, Carlo; Mazza, Salvatore; Mariano Mele, Francesco; Nardi, Anna; Nostro, Concetta; Pignone, Maurizio; Quintiliani, Matteo; Rao, Sandro; Scognamiglio, Laura; Selvaggi, Giulio
The Istituto Nazionale di Geofisica e Vulcanologia (INGV) is an Italian research institution, with focus on Earth Sciences. INGV runs the Italian National Seismic Network (Rete Sismica Nazionale, RSN) and other networks at national scale for monitoring earthquakes and tsunami as a part of the National Civil Protection System coordinated by the Italian Department of Civil Protection (Dipartimento di Protezione Civile, DPC). RSN is composed of about 400 stations, mainly broadband, installed in the Country and in the surrounding regions; about 110 stations feature also co-located strong motion instruments, and about 180 have GPS receivers and belong to the National GPS network (Rete Integrata Nazionale GPS, RING). The data acquisition system was designed to accomplish, in near-real-time, automatic earthquake detection, hypocenter and magnitude determination, moment tensors, shake maps and other products of interest for DPC. Database archiving of all parametric results are closely linked to the existing procedures of the INGV seismic monitoring environment and surveillance procedures. INGV is one of the primary nodes of ORFEUS (Observatories & Research Facilities for European Seismology) EIDA (European Integrated Data Archive) for the archiving and distribution of continuous, quality checked seismic data. The strong motion network data are archived and distributed both in EIDA and in event based archives; GPS data, from the RING network are also archived, analyzed and distributed at INGV. Overall, the Italian earthquake surveillance service provides, in quasi real-time, hypocenter parameters to the DPC. These are then revised routinely by the analysts of the Italian Seismic Bulletin (Bollettino Sismico Italiano, BSI). The results are published on the web, these are available to both the scientific community and the general public. The INGV surveillance includes a pre-operational tsunami alert service since INGV is one of the Tsunami Service providers of the North
Lefrançois, T; Hendrikx, P; Ehrhardt, N; Millien, M; Gomez, L; Gouyet, L; Gaidet, N; Gerbier, G; Vachiéry, N; Petitclerc, F; Carasco-Lacombe, C; Pinarello, V; Ahoussou, S; Levesque, A; Gongora, H V; Trotman, M
The Caribbean region is considered to be at risk for avian influenza (AI) due to a large backyard poultry system, an important commercial poultry production system, the presence of migratory birds, and disparities in the surveillance systems. The Caribbean Animal Health Network (CaribVET) has developed tools to implement AI surveillance in the region with the goals to have 1) a regionally harmonized surveillance protocol and specific web pages for AI surveillance on www.caribvet.net, and 2) an active and passive surveillance for AI in domestic and wild birds. A diagnostic network for the Caribbean, including technology transfer and AI virus molecular diagnostic capability in Guadeloupe (real-time reverse transcription-polymerase chain reaction for the AI virus matrix gene), was developed. Between 2006 and 2009, 627 samples from four Caribbean countries were tested for three circumstances: importation purposes, following a clinical suspicion of AI, or through an active survey of wild birds (mainly waders) during the southward and northward migration periods in Guadeloupe. None of the samples tested were positive, suggesting a limited role of these species in the AI virus ecology in the Caribbean. Following low pathogenic H5N2 outbreaks in the Dominican Republic in 2007, a questionnaire was developed to collect data for a risk analysis of AI spread in the region through fighting cocks. The infection pathway of the Martinique commercial poultry sector by AI, through introduction of infected cocks, was designed, and recommendations were provided to the Caribbean Veterinary Services to improve cock movement control and biosecurity measures. The CaribVET and its organization allowed interaction between diagnostic and surveillance tools on the one hand and epidemiologic studies on the other, both of them developed in congruence with regional strategies. Together, these CaribVET activities contribute to strengthening surveillance of avian influenza virus (AIV) in the
Meijer, Willemijn M.; Cornel, Martina C.; Dolk, Helen; de Walle, Hermien E. K.; Armstrong, Nicola C.; de Jong-van den Berg, Lolkje T. W.
Background European Surveillance of Congenital Anomalies (EUROCAT) is a network of population-based congenital anomaly registries in Europe surveying more than I million births per year, or 25% of the births in the European Union. This paper describes the potential of the EUROCAT collaboration for
Ahmed M. Elmogy
Full Text Available The active surveillance of public and private sites is increasingly becoming a very important and critical issue. It is, therefore, imperative to develop mobile surveillance systems to protect these sites. Modern surveillance systems encompass spatially distributed mobile and static sensors in order to provide effective monitoring of persistent and transient objects and events in a given area of interest (AOI. The realization of the potential of mobile surveillance requires the solution of different challenging problems such as task allocation, mobile sensor deployment, multisensor management, cooperative object detection and tracking, decentralized data fusion, and interoperability and accessibility of system nodes. This paper proposes a market-based approach that can be used to handle different problems of mobile surveillance systems. Task allocation and cooperative target tracking are studied using the proposed approach as two challenging problems of mobile surveillance systems. These challenges are addressed individually and collectively.
Full Text Available Wireless integrated sensor networks, which include collecting, processing data and communication, are used more and more widely for its low cost and convenient deployment. Nowadays the researches of sensor networks are fairly active. The security is one of the key questions in sensor networks. Intrusion detection is a kind of network security technologies used to detect any behavior that will damage or attempt to damage system confidentiality, integrality or availability, and it can provide the reasonable supplement to intrusion prevention mechanism, and construct a second wall of defense for network and system. This paper mainly focuses on the energy efficient intrusion detection technology. According to the characteristics of sensor network and the specialty of the invasions in sensor network, this paper presents an intrusion detection model based on statistics anomaly in sensor networks. The algorithm establishes models for the normal state of the nodes, and makes decisions through the deviation degree of observed value. The algorithm is fault-tolerant for non-invasion anomaly when the communication between nodes break down or the accident wrongly create anomaly.
Agócs, Mary M; Serhan, Fatima; Yen, Catherine; Mwenda, Jason M; de Oliveira, Lúcia H; Teleb, Nadia; Wasley, Annemarie; Wijesinghe, Pushpa R; Fox, Kimberley; Tate, Jacqueline E; Gentsch, Jon R; Parashar, Umesh D; Kang, Gagandeep
Since 2008, the World Health Organization (WHO) has coordinated the Global Rotavirus Surveillance Network, a network of sentinel surveillance hospitals and laboratories that report to ministries of health (MoHs) and WHO clinical features and rotavirus testing data for children aged strategic review to assess surveillance network performance, provide recommendations for strengthening the network, and assess the network's utility as a platform for other vaccine-preventable disease surveillance. The strategic review team determined that during 2011 and 2012, a total of 79 sites in 37 countries met reporting and testing inclusion criteria for data analysis. Of the 37 countries with sites meeting inclusion criteria, 13 (35%) had introduced rotavirus vaccine nationwide. All 79 sites included in the analysis were meeting 2008 network objectives of documenting presence of disease and describing disease epidemiology, and all countries were using the rotavirus surveillance data for vaccine introduction decisions, disease burden estimates, and advocacy; countries were in the process of assessing the use of this surveillance platform for other vaccine-preventable diseases. However, the review also indicated that the network would benefit from enhanced management, standardized data formats, linkage of clinical data with laboratory data, and additional resources to support network functions. In November 2013, WHO's Strategic Advisory Group of Experts on Immunization (SAGE) endorsed the findings and recommendations made by the review team and noted potential opportunities for using the network as a platform for other vaccine-preventable disease surveillance. WHO will work to implement the recommendations to improve the network's functions and to provide higher quality surveillance data for use in decisions related to vaccine introduction and vaccination program sustainability.
Full Text Available This paper presents a moving-object segmentation algorithm using edge information as segment. The proposed method is developed to address challenges due to variations in ambient lighting and background contents. We investigated the suitability of the proposed algorithm in comparison with the traditional-intensity-based as well as edge-pixel-based detection methods. In our method, edges are extracted from video frames and are represented as segments using an efficiently designed edge class. This representation helps to obtain the geometric information of edge in the case of edge matching and moving-object segmentation; and facilitates incorporating knowledge into edge segment during background modeling and motion tracking. An efficient approach for background initialization and robust method of edge matching is presented, to effectively reduce the risk of false alarm due to illumination change and camera motion while maintaining the high sensitivity to the presence of moving object. Detected moving edges are utilized along with watershed algorithm for extracting video object plane (VOP with more accurate boundary. Experiment results with real image sequence reflect that the proposed method is suitable for automated video surveillance applications in various monitoring systems.
With the focus on organizations, this article describes power in relation to mediated surveillance using Luhmann’s systems theory, poststructuralist theory and theory of media sociography. It aims to sketch out the main issues in contemporary surveillance discourse and illustrate the current situ...... and surveillance do digital media provide and how the realization of this potential feeds back into organizations’ power structures.......With the focus on organizations, this article describes power in relation to mediated surveillance using Luhmann’s systems theory, poststructuralist theory and theory of media sociography. It aims to sketch out the main issues in contemporary surveillance discourse and illustrate the current...... situation, as well as discuss surveillance from the perspective of poststructuralist theory in relation to Luhmann’s concepts of trust, risk and especially power. The underlying media sociographical question is which storing-, retrieving-, localisation- and temporal possibilities for communication...
Sarah Jackson Young
Full Text Available In September 2013, civilian contractor Aaron Alexis entered the Washington Navy Yard and murdered twelve people before being fatally shot by police. This incident, together with an incident three months earlier involving Edward Snowden, caused the U.S. government to critically examine their background investigation (BI process; because both Snowden and Alexis had supposedly slipped through the cracks of their investigations, there must be some flaw in the BI procedure. The U.S. Committee on Oversight and Reform concluded that rules forbidding “background checkers from looking at the Internet or social media when performing checks” was one of the main factors contributing to defective BIs (Report, 2014. Since the report’s release, the Director of National Intelligence has been debating and trialing whether information from the Internet should be used to form a data double for BIs (Kopp, 2014; Rockwell, 2014. Using this conversation as a discussion catalyst, I argue that due to the nature of the data double, if the United States were to adopt the use of social networking sites (SNSs for security clearance purposes, neglecting to take into account basic principles of SNSs into the process of BIs may lead to misinformation and unfavorable adjudication. Ultimately, being literate about the social practices involved in SNSs and surveillance would benefit not only investigators, but anyone, including academics, looking at individuals in online spaces.
Ouagal, M; Berkvens, D; Hendrikx, P; Fecher-Bourgeois, F; Saegerman, C
In sub-Saharan Africa, most epidemiological surveillance networks for animal diseases were temporarily funded by foreign aid. It should be possible for national public funds to ensure the sustainability of such decision support tools. Taking the epidemiological surveillance network for animal diseases in Chad (REPIMAT) as an example, this study aims to estimate the network's cost by identifying the various costs and expenditures for each level of intervention. The network cost was estimated on the basis of an analysis of the operational organisation of REPIMAT, additional data collected in surveys and interviews with network field workers and a market price listing for Chad. These costs were then compared with those of other epidemiological surveillance networks in West Africa. The study results indicate that REPIMAT costs account for 3% of the State budget allocated to the Ministry of Livestock. In Chad in general, as in other West African countries, fixed costs outweigh variable costs at every level of intervention. The cost of surveillance principally depends on what is needed for surveillance at the local level (monitoring stations) and at the intermediate level (official livestock sectors and regional livestock delegations) and on the cost of the necessary equipment. In African countries, the cost of surveillance per square kilometre depends on livestock density.
Grange, Zoë L; VAN Andel, Mary; French, Nigel P; Gartrell, Brett D
Social network analysis is being increasingly used in epidemiology and disease modeling in humans, domestic animals, and wildlife. We investigated this tool in describing a translocation network (area that allows movement of animals between geographically isolated locations) used for the conservation of an endangered flightless rail, the Takahe (Porphyrio hochstetteri). We collated records of Takahe translocations within New Zealand and used social network principles to describe the connectivity of the translocation network. That is, networks were constructed and analyzed using adjacency matrices with values based on the tie weights between nodes. Five annual network matrices were created using the Takahe data set, each incremental year included records of previous years. Weights of movements between connected locations were assigned by the number of Takahe moved. We calculated the number of nodes (i(total)) and the number of ties (t(total)) between the nodes. To quantify the small-world character of the networks, we compared the real networks to random graphs of the equivalent size, weighting, and node strength. Descriptive analysis of cumulative annual Takahe movement networks involved determination of node-level characteristics, including centrality descriptors of relevance to disease modeling such as weighted measures of in degree (k(i)(in)), out degree (k(i)(out)), and betweenness (B(i)). Key players were assigned according to the highest node measure of k(i)(in), k(i)(out), and B(i) per network. Networks increased in size throughout the time frame considered. The network had some degree small-world characteristics. Nodes with the highest cumulative tie weights connecting them were the captive breeding center, the Murchison Mountains and 2 offshore islands. The key player fluctuated between the captive breeding center and the Murchison Mountains. The cumulative networks identified the captive breeding center every year as the hub of the network until the final
Nappi, A.; Perrella, A; Bellopede, P.; Lanza, A.; Izzi, A.; Spatarella, M.; Sbreglia, C
Background Direct Antiviral Agents (DAAs) for HCV therapy represents a step ahead in the cure of chronic hepatitis C. Notwithstanding the promising results in several clinical trials, few data are available on adverse effects in real life settings. Methods We have evaluated 170 patients with persistent infection and on those eligible to treatment we have followed up them through a network managed by clinician and hospital pharmacist. Results According to our data we have found that 41% (32 ou...
Latshaw, Megan Weil; Degeberg, Ruhiyyih; Patel, Surili Sutaria; Rhodes, Blaine; King, Ewa; Chaudhuri, Sanwat; Nassif, Julianne
The United States lacks a comprehensive, nationally-coordinated, state-based environmental health surveillance system. This lack of infrastructure leads to: • varying levels of understanding of chemical exposures at the state & local levels • often inefficient public health responses to chemical exposure emergencies (such as those that occurred in the Flint drinking water crisis, the Gold King mine spill, the Elk river spill and the Gulf Coast oil spill) • reduced ability to measure the impact of public health interventions or environmental policies • less efficient use of resources for cleaning up environmental contamination Establishing the National Biomonitoring Network serves as a step toward building a national, state-based environmental health surveillance system. The Network builds upon CDC investments in emergency preparedness and environmental public health tracking, which have created advanced chemical analysis and information sharing capabilities in the state public health systems. The short-term goal of the network is to harmonize approaches to human biomonitoring in the US, thus increasing the comparability of human biomonitoring data across states and communities. The long-term goal is to compile baseline data on exposures at the state level, similar to data found in CDC's National Report on Human Exposure to Environmental Chemicals. Barriers to success for this network include: available resources, effective risk communication strategies, data comparability & sharing, and political will. Anticipated benefits include high quality data on which to base public health and environmental decisions, data with which to assess the success of public health interventions, improved risk assessments for chemicals, and new ways to prioritize environmental health research.
Kendrick, R.; Duncan, A.; Wilm, J.; Thurman, S. T.; Stubbs, D. M.; Ogden, C.
limited telescope is, therefore, replaced by in-process integration and test as part of the PIC fabrication that substantially reduces associated schedule and cost. The low profile and low SWaP of a SPIDER system enables high resolution imaging with a payload that is similar in size and aspect ratio to a solar panel. This allows high resolution low cost options for space based space surveillance telescopes. The low SWaP design enables hosted payloads, cubesat designs as well as traditional bus options that are lower cost. We present a description of the concept and preliminary simulation and experimental data that demonstrate the imaging capabilities of the SPIDER technique.
Muench, David; Hilsenbeck, Barbara; Kieritz, Hilke; Becker, Stefan; Grosselfinger, Ann-Kristin; Huebner, Wolfgang; Arens, Michael
We are living in a world dependent on sophisticated technical infrastructure. Malicious manipulation of such critical infrastructure poses an enormous threat for all its users. Thus, running a critical infrastructure needs special attention to log the planned maintenance or to detect suspicious events. Towards this end, we present a knowledge-based surveillance approach capable of logging visual observable events in such an environment. The video surveillance modules are based on appearance-based person detection, which further is used to modulate the outcome of generic processing steps such as change detection or skin detection. A relation between the expected scene behavior and the underlying basic video surveillance modules is established. It will be shown that the combination already provides sufficient expressiveness to describe various everyday situations in indoor video surveillance. The whole approach is qualitatively and quantitatively evaluated on a prototypical scenario in a server room.
Full Text Available In this work, we present a multi-camera surveillance system based on the use of self-organizing neural networks to represent events on video. The system processes several tasks in parallel using GPUs (graphic processor units. It addresses multiple vision tasks at various levels, such as segmentation, representation or characterization, analysis and monitoring of the movement. These features allow the construction of a robust representation of the environment and interpret the behavior of mobile agents in the scene. It is also necessary to integrate the vision module into a global system that operates in a complex environment by receiving images from multiple acquisition devices at video frequency. Offering relevant information to higher level systems, monitoring and making decisions in real time, it must accomplish a set of requirements, such as: time constraints, high availability, robustness, high processing speed and re-configurability. We have built a system able to represent and analyze the motion in video acquired by a multi-camera network and to process multi-source data in parallel on a multi-GPU architecture.
SULIMAN, C.; CRUCERU, C.; Moldoveanu, F.
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 obtaine...
Zaidi, Syed Sohail Zahoor; Asghar, Humayun; Sharif, Salmaan; Alam, Muhammad Masroor
World Health Assembly (WHA) in 1988 encouraged the member states to launch Global Polio Eradication Initiative (GPEI) (resolution WHA41.28) against "the Crippler" called poliovirus, through strong routine immunization program and intensified surveillance systems. Since its launch, global incidence of poliomyelitis has been reduced by more than 99 % and the disease squeezed to only three endemic countries (Afghanistan, Pakistan, and Nigeria) out of 125. Today, poliomyelitis is on the verge of eradication, and their etiological agents, the three poliovirus serotypes, are on the brink of extinction from the natural environment. The last case of poliomyelitis due to wild type 2 strain occurred in 1999 in Uttar Pradesh, India whereas the last paralytic case due to wild poliovirus type 3 (WPV3) was seen in November, 2012 in Yobe, Nigeria. Despite this progress, undetected circulation cannot fully rule out the eradication as most of the poliovirus infections are entirely subclinical; hence sophisticated environmental surveillance is needed to ensure the complete eradication of virus. Moreover, the vaccine virus in under-immunized communities can sometimes revert and attain wild type characteristics posing a big challenge to the program.
Laura Blackburn; Rebecca Epanchin-Niell; Alexandra Thompson; Andrew Liebhold; Jacqueline Beggs
Efforts to detect and eradicate invading populations before they establish are a critical component of national biosecurity programmes. An essential element for maximizing the efficiency of these efforts is the balancing of expenditures on surveillance (e.g. trapping) versus treatment (e.g. eradication). Identifying the optimal allocation of resources towards...
Full Text Available With the evolution and fusion of wireless sensor network and embedded camera technologies, distributed smart camera networks have emerged as a new class of systems for wide-area surveillance applications. Wireless networks, however, introduce a number of constraints to the system that need to be considered, notably the communication bandwidth constraints. Existing approaches for target tracking using a camera network typically utilize target handover mechanisms between cameras, or combine results from 2D trackers in each camera into 3D target estimation. Such approaches suffer from scale selection, target rotation, and occlusion, drawbacks typically associated with 2D tracking. In this paper, we present an approach for tracking multiple targets directly in 3D space using a network of smart cameras. The approach employs multi-view histograms to characterize targets in 3D space using color and texture as the visual features. The visual features from each camera along with the target models are used in a probabilistic tracker to estimate the target state. We introduce four variations of our base tracker that incur different computational and communication costs on each node and result in different tracking accuracy. We demonstrate the effectiveness of our proposed trackers by comparing their performance to a 3D tracker that fuses the results of independent 2D trackers. We also present performance analysis of the base tracker along Quality-of-Service (QoS and Quality-of-Information (QoI metrics, and study QoS vs. QoI trade-offs between the proposed tracker variations. Finally, we demonstrate our tracker in a real-life scenario using a camera network deployed in a building.
Keller, Mikaela; Blench, Michael; Tolentino, Herman; Freifeld, Clark C; Mandl, Kenneth D; Mawudeku, Abla; Eysenbach, Gunther; Brownstein, John S
Free or low-cost sources of unstructured information, such as Internet news and online discussion sites, provide detailed local and near real-time data on disease outbreaks, even in countries that lack traditional public health surveillance. To improve public health surveillance and, ultimately, interventions, we examined 3 primary systems that process event-based outbreak information: Global Public Health Intelligence Network, HealthMap, and EpiSPIDER. Despite similarities among them, these systems are highly complementary because they monitor different data types, rely on varying levels of automation and human analysis, and distribute distinct information. Future development should focus on linking these systems more closely to public health practitioners in the field and establishing collaborative networks for alert verification and dissemination. Such development would further establish event-based monitoring as an invaluable public health resource that provides critical context and an alternative to traditional indicator-based outbreak reporting.
Willeberg, Preben; Nielsen, Liza Rosenbaum; Salman, Mo
Risk-based surveillance systems reveal occurrence of disease or infection in a sample of population units, which are selected on the basis of risk factors for the condition under study. The purpose of such systems for supporting practical animal disease policy formulations and management decisions...... are: A: to detect an emerging disease or infection, if it becomes introduced into a population; or B: to substantiate freedom from a condition in a population; or C: to detect cases and estimate the prevalence of an endemic condition in a population. In risk-based surveillance these aims should be met...... applicable risk estimate for use in designing and evaluating a risk-based surveillance system would be a crude (unadjusted) relative risk, odds ratio or apparent prevalence. Risk estimates found in the published literature, however, are often the results of multivariable analyses implicitly adjusting...
Willeberg, Preben; Nielsen, Liza Rosenbaum; Salman, Mo
Risk-based surveillance systems reveal occurrence of disease or infection in a sample of population units, which are selected on the basis of risk factors for the condition under study. The purpose of such systems for supporting practical animal disease policy formulations and management decisions...... applicable risk estimate for use in designing and evaluating a risk-based surveillance system would be a crude (unadjusted) relative risk, odds ratio or apparent prevalence. Risk estimates found in the published literature, however, are often the results of multivariable analyses implicitly adjusting...... the estimates for confounding from other risk factors. We describe some potential unintentional effects when using adjusted risk estimates in evaluating the efficacy and sensitivity of risk-based surveillance systems (SSe). In two examples, we quantify and compare the efficacy and SSe using adjusted and crude...
Full Text Available Turning a city into a smart city has attracted considerable attention. A smart city can be seen as a city that uses digital technology not only to improve the quality of people’s life, but also, to have a positive impact in the environment and, at the same time, offer efficient and easy-to-use services. A fundamental aspect to be considered in a smart city is people’s safety and welfare, therefore, having a good security system becomes a necessity, because it allows us to detect and identify potential risk situations, and then take appropriate decisions to help people or even prevent criminal acts. In this paper we present an architecture for automated video surveillance based on the cloud computing schema capable of acquiring a video stream from a set of cameras connected to the network, process that information, detect, label and highlight security-relevant events automatically, store the information and provide situational awareness in order to minimize response time to take the appropriate action.
Full Text Available The dynamic nature of new information and/or knowledge is a big challenge for information systems. Early knowledge management systems focused entirely on technologies for storing, searching and retrieving data; these systems have proved a failure. Juirsica and Mylopoulos1 suggested that in order to build effective technologies for knowledge management, we need to further our understanding of how individuals, groups and organisations use knowledge. As the focus on knowledge management for organisations and consortia alike is moving towards a keen appreciation of how deeply knowledge is embedded in people’s experiences, there is a general realisation that knowledge cannot be stored or captured digitally. This puts more emphasis in creating enabling environments for interactions that stimulate knowledge sharing.Our work aims at developing an un-obtrusive intelligent system that glues together effective contemporary and traditional technologies to aid these interactions and manage the information captured. In addition this system will include tools to aid propagating a repository of scientific information relevant to surveillance of infectious diseases to complement knowledge shared and/or acts as a point of reference.This work is ongoing and based on experiences in developing a knowledge network management system for the Southern African Centre of Infectious Disease Surveillance (SACIDS, A One Health consortium of southern African academic and research institutions involved with infectious diseases of humans and animals in partnership with world-renowned centres of research in industrialised countries.
Bøge, Ask Risom; Lauritsen, Peter
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...
According to the relationship between the antibody concentration and the pathogen intrusion intensity, here we present an immunity-based model for the network security risk estimation (Insre). In Insre, the concepts and formal definitions of self,nonself, antibody, antigen and lymphocyte in the network security domain are given. Then the mathematical models of the self-tolerance, the clonal selection, the lifecycle of mature lymphocyte, immune memory and immune surveillance are established. Building upon the above models, a quantitative computation model for network security risk estimation,which is based on the calculation of antibody concentration, is thus presented. By using Insre, the types and intensity of network attacks, as well as the risk level of network security, can be calculated quantitatively and in real-time. Our theoretical analysis and experimental results show that Insre is a good solution to real-time risk evaluation for the network security.
Troppy, Scott; Haney, Gillian; Cocoros, Noelle; Cranston, Kevin; DeMaria, Alfred
The Massachusetts Virtual Epidemiologic Network (MAVEN) was deployed in 2006 by the Massachusetts Department of Public Health, Bureau of Infectious Disease to serve as an integrated, Web-based disease surveillance and case management system. MAVEN replaced program-specific, siloed databases, which were inaccessible to local public health and unable to integrate electronic reporting. Disease events are automatically created without human intervention when a case or laboratory report is received and triaged in real time to state and local public health personnel. Events move through workflows for initial notification, case investigation, and case management. Initial development was completed within 12 months and recent state regulations mandate the use of MAVEN by all 351 jurisdictions. More than 300 local boards of health are using MAVEN, there are approximately one million events, and 70 laboratories report electronically. MAVEN has demonstrated responsiveness and flexibility to emerging diseases while also streamlining routine surveillance processes and improving timeliness of notifications and data completeness, although the long-term resource requirements are significant.
Meratnia, Nirvana; Havinga, Paul J.M.; Casari, Paolo; Petrioli, Chiara; Grythe, Knut; Husoy, Thor; Zorzi, Michele
This paper provides an overview of the CLAM project, which aims at developing a collaborative embedded monitoring and control platform for submarine surveillance by combining cutting edge acoustic vector sensor technology and 1D, 2D, 3D sensor arrays, underwater wireless sensor networks protocol des
Expansion of syndromic vaccine preventable disease surveillance to include bacterial meningitis and Japanese encephalitis: evaluation of adapting polio and measles laboratory networks in Bangladesh, China and India, 2007-2008.
Cavallaro, Kathleen F; Sandhu, Hardeep S; Hyde, Terri B; Johnson, Barbara W; Fischer, Marc; Mayer, Leonard W; Clark, Thomas A; Pallansch, Mark A; Yin, Zundong; Zuo, Shuyan; Hadler, Stephen C; Diorditsa, Serguey; Hasan, A S M Mainul; Bose, Anindya S; Dietz, Vance
Surveillance for acute flaccid paralysis with laboratory confirmation has been a key strategy in the global polio eradication initiative, and the laboratory platform established for polio testing has been expanded in many countries to include surveillance for cases of febrile rash illness to identify measles and rubella cases. Vaccine-preventable disease surveillance is essential to detect outbreaks, define disease burden, guide vaccination strategies and assess immunization impact. Vaccines now exist to prevent Japanese encephalitis (JE) and some etiologies of bacterial meningitis. We evaluated the feasibility of expanding polio-measles surveillance and laboratory networks to detect bacterial meningitis and JE, using surveillance for acute meningitis-encephalitis syndrome in Bangladesh and China and acute encephalitis syndrome in India. We developed nine syndromic surveillance performance indicators based on international surveillance guidelines and calculated scores using supervisory visit reports, annual reports, and case-based surveillance data. Scores, variable by country and targeted disease, were highest for the presence of national guidelines, sustainability, training, availability of JE laboratory resources, and effectiveness of using polio-measles networks for JE surveillance. Scores for effectiveness of building on polio-measles networks for bacterial meningitis surveillance and specimen referral were the lowest, because of differences in specimens and techniques. Polio-measles surveillance and laboratory networks provided useful infrastructure for establishing syndromic surveillance and building capacity for JE diagnosis, but were less applicable for bacterial meningitis. Laboratory-supported surveillance for vaccine-preventable bacterial diseases will require substantial technical and financial support to enhance local diagnostic capacity. Published by Elsevier Ltd.
Fox, Jesse; Warber, Katie M
Social networking sites serve as both a source of information and a source of tension between romantic partners. Previous studies have investigated the use of Facebook for monitoring former and current romantic partners, but why certain individuals engage in this behavior has not been fully explained. College students (N=328) participated in an online survey that examined two potential explanatory variables for interpersonal electronic surveillance (IES) of romantic partners: attachment style and relational uncertainty. Attachment style predicted both uncertainty and IES, with preoccupieds and fearfuls reporting the highest levels. Uncertainty did not predict IES, however. Future directions for research on romantic relationships and online surveillance are explored.
Madoff, Lawrence C; Li, Annie
The emergence of infectious diseases, caused by novel pathogens or the spread of existing ones to new populations and regions, represents a continuous threat to humans and other species. The early detection of emerging human, animal, and plant diseases is critical to preventing the spread of infection and protecting the health of our species and environment. Today, more than 75% of emerging infectious diseases are estimated to be zoonotic and capable of crossing species barriers and diminishing food supplies. Traditionally, surveillance of diseases has relied on a hierarchy of health professionals that can be costly to build and maintain, leading to a delay or interruption in reporting. However, Internet-based surveillance systems bring another dimension to epidemiology by utilizing technology to collect, organize, and disseminate information in a more timely manner. Partially and fully automated systems allow for earlier detection of disease outbreaks by searching for information from both formal sources (e.g., World Health Organization and government ministry reports) and informal sources (e.g., blogs, online media sources, and social networks). Web-based applications display disparate information online or disperse it through e-mail to subscribers or the general public. Web-based early warning systems, such as ProMED-mail, the Global Public Health Intelligence Network (GPHIN), and Health Map, have been able to recognize emerging infectious diseases earlier than traditional surveillance systems. These systems, which are continuing to evolve, are now widely utilized by individuals, humanitarian organizations, and government health ministries.
Appice, Annalisa; Fumarola, Fabio; Malerba, Donato
Sensor networks comprise of a number of sensors installed across a spatially distributed network, which gather information and periodically feed a central server with the measured data. The server monitors the data, issues possible alarms and computes fast aggregates. As data analysis requests may concern both present and past data, the server is forced to store the entire stream. But the limited storage capacity of a server may reduce the amount of data stored on the disk. One solution is to compute summaries of the data as it arrives, and to use these summaries to interpolate the real data.
Herini, Elisabeth Siti; Gunadi; Triono, Agung; Mulyadi, Asal Wahyuni Erlin; Mardin, Niprida; Rusipah; Soenarto, Yati; Reef, Susan E
Congenital rubella syndrome (CRS) has serious consequences, such as miscarriage, stillbirth, and severe birth defects in infants, resulting from rubella virus infection during pregnancy. However, rubella vaccine has not yet been implemented in Indonesia. This study aimed (1) to estimate the incidence of CRS in Indonesia, (2) describe the clinical features of CRS at our referral hospital, and (3) pilot a CRS surveillance system to be extended to other hospitals. We conducted a 4-month prospective surveillance study of infants aged Indonesia. Conducting hospital-based surveillance of CRS in other hospitals in Indonesia may be appropriate. What is Known: •Congenital rubella syndrome (CRS) has serious consequences in infants resulting from rubella virus infection during pregnancy. •The incidence of CRS in most developed countries has greatly decreased since implementation of rubella vaccination. •Rubella vaccine has not yet been implemented in many developing countries. What is New: •The number of laboratory-confirmed CRS cases among Indonesian infants was high. •Implementation of rubella vaccine into immunization programs in Indonesia is important because of the high number of CRS cases. •Our study highlights the need for ongoing prospective surveillance of CRS in Indonesia.
Mai, Cara T; Kirby, Russell S; Correa, Adolfo; Rosenberg, Deborah; Petros, Michael; Fagen, Michael C
Birth defects remain a leading cause of infant mortality in the United States and contribute substantially to health care costs and lifelong disabilities. State population-based surveillance systems have been established to monitor birth defects, yet no recent systematic examination of their efforts in the United States has been conducted. To understand the current population-based birth defects surveillance practices in the United States. The National Birth Defects Prevention Network conducted a survey of US population-based birth defects activities that included questions about operational status, case ascertainment methodology, program infrastructure, data collection and utilization, as well as priorities and challenges for surveillance programs. Birth defects contacts in the United States, including District of Columbia and Puerto Rico, received the survey via e-mail; follow-up reminders via e-mails and telephone were used to ensure a 100% response rate. Forty-three states perform population-based surveillance for birth defects, covering approximately 80% of the live births in the United States. Seventeen primarily use an active case-finding approach and 26 use a passive case-finding approach. These programs all monitor major structural malformations; however, passive case-finding programs more often monitor a broader list of conditions, including developmental conditions and newborn screening conditions. Active case-finding programs more often use clinical reviewers, cover broader pregnancy outcomes, and collect more extensive information, such as family history. More than half of the programs (24 of 43) reported an ability to conduct follow-up studies of children with birth defects. The breadth and depth of information collected at a population level by birth defects surveillance programs in the United States serve as an important data source to guide public health action. Collaborative efforts at the state and national levels can help harmonize data
马海军; 王文中; 翟素兰; 罗斌
Crow d counting in surveillance video is one of the important modern security tasks with high research significance and application value .It has made great progress in recent years ,but still has not solved the problems about accuracy of crow d counting in surveillance video and time consuming of high resolution images .Therefore ,the crowd counting algo‐rithm by incorporating convolutional neural network and ridge regression was proposed in this paper .We could get the crowd density map from regression of the centers of heads through convolutional neural network ,then used ridge regression model to analyze the crowd density map to got the number of people in current frame .The proposed algorithm had been tested on several videos and compared with several classical algorithms .The experimental performance validated the effectiveness of the proposed method .%监控视频中人数统计是现代安防的重要任务之一，具有较高的研究意义和应用价值。虽然近年来取得较大的进展，但仍无法很好地解决监控场景人数统计精度、高清图像耗时问题。为此，作者提出一种基于卷积神经网络与岭回归联合的人数统计方法。通过卷积神经网络回归图像中人头中心点获得人群密度分布特征图，然后使用岭回归模型分析人群密度分布特征图得到该帧图像对应的人数。作者提出的算法通过在多组视频图像上进行了测试，并与经典算法做了比较。实验结果验证了作者方法的有效性。
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.
Simon, Gaelle; Larsen, Lars Erik; Duerrwald, Ralf
Swine influenza causes concern for global veterinary and public health officials. In continuing two previous networks that initiated the surveillance of swine influenza viruses (SIVs) circulating in European pigs between 2001 and 2008, a third European Surveillance Network for Influenza in Pigs......, mainly conducted through passive surveillance programs, resulted in the examination of more than 9 000 herds in 17 countries. Influenza A viruses were detected in 31% of herds examined from which 1887 viruses were preliminary characterized. The dominating subtypes were the three European enzootic SIVs......: avian-like swine H1N1 (53.6%), human-like reassortant swine H1N2 (13%) and human-like reassortant swine H3N2 (9.1%), as well as pandemic A/H1N1 2009 (H1N1pdm) virus (10.3%). Viruses from these four lineages co-circulated in several countries but with very different relative levels of incidence...
National Aeronautics and Space Administration — A WiMAX networked UAV Telemetry System (WNUTS) is designed for net-centric remote sensing and launch range surveillance applications. WNUTS integrates a MIMO powered...
Gongora, Victor; Trotman, Mark; Thomas, Reginald; Max, Millien; Zamora, Pastor Alfonso; Lepoureau, Maria Teresa Frias; Phanord, Siméon; Quirico, Jocelyn; Douglas, Kirk; Pegram, Rupert; Martinez, Dominique; Petitclerc, Martial; Chouin, Emilie; Marchal, Céline; Chavernac, David; Doyen, David; Vachiéry, Nathalie; Molia, Sophie; Hendrikx, Pascal; Lefrançois, Thierry
The Caribbean Animal Health Network (CaribVET) is a collaboration of veterinary services, diagnostic laboratories, research institutes, universities, and regional/international organizations to improve animal health in the Caribbean. New tools were used by the network to develop regional animal health activities: (1) A steering committee, a coordination unit, and working groups on specific diseases or activities were established. The working group on avian influenza used a collaborative Web site to develop a regionally harmonized avian influenza surveillance protocol and performance indicators. (2) A specific network was implemented on West Nile virus (WNV) to describe the WNV status of the Caribbean countries, to perform a technology transfer of WNV diagnostics, and to establish a surveillance system. (3) The CaribVET Web site (http://www.caribvet.net) encompasses information on surveillance systems, diagnostic laboratories, conferences, bibliography, and diseases of major concern in the region. It is a participatory Web site allowing registered users to add or edit information, pages, or data. An online notification system of sanitary information was set up for Guadeloupe to improve knowledge on animal diseases and facilitate early alert.
Ndihokubwayo Jean B
Full Text Available Abstract Background The recent emergence of a novel strain of influenza virus with pandemic potential underscores the need for quality surveillance and laboratory services to contribute to the timely detection and confirmation of public health threats. To provide a framework for strengthening disease surveillance and response capacities in African countries, the World Health Organization Regional Headquarters for Africa (AFRO developed Integrated Disease Surveillance and Response (IDSR aimed at improving national surveillance and laboratory systems. IDSR emphasizes the linkage of information provided by public health laboratories to the selection of relevant, appropriate and effective public health responses to disease outbreaks. Methods We reviewed the development of Rwanda's National Reference Laboratory (NRL to understand essential structures involved in creating a national public health laboratory network. We reviewed documents describing the NRL's organization and record of test results, conducted site visits, and interviewed health staff in the Ministry of Health and in partner agencies. Findings were developed by organizing thematic categories and grouping examples within them. We purposefully sought to identify success factors as well as challenges inherent in developing a national public health laboratory system. Results Among the identified success factors were: a structured governing framework for public health surveillance; political commitment to promote leadership for stronger laboratory capacities in Rwanda; defined roles and responsibilities for each level; coordinated approaches between technical and funding partners; collaboration with external laboratories; and use of performance results in advocacy with national stakeholders. Major challenges involved general infrastructure, human resources, and budgetary constraints. Conclusions Rwanda's experience with collaborative partnerships contributed to creation of a functional
Dixis Figueroa Pedraza
Full Text Available Abstract Objectives: to identify and analyze the scientific literature on child growth monitoring in the context of the primary public healthcare service network in Brazil, focusing on the main problems detected in studies. Methods: the review was based on searches ofSciELO, Lilacs and PubMed databases to identify articles published between 2006 and 2014. The articles were categorized according to the analytical categories of structure (items needed to carry out primary activities or work processes (set of activities and procedures used in the management of resources. Results: of the 16 articles included in this review, only six dealt with structure and, in these, thetraining of professionals and availability of protocols were the most frequently identified problems. Processes, addressed in 15 articles, highlighted the underutilization of Child Health Handbook to record growth measurements and the adoption of guidelines on the basis of notes taken. Conclusions: the difficulties found demonstrate the everyday circumstances of the public health service which have a detrimental effect on growth surveillance.
Cohen, Jean Marie; Silva, Maria Laura; Caini, Saverio; Ciblak, Meral; Mosnier, Anne; Daviaud, Isabelle; Matias, Gonçalo; Badur, Selim; Valette, Martine; Enouf, Vincent; Paget, John; Fleming, Douglas M
Influenza B represents a high proportion of influenza cases in some seasons (even over 50%). The Influenza B study in General Practice (IBGP) is a multicenter study providing information about the clinical, demographic and socio-economic characteristics of patients affected by lab-confirmed influenza A or B. Influenza B patients and age-matched influenza A patients were recruited within the sentinel surveillance networks of France and Turkey in 2010-11 and 2011-12 seasons. Data were collected for each patient at the swab test day, after 9±2 days and, if not recovered, after 28±5 days. It was related to patient's characteristics, symptoms at presentation, vaccination status, prescriptions of antibiotics and antivirals, duration of illness, follow-up consultations in general practice or emergency room. We performed descriptive analyses and developed a multiple regression model to investigate the effect of patients and disease characteristics on the duration of illness. Overall, 774 influenza cases were included in the study: 419 influenza B cases (209 in France and 210 in Turkey) and 355 influenza A cases (205 in France and 150 in Turkey). There were no differences between influenza A and B patients in terms of clinical presentation and number of consultations with a practitioner; however, the use of antivirals was higher among influenza B patients in both countries. The average (median) reported duration of illness in the age groups 0-14 years, 15-64 years and 65+ years was 7.4 (6), 8.7 (8) and 10.5 (9) days in France, and 6.3 (6), 8.2 (7) and 9.2 (6) days in Turkey; it increased with age but did not differ by virus type; increased duration of illness was associated with antibiotics prescription. In conclusion, our findings show that influenza B infection appears not to be milder disease than influenza A infection.
Full Text Available Japheth A Opintan,1 Mercy J Newman,1 Reuben E Arhin,1 Eric S Donkor,1 Martha Gyansa-Lutterodt,2 William Mills-Pappoe3 1Department of Medical Microbiology, School of Biomedical and Allied Health Sciences, University of Ghana, 2Pharmaceutical Services, Ministry of Health, Ghana Health Services, 3Clinical Laboratory Unit, Institutional Care Division, Ghana Health Service, Accra, Ghana Abstract: Global efforts are underway to combat antimicrobial resistance (AMR. A key target in this intervention is surveillance for local and national action. Data on AMR in Ghana are limited, and monitoring of AMR is nonexistent. We sought to generate baseline data on AMR, and to assess the readiness of Ghana in laboratory-based surveillance. Biomedical scientists in laboratories across Ghana with capacity to perform bacteriological culture were selected and trained. In-house standard operating protocols were used to perform microbiological investigations on clinical specimens. Additional microbiological tests and data analyses were performed at a centralized laboratory. Surveillance data were stored and analyzed using WHONET program files. A total of 24 laboratories participated in the training, and 1,598 data sets were included in the final analysis. A majority of the bacterial species were isolated from outpatients (963 isolates; 60.3%. Urine (617 isolates; 38.6% was the most common clinical specimen cultured, compared to blood (100 isolates; 6.3%. Ten of 18 laboratories performed blood culture. Bacteria isolated included Escherichia coli (27.5%, Pseudomonas spp. (14.0%, Staphylococcus aureus (11.5%, Streptococcus spp. (2.3%, and Salmonella enterica serovar Typhi (0.6%. Most of the isolates were multidrug-resistant, and over 80% of them were extended-spectrum beta-lactamases-producing. Minimum inhibitory concentration levels at 50% and at 90% for ciprofloxacin, ceftriaxone, and amikacin on selected multidrug-resistant bacteria species ranged between 2 µg/mL and
The deployment of visual surveillance and monitoring systems has reached massive proportions. Consequently, a need to automate the processes involved in retrieving useful information from surveillance videos, such as detecting and counting objects, and interpreting their individual and joint behavio
The deployment of visual surveillance and monitoring systems has reached massive proportions. Consequently, a need to automate the processes involved in retrieving useful information from surveillance videos, such as detecting and counting objects, and interpreting their individual and joint behavio
Full Text Available Abstract Background Expatriates are a distinct population at unique risk for health problems related to their travel exposure. Methods We analyzed GeoSentinel data comparing ill returned expatriates with other travelers for demographics, travel characteristics, and proportionate morbidity (PM for travel-related illness. Results Our study included 2,883 expatriates and 11,910 non-expatriates who visited GeoSentinel clinics ill after travel. Expatriates were more likely to be male, do volunteer work, be long-stay travelers (>6 months, and have sought pre-travel advice. Compared to non-expatriates, expatriates returning from Africa had higher proportionate morbidity (PM for malaria, filariasis, schistosomiasis, and hepatitis E; expatriates from the Asia-Pacific region had higher PM for strongyloidiasis, depression, and anxiety; expatriates returning from Latin America had higher PM for mononucleosis and ingestion-related infections (giardiasis, brucellosis. Expatriates returning from all three regions had higher PM for latent TB, amebiasis, and gastrointestinal infections (other than acute diarrhea compared to non-expatriates. When the data were stratified by travel reason, business expatriates had higher PM for febrile systemic illness (malaria and dengue and vaccine-preventable infections (hepatitis A, and volunteer expatriates had higher PM for parasitic infections. Expatriates overall had higher adjusted odds ratios for latent TB and lower odds ratios for acute diarrhea and dermatologic illness. Conclusions Ill returned expatriates differ from other travelers in travel characteristics and proportionate morbidity for specific diseases, based on the region of exposure and travel reason. They are more likely to present with more serious illness.
Based on the community structure characteristics, theory, and methods of frequent subgraph mining, network motifs findings are firstly introduced into social network analysis; the tendentiousness evaluation function and the importance evaluation function are proposed for effectiveness assessment. Compared with the traditional way based on nodes centrality degree, the new approach can be used to analyze the properties of social network more fully and judge the roles of the nodes effectively. I...
Full Text Available This paper describes the design and development of Blimp Based Air Vehicle with the ability to perform vertical take-off and landing that can serve the purpose of surveillance in an area dangerous for humans. The design uses vectored thrusting to propel the blimp. Software is developed for visualizing the mechanical design of the blimp given its design parameters. The blimp is then developed by utilizing Polyurethane as fabric and helium gas is used for lifting the blimp. Brushless DC motors are used to generate thrust for lifting the blimp and servo motor is used to shift the motion axis of blimp by rotating the assembly of gondola carrying the propellers. A wireless camera is mounted for the purpose of surveillance and control. The video data is received at the base station where it isrecorded and afterwards analyzed for the presence of certain object. The control signals for the motors are generated and transmitted by an AT89C52 microcontroller through a 6-channel transmitter. The receiver present on the blimp decodes these signals and controls the motors accordingly.
Zheng, Fei; Wang, Guijin; Lin, Xinggang
Face recognition in surveillance is a hot topic in computer vision due to the strong demand for public security and remains a challenging task owing to large variations in viewpoint and illumination of cameras. In surveillance, image sets are the most natural form of input by incorporating tracking. Recent advances in set-based matching also show its great potential for exploring the feature space for face recognition by making use of multiple samples of subjects. In this paper, we propose a novel method that exploits the salient features (such as eyes, noses, mouth) in set-based matching. To represent image sets, we adopt the affine hull model, which can general unseen appearances in the form of affine combinations of sample images. In our proposal, a robust part detector is first used to find four salient parts for each face image: two eyes, nose, and mouth. For each part, we construct an affine hull model by using the local binary pattern histograms of multiple samples of the part. We also construct an affine model for the whole face region. Then, we find the closest distance between the corresponding affine hull models to measure the similarity between parts/face regions, and a weighting scheme is introduced to combine the five distances (four parts and the whole face region) to obtain the final distance between two subjects. In the recognition phase, a nearest neighbor classifier is used. Experiments on the public ChokePoint dataset and our dataset demonstrate the superior performance of our method.
Construction of high resolution images from low resolution sequences is often important in surveillance applications. In this letter, an affine based multi-scale block-matching image registration algorithm is first proposed. The images to be registered are divided into overlapped blocks of different size according to its motions. The Least Square (LS) image registration algorithm is extended to match the blocks. Then an object based Super Resolution (SR) scheme is designed, the Maximum A Priori (MAP) super resolution algorithm is extended to enhance the resolution of the interest objects. Experimental results show that the proposed multi-scale registration method provides more accurate registration between frames. Further more, the object based super resolution scheme shows an enhanced performance compared with the traditional MAP method.
Zhao, Y Q; Ma, W J
Internet data is introduced into public health arena under the features of fast updating and tremendous volume. Mining and analyzing internet data, researchers can model the internet-based surveillance system to assess the distribution of health-related events. There are two main types of internet-based surveillance systems, i.e. active and passive, which are distinguished by the sources of information. Through passive surveillance system, information is collected from search engine and social media while the active system gathers information through provision of the volunteers. Except for serving as a real-time and convenient complementary approach to traditional disease, food safety and adverse drug reaction surveillance program, Internet-based surveillance system can also play a role in health-related behavior surveillance and policy evaluation. Although several techniques have been applied to filter information, the accuracy of internet-based surveillance system is still bothered by the false positive information. In this article, we have summarized the development and application of internet-based surveillance system in public health to provide reference for a better surveillance program in China.
Nikolay, Birgit; Salje, Henrik; Sturm-Ramirez, Katharine; Azziz-Baumgartner, Eduardo; Homaira, Nusrat; Iuliano, A. Danielle; Paul, Repon C.; Hossain, M. Jahangir; Cauchemez, Simon; Gurley, Emily S.
Background The International Health Regulations outline core requirements to ensure the detection of public health threats of international concern. Assessing the capacity of surveillance systems to detect these threats is crucial for evaluating a country’s ability to meet these requirements. Methods and Findings We propose a framework to evaluate the sensitivity and representativeness of hospital-based surveillance and apply it to severe neurological infectious diseases and fatal respiratory infectious diseases in Bangladesh. We identified cases in selected communities within surveillance hospital catchment areas using key informant and house-to-house surveys and ascertained where cases had sought care. We estimated the probability of surveillance detecting different sized outbreaks by distance from the surveillance hospital and compared characteristics of cases identified in the community and cases attending surveillance hospitals. We estimated that surveillance detected 26% (95% CI 18%–33%) of severe neurological disease cases and 18% (95% CI 16%–21%) of fatal respiratory disease cases residing at 10 km distance from a surveillance hospital. Detection probabilities decreased markedly with distance. The probability of detecting small outbreaks (three cases) dropped below 50% at distances greater than 26 km for severe neurological disease and at distances greater than 7 km for fatal respiratory disease. Characteristics of cases attending surveillance hospitals were largely representative of all cases; however, neurological disease cases aged <5 y or from the lowest socioeconomic group and fatal respiratory disease cases aged ≥60 y were underrepresented. Our estimates of outbreak detection rely on suspected cases that attend a surveillance hospital receiving laboratory confirmation of disease and being reported to the surveillance system. The extent to which this occurs will depend on disease characteristics (e.g., severity and symptom specificity) and
Full Text Available Underwater acoustic sensor networks (UWASNs are playing a lot of interest in ocean applications, such as ocean pollution monitoring, ocean animal surveillance, oceanographic data collection, assisted- navigation, and offshore exploration, UWASN is composed of underwater sensors that engage sound to transmit information collected in the ocean. The reason to utilize sound is that radio frequency (RF signals used by terrestrial sensor networks (TWSNs can merely transmit a few meters in the water. Unfortunately, the efficiency of UWASNs is inferior to that of the terrestrial sensor networks (TWSNs. Some of the challenges in under water communication are propagation delay, high bit error rate and limited bandwidth. Our aim is to minimize the power consumption and to improve the reliability of data transmission by finding the optimum number of clusters based on energy consumption.
Full Text Available Abstract Background Day care-associated infectious diseases are widely recognized as a public health problem but rarely studied. Insights into their dynamics and their association with the day care setting are important for effective decision making in management of infectious disease control. This paper describes the purpose, design and potential of our national multi-center, day care-based sentinel surveillance network for infectious diseases (the KIzSS network. The aim of the KIzSS network is to acquire a long-term insight into the syndromic and microbiological aspects of day care-related infectious diseases and associated disease burden and to model these aspects with day care setting characteristics. Methods/design The KIzSS network applies a prospective cohort design, following day care centers rather than individual children or staff members over time. Data on infectious disease symptoms and related morbidity (children and staff, medical consumption, absenteeism and circulating enteric pathogens (children are collected on a daily, weekly or monthly basis. Every two years, a survey is performed to assess the characteristics of participating day care centers. Discussion The KIzSS network offers a unique potential to study infectious disease dynamics in the day care setting over a sustained period of time. The created (biodatabases will help us to assess day care-related disease burden of infectious diseases among attending children and staff and their relation with the day care setting. This will support the much needed development of evidence-based and pragmatic guidelines for infectious disease control in day care centers.
倪佳琳; 许浩; 胡雪明; 钟海明; 张静; 金汇明; 肖文佳; 许学斌; 冉陆
Objective The establishment of a laboratory network surveillance system and analyze the antibiotic resistance characteristics of Salmonella enteritidis,and provide scientific evidence for the prevention and control measures development.Methods A total of 184 foodborne and environmental strains and 1146 diarrhea strains of Salmonella enteritidis were isolated in 8 public health laboratories and 24 clinical laboratories from 2006 to 2012,their drug resistance to 16 antibiotics were detected by using disk diffusion method (K-B method) and the drug resistance database was established with WHONET software.Results The detection rate of Salmonella enteritidis in poultry meat was highest (155/184).The laboratory confirmed cases were mainly distributed in people aged 18-59 years and ＜ 5 years.More cases occurred in children aged 1-4 years than those aged ＜ 1 years,and the cases in people aged ＞ 60 years increased gradually.The resistant rate of all Salmonella enteritidis strains to nalidixic acid was over 90％.The multidrug-resistant strains (to ampicillin,chloramphenicol,streptomycin,sulfamethoxazole and tetracycline) were isolated from chicken meat samples and 1 foodborne sample (in 2009),while foodborne strains and diarrhea strains resistant to cefepime were detected in 2011 and 2008 respectively.The resistant rates of diarrhea strains resistant to ciprofloxacin and cefotaxime were higher than those of foodbome strains.The strains resistant to the third generation cephalosporins and ciprofloxacin in lower age group accounted for approximately 2/3 and 1/2 of the total.Conclusion Community acquired and foodborne infections of Salmonella enteritidis were detected in Changning district.The multidrug resistant strains detected in Changning were probably highly pathogenic.It is important to improve laboratory's routine detection capacity,reduce the elderly and children's unnecessary antibiotic exposure for the mitigation of disease burden caused by Salmonella
Saxton, Peter J W; Dickson, Nigel P; Hughes, Anthony J
Most HIV behavioural surveillance programmes for gay, bisexual and other men who have sex with men (MSM) sample from location-based (offline) or web-based (online) populations, but few combine these two streams. MSM sampled online have been found to differ demographically and behaviourally from those sampled offline, meaning trends identified in one system may not hold for the other. The aim was to examine trends among MSM responding to supplementary repeat online behavioural surveillance surveys who had not participated in offline surveillance earlier that year in the same city, to see whether trends were parallel, converged or diverged. We recruited a total of 1613 MSM from an Internet dating site in Auckland, New Zealand in 2006, 2008 and 2011 using identical questionnaires and eligibility criteria to offline surveillance. Condom use was stable over time, HIV testing rates rose, the proportion reporting over 20 recent male partners declined, and anal intercourse rates increased, consistent with trends in offline surveillance conducted concomitantly and reported elsewhere. Variant trends included greater stability in condom use with casual partners among online-recruited MSM, and a rise in regular fuckbuddy partnering not identified among offline-recruited MSM. Among MSM recruited online, the frequency of checking Internet dating profiles increased between 2008 and 2011. In conclusion, supplementary web-based behavioural surveillance among MSM generally corroborates trends identified in offline surveillance. There are however some divergent trends, that would have been overlooked if only one form of surveillance had been conducted. As MSM populations increasingly shift their socialising patterns online and diversify, multiple forms of HIV behavioural monitoring may be required.
Ober-Gecks, Antje; Zwicker, Marius; Henrich, Dominik
A graphics processing unit (GPU)-based implementation of a space carving method for the reconstruction of the photo hull is presented. In particular, the generalized voxel coloring with item buffer approach is transferred to the GPU. The fast computation on the GPU is realized by an incrementally calculated standard deviation within the likelihood ratio test, which is applied as color consistency criterion. A fast and efficient computation of complete voxel-pixel projections is provided using volume rendering methods. This generates a speedup of the iterative carving procedure while considering all given pixel color information. Different volume rendering methods, such as texture mapping and raycasting, are examined. The termination of the voxel carving procedure is controlled through an anytime concept. The photo hull algorithm is examined for its applicability to real-world surveillance scenarios as an online reconstruction method. For this reason, a GPU-based redesign of a visual hull algorithm is provided that utilizes geometric knowledge about known static occluders of the scene in order to create a conservative and complete visual hull that includes all given objects. This visual hull approximation serves as input for the photo hull algorithm.
Calavia, Lorena; Baladrón, Carlos; Aguiar, Javier M; Carro, Belén; Sánchez-Esguevillas, Antonio
This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network.
Kozma, Robert; Wang, Lan; Iftekharuddin, Khan; McCracken, Ernest; Khan, Muhammad; Islam, Khandakar; Bhurtel, Sushil R; Demirer, R Murat
The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios.
Haddad Samira M
Full Text Available Abstract Background The purpose of the study was to evaluate intraclass correlation coefficients (ICC of variables concerning personal characteristics, structure, outcome and process in the Brazilian Network for Surveillance of Severe Maternal Morbidity study conducted to identify severe maternal morbidity/near miss cases using the World Health Organization criteria. Method It was a cross-sectional, multicenter study involving 27 hospitals providing care for pregnant women in Brazil. Cluster size and the mean size of the primary sampling unit were described. Estimated prevalence rates, ICC, their respective 95% confidence intervals, the design effect and the mean cluster size were presented for each variable. Results Overall, 9,555 cases of severe maternal morbidity (woman admitted with potentially life-threatening conditions, near miss events or death were included in the study. ICC ranged from Conclusions These results may be used to design new cluster trials in maternal and perinatal health and to help calculate sample sizes.
R. Murat Demirer
Full Text Available The feasibility of using Commercial Off-The-Shelf (COTS sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost ( < $50 US miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios.
Ao, Trong T; Rahman, Mahmudur; Haque, Farhana; Chakraborty, Apurba; Hossain, M Jahangir; Haider, Sabbir; Alamgir, A S M; Sobel, Jeremy; Luby, Stephen P; Gurley, Emily S
We assessed a media-based public health surveillance system in Bangladesh during 2010-2011. The system is a highly effective, low-cost, locally appropriate, and sustainable outbreak detection tool that could be used in other low-income, resource-poor settings to meet the capacity for surveillance outlined in the International Health Regulations 2005.
Greeff SC de; Melker HE de; Schellekes JFP; Conyn-van Spaendonk MAE; CIE; LIS
To gain insight into the incidence and severity of pertussis in the Netherlands in 1999 and 2000, surveillance data based on notifications, laboratory data, hospitalisations and deaths were analysed for these two years and compared to the 1989-1998 period. Results of the paediatric surveillance are
Rasamoelina-Andriamanivo, H; Duboz, R; Lancelot, R; Maminiaina, O F; Jourdan, M; Rakotondramaro, T M C; Rakotonjanahary, S N; de Almeida, R Servan; Rakotondravao; Durand, B; Chevalier, V
Madagascar's 36.5-million-head poultry industry holds a foremost place in its economy and the livelihood of its people. Unfortunately, regular Newcastle disease outbreaks associated with high mortality causes high losses for smallholders and threatens their livelihood. Therefore, Madagascar is seeking concrete, achievable and sustainable methods for the surveillance and the control of Newcastle disease. In this paper, we present and analyze the results of a field study conducted in Madagascar between December 2009 and December 2010. The study area was the Lac Alaotra region, a landlocked area in the north-eastern part of the country's center. Poultry trading is suspected of playing a major role in the spread of avian diseases, especially in developing countries characterized by many live-bird markets and middlemen. Therefore, the goals of our study were to: (i) describe and analyze smallholders' poultry trading network in the Lake Alaotra region using social network analysis; (ii) assess the role of the network in the spread of Newcastle disease; and (iii) propose the implementation of a targeted disease surveillance based on the characteristics of the poultry trading network. We focused our field study on the harvesting of two data sets. The first is a complete description of the poultry trading network in the landlocked area of Lac Alaotra, including a description of the poultry movements between groups of villages. The second set of data measures the occurrence of outbreaks in the same area by combining a participatory approach with an event-based surveillance method. These data were used to determine the attributes of the network, and to statistically assess the association between the position of nodes and the occurrence of outbreaks. By using social network analysis techniques combined with a classification method and a logistic model, we finally identified 3 nodes (set of villages), of the 387 in the initial network, to focus on for surveillance and control
Meijer, Adam; Brown, Caroline; Hungnes, Olav; Schweiger, Brunhilde; Valette, Martine; Werf, Sylvie van der; Zambon, Maria
All laboratories participating in the Community Network of Reference Laboratories for Human Influenza in Europe (CNRL) co-ordinated by the European Influenza Surveillance Scheme (EISS) should be able to perform a range of influenza diagnostics. This includes direct detection, culture, typing, subtyp
Meijer, A.; Brown, C.; Hungnes, O.; Schweiger, B.; Valette, M.; Werf, S. van der; Zambon, M.
All laboratories participating in the Community Network of Reference Laboratories for Human Influenza in Europe (CNRL) co-ordinated by the European Influenza Surveillance Scheme (EISS) should be able to perform a range of influenza diagnostics. This includes direct detection, culture, typing, subtyp
María R Viñas
Full Text Available BACKGROUND: To implement effective control measures, timely outbreak detection is essential. Shigella is the most common cause of bacterial diarrhea in Argentina. Highly resistant clones of Shigella have emerged, and outbreaks have been recognized in closed settings and in whole communities. We hereby report our experience with an evolving, integrated, laboratory-based, near real-time surveillance system operating in six contiguous provinces of Argentina during April 2009 to March 2012. METHODOLOGY: To detect localized shigellosis outbreaks timely, we used the prospective space-time permutation scan statistic algorithm of SaTScan, embedded in WHONET software. Twenty three laboratories sent updated Shigella data on a weekly basis to the National Reference Laboratory. Cluster detection analysis was performed at several taxonomic levels: for all Shigella spp., for serotypes within species and for antimicrobial resistance phenotypes within species. Shigella isolates associated with statistically significant signals (clusters in time/space with recurrence interval ≥365 days were subtyped by pulsed field gel electrophoresis (PFGE using PulseNet protocols. PRINCIPAL FINDINGS: In three years of active surveillance, our system detected 32 statistically significant events, 26 of them identified before hospital staff was aware of any unexpected increase in the number of Shigella isolates. Twenty-six signals were investigated by PFGE, which confirmed a close relationship among the isolates for 22 events (84.6%. Seven events were investigated epidemiologically, which revealed links among the patients. Seventeen events were found at the resistance profile level. The system detected events of public health importance: infrequent resistance profiles, long-lasting and/or re-emergent clusters and events important for their duration or size, which were reported to local public health authorities. CONCLUSIONS/SIGNIFICANCE: The WHONET-SaTScan system may serve as a
Olson Donald R
Full Text Available Abstract Background We conducted a pilot utility evaluation and information needs assessment of the Distribute Project at the 2010 Washington State Public Health Association (WSPHA Joint Conference. Distribute is a distributed community-based syndromic surveillance system and network for detection of influenza-like illness (ILI. Using qualitative methods, we assessed the perceived usefulness of the Distribute system and explored areas for improvement. Nine state and local public health professionals participated in a focus group (n = 6 and in semi-structured interviews (n = 3. Field notes were taken, summarized and analyzed. Findings Several emergent themes that contribute to the perceived usefulness of system data and the Distribute system were identified: 1 Standardization: a common ILI syndrome definition; 2 Regional Comparability: views that support county-by-county comparisons of syndromic surveillance data; 3 Completeness: complete data for all expected data at a given time; 4 Coverage: data coverage of all jurisdictions in WA state; 5 Context: metadata incorporated into the views to provide context for graphed data; 6 Trusted Data: verification that information is valid and timely; and 7 Customization: the ability to customize views as necessary. As a result of the focus group, a new county level health jurisdiction expressed interest in contributing data to the Distribute system. Conclusion The resulting themes from this study can be used to guide future information design efforts for the Distribute system and other syndromic surveillance systems. In addition, this study demonstrates the benefits of conducting a low cost, qualitative evaluation at a professional conference.
Viñas, María R; Tuduri, Ezequiel; Galar, Alicia; Yih, Katherine; Pichel, Mariana; Stelling, John; Brengi, Silvina P; Della Gaspera, Anabella; van der Ploeg, Claudia; Bruno, Susana; Rogé, Ariel; Caffer, María I; Kulldorff, Martin; Galas, Marcelo
To implement effective control measures, timely outbreak detection is essential. Shigella is the most common cause of bacterial diarrhea in Argentina. Highly resistant clones of Shigella have emerged, and outbreaks have been recognized in closed settings and in whole communities. We hereby report our experience with an evolving, integrated, laboratory-based, near real-time surveillance system operating in six contiguous provinces of Argentina during April 2009 to March 2012. To detect localized shigellosis outbreaks timely, we used the prospective space-time permutation scan statistic algorithm of SaTScan, embedded in WHONET software. Twenty three laboratories sent updated Shigella data on a weekly basis to the National Reference Laboratory. Cluster detection analysis was performed at several taxonomic levels: for all Shigella spp., for serotypes within species and for antimicrobial resistance phenotypes within species. Shigella isolates associated with statistically significant signals (clusters in time/space with recurrence interval ≥365 days) were subtyped by pulsed field gel electrophoresis (PFGE) using PulseNet protocols. In three years of active surveillance, our system detected 32 statistically significant events, 26 of them identified before hospital staff was aware of any unexpected increase in the number of Shigella isolates. Twenty-six signals were investigated by PFGE, which confirmed a close relationship among the isolates for 22 events (84.6%). Seven events were investigated epidemiologically, which revealed links among the patients. Seventeen events were found at the resistance profile level. The system detected events of public health importance: infrequent resistance profiles, long-lasting and/or re-emergent clusters and events important for their duration or size, which were reported to local public health authorities. The WHONET-SaTScan system may serve as a model for surveillance and can be applied to other pathogens, implemented by other
Viñas, María R.; Tuduri, Ezequiel; Galar, Alicia; Yih, Katherine; Pichel, Mariana; Stelling, John; Brengi, Silvina P.; Della Gaspera, Anabella; van der Ploeg, Claudia; Bruno, Susana; Rogé, Ariel; Caffer, María I.; Kulldorff, Martin; Galas, Marcelo
Background To implement effective control measures, timely outbreak detection is essential. Shigella is the most common cause of bacterial diarrhea in Argentina. Highly resistant clones of Shigella have emerged, and outbreaks have been recognized in closed settings and in whole communities. We hereby report our experience with an evolving, integrated, laboratory-based, near real-time surveillance system operating in six contiguous provinces of Argentina during April 2009 to March 2012. Methodology To detect localized shigellosis outbreaks timely, we used the prospective space-time permutation scan statistic algorithm of SaTScan, embedded in WHONET software. Twenty three laboratories sent updated Shigella data on a weekly basis to the National Reference Laboratory. Cluster detection analysis was performed at several taxonomic levels: for all Shigella spp., for serotypes within species and for antimicrobial resistance phenotypes within species. Shigella isolates associated with statistically significant signals (clusters in time/space with recurrence interval ≥365 days) were subtyped by pulsed field gel electrophoresis (PFGE) using PulseNet protocols. Principal Findings In three years of active surveillance, our system detected 32 statistically significant events, 26 of them identified before hospital staff was aware of any unexpected increase in the number of Shigella isolates. Twenty-six signals were investigated by PFGE, which confirmed a close relationship among the isolates for 22 events (84.6%). Seven events were investigated epidemiologically, which revealed links among the patients. Seventeen events were found at the resistance profile level. The system detected events of public health importance: infrequent resistance profiles, long-lasting and/or re-emergent clusters and events important for their duration or size, which were reported to local public health authorities. Conclusions/Significance The WHONET-SaTScan system may serve as a model for
Lefrançois, T; Hendrikx, P; Vachiéry, N; Ehrhardt, N; Millien, M; Gomez, L; Gouyet, L; Gerbier, G; Gongora, V; Shaw, J; Trotman, M
The Caribbean region is considered to be at risk for avian influenza (AI) because of predominance of the backyard poultry system, important commercial poultry production, migratory birds and disparities in the surveillance systems. The Caribbean animal health network (CaribVET) has developed tools to implement AI surveillance in the region: (i) a regionally harmonized surveillance protocol, (ii) specific web pages for AI surveillance on http://www.caribvet.net, and (iii) a diagnostic network for the Caribbean including AI virus molecular diagnostic capability in Guadeloupe and technology transfer. Altogether 303 samples from four Caribbean countries were tested between June 2006 and March 2009 by real time PCR either for importation purposes or following clinical suspicion. Following AI H5N2 outbreaks in the Dominican Republic in 2007, a questionnaire was developed to collect data for risk analysis of AI spread in the region through fighting cocks. The infection pathway of Martinique commercial poultry sector by AI through introduction of infected cocks was designed and recommendations were provided to the Caribbean veterinary services to improve fighting cock movement controls and biosecurity measures. Altogether, these CaribVET activities contribute to strengthen surveillance of AI in the Caribbean region and may allow the development of research studies on AI risk analysis.
Schooley, Michael G.; Thompson, Dean
This report documents the results of an internal DRS effort to develop an Ethernet based integrated defense system to improve defense of cities, harbors, airports, power production, energy supplies, bridges, monuments, dams and so forth. Results of the integration of multiple SCOUT LPI radars and multiple Electro-optical targeting systems will be provided, illustrating the benefits of interfacing surveillance radars with imaging sensors to confirm detection and provide visual recognition and identification. An analysis of the handover errors will be provided including errors due to; sensor platforms location and orientation uncertainty, target location measurement errors, data latency and motion prediction errors, which contribute to target handoff and the re-acquisition timeline. These predictions will be compared to measured results. The system architecture will be defined including; security, support for both stationary and moving sensor platforms, remote control of sensor systems and distribution of imagery through the network and remote diagnostics, maintenance and software upgrades. Growth capabilities include secure wireless communication to/from moving platforms, integration with sonar and seismic sensors, cooperative location of friendly forces and acoustic detection and triangulation of gunshots with automated cueing of sensors and security forces to the shooters most probable location. The use of ad hoc multi-hopping wireless networking supplements hardwire networks, augments disaster response capabilities, provides high-speed communications for moving platforms and supplements GPS outage areas.
Wireless sensor networks have been employed in a wide variety of applications, despite the limited energy and communication resources at each sensor node. Low power custom VLSI chips implementing passive acoustic sensing algorithms have been successfully integrated into an acoustic surveillance unit and demonstrated for detection and location of sound sources. In this dissertation, I explore active and passive acoustic sensing techniques, signal processing and classification algorithms for detection and classification in a multinodal sensor network environment. I will present the design and characterization of a continuous-wave micro-Doppler sonar to image objects with articulated moving components. As an example application for this system, we use it to image gaits of humans and four-legged animals. I will present the micro-Doppler gait signatures of a walking person, a dog and a horse. I will discuss the resolution and range of this micro-Doppler sonar and use experimental results to support the theoretical analyses. In order to reduce the data rate and make the system amenable to wireless sensor networks, I will present a second micro-Doppler sonar that uses bandpass sampling for data acquisition. Speech recognition algorithms are explored for biometric identifications from one's gait, and I will present and compare the classification performance of the two systems. The acoustic micro-Doppler sonar design and biometric identification results are the first in the field as the previous work used either video camera or microwave technology. I will also review bearing estimation algorithms and present results of applying these algorithms for bearing estimation and tracking of moving vehicles. Another major source of the power consumption at each sensor node is the wireless interface. To address the need of low power communications in a wireless sensor network, I will also discuss the design and implementation of ultra wideband transmitters in a three dimensional
Casanovas, R., E-mail: firstname.lastname@example.org [Unitat de Fisica Medica, Facultat de Medicina i Ciencies de la Salut, Universitat Rovira i Virgili, ES-43201 Reus (Tarragona) (Spain); Morant, J.J. [Servei de Proteccio Radiologica, Facultat de Medicina i Ciencies de la Salut, Universitat Rovira i Virgili, ES-43201 Reus (Tarragona) (Spain); Lopez, M. [Unitat de Fisica Medica, Facultat de Medicina i Ciencies de la Salut, Universitat Rovira i Virgili, ES-43201 Reus (Tarragona) (Spain); Servei de Proteccio Radiologica, Facultat de Medicina i Ciencies de la Salut, Universitat Rovira i Virgili, ES-43201 Reus (Tarragona) (Spain); Hernandez-Giron, I. [Unitat de Fisica Medica, Facultat de Medicina i Ciencies de la Salut, Universitat Rovira i Virgili, ES-43201 Reus (Tarragona) (Spain); Batalla, E. [Servei de Coordinacio d' Activitats Radioactives, Departament d' Economia i Finances, Generalitat de Catalunya, ES-08018 Barcelona (Spain); Salvado, M. [Unitat de Fisica Medica, Facultat de Medicina i Ciencies de la Salut, Universitat Rovira i Virgili, ES-43201 Reus (Tarragona) (Spain)
The automatic real-time environmental radiation surveillance network of Catalonia (Spain) comprises two subnetworks; one with 9 aerosol monitors and the other with 8 Geiger monitors together with 2 water monitors located in the Ebre river. Since September 2006, several improvements were implemented in order to get better quality and quantity of data, allowing a more accurate data analysis. However, several causes (natural causes, equipment failure, artificial external causes and incidents in nuclear power plants) may produce radiological measured values mismatched with the own station background, whether spurious without significance or true radiological values. Thus, data analysis for a 50-month period was made and allowed to establish an easily implementable statistical criterion to find those values that require special attention. This criterion proved a very useful tool for creating a properly debugged database and to give a quick response to equipment failures or possible radiological incidents. This paper presents the results obtained from the criterion application, including the figures for the expected, raw and debugged data, percentages of missing data grouped by causes and radiological measurements from the networks. Finally, based on the discussed information, recommendations for the improvement of the network are identified to obtain better radiological information and analysis capabilities. - Highlights: > Causes producing data mismatching with the own stations background are described. > Causes may be natural, equipment failure, external or nuclear plants incidents. > These causes can produce either spurious or true radiological data. > A criterion to find these data was implemented and tested for a 50-month period. > Recommendations for the improvement of the network are identified.
According to the need of video monitoring system at present, through the research of the current video monitoring system plan, the paper proposed the embedded Linux video monitoring system based on the WEB structure. The system transfers the video information out through V4L programming based video acquisition methods, with tha aid of embedded Linux network function, and in the form of WEB server. This system takes UP- TECHPXA270- S teaching and scientific research platform as a hardware development platform, with USB Webcam camera as a video acquisition tool, selects the embedded Linux operation system as software development platform, carries out the software compression of video image through the KaiYuan software library--Libjpeg, in the client-side, we can cross the platform to visit embedded video transmission server in the way of browser. System testing results show that the proposed system is practical and effective.%针对目前对视频监控系统的需求，本文通过对目前主流视频监控系统方案的研究，提出了基于WEB架构的嵌入式Linux视频监控系统。该系统通过基于V4L编程的视频采集方式，借助嵌入式Linux的网络功能，以WEB服务器的形式将视频图像信息传输出去。该系统以UP-TECHPXA270-S教学科研平台作为硬件开发平台，以USB WebCam摄像头作为视频获取工具，选择嵌入式Linux操作系统为软件开发平台，通过开源软件库libjpeg对视频图像进行软件压缩，在客户端可跨平台以浏览器的方式访问嵌入式视频传输服务器。系统测试结果表明，本文提出的系统切实有效。
Intelligence, Surveillance, and Reconnaissance ( ISR ) Applications by Latasha Solomon, Wesley Wang, and Miriam Häge...Surveillance, and Reconnaissance ( ISR ) Applications by Latasha Solomon Sensors and Electron Devices Directorate, ARL Wesley Wang...Intelligence, Surveillance, and Reconnaissance ( ISR ) Applications 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S
Willeberg, Preben; Nielsen, Liza Rosenbaum; Salman, Mo
We estimated the effects of confounder adjustment as a part of the underlying quantitative risk assessments on the performance of a hypothetical example of a risk-based surveillance system, in which a single risk factor would be used to identify high risk sampling units for testing. The differences...... between estimates of surveillance system performance with and without unwarranted confounder adjustment were shown to be of both numerical and economical significance. Analytical procedures applied to multiple risk factor datasets which yield confounder-adjusted risk estimates should be carefully...... considered for their appropriateness, if the risk estimates are to be used for informing risk-based surveillance systems....
Incidence and Trends of Infections with Pathogens Transmitted Commonly Through Food and the Effect of Increasing Use of Culture-Independent Diagnostic Tests on Surveillance - Foodborne Diseases Active Surveillance Network, 10 U.S. Sites, 2013-2016.
Marder, Ellyn P; Cieslak, Paul R; Cronquist, Alicia B; Dunn, John; Lathrop, Sarah; Rabatsky-Ehr, Therese; Ryan, Patricia; Smith, Kirk; Tobin-D'Angelo, Melissa; Vugia, Duc J; Zansky, Shelley; Holt, Kristin G; Wolpert, Beverly J; Lynch, Michael; Tauxe, Robert; Geissler, Aimee L
Foodborne diseases represent a substantial public health concern in the United States. CDC's Foodborne Diseases Active Surveillance Network (FoodNet) monitors cases reported from 10 U.S. sites* of laboratory-diagnosed infections caused by nine enteric pathogens commonly transmitted through food. This report describes preliminary surveillance data for 2016 on the nine pathogens and changes in incidences compared with 2013-2015. In 2016, FoodNet identified 24,029 infections, 5,512 hospitalizations, and 98 deaths caused by these pathogens. The use of culture-independent diagnostic tests (CIDTs) by clinical laboratories to detect enteric pathogens has been steadily increasing since FoodNet began surveying clinical laboratories in 2010 (1). CIDTs complicate the interpretation of FoodNet surveillance data because pathogen detection could be affected by changes in health care provider behaviors or laboratory testing practices (2). Health care providers might be more likely to order CIDTs because these tests are quicker and easier to use than traditional culture methods, a circumstance that could increase pathogen detection (3). Similarly, pathogen detection could also be increasing as clinical laboratories adopt DNA-based syndromic panels, which include pathogens not often included in routine stool culture (4,5). In addition, CIDTs do not yield isolates, which public health officials rely on to distinguish pathogen subtypes, determine antimicrobial resistance, monitor trends, and detect outbreaks. To obtain isolates for infections identified by CIDTs, laboratories must perform reflex culture(†); if clinical laboratories do not, the burden of culturing falls to state public health laboratories, which might not be able to absorb that burden as the adoption of these tests increases (2). Strategies are needed to preserve access to bacterial isolates for further characterization and to determine the effect of changing trends in testing practices on surveillance.
Holland, Robin L; Blanke, Steven R
In this issue of Cell Host & Microbe, Suzuki et al. (2014) describe a Vibrio cholerae Type-III-secreted effector that targets mitochondrial dynamics to dampen host innate immune signaling. This suggests that mammalian hosts possess surveillance mechanisms to monitor pathogen-mediated alterations in the integrity of normal cellular processes and organelles.
Nielsen, Jimmy Jessen
selection in Wi-Fi networks and predictive handover optimization in heterogeneous wireless networks. The investigations in this work have indicated that location based network optimizations are beneficial compared to typical link measurement based approaches. Especially the knowledge of geographical...
Full Text Available Swine influenza causes concern for global veterinary and public health officials. In continuing two previous networks that initiated the surveillance of swine influenza viruses (SIVs circulating in European pigs between 2001 and 2008, a third European Surveillance Network for Influenza in Pigs (ESNIP3, 2010-2013 aimed to expand widely the knowledge of the epidemiology of European SIVs. ESNIP3 stimulated programs of harmonized SIV surveillance in European countries and supported the coordination of appropriate diagnostic tools and subtyping methods. Thus, an extensive virological monitoring, mainly conducted through passive surveillance programs, resulted in the examination of more than 9 000 herds in 17 countries. Influenza A viruses were detected in 31% of herds examined from which 1887 viruses were preliminary characterized. The dominating subtypes were the three European enzootic SIVs: avian-like swine H1N1 (53.6%, human-like reassortant swine H1N2 (13% and human-like reassortant swine H3N2 (9.1%, as well as pandemic A/H1N1 2009 (H1N1pdm virus (10.3%. Viruses from these four lineages co-circulated in several countries but with very different relative levels of incidence. For instance, the H3N2 subtype was not detected at all in some geographic areas whereas it was still prevalent in other parts of Europe. Interestingly, H3N2-free areas were those that exhibited highest frequencies of circulating H1N2 viruses. H1N1pdm viruses were isolated at an increasing incidence in some countries from 2010 to 2013, indicating that this subtype has become established in the European pig population. Finally, 13.9% of the viruses represented reassortants between these four lineages, especially between previous enzootic SIVs and H1N1pdm. These novel viruses were detected at the same time in several countries, with increasing prevalence. Some of them might become established in pig herds, causing implications for zoonotic infections.
Simon, Gaëlle; Larsen, Lars E; Dürrwald, Ralf; Foni, Emanuela; Harder, Timm; Van Reeth, Kristien; Markowska-Daniel, Iwona; Reid, Scott M; Dan, Adam; Maldonado, Jaime; Huovilainen, Anita; Billinis, Charalambos; Davidson, Irit; Agüero, Montserrat; Vila, Thaïs; Hervé, Séverine; Breum, Solvej Østergaard; Chiapponi, Chiara; Urbaniak, Kinga; Kyriakis, Constantinos S; Brown, Ian H; Loeffen, Willie
Swine influenza causes concern for global veterinary and public health officials. In continuing two previous networks that initiated the surveillance of swine influenza viruses (SIVs) circulating in European pigs between 2001 and 2008, a third European Surveillance Network for Influenza in Pigs (ESNIP3, 2010-2013) aimed to expand widely the knowledge of the epidemiology of European SIVs. ESNIP3 stimulated programs of harmonized SIV surveillance in European countries and supported the coordination of appropriate diagnostic tools and subtyping methods. Thus, an extensive virological monitoring, mainly conducted through passive surveillance programs, resulted in the examination of more than 9 000 herds in 17 countries. Influenza A viruses were detected in 31% of herds examined from which 1887 viruses were preliminary characterized. The dominating subtypes were the three European enzootic SIVs: avian-like swine H1N1 (53.6%), human-like reassortant swine H1N2 (13%) and human-like reassortant swine H3N2 (9.1%), as well as pandemic A/H1N1 2009 (H1N1pdm) virus (10.3%). Viruses from these four lineages co-circulated in several countries but with very different relative levels of incidence. For instance, the H3N2 subtype was not detected at all in some geographic areas whereas it was still prevalent in other parts of Europe. Interestingly, H3N2-free areas were those that exhibited highest frequencies of circulating H1N2 viruses. H1N1pdm viruses were isolated at an increasing incidence in some countries from 2010 to 2013, indicating that this subtype has become established in the European pig population. Finally, 13.9% of the viruses represented reassortants between these four lineages, especially between previous enzootic SIVs and H1N1pdm. These novel viruses were detected at the same time in several countries, with increasing prevalence. Some of them might become established in pig herds, causing implications for zoonotic infections.
Anderka, Marlene; Mai, Cara T; Romitti, Paul A; Copeland, Glenn; Isenburg, Jennifer; Feldkamp, Marcia L; Krikov, Sergey; Rickard, Russel; Olney, Richard S; Canfield, Mark A; Stanton, Carol; Mosley, Bridget; Kirby, Russell S
Population-based birth defects surveillance is a core public health activity in the United States (U.S.); however, the lack of national data quality standards has limited the use of birth defects surveillance data across state programs. Development of national standards will facilitate data aggregation and utilization across birth defects surveillance programs in the U.S. Based on national standards for other U.S. public health surveillance programs, existing National Birth Defects Prevention Network (NBDPN) guidelines for conducting birth defects surveillance, and information from birth defects surveillance programs regarding their current data quality practices, we developed 11 data quality measures that focused on data completeness (n = 5 measures), timeliness (n = 2), and accuracy (n = 4). For each measure, we established tri-level performance criteria (1 = rudimentary, 2 = essential, 3 = optimal). In January 2014, we sent birth defects surveillance programs in each state, District of Columbia, Puerto Rico, Centers for Disease Control and Prevention (CDC), and the U.S. Department of Defense Birth and Infant Health Registry an invitation to complete a self-administered NBDPN Standards Data Quality Assessment Tool. The completed forms were electronically submitted to the CDC for analyses. Of 47 eligible population-based surveillance programs, 45 submitted a completed assessment tool. Two of the 45 programs did not meet minimum inclusion criteria and were excluded; thus, the final analysis included information from 43 programs. Average scores for four of the five completeness performance measures were above level 2. Conversely, the average scores for both timeliness measures and three of the four accuracy measures were below level 2. Surveillance programs using an active case-finding approach scored higher than programs using passive case-finding approaches for the completeness and accuracy measures, whereas their average scores were lower
用户在家中安装一台嵌入式多媒体中心即可随时随地使用PC客户端或智能手机App查看所属社区的公共视频监控资源和用户自家私有的视频资源。设计实时监控视频分析处理软件，检测家中的弱势群体是否出现危险的情况，将3G智能手机与互联网结合应用，当危险发生时软件将在第一时间做出智能判断并对危险情景进行截图，然后通过互联网将截图以及报警信息发送给相关监护人用户，为用户的迅速判断以及合理决定提供可视化的数据支撑。%The user in the center of the home to install a embedded multimedia can be anywhere at any time using the PC client,or a smart phone app to view the community's public video surveillance and user's own private video resources. Real-time monitoring of video analysis software, check whether the disadvantaged groups of the home has the dangerous situation,combines 3G smart phones and the internet application,when danger happening software will make intelligent judgment and to a dangerous situation in the first time to capture,then the screenshot via the internet and send alarm information to the related guardian users, for users to quickly determine if provide the data visualization and reasonable decision support.
Full Text Available Abstract Background Also in Mediterranean countries, which are considered a low risk population for cardiovascular disease (CVD, the increase in body mass index (BMI has become a public health priority. To evaluate the feasibility of a CVD and obesity surveillance network, forty General Practitioners (GPs were engaged to perform a screening to assess obesity, cardiovascular risk, lifestyle habits and medication use. Methods A total of 1,046 women and 1,044 men aged 35–74 years were randomly selected from GPs' lists stratifying by age decade and gender. Anthropometric and blood pressure measurements were performed by GPs using standardized methodologies. BMI was computed and categorized in normal weight (BMI 18.5–24.9 kg/m2, overweight (BMI 25.0–29.9 kg/m2 and obese (BMI ≥ 30 kg/m2. Food frequency (per day: fruits and vegetables; per week: meat, cheese, fish, pulses, chocolate, fried food, sweet, wholemeal food, rotisserie food and sugar drink and physical activity (at work and during leisure time were investigated through a questionnaire. CVD risk was assessed using the Italian CUORE Project risk function. Results The percentage of missing values was very low. Prevalence of overweight was 34% in women and 50% in men; prevalence of obesity was 23% in both men and women. Level of physical activity was mostly low or very low. BMI was inversely associated with consumption of pulses, rotisserie food, chocolate, sweets and physical activity during leisure time and directly associated with consumption of meat. Mean value of total cardiovascular risk was 4% in women and 11% in men. One percent of women and 16% of men were at high cardiovascular risk (≥ 20% in 10 years. Normal weight persons were four times more likely to be at low risk than obese persons. Conclusion This study demonstrated the feasibility of a surveillance network of GPs in Italy focusing on obesity and other CVD risk factors. It also provided information on lifestyle habits
Full Text Available Abstract Background Oral rabies vaccination programs have been implemented to control the spread of wildlife rabies in the United States. However, current surveillance systems are inadequate for the efficient management and evaluation of these large scale vaccine baiting programs. With this in mind, a GIS-based rabies surveillance database and Internet mapping application was created. This surveillance system, RabID, provides a new resource for the rapid mapping and dissemination of data on animal rabies cases in relation to unaffected, enzootic, and baited areas where current interventions are underway. Results RabID is a centralized database for diagnostic and demographic information collected by local, state, and federal agencies involved in rabies surveillance. The geo-referenced database remits data to an Internet-accessible mapping application that displays rabies surveillance data in relation to environmental and geographic features. Conclusion RabID provides a pioneering example of the power of geographically based Internet-accessible, infectious disease surveillance. This surveillance system was developed from existing technology and is readily adaptable to other infectious diseases and may be particularly useful for zoonoses. The development and application of public health informatics technology may enhance the effectiveness of public health interventions and allow better evaluation of public health interventions.
Cloud Networking: Understanding Cloud-Based Data Center Networks explains the evolution of established networking technologies into distributed, cloud-based networks. Starting with an overview of cloud technologies, the book explains how cloud data center networks leverage distributed systems for network virtualization, storage networking, and software-defined networking. The author offers insider perspective to key components that make a cloud network possible such as switch fabric technology and data center networking standards. The final chapters look ahead to developments in architectures
Vilain, Pascal; Bourdé, Arnaud; Cassou, Pierre-Jean Marianne dit; Jacques-Antoine, Yves; Morbidelli, Philippe; Filleul, Laurent
Objective To show with examples that syndromic surveillance system can be a reactive tool for public health surveillance. Introduction The late health events such as the heat wave of 2003 showed the need to make public health surveillance evolve in France. Thus, the French Institute for Public Health Surveillance has developed syndromic surveillance systems based on several information sources such as emergency departments (1). In Reunion Island, the chikungunya outbreak of 2005–2006, then the influenza pandemic of 2009 contributed to the implementation and the development of this surveillance system (2–3). In the past years, this tool allowed to follow and measure the impact of seasonal epidemics. Nevertheless, its usefulness for the detection of minor unusual events had yet to be demonstrated. Methods In Reunion Island, the syndromic surveillance system is based on the activity of six emergency departments. Two types of indicators are constructed from collected data: - Qualitative indicators for the alert (every visit whose diagnostic relates to a notifiable disease or potential epidemic disease);- Quantitative indicators for the epidemic/cluster detection (number of visits based on syndromic grouping). Daily and weekly analyses are carried out. A decision algorithm allows to validate the signal and to organize an epidemiological investigation if necessary. Results Each year, about 150 000 visits are registered in the six emergency departments that is 415 consultations per day on average. Several unusual health events on small-scale were detected early. In August 2011, the surveillance system allowed to detect the first autochthonous cases of measles, a few days before this notifiable disease was reported to health authorities (Figure 1). In January 2012, the data of emergency departments allowed to validate the signal of viral meningitis as well as to detect a cluster in the West of the island and to follow its trend. In June 2012, a family foodborne illness
Ross, H A; Lento, G M; Dalebout, M L; Goode, M; Ewing, G; McLaren, P; Rodrigo, A G; Lavery, S; Baker, C S
DNA Surveillance is a Web-based application that assists in the identification of the species and population of unknown specimens by aligning user-submitted DNA sequences with a validated and curated data set of reference sequences. Phylogenetic analyses are performed and results are returned in tree and table format summarizing the evolutionary distances between the query and reference sequences. DNA Surveillance is implemented with mitochondrial DNA (mtDNA) control region sequences representing the majority of recognized cetacean species. Extensions of the system to include other gene loci and taxa are planned. The service, including instructions and sample data, is available at http://www.dna-surveillance.auckland.ac.nz.
A sophisticated real time architecture for capturing relevant battlefield information of personnel and terrestrial events from a network of mast based imaging and unmanned aerial systems (UAS) with target detection, tracking, classification and visualization is presented. Persistent surveillance of personnel and vehicles is achieved using a unique spatial and temporally invariant motion detection and tracking algorithm for mast based cameras in combination with aerial remote sensing to autonomously monitor unattended ground based sensor networks. UAS autonomous routing is achieved using bio-inspired algorithms that mimic how bacteria locate nutrients in their environment. Results include field test data, performance and lessons learned. The technology also has application to detecting and tracking low observables (manned and UAS), counter MANPADS, airport bird detection and search and rescue operations.
Sangal, Lucky; Joshi, Sudhir; Anandan, Shalini; Balaji, Veeraraghavan; Johnson, Jaichand; Satapathy, Asish; Haldar, Pradeep; Rayru, Ramesh; Ramamurthy, Srinath; Raghavan, Asha; Bhatnagar, Pankaj
As part of national program, laboratory supported vaccine preventable diseases surveillance was initiated in Kerala in 2015. Mechanisms have been strengthened for case investigation, reporting, and data management. Specimens collected and sent to state and reference laboratories for confirmation and molecular surveillance. The major objective of this study is to understand the epidemiological information generated through surveillance system and its utilization for action. Surveillance data captured from reporting register, case investigation forms, and laboratory reports was analyzed. Cases were allotted unique ID and no personal identifying information was used for analysis. Throat swabs were collected from investigated cases as part of surveillance system. All Corynebacterium diphtheriae isolates were confirmed with standard biochemical tests, ELEK's test, and real-time PCR. Isolates were characterized using whole genome-based multi locus sequence typing method. Case investigation forms and laboratory results were recorded electronically. Public health response by government was also reviewed. A total of 533 cases were identified in 11 districts of Kerala in 2016, of which 92% occurred in 3 districts of north Kerala; Malappuram, Kozhikode, and Kannur. Almost 79% cases occurred in >10 years age group. In surveillance for providing real-time information on disease occurrence and mortality is imperative. The epidemiological data thus generated was used for targeted interventions and to formulate vaccine policies. The data on molecular surveillance have given an insight on strain variation and transmission patterns.
Davidson, Michael W; Haim, Dotan A; Radin, Jennifer M
Seasonal influenza infects approximately 5-20% of the U.S. population every year, resulting in over 200,000 hospitalizations. The ability to more accurately assess infection levels and predict which regions have higher infection risk in future time periods can instruct targeted prevention and treatment efforts, especially during epidemics. Google Flu Trends (GFT) has generated significant hope that "big data" can be an effective tool for estimating disease burden and spread. The estimates generated by GFT come in real-time--two weeks earlier than traditional surveillance data collected by the U.S. Centers for Disease Control and Prevention (CDC). However, GFT had some infamous errors and is significantly less accurate at tracking laboratory-confirmed cases than syndromic influenza-like illness (ILI) cases. We construct an empirical network using CDC data and combine this with GFT to substantially improve its performance. This improved model predicts infections one week into the future as well as GFT predicts the present and does particularly well in regions that are most likely to facilitate influenza spread and during epidemics.
Gordean L Bjornson; Scheifele, David W; Alison Bell; Arlene King
OBJECTIVE: To identify and describe all cases of invasive group A streptococcal (GAS) infection occurring in British Columbia during a two-year period.DESIGN: Active, laboratory-based surveillance with supplemental case description.SETTING: Forty community and regional hospitals and the provincial laboratory participated, encompassing all health regions.POPULATION STUDIED: Entire provincial population from April 1, 1996 to March 31, 1998.MAIN RESULTS: Over the 24-month surveillance period, 18...
Madsen, Per Printz
The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...
Madsen, Per Printz
The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...
Singal, Amit G; Tiro, Jasmin; Li, Xilong; Adams-Huet, Beverley; Chubak, Jessica
Fewer than 1 in 5 patients with cirrhosis receive hepatocellular carcinoma (HCC) surveillance; however, most studies were performed in select patient populations, which may not be informative of practice patterns in population-based community practices. Further, few reported guideline-concordant consistent surveillance rates. Characterize guideline-concordant HCC surveillance rates and patient-level factors associated with surveillance among a population-based cohort of patients with cirrhosis. We retrospectively characterized HCC surveillance among cirrhosis patients followed between January 2010 and December 2012 at an integrated health care delivery system in Washington state. Consistent surveillance was defined as an ultrasound every 6 months, and inconsistent surveillance was defined as ≥1 ultrasound during the 2-year follow-up period. Univariate and multivariate analyses were conducted to identify correlates of HCC surveillance receipt. Of 1137 patients with cirrhosis, 22 (2%) underwent consistent surveillance, 371 (33%) had inconsistent surveillance, and 744 (65%) received no surveillance during follow-up. Correlates of HCC surveillance receipt in multivariate analysis included Gastroenterology/Hepatology subspecialty care [odds ratio (OR), 1.88; 95% confidence interval (CI), 1.44-2.46], Child Pugh B/C cirrhosis (OR, 1.61; 95% CI, 1.07-2.43), elevated aspartate aminotransferase (OR, 1.63; 95% CI, 1.13-2.35), and etiology of liver disease. Compared with hepatitis C-infected patients, patients with hepatitis B infection were more likely to undergo surveillance (OR, 2.72; 95% CI, 1.28-5.81), whereas patients with alcohol-related cirrhosis (OR, 0.63; 95% CI, 0.42-0.93) and nonalcoholic steatohepatitis (OR, 0.39; 95% CI, 0.28-0.56) were less likely to undergo surveillance. Although one third of patients undergo inconsistent HCC surveillance, surveillance.
Full Text Available In many court cases, surveillance videos are used as significant court evidence. As these surveillance videos can easily be forged, it may cause serious social issues, such as convicting an innocent person. Nevertheless, there is little research being done on forgery of surveillance videos. This paper proposes a forensic technique to detect forgeries of surveillance video based on sensor pattern noise (SPN. We exploit the scaling invariance of the minimum average correlation energy Mellin radial harmonic (MACE-MRH correlation filter to reliably unveil traces of upscaling in videos. By excluding the high-frequency components of the investigated video and adaptively choosing the size of the local search window, the proposed method effectively localizes partially manipulated regions. Empirical evidence from a large database of test videos, including RGB (Red, Green, Blue/infrared video, dynamic-/static-scene video and compressed video, indicates the superior performance of the proposed method.
Molia, Sophie; Boly, Ismaël Ardho; Duboz, Raphaël; Coulibaly, Boubacar; Guitian, Javier; Grosbois, Vladimir; Fournié, Guillaume; Pfeiffer, Dirk Udo
Live bird markets (LBMs) play an important role in the transmission of avian influenza (AI) and Newcastle disease (ND) viruses in poultry. Our study had two objectives: (1) characterizing LBMs in Mali with a focus on practices influencing the risk of transmission of AI and ND, and (2) identifying which LBMs should be targeted for surveillance and control based on properties of the live poultry trade network. Two surveys were conducted in 2009-2010: a descriptive study in all 96 LBMs of an area encompassing approximately 98% of the Malian poultry population and a network analysis study in Sikasso county, the main poultry supplying county for the capital city Bamako. Regarding LBMs' characteristics, risk factors for the presence of AI and ND viruses (being open every day, more than 2 days before a bird is sold, absence of zoning to segregate poultry-related work flow areas, waste removal or cleaning and disinfecting less frequently than on a daily basis, trash disposal of dead birds and absence of manure processing) were present in 80-100% of the LBMs. Furthermore, LBMs tended to have wide catchment areas because of consumers' preference for village poultry meat, thereby involving a large number of villages in their supply chain. In the poultry trade network from/to Sikasso county, 182 traders were involved and 685 links were recorded among 159 locations. The network had a heterogeneous degree distribution and four hubs were identified based on measures of in-degrees, out-degrees and betweenness: the markets of Medine and Wayerma and the fairs of Farakala and Niena. These results can be used to design biosecurity-improvement interventions and to optimize the prevention, surveillance and control of transmissible poultry diseases in Malian LBMs. Further studies should investigate potential drivers (seasonality, prices) of the poultry trade network and the acceptability of biosecurity and behavior-change recommendations in the Malian socio-cultural context.
Huesch, Marco D
Surveillance of the safety of prescribed drugs after marketing approval has been secured remains fraught with complications. Formal ascertainment by providers and reporting to adverse-event registries, formal surveys by manufacturers, and mining of electronic medical records are all well-known approaches with varying degrees of difficulty, cost, and success. Novel approaches may be a useful adjunct, especially approaches that mine or sample internet-based methods such as online social networks. A novel commercial software-as-a-service data-mining product supplied by Sysomos from Datasift/Facebook was used to mine all mentions on Facebook of statins and stain-related side effects in the US in the 1-month period 9 January 2017 through 8 February 2017. A total of 4.3% of all 25,700 mentions of statins also mentioned typical stain-related side effects. Multiple methodological weaknesses stymie interpretation of this percentage, which is however not inconsistent with estimates that 5-20% of patients taking statins will experience typical side effects at some time. Future work on pharmacovigilance may be informed by this novel commercial tool, but the inability to mine the full text of a posting poses serious challenges to content categorization.
Zhou, Yan; Zlatanova, Sisi; Wang, Zhe; Zhang, Yeting; Liu, Liu
Video surveillance systems are increasingly used for a variety of 3D indoor applications. We can analyse human behaviour, discover and avoid crowded areas, monitor human traffic and so forth. In this paper we concentrate on use of surveillance cameras to track and reconstruct the path a person has followed. For the purpose we integrated video surveillance data with a 3D indoor model of the building and develop a single human moving path tracking method. We process the surveillance videos to detected single human moving traces; then we match the depth information of 3D scenes to the constructed 3D indoor network model and define the human traces in the 3D indoor space. Finally, the single human traces extracted from multiple cameras are connected with the help of the connectivity provided by the 3D network model. Using this approach, we can reconstruct the entire walking path. The provided experiments with a single person have verified the effectiveness and robustness of the method.
Astagneau, P; L'Hériteau, F; Daniel, F; Parneix, P; Venier, A-G; Malavaud, S; Jarno, P; Lejeune, B; Savey, A; Metzger, M-H; Bernet, C; Fabry, J; Rabaud, C; Tronel, H; Thiolet, J-M; Coignard, B
Surgical-site infections (SSIs) are a key target for nosocomial infection control programmes. We evaluated the impact of an eight-year national SSI surveillance system named ISO-RAISIN (infection du site opératoire - Réseau Alerte Investigation Surveillance des Infections). Consecutive patients undergoing surgery were enrolled during a three-month period each year and surveyed for 30 days following surgery. A standardised form was completed for each patient including SSI diagnosis according to standard criteria, and several risk factors such as wound class, American Society of Anesthesiologists (ASA) score, operation duration, elective/emergency surgery, and type of surgery. From 1999 to 2006, 14,845 SSIs were identified in 964,128 patients (overall crude incidence: 1.54%) operated on in 838 participating hospitals. The crude overall SSI incidence decreased from 2.04% to 1.26% (P<0.001; relative reduction: -38%) and the National Nosocomial Infections Surveillance system (NNIS)-0 adjusted SSI incidence from 1.10% to 0.74% (P<0.001; relative reduction: -33%). The most significant SSI incidence reduction was observed for hernia repair and caesarean section, and to a lesser extent, cholecystectomy, hip prosthesis arthroplasty, and mastectomy. Active surveillance striving for a benchmark throughout a network is an effective strategy to reduce SSI incidence.
Bourmpos, Michail; Argyris, Apostolos; Syvridis, Dimitris
A continuously growing number of municipalities has optical fiber networks supporting communications at their disposal. These fiber installations can also be utilized to convey low data optical signals from a large number of deployed sensing elements, usually positioned in critical infrastructure locations, providing a variety of useful information. Such information can be used in the context of a "smart city" to provide citizens with higher-level services or even to proactively ensure public security and safety. This work demonstrates a fiber sensing network based on low-cost fiber Bragg grating sensors that are able to appropriately oversee diverse monitoring parameters.
Manniën, Judith; Wille, Jan C; Snoeren, Ruud L M M; Hof, Susan van den
OBJECTIVE: To compare the number of surgical site infections (SSIs) registered after hospital discharge with respect to various surgical procedures and to identify the procedures for which postdischarge surveillance (PDS) is most important. DESIGN: Prospective SSI surveillance with voluntary PDS.
The use of sensor networks has been proposed for military surveillance and environmental monitoring applications. Those systems are composed of a heterogeneous set of sensors to observe the environment. In centralised systems the observed data will be conveyed to the control room to process the
The use of sensor networks has been proposed for military surveillance and environmental monitoring applications. Those systems are composed of a heterogeneous set of sensors to observe the environment. In centralised systems the observed data will be conveyed to the control room to process the data
Skowronski, Danuta M; Chambers, Catharine; Sabaiduc, Suzana; Murti, Michelle; Gustafson, Reka; Pollock, Sue; Hoyano, Dee; Rempel, Shirley; Allison, Sandra; De Serres, Gaston; Dickinson, James A; Tellier, Raymond; Fonseca, Kevin; Drews, Steven J; Martineau, Christine; Reyes-Domingo, Francesca; Wong, Tom; Tang, Patrick; Krajden, Mel
Respiratory specimens collected from outpatients with influenza-like illness in three Canadian provinces (British Columbia (BC), Alberta and Quebec) participating in a community-based sentinel surveillance network were prospectively screened for enterovirus-D68 (EV-D68) from 1 August to 31 December 2014 and compared to specimens collected from 1 October 2013 to 31 July 2014. Eighteen (1%) of 1,894 specimens were EV-D68-positive: 1/348 (0.3%) collected from October to December 2013 and 11/460 (2.4%) from October to December 2014, an eight-fold increase in detection rates (p=0.01), consistent with epidemic circulation in autumn 2014. The remaining EV-D68 detections were in September 2014 (6/37). Enhanced passive surveillance was also conducted on all inpatient and outpatient EV-D68 cases (n=211) detected at the BC provincial reference laboratory from 28 August to 31 December 2014. Incidence of hospitalisations was 3/100,000 overall and 21, 17, 4 and 1/100,000 among those1 among paediatric but not adult cases. Three cases in BC with comorbidity or co-infection died and five exhibited neurological features persisting >9 months. Active surveillance in outpatient and inpatient settings is needed from more areas and additional seasons to better understand EV-D68 epidemiology and potential at-risk groups for severe or unusual manifestations.
Gresham, Louise S; Smolinski, Mark S; Suphanchaimat, Rapeepong; Kimball, Ann Marie; Wibulpolprasert, Suwit
Connecting Organizations for Regional Disease Surveillance (CORDS) is an international non-governmental organization focused on information exchange between disease surveillance networks in different areas of the world. By linking regional disease surveillance networks, CORDS builds a trust-based social fabric of experts who share best practices, surveillance tools and strategies, training courses, and innovations. CORDS exemplifies the shifting patterns of international collaboration needed to prevent, detect, and counter all types of biological dangers - not just naturally occurring infectious diseases, but also terrorist threats. Representing a network-of-networks approach, the mission of CORDS is to link regional disease surveillance networks to improve global capacity to respond to infectious diseases. CORDS is an informal governance cooperative with six founding regional disease surveillance networks, with plans to expand; it works in complement and cooperatively with the World Health Organization (WHO), the World Organization for Animal Health (OIE), and the Food and Animal Organization of the United Nations (FAO). As described in detail elsewhere in this special issue of Emerging Health Threats, each regional network is an alliance of a small number of neighboring countries working across national borders to tackle emerging infectious diseases that require unified regional efforts. Here we describe the history, culture and commitment of CORDS; and the novel and necessary role that CORDS serves in the existing international infectious disease surveillance framework.
Louise S. Gresham
Full Text Available Connecting Organizations for Regional Disease Surveillance (CORDS is an international non-governmental organization focused on information exchange between disease surveillance networks in different areas of the world. By linking regional disease surveillance networks, CORDS builds a trust-based social fabric of experts who share best practices, surveillance tools and strategies, training courses, and innovations. CORDS exemplifies the shifting patterns of international collaboration needed to prevent, detect, and counter all types of biological dangers – not just naturally occurring infectious diseases, but also terrorist threats. Representing a network-of-networks approach, the mission of CORDS is to link regional disease surveillance networks to improve global capacity to respond to infectious diseases. CORDS is an informal governance cooperative with six founding regional disease surveillance networks, with plans to expand; it works in complement and cooperatively with the World Health Organization (WHO, the World Organization for Animal Health (OIE, and the Food and Animal Organization of the United Nations (FAO. As described in detail elsewhere in this special issue of Emerging Health Threats, each regional network is an alliance of a small number of neighboring countries working across national borders to tackle emerging infectious diseases that require unified regional efforts. Here we describe the history, culture and commitment of CORDS; and the novel and necessary role that CORDS serves in the existing international infectious disease surveillance framework.
Joensen, Katrine Grimstrup; Hasman, Henrik; Scheutz, F.
Objectives: Fast and accurate typing of foodborne pathogens is essential for effective surveillance and the ability to detect and prevent outbreaks. Current routine typing is based on a variety of different typing techniques, making the complete typing procedure laborious, time......-consuming and expensive. With whole-genome sequencing (WGS) becoming continuously cheaper and more available, it has huge potential in both diagnostics and routine surveillance. The aim of this study was to evaluate WGS-based typing, in a real-time setup, for routine typing and surveillance of verocytotoxin-producing E...... the IonTorrent PGM benchtop sequencing technology. WGS-based typing was carried out using web-based tools, developed by the Center for Genomic Epidemiology (www.genomicepidemiology.org), for determination of MLST types, virulence genes and phylogenetic relationship between the isolates. The WGS...
刘晓锋; 常云涛; 王珣
将无人飞机技术应用到稀疏路网的交通监控当中,提出了无人飞机在有无续航里程约束条件下的交通监控部署方法.给出了无人飞机的监控路段和节点的选择方法；在无续航里程约束条件下,将无人飞机的交通监控问题转化为旅行商问题,并运用模拟退火算法予以求解；在有续航里程约束条件下,运用K -means聚类方法,将无人飞机的监控区域划分成若干子监控区,从而将该问题转化为无续航里程约束的无人飞机交通监控部署问题.以新疆库库高速公路和路网为例,对稀疏路网条件下的无人飞机交通监控部署方法进行实证分析和试飞试验.试验结果表明:无人飞机在稀疏路网条件下是一种有效的交通监控设备,可用于我国西部稀疏路网的交通监控.%Unmanned Aerial Vehicle (UAV) technology was introduced into the traffic surveillance in sparse road network and an UAV allocation method for traffic surveillance with/without UAV continuous flight distance constraint was proposed. First, the method of choosing the surveillance road segments and nodes was proposed. Then, UAV traffic surveillance problem without continuous flight distance constraint was formulated as a traveling salesman problem, and the simulated annealing algorithm was introduced to solve this problem. As for UAV traffic surveillance problem with continuous flight distance constraint, K-means clustering algorithm was used to divide the UAV surveillance area into multiple sub-zones to convert this problem into UAV traffic surveillance scenario without continuous flight distance constraint. Finally, taking Korla-Kuqa expressway of Xinjiang and its road network as example, the proposed UAV-based traffic surveillance allocation method for sparse road network was demonstrated and validated by using several field experiments. The experimental results show that UAV is an effective and useful tool for traffic surveillance in sparse
Poirel Christopher L
Full Text Available Abstract Background Many methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account. Results Our approach naturally generalizes Fisher’s exact test, a gene set-based technique. Given a function of interest, we compute the subgraph of the network induced by genes annotated to this function. We use the sequence of sizes of the connected components of this sub-network to estimate its connectivity. We estimate the statistical significance of the connectivity empirically by a permutation test. We present three applications of our method: i determine which functions are enriched in a given network, ii given a network and an interesting sub-network of genes within that network, determine which functions are enriched in the sub-network, and iii given two networks, determine the functions for which the connectivity improves when we merge the second network into the first. Through these applications, we show that our approach is a natural alternative to network clustering algorithms. Conclusions We presented a novel approach to functional enrichment that takes into account the pairwise relationships among genes annotated by a particular function. Each of the three applications discovers highly relevant functions. We used our methods to study biological data from three different organisms. Our results demonstrate the wide applicability of our methods. Our algorithms are
Kim, Youngho; O'Kelly, Morton
This study proposes a bootstrap-based space-time surveillance model. Designed to find emerging hotspots in near-real time, the bootstrap based model is characterized by its use of past occurrence information and bootstrap permutations. Many existing space-time surveillance methods, using population at risk data to generate expected values, have resulting hotspots bounded by administrative area units and are of limited use for near-real time applications because of the population data needed. However, this study generates expected values for local hotspots from past occurrences rather than population at risk. Also, bootstrap permutations of previous occurrences are used for significant tests. Consequently, the bootstrap-based model, without the requirement of population at risk data, (1) is free from administrative area restriction, (2) enables more frequent surveillance for continuously updated registry database, and (3) is readily applicable to criminology and epidemiology surveillance. The bootstrap-based model performs better for space-time surveillance than the space-time scan statistic. This is shown by means of simulations and an application to residential crime occurrences in Columbus, OH, year 2000.
C.Pranit Jeba Samuel
Full Text Available Surveillance is a key factor to ensure safety in various fields, here motivity of fishing boats in ocean/sea are monitored for illegal intrusion in other nations boundary. Hence an effective scheme isdesigned to overcome this threat with Global positioning system (GPS which provides dynamic location of fishing vessel in water and microcontroller which competes on GPS and predefined boundary locations to determine whether the boat have crossed the border or not. If so the fisherman is alerted and the message is transmitted to nearby coast guard ships through RF signals at VHF (30-300MHz range which covers wide area. On adumbrated the patrolling units can alert the fisherman from their position or if necessary the entire movement of the fishing vessel could be controlled remotely for trespassing. This measures fixes the cross boundary fishing problems between nations as the fisherman’s are unaware about their position in water.
Fox, Jesse; Tokunaga, Robert S
Romantic relationship dissolution can be stressful, and social networking sites make it difficult to separate from a romantic partner online as well as offline. An online survey (N = 431) tested a model synthesizing attachment, investment model variables, and post-dissolution emotional distress as predictors of interpersonal surveillance (i.e., "Facebook stalking") of one's ex-partner on Facebook after a breakup. Results indicated that anxious attachment predicted relational investment but also seeking relationship alternatives; avoidant attachment was negatively related to investment but positively related to seeking alternatives. Investment predicted commitment, whereas seeking alternatives was negatively related to commitment. Commitment predicted emotional distress after the breakup. Distress predicted partner monitoring immediately following the breakup, particularly for those who did not initiate the breakup, as well as current partner monitoring. Given their affordances, social media are discussed as potentially unhealthy enablers for online surveillance after relationship termination.
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.
Providing a reliable and efficient communication infrastructure for critical regions is generally a strategy used to enhance regional safety or to sustain regional development. For such purposes, the spider-web network is prototyped as a cellular telecommunication infrastructure for its advantages including being interference-free, possessing fault-tolerance, having security management, and countering radio's multipath effects. Besides, it is used to develop area-based-street-SCADA (supervisory control and ...
Full Text Available Abstract Background Emerging animal and zoonotic diseases and increasing international trade have resulted in an increased demand for veterinary surveillance systems. However, human and financial resources available to support government veterinary services are becoming more and more limited in many countries world-wide. Intuitively, issues that present higher risks merit higher priority for surveillance resources as investments will yield higher benefit-cost ratios. The rapid rate of acceptance of this core concept of risk-based surveillance has outpaced the development of its theoretical and practical bases. Discussion The principal objectives of risk-based veterinary surveillance are to identify surveillance needs to protect the health of livestock and consumers, to set priorities, and to allocate resources effectively and efficiently. An important goal is to achieve a higher benefit-cost ratio with existing or reduced resources. We propose to define risk-based surveillance systems as those that apply risk assessment methods in different steps of traditional surveillance design for early detection and management of diseases or hazards. In risk-based designs, public health, economic and trade consequences of diseases play an important role in selection of diseases or hazards. Furthermore, certain strata of the population of interest have a higher probability to be sampled for detection of diseases or hazards. Evaluation of risk-based surveillance systems shall prove that the efficacy of risk-based systems is equal or higher than traditional systems; however, the efficiency (benefit-cost ratio shall be higher in risk-based surveillance systems. Summary Risk-based surveillance considerations are useful to support both strategic and operational decision making. This article highlights applications of risk-based surveillance systems in the veterinary field including food safety. Examples are provided for risk-based hazard selection, risk-based
Full Text Available Web Geographic Information System (Web GIS has been extensively and successfully exploited in various arenas. However, to date, the application of this technology in public health surveillance has yet to be systematically explored in the Web 2.0 era. We reviewed existing Web GIS-based Public Health Surveillance Systems (WGPHSSs and assessed them based on 20 indicators adapted from previous studies. The indicators comprehensively cover various aspects of WGPHSS development, including metadata, data, cartography, data analysis, and technical aspects. Our literature search identified 58 relevant journal articles and 27 eligible WGPHSSs. Analyses of results revealed that WGPHSSs were frequently used for infectious-disease surveillance, and that geographical and performance inequalities existed in their development. The latest Web and Web GIS technologies have been used in developing WGPHSSs; however, significant deficiencies in data analysis, system compatibility, maintenance, and accessibility exist. A balance between public health surveillance and privacy concerns has yet to be struck. Use of news and social media as well as Web-user searching records as data sources, participatory public health surveillance, collaborations among health sectors at different spatial levels and among various disciplines, adaption or reuse of existing WGPHSSs, and adoption of geomashup and open-source development models were identified as the directions for advancing WGPHSSs.
Andrew F. van den Hurk
Full Text Available Control of arboviral disease is dependent on the sensitive and timely detection of elevated virus activity or the identification of emergent or exotic viruses. The emergence of Japanese encephalitis virus (JEV in northern Australia revealed numerous problems with performing arbovirus surveillance in remote locations. A sentinel pig programme detected JEV activity, although there were a number of financial, logistical, diagnostic and ethical limitations. A system was developed which detected viral RNA in mosquitoes collected by solar or propane powered CO2-baited traps. However, this method was hampered by trap-component malfunction, microbial contamination and large mosquito numbers which overwhelmed diagnostic capabilities. A novel approach involves allowing mosquitoes within a box trap to probe a sugar-baited nucleic-acid preservation card that is processed for expectorated arboviruses. In a longitudinal field trial, both Ross River and Barmah Forest viruses were detected numerous times from multiple traps over different weeks. Further refinements, including the development of unpowered traps and use of yeast-generated CO2, could enhance the applicability of this system to remote locations. New diagnostic technology, such as next generation sequencing and biosensors, will increase the capacity for recognizing emergent or exotic viruses, while cloud computing platforms will facilitate rapid dissemination of data.
L.D.F. Venderbos (Lionne); M.J. Roobol-Bouts (Monique); C.H. Bangma (Chris); R.C.N. van den Bergh (Roderick); L.P. Bokhorst (Leonard); D. Nieboer (Daan); Godtman, R; J. Hugosson (Jonas); van der Kwast, T; E.W. Steyerberg (Ewout)
textabstractTo study whether probabilistic selection by the use of a nomogram could improve patient selection for active surveillance (AS) compared to the various sets of rule-based AS inclusion criteria currently used. We studied Dutch and Swedish patients participating in the European Randomized s
Pituch, Hanna; Obuch-Woszczatyński, Piotr; Lachowicz, Dominika; Wultańska, Dorota; Karpiński, Paweł; Młynarczyk, Grażyna; van Dorp, Sofie M; Kuijper, Ed J
As part of the European Clostridium difficile infections (CDI) surveillance Network (ECDIS-Net), which aims to build capacity for CDI surveillance in Europe, we constructed a new network of hospital-based laboratories in Poland. We performed a survey in 13 randomly selected hospital-laboratories in different sites of the country to determine their annual CDI incidence rates from 2011 to 2013. Information on C. difficile laboratory diagnostic testing and indications for testing was also collected. Moreover, for 2012 and 2013 respectively, participating hospital-laboratories sent all consecutive isolates from CDI patients between February and March to the Anaerobe Laboratory in Warsaw for further molecular characterisation, including the detection of toxin-encoding genes and polymerase chain reaction (PCR)-ribotyping. Within the network, the mean annual hospital CDI incidence rates were 6.1, 8.6 and 9.6 CDI per 10,000 patient-days in 2011, 2012, and 2013 respectively. Six of the 13 laboratories tested specimens only on the request of a physician, five tested samples of antibiotic-associated diarrhoea or samples from patients who developed diarrhoea more than two days after admission (nosocomial diarrhoea), while two tested all submitted diarrhoeal faecal samples. Most laboratories (9/13) used tests to detect glutamate dehydrogenase and toxin A/B either separately or in combination. In the two periods of molecular surveillance, a total of 166 strains were characterised. Of these, 159 were toxigenic and the majority belonged to two PCR-ribotypes: 027 (n=99; 62%) and the closely related ribotype 176 (n=22; 14%). The annual frequency of PCR-ribotype 027 was not significantly different during the surveillance periods (62.9% in 2012; 61.8% in 2013). Our results indicate that CDIs caused by PCR-ribotype 027 predominate in Polish hospitals participating in the surveillance, with the closely related 176 ribotype being the second most common agent of infection.
The Spanish national health care-associated infection surveillance network (INCLIMECC): data summary January 1997 through December 2006 adapted to the new National Healthcare Safety Network Procedure-associated module codes.
Pérez, Cristina Díaz-Agero; Rodela, Ana Robustillo; Monge Jodrá, Vincente
In 1997, a national standardized surveillance system (designated INCLIMECC [Indicadores Clínicos de Mejora Continua de la Calidad]) was established in Spain for health care-associated infection (HAI) in surgery patients, based on the National Nosocomial Infection Surveillance (NNIS) system. In 2005, in its procedure-associated module, the National Healthcare Safety Network (NHSN) inherited the NNIS program for surveillance of HAI in surgery patients and reorganized all surgical procedures. INCLIMECC actively monitors all patients referred to the surgical ward of each participating hospital. We present a summary of the data collected from January 1997 to December 2006 adapted to the new NHSN procedures. Surgical site infection (SSI) rates are provided by operative procedure and NNIS risk index category. Further quality indicators reported are surgical complications, length of stay, antimicrobial prophylaxis, mortality, readmission because of infection or other complication, and revision surgery. Because the ICD-9-CM surgery procedure code is included in each patient's record, we were able to reorganize our database avoiding the loss of extensive information, as has occurred with other systems.
Madsen, Per Printz
This paper describe a Neural Network based method for consumption forecasting. This work has been financed by the The ENCOURAGE project. The aims of The ENCOURAGE project is to develop embedded intelligence and integration technologies that will directly optimize energy use in buildings and enable...
In a traditional home video surveillance system, the house master can' t handle it when an emergent event occurs far away from home. A method using Web 2.0 based on cooperative home video surveillance system is proposed in this paper. In this system, the master's relatives, friends and neighbours are involved in a surveillance group, and monitoring images can be delivered to group members as alarm signals are issued. Finally, the system stability and efficiency of data encryption are proved to be well in experimerts.%为解决家庭监视系统中,房主离开时所产生的事故隐患,采用Web 2.0方法和P2P网络串流技术,同时将房主的好友和邻居等加入监视群体,设计了具备监视视频加密功能的安全联防网络系统,只需其中任何一位成员发出警示信息,就可立即将监视画面传给其他监视群体成员.最后,通过实验来验证所设计系统的稳定性和视频加密效能.
P.M. Coloma (Preciosa); B. Becker (Benedikt); M.C.J.M. Sturkenboom (Miriam); E.M. Van Mulligen (Erik M.); J.A. Kors (Jan)
textabstractIntroduction: There is growing interest in whether social media can capture patient-generated information relevant for medicines safety surveillance that cannot be found in traditional sources. Objective: The aim of this study was to evaluate the potential contribution of mining social m
Surgical site infections (SSI) are the most-common healthcare-associated infections among surgical patients and have severe adverse consequences. Surveillance is the ongoing systematic collection, analysis, interpretation, and feedback of data, and has been accepted worldwide as a primary step
Aditya Lia Ramadona
Full Text Available Research is needed to create early warnings of dengue outbreaks to inform stakeholders and control the disease. This analysis composes of a comparative set of prediction models including only meteorological variables; only lag variables of disease surveillance; as well as combinations of meteorological and lag disease surveillance variables. Generalized linear regression models were used to fit relationships between the predictor variables and the dengue surveillance data as outcome variable on the basis of data from 2001 to 2010. Data from 2011 to 2013 were used for external validation purposed of prediction accuracy of the model. Model fit were evaluated based on prediction performance in terms of detecting epidemics, and for number of predicted cases according to RMSE and SRMSE, as well as AIC. An optimal combination of meteorology and autoregressive lag terms of dengue counts in the past were identified best in predicting dengue incidence and the occurrence of dengue epidemics. Past data on disease surveillance, as predictor alone, visually gave reasonably accurate results for outbreak periods, but not for non-outbreaks periods. A combination of surveillance and meteorological data including lag patterns up to a few years in the past showed most predictive of dengue incidence and occurrence in Yogyakarta, Indonesia. The external validation showed poorer results than the internal validation, but still showed skill in detecting outbreaks up to two months ahead. Prior studies support the fact that past meteorology and surveillance data can be predictive of dengue. However, to a less extent has prior research shown how the longer-term past disease incidence data, up to years, can play a role in predicting outbreaks in the coming years, possibly indicating cross-immunity status of the population.
Ramadona, Aditya Lia; Lazuardi, Lutfan; Hii, Yien Ling; Holmner, Åsa; Kusnanto, Hari; Rocklöv, Joacim
Research is needed to create early warnings of dengue outbreaks to inform stakeholders and control the disease. This analysis composes of a comparative set of prediction models including only meteorological variables; only lag variables of disease surveillance; as well as combinations of meteorological and lag disease surveillance variables. Generalized linear regression models were used to fit relationships between the predictor variables and the dengue surveillance data as outcome variable on the basis of data from 2001 to 2010. Data from 2011 to 2013 were used for external validation purposed of prediction accuracy of the model. Model fit were evaluated based on prediction performance in terms of detecting epidemics, and for number of predicted cases according to RMSE and SRMSE, as well as AIC. An optimal combination of meteorology and autoregressive lag terms of dengue counts in the past were identified best in predicting dengue incidence and the occurrence of dengue epidemics. Past data on disease surveillance, as predictor alone, visually gave reasonably accurate results for outbreak periods, but not for non-outbreaks periods. A combination of surveillance and meteorological data including lag patterns up to a few years in the past showed most predictive of dengue incidence and occurrence in Yogyakarta, Indonesia. The external validation showed poorer results than the internal validation, but still showed skill in detecting outbreaks up to two months ahead. Prior studies support the fact that past meteorology and surveillance data can be predictive of dengue. However, to a less extent has prior research shown how the longer-term past disease incidence data, up to years, can play a role in predicting outbreaks in the coming years, possibly indicating cross-immunity status of the population.
Tasaki, Tomohiro; Kawahata, Takatsune; Osako, Masahiro; Matsui, Yasuhiro; Takagishi, Susumu; Morita, Akihiro; Akishima, Shigeki
To assist in the efficient surveillance against illegal dumping, this study examined and evaluated two methods to illustrate the illegal dumping potential of sites using GIS (Geographic Information System) data. One approach focused on the occurrence of illegal dumping sites; the other on the size of the illegal dumping. Both approaches to zoning were implemented for the Kanto region of Japan, utilizing seven or eight major geographical attributes most closely related to illegal dumping. The zoning results revealed the areas requiring patrols against illegal dumping. Evaluation of the zoning results using the ROC (Receiver Operating Characteristic) curve showed the number of illegal dumping sites detectable under certain surveillance conditions and that the size-based zoning was superior, but this superiority was insignificant for revealing sites with higher potential for large illegal dumping, for which it would be sufficient to use the occurrence-based zoning. The evaluation also showed the contribution of each geographical attribute. Finally, application of the ROC curve to the surveillance planning process was examined, which enables the total social cost of pollution by illegal dumping, rehabilitation of dumping sites, and illegal dumping surveillance to be minimized.
王梦来; 李想; 陈奇; 李澜博; 赵衍运
It is well-known that event detection in real-world surveillance videos is a challenging task. The corpus of TRECVID-SED evaluation is acquired from the surveillance video of London Gatwick International Airport and it is well known for its high diﬃculties. We propose a comprehensive event detection framework based on an effective part-based deep network cascade — head-shoulder networks (HsNet) and tra jectory analysis. On the one hand, the deep network detects pedestrians very precisely, laying a foundation for tracking pedestrians. On the other hand, convolutional neural networks (CNNs) are good at detecting key-pose-based single events. Trajectory analysis is introduced for group events. In TRECVID-SED15 evaluation, our approach outperformed others in 3 out of 6 events, demonstrating the power of our proposal.%复杂监控视频中事件检测是一个具有挑战性的难题,而TRECVID-SED 评测使用的数据集取自机场的实际监控视频,以高难度著称。针对TRECVID-SED评测集,提出了一种基于卷积神经网络(Convolutional neural network, CNN)级联网络和轨迹分析的监控视频事件检测综合方案。在该方案中,引入级联CNN 网络在拥挤场景中准确地检测行人,为跟踪行人奠定了基础；采用CNN 网络检测具有关键姿态的个体事件,引入轨迹分析方法检测群体事件。该方案在国际评测中取得了很好的评测排名：在6个事件检测的评测中,3个事件检测排名第一。
Cui, Xiuliang; He, Haochen; He, Fuchu; Wang, Shengqi; Li, Fei; Bo, Xiaochen
It can be difficult for biomedical researchers to understand complex molecular networks due to their unfamiliarity with the mathematical concepts employed. To represent molecular networks with clear meanings and familiar forms for biomedical researchers, we introduce a knowledge-based computational framework to decipher biomedical networks by making systematic comparisons to well-studied “basic networks”. A biomedical network is characterized as a spectrum-like vector called “network fingerprint”, which contains similarities to basic networks. This knowledge-based multidimensional characterization provides a more intuitive way to decipher molecular networks, especially for large-scale network comparisons and clustering analyses. As an example, we extracted network fingerprints of 44 disease networks in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The comparisons among the network fingerprints of disease networks revealed informative disease-disease and disease-signaling pathway associations, illustrating that the network fingerprinting framework will lead to new approaches for better understanding of biomedical networks. PMID:26307246
The purpose of INL’s research on this project is to demonstrate the feasibility of a host event based network monitoring tool and the effects on host performance. Current host based network monitoring tools work on polling which can miss activity if it occurs between polls. Instead of polling, a tool could be developed that makes use of event APIs in the operating system to receive asynchronous notifications of network activity. Analysis and logging of these events will allow the tool to construct the complete real-time and historical network configuration of the host while the tool is running. This research focused on three major operating systems commonly used by SCADA systems: Linux, WindowsXP, and Windows7. Windows 7 offers two paths that have minimal impact on the system and should be seriously considered. First is the new Windows Event Logging API, and, second, Windows 7 offers the ALE API within WFP. Any future work should focus on these methods.
Full Text Available INTRODUCTION: Prevalence of infection with HIV-1 non-B subtypes in Italy has been reported to raise, due to increased migration flows and travels. HIV-1 variants show different biological and immunological properties that impact on disease progression rate, response to antiretroviral therapy (ART and sensitivity of diagnostic tests with important implications for public health. Therefore, a constant surveillance of the dynamics of HIV variants in Italy should be a high public health priority. Organization of surveillance studies requires building up a platform constituted of a network of clinical centers, laboratories and institutional agencies, able to properly collect samples for the investigation of HIV subtypes heterogeneity and to provide a database with reliable demographic, clinical, immunological and virological data. AIM: We here report our experience in building up such a platform, co-ordinated by the National AIDS Center of the Istituto Superiore di Sanita, taking advantage of a pilot study aimed at evaluating HIV subtypes diversity in populations of HIV-infected migrant people in Italy. MATERIALS AND METHODS: Four hundred and thirty four HIV-infected migrants were enrolled in 9 Italian clinical centers located throughout the Italian territory. Standard Operating Procedures (SOPs for sample collection were provided by the National AIDS Center to each clinical center. In addition, clinical centers were required to fill up a case report form (crf for each patient, which included demographic, clinical, immunological and virological information. RESULTS: All centers properly collected and stored samples from each enrolled individual. Overall, the required information was correctly provided for more than 90% of the patients. However, some fields of the crf, particularly those including information on the last HIV-negative antibody test and presence of co-infections, were properly filled up in less than 80% of the enrolled migrants. Centers
Full Text Available This paper presents a network evolution model, which is based on the clustering approach. The proposed approach depicts the network evolution, which demonstrates the network formation from individual nodes to fully evolved network. An agglomerative hierarchical clustering method is applied for the evolution of network. In the paper, we present three case studies which show the evolution of the networks from the scratch. These case studies include: terrorist network of 9/11 incidents, terrorist network of WMD (Weapons Mass Destruction plot against France and a network of tweets discussing a topic. The network of 9/11 is also used for evaluation, using other social network analysis methods which show that the clusters created using the proposed model of network evolution are of good quality, thus the proposed method can be used by law enforcement agencies in order to further investigate the criminal networks
reported availabilty of relatively high- paying jobs. The consequences of increased migration could be significant. No significant impacts at U.S. Army...Air Force Base are contributing to overdrawing the aquifers, and at current usage rates the aquifers could be depleted (44). The "Draft Environmental
Berg JMJ van den; Boer AS de; Mintjes-de Groot AJ; Sprenger MJW; Cucic S; Pelt W van; Centraal Begeleidingsorgaan; CIE
In the Project Surveillance Hospital Acquired Infections a surveillance system in a national network of hospitals is being developed and implemented. In the project surveillance of hospital acquired infections is implemented in components: surveillance of surgical wound infections, surveillance of i
Tsuboi, Toshiki; Kitamura, Koji; Nishida, Yoshihumi; Motomura, Yoichi; Takano, Tachio; Yamanaka, Tatsuhiro; Mizoguchi, Hiroshi
This paper proposes a new technology,``a bodygraphic injury surveillance system (BISS)'' that not only accumulates accident situation data but also represents injury data based on a human body coordinate system in a standardized and multilayered way. Standardized and multilayered representation of injury enables accumulation, retrieval, sharing, statistical analysis, and modeling causalities of injury across different fields such as medicine, engineering, and industry. To confirm the effectiveness of the developed system, the authors collected 3,685 children's injury data in cooperation with a hospital. As new analyses based on the developed BISS, this paper shows bodygraphically statistical analysis and childhood injury modeling using the developed BISS and Bayesian network technology.
A large class of phylogenetic networks can be obtained from trees by the addition of horizontal edges between the tree edges. These networks are called tree-based networks. We present a simple necessary and sufficient condition for tree-based networks and prove that a universal tree-based network exists for any number of taxa that contains as its base every phylogenetic tree on the same set of taxa. This answers two problems posted by Francis and Steel recently. A byproduct is a computer program for generating random binary phylogenetic networks under the uniform distribution model.
Blanc, P D; Jones, M R; Olson, K R
There is no gold standard for determining poisoning incidence. We wished to compare four measures of poisoning incidence: International Classification of Diseases 9th Revision (ICD-9) principal (N-code) and supplemental external cause of injury (E-code) designations, poison control center (PCC) reporting, and detection by the Drug Abuse Warning Network (DAWN). We studied a case series at two urban hospitals. We assigned ICD-9 N-code and E-code classifications, determining whether these matched with medical records. We ascertained PCC and DAWN system reporting. A total of 724 subjects met entry criteria; 533 were studied (74%). We matched poisoning N-codes for 278 patients (52%), E-code by cause in 306 patients (57%), and E-code by intent in 171 patients (32%). A total of 383 patients (72%) received any poisoning N-code or any E-code. We found that PCC and DAWN reporting occurred for 123 of all patients (23%) and 399 of 487 eligible patients (82%), respectively. In multiple logistic regression, factors of age, hospital admission, suicidal intent, principal poisoning or overdose type, and mixed drug overdose were statistically significant predictors of case match or report varying by surveillance measure. Our findings indicate that common surveillance measures of poisoning and drug overdose may systematically undercount morbidity.
Location-based services have been identified as a promising communication paradigm in highly mobile and dynamic vehicular networks. However, existing mobile ad hoc networking cannot be directly applied to vehicular networking due to differences in traffic conditions, mobility models and network topologies. On the other hand, hybrid architectures…
McKenzie, Jeanie; Girin, Natalie; Roth, Adam; Vivili, Paula; Williams, Gail; Hoy, Damian
Abstract Introduction and Aims Alcohol use is a leading risk factor for disease and injury in Pacific Island countries and territories (PICT). This paper examines drinking patterns across 20 PICTs. Design and Methods We synthesised published data from the STEPwise approach to surveillance or similar surveys for adults 25–64 years, and from the Global School‐Based Student Health surveys and Youth Risk Behavior Surveillance System (YRBSS) for youth. We examined current and heavy drinking, and for adults also frequency of consumption. Using YRBSS, we studied trends in youth alcohol use in US‐affiliated PICTs between 2001 and 2013. Results Alcohol consumption in adults and youth varied considerably across PICTs. In eight PICT populations, over 60% of male adults were current drinkers. Male adults consumed alcohol more frequently and engaged in heavy drinking more than female adults. Similar gender differences occurred in current and heavy drinking among youth. Across 10 PICTs, current drinking prevalence in males 13–15 years ranged from 10% to over 40%. Declines in alcohol use among grade 9–12 students were observed in YRBSS, although the magnitude differed by island and sex. Discussion and Conclusions Alcohol consumption varies widely between PICTs. There are marked gender differences in use and abstention. There is scope in PICTs for implementation of best practice strategies to reduce alcohol‐related harm. These need to be gender responsive and cognisant of concerning patterns of youth drinking. Strengthening surveillance of alcohol use and its consequences is vital to inform and monitor the impact of national and regional policies. [Kessaram T, McKenzie J, Girin N, Roth A, Vivili P, Williams G, Hoy D. Alcohol use in the Pacific region: Results from the STEPwise approach to surveillance, Global School‐Based Student Health Survey and Youth Risk Behavior Surveillance System. Drug Alcohol Rev 2016;35:412–423] PMID:26358376
Gisele Peirano; Johann DD. Pitout; Laupland, Kevin B.; Bonnie Meatherall; Daniel B Gregson
The characteristics of hypermucoviscosity isolates among Klebsiella pneumoniae causing community-acquired bacteremia were investigated. The hypermucoviscous phenotype was present in 8.2% of K pneumoniae isolates, and was associated with rmpA and the K2 serotype; liver abscesses were the most common clinical presentation. The present analysis represents the first population-based surveillance study of hypermucoviscosity among K pneumoniae causing bacteremia.
Ekegren, Christina L; Gabbe, Belinda J; Donaldson, Alex; Cook, Jill; Lloyd, David; Finch, Caroline F
Far fewer injury surveillance systems exist within community sport than elite sport. As a result, most epidemiological data on sports injuries have limited relevance to community-level sporting populations. There is potential for data from community club-based injury surveillance systems to provide a better understanding of community sports injuries. This study aimed to describe the incidence and profile of community-level Australian football injuries reported using a club-based injury surveillance system. Prospective, epidemiological study. Sports trainers from five community-level Australian football leagues recorded injury data during two football seasons using the club-based system. An online surveillance tool developed by Sports Medicine Australia ('Sports Injury Tracker') was used for data collection. The injury incidence, profile and match injury rate were reported. Injury data for 1205 players were recorded in season one and for 823 players in season two. There was significant variability in injury incidence across clubs. However, aggregated data were consistent across football seasons, with an average of 0.7 injuries per player per season and 38-39 match injuries per 1000 h match exposure. A large proportion of injuries occurred during matches, involved the lower limb and resulted from contact. Data from the club-based system provided a profile of injuries consistent with previous studies in community-level Australian football. Moreover, injury incidence was consistent with other studies using similar personnel to record data. However, injury incidence was lower than that reported in studies using player self-report or healthcare professionals and may be an underestimate of true values. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
The objective of this proposal is to design our own ELINT based satellite system to detect and locate the target by using satellite Trilateration Principle. The target position can be found by measuring the radio signals arrived at three satellites using Time Difference of Arrival(TDOA) technique. To locate a target it is necessary to determine the satellite position. The satellite motion and its position is obtained by using Simplified General Perturbation Model(SGP4) in MATLAB. This SGP4 accepts satellite Two Line Element(TLE) data and returns the position in the form of state vectors. These state vectors are then converted into observable parameters and then propagated in space. This calculations can be done for satellite constellation and non - visibility periods can be calculated. Satellite Trilateration consists of three satellites flying in formation with each other. The satellite constellation design consists of three satellites with an inclination of 61.3° maintained at equal distances between each other. The design is performed using MATLAB and simulated to obtain the necessary results. The target's position can be obtained using the three satellites ECEF Coordinate system and its position and velocity can be calculated in terms of Latitude and Longitude. The target's motion is simulated to obtain the Speed and Direction of Travel.
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.
Brinkel, Johanna; Krämer, Alexander; Krumkamp, Ralf; May, Jürgen; Fobil, Julius
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.
Jelling Kristoffersen, Kåre; Kjærgaard, Mikkel Baun; Chen, Jianjun;
Adding content is seen as the next important step in the development and deployment of broadband networks. This paper proposes three different ways of adding content to wireless broadband networks. First, the home gateway is presented as the focal point for delivery of digital services to future...
Nguyen, Hieu T.; Ramu, Prakash; Liu, Xiaoqing; Wei, Hai; Yadegar, Jacob
Content-based video retrieval from archived image/video is a very attractive capability of modern intelligent video surveillance systems. This paper presents an innovative Semantic-Based Video Indexing and Retrieval (SBVIR) software toolkit to help users of intelligent video surveillance to easily and rapidly search the content of large video archives to conduct video-based forensic and image intelligence. Tailored for maritime environment, SBVIR is suited for surveillance applications in harbor, sea shores, or around ships. The system comprises two major modules: a video analytic module that performs automatic target detection, tracking, classification, activities recognition, and a retrieval module that performs data indexing, and information retrieval. SBVIR is capable of detecting and tracking objects from multiple cameras robustly in condition of dynamic water background and illumination changes. The system provides hierarchical target classification among a large ontology of watercraft classes, and is capable of recognizing a variety of boat activities. Video retrieval is achieved with both query-by-keyword and query-by-example. Users can query video content using semantic concepts selected from a large dictionary of objects and activities, display the history linked to a given target/activity, and search for anomalies. The user can interact with the system and provide feedbacks to tune the system for improved accuracy and relevance of retrieved data. SBVIR has been tested for real maritime surveillance scenarios and shown to be able to generate highly-semantic metadata tags that can be used during the retrieval to provide user with relevant and accurate data in real-time.
Fricker, Ronald D; Hegler, Benjamin L; Dunfee, David A
This paper compares the performance of three detection methods, entitled C1, C2, and C3, that are implemented in the early aberration reporting system (EARS) and other syndromic surveillance systems versus the CUSUM applied to model-based prediction errors. The cumulative sum (CUSUM) performed significantly better than the EARS' methods across all of the scenarios we evaluated. These scenarios consisted of various combinations of large and small background disease incidence rates, seasonal cycles from large to small (as well as no cycle), daily effects, and various types and levels of random daily variation. This leads us to recommend replacing the C1, C2, and C3 methods in existing syndromic surveillance systems with an appropriately implemented CUSUM method.
Shahabeddini Parizi, Mohammad; Radziwon, Agnieszka
could be obtained through network interaction. Based on two extreme cases of SMEs representing low-tech industry and an in-depth analysis of their manufacturing facilities this paper presents how collaboration between firms embedded in a regional ecosystem could result in implementation of new...... automation solutions. The empirical data collection involved application of a combination of comparative case study method with action research elements. This article provides an outlook over the challenges in implementing technological improvements and the way how it could be resolved in collaboration......, this paper develops and discusses a set of guidelines for systematic productivity improvement within an innovative collaboration in regards to automation processes in SMEs....
Crowe, Samuel J.; Jasperse, Joseph; Privette, Grayson; Stone, Erin; Miller, Laura; Hertz, Darren; Fu, Clementine; Maenner, Matthew J.; Jambai, Amara; Morgan, Oliver
In 2015, community event–based surveillance (CEBS) was implemented in Sierra Leone to assist with the detection of Ebola virus disease (EVD) cases. We assessed the sensitivity of CEBS for finding EVD cases during a 7-month period, and in a 6-week subanalysis, we assessed the timeliness of reporting cases with no known epidemiologic links at time of detection. Of the 12,126 CEBS reports, 287 (2%) met the suspected case definition, and 16 were confirmed positive. CEBS detected 30% (16/53) of the EVD cases identified during the study period. During the subanalysis, CEBS staff identified 4 of 6 cases with no epidemiologic links. These CEBS-detected cases were identified more rapidly than those detected by the national surveillance system; however, too few cases were detected to determine system timeliness. Although CEBS detected EVD cases, it largely generated false alerts. Future versions of community-based surveillance could improve case detection through increased staff training and community engagement. PMID:27434608
Fadigas, I. S.; Pereira, H. B. B.
The characterization of complex networks is a procedure that is currently found in several research studies. Nevertheless, few studies present a discussion on networks in which the basic element is a clique. In this paper, we propose an approach based on a network of cliques. This approach consists not only of a set of new indices to capture the properties of a network of cliques but also of a method to characterize complex networks of cliques (i.e., some of the parameters are proposed to characterize the small-world phenomenon in networks of cliques). The results obtained are consistent with results from classical methods used to characterize complex networks.
Full Text Available Abstract Background In order to proceed from a paper based registration to a surveillance system that is based on extraction of electronic health records (EHR, knowledge is needed on the number and representativeness of sentinel GPs using a government-certified EHR system and the quality of EHR data for research, expressed in the compliance rate with three criteria: recording of home visits, use of prescription module and diagnostic subject headings. Methods Data were collected by annual postal surveys between 2005 and 2009 among all sentinel GPs. We tested relations between four key GP characteristics (age, gender, language community, practice organisation and use of a certified EHR system by multivariable logistic regression. The relation between EHR software package, GP characteristics and compliance with three quality criteria was equally measured by multivariable logistic regression. Results A response rate of 99% was obtained. Of 221 sentinel GPs, 55% participated in the surveillance without interruption from 2005 onwards, i.e. all five years, and 78% were participants in 2009. Sixteen certified EHR systems were used among 91% of the Dutch and 63% of the French speaking sentinel GPs. The EHR software package was strongly related to the community and only one EHR system was used by a comparable number of sentinel GPs in both communities. Overall, the prescription module was always used and home visits were usually recorded. Uniform subject headings were only sometimes used and the compliance with this quality criterion was almost exclusively related to the EHR software package in use. Conclusions The challenge is to progress towards a sentinel network of GPs delivering care-based data that are (partly extracted from well performing EHR systems and still representative for Belgian general practice.
Ferrer, E; Alfonso, P; Ippoliti, C; Abeledo, M; Calistri, P; Blanco, P; Conte, A; Sánchez, B; Fonseca, O; Percedo, M; Pérez, A; Fernández, O; Giovannini, A
The authors designed a risk-based approach to the selection of poultry flocks to be sampled in order to further improve the sensitivity of avian influenza (AI) active surveillance programme in Cuba. The study focused on the western region of Cuba, which harbours nearly 70% of national poultry holdings and comprise several wetlands where migratory waterfowl settle (migratory waterfowl settlements - MWS). The model took into account the potential risk of commercial poultry farms in western Cuba contracting from migratory waterfowl of the orders Anseriformes and Charadriiformes through dispersion for pasturing of migratory birds around the MWS. We computed spatial risk index by geographical analysis with Python scripts in ESRI(®) ArcGIS 10 on data projected in the reference system NAD 1927-UTM17. Farms located closer to MWS had the highest values for the risk indicator pj and in total 31 farms were chosen for targeted surveillance during the risk period. The authors proposed to start active surveillance in the study area 3 weeks after the onset of Anseriformes migration, with additional sampling repeated twice in the same selected poultry farms at 15 days interval (Comin et al., 2012; EFSA, 2008) to cover the whole migration season. In this way, the antibody detectability would be favoured in case of either a posterior AI introduction or enhancement of a previous seroprevalence under the sensitivity level. The model identified the areas with higher risk for AIV introduction from MW, aiming at selecting poultry premises for the application of risk-based surveillance. Given the infrequency of HPAI introduction into domestic poultry populations and the relative paucity of occurrences of LPAI epidemics, the evaluation of the effectiveness of this approach would require its application for several migration seasons to allow the collection of sufficient reliable data.
Anindya Sekhar Bose; Hamid Jafari; Stephen Sosler; Arvinder Pal Singh Narula; V M Kulkarni; Nalini Ramamurty; John Oommen; Jadi, Ramesh S; Banpel, R. V.; Ana Maria Henao-Restrepo
BACKGROUND: According to WHO estimates, 35% of global measles deaths in 2011 occurred in India. In 2013, India committed to a goal of measles elimination by 2020. Laboratory supported case based measles surveillance is an essential component of measles elimination strategies. Results from a case-based measles surveillance system in Pune district (November 2009 through December 2011) are reported here with wider implications for measles elimination efforts in India. METHODS: Standard protocols...
Troullos, Emanuel; Baird, Lisa; Jayawardena, Shyamalie
Conducting and analyzing clinical studies of cough and cold medications is challenging due to the rapid onset and short duration of the symptoms. The use of Internet-based surveillance tools is a new approach in clinical studies that is gradually becoming popular and may become a useful method of recruitment. As part of an initiative to assess the safety and efficacy of cough and cold ingredients in children 6-11 years of age, a surveillance program was proposed as a means to identify and recruit pediatric subjects for clinical studies. The objective of the study was to develop an Internet-based surveillance system and to assess the feasibility of using such a system to recruit children for common cold clinical studies, record the natural history of their cold symptoms, and determine the willingness of parents to have their children participate in clinical studies. Healthy potential subjects were recruited via parental contact online. During the 6-week surveillance period, parents completed daily surveys to record details of any cold symptoms in their children. If a child developed a cold, symptoms were followed via survey for 10 days. Additional questions evaluated the willingness of parents to have their children participate in a clinical study shortly after onset of symptoms. The enrollment target of 248 children was reached in approximately 1 week. Children from 4 distinct geographic regions of the United States were recruited. Parents reported cold symptoms in 163 children, and 134 went on to develop colds. The most prevalent symptoms were runny nose, stuffed-up nose, and sneezing. The most severe symptoms were runny nose, stuffed-up nose, and sore/scratchy throat. The severity of most symptoms peaked 1-2 days after onset. Up to 54% of parents expressed willingness to bring a sick child to a clinical center shortly after the onset of symptoms. Parents found the Internet-based surveys easy to complete. Internet-based surveillance and recruitment can be useful
Finelli, Lyn; Whitaker, Brett; Fowlkes, Ashley
Background: Parainfluenza viruses (PIV) have been shown to contribute substantially to pediatric hospitalizations in the United States. However, to date, there has been no systematic surveillance to estimate the burden among pediatric outpatients. Methods: From August 2010 through July 2014, outpatient health care providers with enumerated patient populations in 13 states and jurisdictions participating in the Influenza Incidence Surveillance Project conducted surveillance of patients with influenza-like illness (ILI). Respiratory specimens were collected from the first 10 ILI patients each week with demographic and clinical data. Specimens were tested for multiple respiratory viruses, including PIV1–4, using reverse transcriptase–polymerase chain reaction assays. Cumulative incidence was calculated using provider patient population size as the denominator. Results: PIVs 1–3 were detected in 8.0% of 7716 ILI-related outpatient specimens: 30% were PIV1, 26% PIV2 and 44% PIV3. PIV circulation varied noticeably by year and type, with PIV3 predominating in 2010–2011 (incidence 110 per 100,000 children), PIV1 in 2011–2012 (89 per 100,000), dual predominance of PIV2 and PIV3 (88 and 131 per 100,000) in 2012–2013 and PIV3 (100 per 100,000) in 2013–2014. The highest incidence of PIV detections was among patients aged <5 years (259–1307 per 100,000). The median age at detection for PIV3 (3.4 years) was significantly lower than the median ages for PIV1 (4.5 years) and PIV2 (7.0 years; P < 0.05). Conclusions: PIVs 1–3 comprise a substantial amount of medically attended pediatric ILI, particularly among children aged <5 years. Distinct seasonal circulation patterns as well as significant differences in rates by age were observed between PIV types. PMID:26974891
Full Text Available Due to the particularities of the underwater environment, some negative factors will seriously interfere with data transmission rates, reliability of data communication, communication range, and network throughput and energy consumption of underwater sensor networks (UWSNs. Thus, full consideration of node energy savings, while maintaining a quick, correct and effective data transmission, extending the network life cycle are essential when routing protocols for underwater sensor networks are studied. In this paper, we have proposed a novel routing algorithm for UWSNs. To increase energy consumption efficiency and extend network lifetime, we propose a time-slot based routing algorithm (TSR.We designed a probability balanced mechanism and applied it to TSR. The theory of network coding is introduced to TSBR to meet the requirement of further reducing node energy consumption and extending network lifetime. Hence, time-slot based balanced network coding (TSBNC comes into being. We evaluated the proposed time-slot based balancing routing algorithm and compared it with other classical underwater routing protocols. The simulation results show that the proposed protocol can reduce the probability of node conflicts, shorten the process of routing construction, balance energy consumption of each node and effectively prolong the network lifetime.
Fu, Clementine; Lopes, Sérgio; Mellor, Steve; Aryal, Siddhi; Sovannaroth, Siv; Roca-Feltrer, Arantxa
Strengthening the surveillance component is key toward achieving country-wide malaria elimination in Cambodia. A Web-based upgraded malaria information system (MIS) was deemed to essentially act as the central component for surveillance strengthening. New functionality (eg, data visualization) and operational (eg, data quality) attributes of the system received particular attention. However, building from the lessons learned in previous systems' developments, other aspects unique to Cambodia were considered to be equally important; for instance, feasibility issues, particularly at the field level (eg, user acceptability at various health levels), and sustainability needs (eg, long-term system flexibility). The Cambodian process of identifying the essential changes and critical attributes for this new information system can provide a model for other countries at various stages of the disease control and elimination continuum. Sharing these experiences not only facilitates the establishment of "best practices" but also accelerates global and regional malaria elimination efforts. In this article, Cambodia's experience in developing and upgrading its MIS to remain responsive to country-specific needs demonstrates the necessity for considering functionality, operationalization, feasibility, and sustainability of an information system in the context of malaria elimination. ©Clementine Fu, Sérgio Lopes, Steve Mellor, Siddhi Aryal, Siv Sovannaroth, Arantxa Roca-Feltrer. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.06.2017.
Chang, Shu-Fen; Yang, Cheng-Fen; Hsu, Tung-Chieh; Su, Chien-Ling; Lin, Chien-Chou; Shu, Pei-Yun
We present the results of a laboratory-based surveillance of dengue in Taiwan in 2014. A total of 240 imported dengue cases were identified. The patients had arrived from 16 countries, and Malaysia, Indonesia, the Philippines, and China were the most frequent importing countries. Phylogenetic analyses showed that genotype I of dengue virus type 1 (DENV-1) and the cosmopolitan genotype of DENV-2 were the predominant DENV strains circulating in southeast Asia. The 2014 dengue epidemic was the largest ever to occur in Taiwan since World War II, and there were 15,492 laboratory-confirmed indigenous dengue cases. Phylogenetic analysis showed that the explosive dengue epidemic in southern Taiwan was caused by a DENV-1 strain of genotype I imported from Indonesia. There were several possible causes of this outbreak, including delayed notification of the outbreak, limited staff and resources for control measures, abnormal weather conditions, and a serious gas pipeline explosion in the dengue hot spot areas in Kaohsiung City. However, the results of this surveillance indicated that both active and passive surveillance systems should be strengthened so appropriate public health measures can be taken promptly to prevent large-scale dengue outbreaks.
Full Text Available This paper proposes a fusion iterations strategy based on the Standard map to generate a chaotic path planner of the mobile robot for surveillance missions. The distances of the chaotic trajectories between the adjacent iteration points which are produced by the Standard map are too large for the robot to track. So a fusion iterations strategy combined with the large region iterations and the small grids region iterations is designed to resolve the problem. The small region iterations perform the iterations of the Standard map in the divided small grids, respectively. It can reduce the adjacent distances by dividing the whole surveillance workspace into small grids. The large region iterations combine all the small grids region iterations into a whole, switch automatically among the small grids, and maintain the chaotic characteristics of the robot to guarantee the surveillance missions. Compared to simply using the Standard map in the whole workspace, the proposed strategy can decrease the adjacent distances according to the divided size of the small grids and is convenient for the robot to track.
Our analysis showed that slaughterhouse inspection is the most effective surveillance component in reducing the time for disease detection, while routine surveillance in reducing the number of multi-farms epidemics. On the other hand, testing exchanged cattle improved the performance of the surveillance system only marginally.
Full Text Available The traditional BP neural network algorithm has some bugs such that it is easy to fall into local minimum and the slow convergence speed. Particle swarm optimization is an evolutionary computation technology based on swarm intelligence which can not guarantee global convergence. Artificial Bee Colony algorithm is a global optimum algorithm with many advantages such as simple, convenient and strong robust. In this paper, a new BP neural network based on Artificial Bee Colony algorithm and particle swarm optimization algorithm is proposed to optimize the weight and threshold value of BP neural network. After network traffic prediction experiment, we can conclude that optimized BP network traffic prediction based on PSO-ABC has high prediction accuracy and has stable prediction performance.
Anna, Sominina; Burtseva, Elena; Eropkin, Mikhail; Karpova, Ludmila; Zarubaev, Vladimir; Smorodintseva, Elizaveta; Konovalova, Nadezhda; Danilenko, Daria; Prokopetz, Alexandra; Grudinin, Mikhail; Pisareva, Maria; Anfimov, Pavel; Stolyarov, Kirill; Kiselev, Oleg; Shevchenko, Elena; Ivanova, Valeriya; Trushakova, Svetlana; Breslav, Nataliya; Lvov, Dmitriy; Klimov, Alexander; Moen, Ann; Cox, Nancy
Exchange of information on and sharing of influenza viruses through the GISRS network has great significance for understanding influenza virus evolution, recognition of a new pandemic virus emergence and for preparing annual WHO recommendations on influenza vaccine strain composition. Influenza surveillance in Russia is based on collaboration of two NICs with 59 Regional Bases. Most epidemiological and laboratory data are entered through the internet into the electronic database at the Research Institute of Influenza (RII), where they are analyzed and then reported to the Ministry of Public Health of Russia. Simultaneously, data are introduced into WHO's Flu Net and Euro Flu, both electronic databases. Annual influenza epidemics of moderate intensity were registered during four pre-pandemic seasons. Children aged 0-2 and 3-6 years were the most affected groups of the population. Influenza registered clinically among hospitalized patients with respiratory infections for the whole epidemic period varied between 1.3 and 5.4% and up but to 18.5-23.0% during the peak of the two pandemic waves caused by influenza A(H1N1) pdm 09 virus and to lesser extent (2.9 to 8.5%) during usual seasonal epidemics. Most epidemics were associated with influenza A(H1N1), A(H3N2) and B co-circulation. During the two pandemic waves (in 2009-2010 and 2010-2011) influenza A(H1N1) pdm 09 predominated. It was accompanied by a rapid growth of influenza morbidity with a significant increase of both hospitalization and mortality. The new pandemic virus displaced the previous seasonal A(H1N1) virus completely. As a rule, most of the influenza viruses circulating in Russia were antigenic ally related to the strains recommended by WHO for vaccine composition for the Northern hemisphere with the exception of two seasons when an unexpected replacement of the influenza B Victoria lineage by Yamagata lineage (2007-2008) and the following return of Victoria lineage viruses (2008-2009) was registered
Vega, Maricruz; Verma, Manisha; Beswick, David; Bey, Stephanie; Hossack, Jared; Merriman, Nathan; Shah, Ashish; Navarro, Victor
The population-based incidence rate of drug-induced liver injury (DILI) in the USA is not known. The Drug-Induced Liver Injury Network (DILIN) accrues cases of hepatotoxicity due to medications and herbal and dietary supplements (HDS) from limited geographical areas. The current analysis was an ancillary study of DILIN aimed at determining the annual incidence of DILI in the USA on a population basis, through surveillance in the state of Delaware. At the outset of the study, there were 41 gastroenterologists in the state of Delaware and all agreed to participate in surveillance for DILI, which comprised active reporting of suspected cases to the DILIN. The gastroenterologists underwent training in the diagnosis of DILI and were provided with DILIN inclusion criteria. Only cases that met the DILIN laboratory inclusion criteria in 2014 were included in the incidence calculation, and these patients were invited to participate in the DILIN Prospective Study. The number of suspected cases that met inclusion criteria served as the numerator and the 2014 Delaware adult population as the denominator. During 2014, 23 patients were identified by the surveillance network, 20 of whom met DILIN laboratory inclusion criteria, leading to an incidence of 2.7 cases of DILI per 100,000 adult residents [95% confidence interval (CI) 1.5-3.9 per 100,000]. Fourteen subjects agreed to participate in the DILIN; six declined. Among enrolled cases, the mean age was 51 years, 57% were women, and 71% were white. Eight cases were attributed to antibiotics (36%) and other drugs (21%) and six to HDS (43%). The pattern of injury was hepatocellular in all HDS cases, but only 50% of conventional drug cases (p = 0.05), which more commonly presented with eosinophilia (p = 0.47) and higher alkaline phosphatase levels (p = 0.05). Half of patients were jaundiced, none developed liver failure, and all recovered without the need for transplantation. Prospective, gastroenterologist-based
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.
Cox-Witton, Keren; Reiss, Andrea; Woods, Rupert; Grillo, Victoria; Baker, Rupert T.; Blyde, David J.; Boardman, Wayne; Cutter, Stephen; Lacasse, Claude; McCracken, Helen; Pyne, Michael; Smith, Ian; Vitali, Simone; Vogelnest, Larry; Wedd, Dion; Phillips, Martin; Bunn, Chris; Post, Lyndel
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. PMID:24787430
Full Text Available Synthetic Aperture Radar (SAR is widely used in ship surveillance. High-Resolution Wide-Swath (HRWS SAR data are simultaneously collected, which introduces challenges and offers new research opportunities. SAR-based ship-surveillance technologies and the performance requirements of SAR systems are reviewed and summarized. Furthermore, the characteristics of HRWS SAR imaging and ship surveillance technologies are considered in tandem, and preliminary research results on ship detection, feature extraction, and classification are discussed. Finally, we point out issues to be addressed in future work.
Full Text Available Vision based vehicle detection is a critical technology that plays an important role in not only vehicle active safety but also road video surveillance application. Traditional shallow model based vehicle detection algorithm still cannot meet the requirement of accurate vehicle detection in these applications. In this work, a novel deep learning based vehicle detection algorithm with 2D deep belief network (2D-DBN is proposed. In the algorithm, the proposed 2D-DBN architecture uses second-order planes instead of first-order vector as input and uses bilinear projection for retaining discriminative information so as to determine the size of the deep architecture which enhances the success rate of vehicle detection. On-road experimental results demonstrate that the algorithm performs better than state-of-the-art vehicle detection algorithm in testing data sets.
Santosh Kumar Chaudhari
Full Text Available A Network Management System (NMS plays a very important role in managing an ever-evolving telecommunication network. Generally an NMS monitors & maintains the health of network elements. The growing size of the network warrants extra functionalities from the NMS. An NMS provides all kinds of information about networks which can be used for other purposes apart from monitoring & maintaining networks like improving QoS & saving energy in the network. In this paper, we add another dimension to NMS services, namely, making an NMS energy aware. We propose a Decision Management System (DMS framework which uses a machine learning technique called Bayesian Belief Networks (BBN, to make the NMS energy aware. The DMS is capable of analysing and making control decisions based on network traffic. We factor in the cost of rerouting and power saving per port. Simulations are performed on standard network topologies, namely, ARPANet and IndiaNet. It is found that ~2.5-6.5% power can be saved.
Full Text Available Abstract Background Prospective surveillance is a recognised approach for measuring death rates in humanitarian emergencies. However, there is limited evidence on how such surveillance should optimally be implemented and on how data are actually used by agencies. This case study investigates the implementation and utilisation of mortality surveillance data by Médecins Sans Frontières (MSF in eastern Chad. We aimed to describe and analyse the community-based mortality surveillance system, trends in mortality data and the utilisation of these data to guide MSF’s operational response. Methods The case study included 5 MSF sites including 2 refugee camps and 3 camps for internally displaced persons (IDPs. Data were obtained through key informant interviews and systematic review of MSF operational reports from 2004–2008. Results Mortality data were collected using community health workers (CHWs. Mortality generally decreased progressively. In Farchana and Breidjing refugee camps, crude death rates (CDR decreased from 0.9 deaths per 10,000 person-days in 2004 to 0.2 in 2008 and from 0.7 to 0.1, respectively. In Gassire, Ade and Kerfi IDP camps, CDR decreased from 0.4 to 0.04, 0.3 to 0.04 and 1.0 to 0.3. Death rates among children under 5 years (U5DR followed similar trends. CDR and U5DR crossed emergency thresholds in one site, Kerfi, where CDR rapidly rose to 2.1 and U5DR to 7.9 in July 2008 before rapidly decreasing to below emergency levels by September 2008. Discussion Mortality data were used regularly to monitor population health status and on two occasions as a tool for advocacy. Lessons learned included the need for improved population estimates and standardized reporting procedures for improved data quality and dissemination; the importance of a simple and flexible model for data collection; and greater investment in supervising CHWs. Conclusions This model of community based mortality surveillance can be adapted and used by
蒋一波; 王万良; 陈伟杰; 郑建炜; 姚信威
This paper studies the problem of surveillance area of WVSN (wireless video sensor network) with obstacles, which is finding the optimized view-orientations for all video sensors to maximize multimedia coverage. In this paper, the characteristics of direction adjustable sensing model are discussed and the relation between sensors and obstacles is analyzed. Then, a coverage enhancement algorithm PFOFSA (potential field based occlusion-free surveillance algorithm) is proposed, which could effectively minimize the negative effect of occlusion and overlapping in the sensing field. In PFOFSA, three kinds of virtual centroid point are defined for simplifying the structure of effective region, occlusion region and overlapping region. Two kinds of relationship between virtual force and orientation rotation are constructed and made comparison in experiments. Finally, a set of simulation results are performed to demonstrate the effectiveness of PFOFSA. According to the experiments, PFOFSA could maximize the coverage of WVSN with obstacles and make higher coverage rate than other algorithms.%针对监控区域存在障碍物的情况,从无线视频传感节点的有向感知特性出发,讨论了视频传感器网络覆盖效果与监控区域之间的相互关系.在此基础上,定义了视频传感器网络的无盲区覆盖模型.基于虚拟势场的工作原理,提出了一种适用于无盲区覆盖模型的覆盖率动态优化算法PFOFSA(potential field based occlusion-free surveillance algorithm).设计了PFOFSA中虚拟力的相互作用方法与监控节点运动规则,通过监控区域、重叠区域和遮挡区域之间的相互作用,逐步消除网络中的感知重叠区和盲区,优化视频无线传感器网络的覆盖率.最后,通过一系列的仿真实验分析了不同监控区域参数对PFOFSA算法的影响,验证了算法的有效性.
Marques, Ana Rita; Pereira, Marcelo; Ferreira Neto, Jose Soares; Ferreira, Fernando
The farming of Pacific white shrimp Litopennaeus vannamei in northeast Brazil, has proven to be a promising sector. However, the farming of Pacific white shrimp in Brazil has been affected negatively by the occurrence of viral diseases, threatening this sector's expansion and sustainability. For this reason, the drafting of a surveillance system for early detection and definition of freedom from viral diseases, whose occurrence could result in high economic loses, is of the utmost importance. The stochastic model AquaVigil was implemented to prospectively evaluate different surveillance strategies to determine freedom from disease and identify the strategy with the lowest sampling efforts, making the best use of available resources through risk-based surveillance. The worked example presented was designed for regional application for the state of Ceará and can easily be applied to other Brazilian states. The AquaVigil model can analyse any risk-based surveillance system that considers a similar outline to the strategy here presented.
JIA-QI MA; LI-PING WANG; XUAO-PENG QI; XIAO-MING SHI; GONG-HUAN YANG
Objective To establish a conceptual model of automatic early warning of infectious diseases based on internet reporting surveillance system,with a view to realizing an automated warning system on a daily basis and timely identifying potential outbreaks of infectious diseases. Methods The statistic conceptual model was established using historic surveillance data with movable percentile method.Results Based on the infectious disease surveillance information platform,the conceptualmodelfor early warning was established.The parameter,threshold,and revised sensitivity and specificity of early warning value were changed to realize dynamic alert of infectious diseases on a daily basis.Conclusion The instructive conceptual model of dynamic alert can be used as a validating tool in institutions of infectious disease surveillance in different districts.
Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Wei, Ze-Gang; Chen, Luonan
The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce
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Competition based neural networks have been used to solve the generalized assignment problem and the quadratic assignment problem.Both problems are very difficult and are ε approximation complete.The neural network approach has yielded highly competitive performance and good performance for the quadratic assignment problem.These neural networks are guaranteed to produce feasible solutions.
Full Text Available A novel Durer-pentagon-based complex network was constructed by adding a centre node. The properties of the complex network including the average degree, clustering coefficient, average path length, and fractal dimension were determined. The proposed complex network is small-world and fractal.
Full Text Available Abstract Background Climate change has a significant impact on population health. Population vulnerabilities depend on several determinants of different types, including biological, psychological, environmental, social and economic ones. Surveillance of climate-related health vulnerabilities must take into account these different factors, their interdependence, as well as their inherent spatial and temporal aspects on several scales, for informed analyses. Currently used technology includes commercial off-the-shelf Geographic Information Systems (GIS and Database Management Systems with spatial extensions. It has been widely recognized that such OLTP (On-Line Transaction Processing systems were not designed to support complex, multi-temporal and multi-scale analysis as required above. On-Line Analytical Processing (OLAP is central to the field known as BI (Business Intelligence, a key field for such decision-support systems. In the last few years, we have seen a few projects that combine OLAP and GIS to improve spatio-temporal analysis and geographic knowledge discovery. This has given rise to SOLAP (Spatial OLAP and a new research area. This paper presents how SOLAP and climate-related health vulnerability data were investigated and combined to facilitate surveillance. Results Based on recent spatial decision-support technologies, this paper presents a spatio-temporal web-based application that goes beyond GIS applications with regard to speed, ease of use, and interactive analysis capabilities. It supports the multi-scale exploration and analysis of integrated socio-economic, health and environmental geospatial data over several periods. This project was meant to validate the potential of recent technologies to contribute to a better understanding of the interactions between public health and climate change, and to facilitate future decision-making by public health agencies and municipalities in Canada and elsewhere. The project also aimed at
HOSSEIN BALOOCHIAN; MOZAFAR BAGMOHAMMADI
Most of the energy in a sensor network is used for transmission of data packets. For this reason, optimization of energy consumption is of utmost importance in these networks. This paper presents NCF, a flood routing protocol based on network coding. Simulations show that in addition to eliminating the drawbacks of traditional flooding methods, like the explosion phenomenon, NCF increases the lifetime of the network by at least 20% and decreases the number of packet transmissions. Another adv...
The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...
Zhang, Emma Xuxiao; Yang, Yinping; Di Shang, Richard; Simons, Joseph John Pyne; Quek, Boon Kiat; Yin, Xiao Feng; See, Wanhan; Oh, Olivia Seen Huey; Nandar, Khine Sein Tun; Ling, Vivienne Ruo Yun; Chan, Pei Pei; Wang, Zhaoxia; Goh, Rick Siow Mong; James, Lyn
We conducted in-depth analysis on the use of a popular Chinese social networking and microblogging site, Sina Weibo, to monitor an avian influenza A(H7N9) outbreak in China and to assess the value of social networking sites in the surveillance of disease outbreaks that occur overseas. Two data sets were employed for our analysis: a line listing of confirmed cases obtained from conventional public health information channels and case information from Weibo posts. Our findings showed that the level of activity on Weibo corresponded with the number of new cases reported. In addition, the reporting of new cases on Weibo was significantly faster than those of conventional reporting sites and non-local news media. A qualitative review of the functions of Weibo also revealed that Weibo enabled timely monitoring of other outbreak-relevant information, provided access to additional crowd-sourced epidemiological information and was leveraged by the local government as an interactive platform for risk communication and monitoring public sentiment on the policy response. Our analysis demonstrated the potential for social networking sites to be used by public health agencies to enhance traditional communicable disease surveillance systems for the global surveillance of overseas public health threats. Social networking sites also can be used by governments for calibration of response policies and measures and for risk communication. PMID:26306219
Zhang, Emma Xuxiao; Yang, Yinping; Di Shang, Richard; Simons, Joseph John Pyne; Quek, Boon Kiat; Yin, Xiao Feng; See, Wanhan; Oh, Olivia Seen Huey; Nandar, Khine Sein Tun; Ling, Vivienne Ruo Yun; Chan, Pei Pei; Wang, Zhaoxia; Goh, Rick Siow Mong; James, Lyn; Tey, Jeannie Su Hui
We conducted in-depth analysis on the use of a popular Chinese social networking and microblogging site, Sina Weibo, to monitor an avian influenza A(H7N9) outbreak in China and to assess the value of social networking sites in the surveillance of disease outbreaks that occur overseas. Two data sets were employed for our analysis: a line listing of confirmed cases obtained from conventional public health information channels and case information from Weibo posts. Our findings showed that the level of activity on Weibo corresponded with the number of new cases reported. In addition, the reporting of new cases on Weibo was significantly faster than those of conventional reporting sites and non-local news media. A qualitative review of the functions of Weibo also revealed that Weibo enabled timely monitoring of other outbreak-relevant information, provided access to additional crowd-sourced epidemiological information and was leveraged by the local government as an interactive platform for risk communication and monitoring public sentiment on the policy response. Our analysis demonstrated the potential for social networking sites to be used by public health agencies to enhance traditional communicable disease surveillance systems for the global surveillance of overseas public health threats. Social networking sites also can be used by governments for calibration of response policies and measures and for risk communication.
Emma Xuxiao Zhang
Full Text Available We conducted in-depth analysis on the use of a popular Chinese social networking and microblogging site, Sina Weibo, to monitor an avian influenza A(H7N9 outbreak in China and to assess the value of social networking sites in the surveillance of disease outbreaks that occur overseas. Two data sets were employed for our analysis: a line listing of confirmed cases obtained from conventional public health information channels and case information from Weibo posts. Our findings showed that the level of activity on Weibo corresponded with the number of new cases reported. In addition, the reporting of new cases on Weibo was significantly faster than those of conventional reporting sites and non-local news media. A qualitative review of the functions of Weibo also revealed that Weibo enabled timely monitoring of other outbreak-relevant information, provided access to additional crowd-sourced epidemiological information and was leveraged by the local government as an interactive platform for risk communication and monitoring public sentiment on the policy response. Our analysis demonstrated the potential for social networking sites to be used by public health agencies to enhance traditional communicable disease surveillance systems for the global surveillance of overseas public health threats. Social networking sites also can be used by governments for calibration of response policies and measures and for risk communication.
Micro Air Vehicles (MAVs) will be developed for tracking individuals, locating terrorist threats, and delivering remote sensors, for surveillance and chemical/biological agent detection. The tasks are: (1) Develop robust MAV platform capable of carrying sensor payload. (2) Develop fully autonomous capabilities for delivery of sensors to remote and distant locations. The current capabilities and accomplishments are: (1) Operational electric (inaudible) 6-inch MAVs with novel flexible wing, providing superior aerodynamic efficiency and control. (2) Vision-based flight stability and control (from on-board cameras).
Galanis, E.; Wong, Danilo Lo Fo; Patrick, M.E.
Salmonellae are a common cause of foodborne disease worldwide. The World Health Organization (WHO) supports international foodborne disease surveillance through WHO Global Salm-Surv and other activities. WHO Global Salm-Surv members annually report the 15 most frequently isolated Salmonella...... serotypes to a Web-based country databank. We describe the global distribution of reported Salmonella serotypes from human and nonhuman sources from 2000 to 2002. Among human isolates, Salmonella enterica serovar Enteritidis was the most common serotype, accounting for 65% of all isolates. Among nonhuman...... professionals to explore hypotheses related to the sources and distribution of salmonellae worldwide....
Wang Qi; Wang Qingshan; Wang Dongxue
The network coding is a new technology in the field of information in 21st century.It could enhance the network throughput and save the energy consumption,and is mainly based on the single transmission rate.However,with the development of wireless network and equipment,wireless local network MAC protocols have already supported the multi-rate transmission.This paper investigates the optimal relay selection problem based on network coding.Firstly,the problem is formulated as an optimization problem.Moreover,a relay algorithm based on network coding is proposed and the transmission time gain of our algorithm over the traditional relay algorithm is analyzed.Lastly,we compare total transmission time and the energy consumption of our proposed algorithm,Network Coding with Relay Assistance (NCRA),Transmission Request (TR),and the Direct Transmission (DT) without relay algorithm by adopting IEEE 802.11b.The simulation results demonstrate that our algorithm that improves the coding opportunity by the cooperation of the relay nodes leads to the transmission time decrease of up to 17％ over the traditional relay algorithms.
Yogendra Kumar Jain
Full Text Available A honeypot is a non-production system, design to interact with cyber-attackers to collect intelligence on attack techniques and behaviors. There has been great amount of work done in the field of networkintrusion detection over the past three decades. With networks getting faster and with the increasing dependence on the Internet both at the personal and commercial level, intrusion detection becomes a challenging process. The challenge here is not only to be able to actively monitor large numbers of systems, but also to be able to react quickly to different events. Before deploying a honeypot it is advisable to have a clear idea of what the honeypot should and should not do. There should be clear understandingof the operating systems to be used and services (like a web server, ftp server etc a honeypot will run. The risks involved should be taken into consideration and methods to tackle or reduce these risks should be understood. It is also advisable to have a plan on what to do should the honeypot be compromised. In case of production honeypots, a honeypot policy addressing security issues should be documented. Any legal issues with respect to the honeypots or their functioning should also be taken into consideration. In this paper we explain the relatively new concept of “honeypot.” Honeypots are a computer specifically designed to help learn the motives, skills and techniques of the hacker community and also describes in depth the concepts of honeypots and their contribution to the field of network security. The paper then proposes and designs an intrusion detection tool based on some of the existing intrusion detection techniques and the concept of honeypots.
Ghiassian, Susan Dina
With the availability of large-scale data, it is now possible to systematically study the underlying interaction maps of many complex systems in multiple disciplines. Statistical physics has a long and successful history in modeling and characterizing systems with a large number of interacting individuals. Indeed, numerous approaches that were first developed in the context of statistical physics, such as the notion of random walks and diffusion processes, have been applied successfully to study and characterize complex systems in the context of network science. Based on these tools, network science has made important contributions to our understanding of many real-world, self-organizing systems, for example in computer science, sociology and economics. Biological systems are no exception. Indeed, recent studies reflect the necessity of applying statistical and network-based approaches in order to understand complex biological systems, such as cells. In these approaches, a cell is viewed as a complex network consisting of interactions among cellular components, such as genes and proteins. Given the cellular network as a platform, machinery, functionality and failure of a cell can be studied with network-based approaches, a field known as systems biology. Here, we apply network-based approaches to explore human diseases and their associated genes within the cellular network. This dissertation is divided in three parts: (i) A systematic analysis of the connectivity patterns among disease proteins within the cellular network. The quantification of these patterns inspires the design of an algorithm which predicts a disease-specific subnetwork containing yet unknown disease associated proteins. (ii) We apply the introduced algorithm to explore the common underlying mechanism of many complex diseases. We detect a subnetwork from which inflammatory processes initiate and result in many autoimmune diseases. (iii) The last chapter of this dissertation describes the
GAO Wei-xin; LUO Xian-jue
This paper presents a new algorithm based on Hopfield neural network to find the optimal solution for an electric distribution network. This algorithm transforms the distribution power network-planning problem into a directed graph-planning problem. The Hopfield neural network is designed to decide the in-degree of each node and is in combined application with an energy function. The new algorithm doesn't need to code city streets and normalize data, so the program is easier to be realized. A case study applying the method to a district of 29 street proved that an optimal solution for the planning of such a power system could be obtained by only 26 iterations. The energy function and algorithm developed in this work have the following advantages over many existing algorithms for electric distribution network planning: fast convergence and unnecessary to code all possible lines.
Full Text Available In present study, I present a method of network evolution that based on random network, and facilitated by node attraction. In this method, I assume that the initial network is a random network, or a given initial network. When a node is ready to connect, it tends to link to the node already owning the most connections, which coincides with the general rule (Barabasi and Albert, 1999 of node connecting. In addition, a node may randomly disconnect a connection i.e., the addition of connections in the network is accompanied by the pruning of some connections. The dynamics of network evolution is determined of the attraction factor Lamda of nodes, the probability of node connection, the probability of node disconnection, and the expected initial connectance. The attraction factor of nodes, the probability of node connection, and the probability of node disconnection are time and node varying. Various dynamics can be achieved by adjusting these parameters. Effects of simplified parameters on network evolution are analyzed. The changes of attraction factor Lamda can reflect various effects of the node degree on connection mechanism. Even the changes of Lamda only will generate various networks from the random to the complex. Therefore, the present algorithm can be treated as a general model for network evolution. Modeling results show that to generate a power-law type of network, the likelihood of a node attracting connections is dependent upon the power function of the node's degree with a higher-order power. Matlab codes for simplified version of the method are provided.
The deployment of previous wireless standards has provided more benefits for urban dwellers than rural dwellers. 5G deployment may not be different. This paper identifies that Community Based Networks as carriers that deserve recognition as potential 5G providers may change this. The argument...... is hinged on a research aimed at understanding how and why Community Based Networks deploy telecom and Broadband infrastructure. The study was a qualitative study carried out inductively using Grounded Theory. Six cases were investigated.Two Community Based Network Mobilization models were identified....... The findings indicate that 5G connectivity can be extended to rural areas by these networks, via heterogenous networks. Hence the delivery of 5G data rates delivery via Wireless WAN in rural areas can be achieved by utilizing the causal factors of the identified models for Community Based Networks....
Rueda, M. J.; Villagarcía, M. G.; Barrera, C.; Pérez, J.; Cianca, A.; Godoy, J.; Maroto, L.; Cardona, L.; Llinás, O.
On January 2003 it has began the experimental core deployment of a Marine Obsevational network in Gran Canaria Island sorrounding waters, as a first step of a network which will spread to the whole Canarian Archipelago. The network initially consists of 6 buoys, 3 to 5 are expected to be permanently operative whereas the rest will be under maintenance and improvement. In the beginning each buoy has a double mission: on one hand to contribute to the general observation of oceanographic/ meteorologic parameters of general interest; on the other, to provide specific interesting data to a specific user at least. Some users are the aquaculture enterprises that develop their productive activity in cages moored at sea, the water management companies, public institutions in charge of management of environmentally protected areas and organisers of sailing competitions. Each buoy is composed of a common sensors assembly (position: GPS, compass; meteorology: speed and direction of wind, air temperature, relative humidity; oceanography: water temperature, conductivity, pH, oxygen) and a specific sensor set-up (turbidity, chlorophyll, nutrients, hydrocarbons) depending on the each buoy function. Power, control and processing elements are also included in the buoy. The basic observational program consists of a reading cycle of all the parameters each hour, though it is also possible the programming of specific cycles or the request of a needed demand. Data are transmitted via VHF to a proximal point in land which is linked to a specific user, who acts as a local control element. From each point, the data are sent via a mobile or fixed telephone line to the central control, located at the ICCM. Upon arrival, the data undergo several quality and transformation processes in order to be able to publish those parameters of general interest in the project web (http://iccm.rcanaria.es), and those specific for each user according to their particular protocol. Additionally, it is
Susilarini, Ni Ketut; Sitorus, Martahan; Praptaningsih, Catharina Yekti; Sampurno, Ondri Dwi; Bratasena, Arie; Mulyadi, Ester; Rusli, Roselinda; Fandil, Ahmad; Mangiri, Amalya; Apsari, Hana; Hariyanto, Edy; Samaan, Gina
A sentinel hospital-based severe acute respiratory infection (SARI) surveillance system was established in Indonesia in 2013. Deciding on the number, geographic location and hospitals to be selected as sentinel sites was a challenge. Based on the recently published WHO guideline for influenza surveillance (2012), this study presents the process for hospital sentinel site selection. From the 2,165 hospitals in Indonesia, the first step was to shortlist to hospitals that had previously participated in respiratory disease surveillance systems and had acceptable surveillance performance history. The second step involved categorizing the shortlist according to five regions in Indonesia to maximize geographic representativeness. A checklist was developed based on the WHO recommended attributes for sentinel site selection including stability, feasibility, representativeness and the availability of data to enable disease burden estimation. Eight hospitals, a maximum of two per geographic region, were visited for checklist administration. Checklist findings from the eight hospitals were analyzed and sentinel sites selected in the third step. Six hospitals could be selected based on resources available to ensure system stability over a three-year period. For feasibility, all eight hospitals visited had mechanisms for specimen shipment and the capacity to report surveillance data, but two had limited motivation for system participation. For representativeness, the eight hospitals were geographically dispersed around Indonesia, and all could capture cases in all age and socio-economic groups. All eight hospitals had prerequisite population data to enable disease burden estimation. The two hospitals with low motivation were excluded and the remaining six were selected as sentinel sites. The multi-step process enabled sentinel site selection based on the WHO recommended attributes that emphasize right-sizing the surveillance system to ensure its stability and maximizing its
Full Text Available Target tracking is one of the applications of wireless sensor network which is set up in the areas of field surveillance, habitat monitoring, and intruder tracking. Energy saving is one of the main challenges in target tracking sensor networks. In this paper, we present a Clustering and Prediction-Based Protocol (CPBP for Target Tracking in Wireless Sensor Networks (WSNs. Also, the Base Station (BS was exploited as a cluster formation manager and target movement predictor. Our protocol uses two parameters, distance and energy, for clustering algorithm. For evaluation, the proposed protocol was compared to a number of protocols in terms of network lifetime, number of transmitted packets and number of target miss during network lifetime. Performance of the proposed protocol was compared with cluster size 5 and 7. The simulation results represented desirable performance of the presented protocol.
Khalil, George M; Gotway Crawford, Carol A
Since Alan Pritchard defined bibliometrics as "the application of statistical methods to media of communication" in 1969, bibliometric analyses have become widespread. To date, however, bibliometrics has not been used to analyze publications related to the U.S. Behavioral Risk Factor Surveillance System (BRFSS). To determine the most frequently cited BRFSS-related topical areas, institutions, and journals. A search of the Web of Knowledge database in 2013 identified U.S.-published studies related to BRFSS, from its start in 1984 through 2012. Search terms were BRFSS, Behavioral Risk Factor Surveillance System, or Behavioral Risk Survey. The resulting 1,387 articles were analyzed descriptively and produced data for VOSviewer, a computer program that plotted a relevance distance-based map and clustered keywords from text in titles and abstracts. Topics, journals, and publishing institutions ranged widely. Most research was clustered by content area, such as cancer screening, access to care, heart health, and quality of life. The American Journal of Preventive Medicine and American Journal of Public Health published the most BRFSS-related papers (95 and 70, respectively). Bibliometrics can help identify the most frequently published BRFSS-related topics, publishing journals, and publishing institutions. BRFSS data are widely used, particularly by CDC and academic institutions such as the University of Washington and other universities hosting top-ranked schools of public health. Bibliometric analysis and mapping provides an innovative way of quantifying and visualizing the plethora of research conducted using BRFSS data and summarizing the contribution of this surveillance system to public health. Copyright © 2015 American Journal of Preventive Medicine. All rights reserved.
Rubenstein, Beth L; Spencer, Craig; Mansourian, Hani; Noble, Eva; Munganga, Gustave B; Stark, Lindsay
Children who are separated from their families and usual caregivers in emergencies face a multitude of risks. The humanitarian community lacks methods to systematically capture changes in the frequency and nature of such separations over time. A mobile phone-based community surveillance system was piloted in the Democratic Republic of the Congo. The goal was to identify new cases of unaccompanied and separated children on a weekly basis. Over an 11-week period, community focal points reported 62 cases of separation across 10 communities. The majority of children had been under the care of their parents prior to separation. More than half of the children were unaccompanied, meaning that they were living without an adult relative or customary caregiver. The pilot results suggest that implementing a mobile phone-based surveillance system in a humanitarian setting may be feasible and cost-effective and fills a critical gap in the measurement of separated and unaccompanied children in emergencies. A longer pilot to better understand how the system performs over time is recommended.
Abbas, Mohamed; Tartari, Ermira; Allegranzi, Benedetta; Pittet, Didier; Harbarth, Stephan
This systematic literature review reveals that participating in a surgical site infection (SSI) surveillance network is associated with short-term reductions in SSI rates: relative risk [RR] for year 2, 0.80 (95% confidence interval [CI], 0.79-0.82); year 3 RR, 0.92 (95% CI, 0.90-0.94); year 4 RR, 0.98 (95% CI, 0.96-1.00). Infect Control Hosp Epidemiol 2017;1-3.
Full Text Available Abstract Background With international concern over emerging infectious diseases (EID and bioterrorist attacks, public health is being required to have early outbreak detection systems. A disease surveillance team was organized to establish a hospital emergency department-based syndromic surveillance system (ED-SSS capable of automatically transmitting patient data electronically from the hospitals responsible for emergency care throughout the country to the Centers for Disease Control in Taiwan (Taiwan-CDC starting March, 2004. This report describes the challenges and steps involved in developing ED-SSS and the timely information it provides to improve in public health decision-making. Methods Between June 2003 and March 2004, after comparing various surveillance systems used around the world and consulting with ED physicians, pediatricians and internal medicine physicians involved in infectious disease control, the Syndromic Surveillance Research Team in Taiwan worked with the Real-time Outbreak and Disease Surveillance (RODS Laboratory at the University of Pittsburgh to create Taiwan's ED-SSS. The system was evaluated by analyzing daily electronic ED data received in real-time from the 189 hospitals participating in this system between April 1, 2004 and March 31, 2005. Results Taiwan's ED-SSS identified winter and summer spikes in two syndrome groups: influenza-like illnesses and respiratory syndrome illnesses, while total numbers of ED visits were significantly higher on weekends, national holidays and the days of Chinese lunar new year than weekdays (p Conclusion Taiwan's ED-SSS represents the first nationwide real-time syndromic surveillance system ever established in Asia. The experiences reported herein can encourage other countries to develop their own surveillance systems. The system can be adapted to other cultural and language environments for better global surveillance of infectious diseases and international collaboration.
Yamaki, Kiyoshi; Lowry, Brienne Davis; Buscaj, Emilie; Zisko, Leigh; Rimmer, James H
The aim of this study was to assess the availability of public health surveillance data on obesity among American children with disabilities in state-based surveillance programs. We reviewed annual cross-sectional datasets in state-level surveillance programs for high school students, implemented 2001-2011, for the inclusion of weight and height and disability screening questions. When datasets included a disability screen, its content and consistency of use across years were examined. We identified 54 surveillance programs with 261 annual datasets containing obesity data. Twelve surveillance programs in 11 states included a disability screening question that could be used to extract obesity data for high school students with disabilities, leaving the other 39 states with no state-level obesity data for students with disabilities. A total of 43 annual datasets, 16.5 % of the available datasets, could be used to estimate the obesity status of students with disabilities. The frequency of use of disability questions varied across states, and the content of the questions often changed across years and within a state. We concluded that state surveillance programs rarely contained questions that could be used to identify high school students with disabilities. This limits the availability of data that can be used to monitor obesity and related health statuses among this population in the majority of states.
SUN Xue-bin; ZHOU Zheng
This paper proposes a tracking-based target locating algorithm to locate a target moving in a geographical region under the surveillance of a wireless sensor network. This algorithm first finds a sensor node that has detected the target, and then uses local messages between neighboring nodes to track the trail of the target. The authors implement this algorithm and compare it with an optimized flood-based target locating algorithm. Simulation results show that this algorithm effectively reduces the message transmission, conserves energy and consequently enhances the practicability of resource-limited wireless sensor networks.
Hessar, Farzad; Roy, Sumit
Co-existence between unlicensed networks that share spectrum spatio-temporally with terrestrial (e.g. Air Traffic Control) and shipborne radars in 3-GHz band is attracting significant interest. Similar to every primary-secondary coexistence scenario, interference from unlicensed devices to a primary receiver must be within acceptable bounds. In this work, we formulate the spectrum sharing problem between a pulsed, search radar (primary) and 802.11 WLAN as the secondary. We compute the protection region for such a search radar for a) a single secondary user (initially) as well as b) a random spatial distribution of multiple secondary users. Furthermore, we also analyze the interference to the WiFi devices from the radar's transmissions to estimate the impact on achievable WLAN throughput as a function of distance to the primary radar.
Garcia-Sanchez, Felipe; Garcia-Sanchez, Antonio-Javier; Losilla, Fernando; Garcia-Haro, Joan
IEEE 802.15.4 networking technology is designed to be the common standard for integrating WSN applications in heterogeneous environments. However, applications considering mobile nodes along with strict temporal requirements, such as those required for video transmission, are an unexplored field for this technology. These applications involve different challenges and issues that the direct employment of the IEEE 802.15.4 standard does not resolve. Therefore, in this paper a cross-layer mechanism consisting of application and medium access arbitration is presented, enabling the efficient connection and operation of mobile nodes together with the transmission of video flows. The proposed mechanism is evaluated via simulation and its feasibility checked by means of a first prototype. The study of power consumption is also taken into account and so are the quality of service parameters and the human quality perception of the received video stream. The results obtained are presented and further discussed.
Full Text Available Cloud computing and web emerging application has created the need for more powerful data centers with high performance interconnection networks.Current data center networks,based on electronic packet switches,will not be able to satisfy the required communication bandwidth of emerging applications without consuming excessive power.Optical interconnercts have gained attention recently as a promising solution offering high throughput,low latency and reduced energy cosumption compared to current networks based in commidity switches.This paper presents a novel architecture for data center networks based on optical OFDM using Wavelength Selective Swithces(WSS. The OFDM-based solution provides high throughput,reduced latency and fine grain bandwidth allocation. A heuristic algorithm for the bandwidth allocation is presented and evaluated in terms of utilization. The power analysis shows that the proposed scheme is almost 60% more energy efficient compared to the current networks based on eommodity switches.
Niesters, H G; Rossen, J W; van der Avoort, H; Baas, D; Benschop, K; Claas, E C; Kroneman, A; van Maarseveen, N; Pas, S; van Pelt, W; Rahamat-Langendoen, J C; Schuurman, R; Vennema, H; Verhoef, L; Wolthers, K; Koopmans, M
Laboratory-based surveillance, one of the pillars of monitoring infectious disease trends, relies on data produced in clinical and/or public health laboratories. Currently, diagnostic laboratories worldwide submit strains or samples to a relatively small number of reference laboratories for characterisation and typing. However, with the introduction of molecular diagnostic methods and sequencing in most of the larger diagnostic and university hospital centres in high-income countries, the distinction between diagnostic and reference/public health laboratory functions has become less clear-cut. Given these developments, new ways of networking and data sharing are needed. Assuming that clinical and public health laboratories may be able to use the same data for their own purposes when sequence-based testing and typing are used, we explored ways to develop a collaborative approach and a jointly owned database (TYPENED) in the Netherlands. The rationale was that sequence data - whether produced to support clinical care or for surveillance -can be aggregated to meet both needs. Here we describe the development of the TYPENED approach and supporting infrastructure, and the implementation of a pilot laboratory network sharing enterovirus sequences and metadata.
Grilo, M.; Fadigas, I. S.; Miranda, J. G. V.; Cunha, M. V.; Monteiro, R. L. S.; Pereira, H. B. B.
Here, we present a study on how the structure of semantic networks based on cliques (specifically, article titles) behaves when vertex removal strategies (i.e., random and uniform vertex removal - RUR, highest degree vertex removal - HDR, and highest intermediation centrality vertex removal - HICR) are applied to this type of network. We propose a method for calculation of the average size of the small components and we identify the existence of a fraction (fp) where the topological structure of the network changes. Semantic networks based on cliques maintain the small-world phenomenon when subjected to RUR, HDR and HICR for fractions of removed vertices less than or equal to fp.
The deployment of previous wireless standards has provided more benefits for urban dwellers than rural dwellers. 5G deployment may not be different. This paper identifies that Community Based Networks as carriers that deserve recognition as potential 5G providers may change this. The argument....... The findings indicate that 5G connectivity can be extended to rural areas by these networks, via heterogenous networks. Hence the delivery of 5G data rates delivery via Wireless WAN in rural areas can be achieved by utilizing the causal factors of the identified models for Community Based Networks....
Barnett, Ian; Kuijjer, Marieke L; Mucha, Peter J; Onnela, Jukka-Pekka
Network representations of systems from various scientific and societal domains are neither completely random nor fully regular, but instead appear to contain recurring structural building blocks. These features tend to be shared by networks belonging to the same broad class, such as the class of social networks or the class of biological networks. At a finer scale of classification within each such class, networks describing more similar systems tend to have more similar features. This occurs presumably because networks representing similar purposes or constructions would be expected to be generated by a shared set of domain specific mechanisms, and it should therefore be possible to classify these networks into categories based on their features at various structural levels. Here we describe and demonstrate a new, hybrid approach that combines manual selection of features of potential interest with existing automated classification methods. In particular, selecting well-known and well-studied features that ...
LI Ren-jie; YU Song-yu; XIONG Hong-kai
Moving object detection in video surveillance is an important step.This paper addresses an automatic object detection algorithm based on spatio-temporal compensation for video surveillance.Temporal difference of the pairs of two frames with a k-frame distance is utilized to obtain coarse object masks.Usually,object regions in these coarse masks have discontinuous boundaries and some holes.Region growing with the distance constraint is proposed to compensate these coarse object regions in spatial domain,followed by filling holes.The added distance constraint can prevent object regions from growing infinitely.The proposed fining holes method is simple and effective.To solve the temporarily stopping problem of moving objects,temporal compensation is proposed to compensate the object mask by utilizing temporal coherence of moving objects in temporal domain.The proposed detection algorithm can extract moving objects as completely as possible.Experimental results have successfully demonstrated the validity of the proposed algorithm.
Full Text Available The tremendous loss of lives and properties that may be attributed to criminals in recent times worldwide has become a source of worry to all and sundry. The situation has come to the alarming rate that the authority has sought for the immediate means of checkmating it without delay. Therefore, this work centers on the design and implementation of an Internet Protocol (IPbased security surveillance system. It incorporates remote viewing and storage of live video feeds and also remote motion control of the camera, all monitored with the use of a Personal Computer (PC. All the designs in this paper are software based. Hence, the software applications are developed using Visual C-Sharp (C# programming language to enable the proper monitoring and control of the entire system in which video feeds from the camera are viewed and also recorded on PC. The result obtained showed that with proper implementation, the surveillance system was found to be superb in all its ramifications.
Garre-Olmo, Josep; Flaqué, Margarita; Gich, Jordi; Pulido, Teresa Osuna; Turbau, Josefina; Vallmajo, Natalia; Viñas, Marta; López-Pousa, Secundí
Background Traditional epidemiological studies do not allow elucidating the reality of referral and diagnosis patterns of dementia in routine clinical practice within a defined territory. This information is useful and necessary in order to plan and allocate healthcare resources. This paper presents the results from a dementia case registry based on epidemiological surveillance fundamentals. Methods Standardised registry of dementia diagnoses made in 2007 by specialised care centres in the Health Region of Girona (RSG) (Spain), which encompasses an area of 5,517 sq. km and a reference population of 690,207 inhabitants. Results 577 cases of dementia were registered, of which 60.7% corresponded to cases of Alzheimer's disease. Presenile dementia accounted for 9.3% of the cases. Mean time between the onset of symptoms and clinical diagnosis was 2.4 years and the severity of the dementia was mild in 60.7% of the cases. High blood pressure, a family history of dementia, dislipidemia, and a past history of depression were the most common conditions prior to the onset of the disease (>20%). Conclusion The ReDeGi is a viable epidemiological surveillance device that provides information about the clinical and demographic characteristics of patients diagnosed with dementia in a defined geographical area. PMID:19175921
Dil, Yasemin; Strachan, Daniel; Cairncross, Sandy; Korkor, Andrew Seidu; Hill, Zelee
Community health workers (CHWs) are an important element of many health systems and programmes for the promotion and delivery of a wide range of health interventions and disease surveillance. Understanding the motivation and retention of CHWs is recognized as essential but there are few data from sub-Saharan Africa. This qualitative study explored factors that motivate, and the challenges faced by community-based surveillance volunteers (CBSVs) in the Northern Region of Ghana through semi-structured interviews with 28 CBSVs, 12 zonal coordinators, nine Ghana Health Service (GHS) sub-district level staff, ten GHS district level staff and two GHS regional level staff in the administrative capital. The community emerged as an important motivating factor in terms of altruism, a sense of duty to the community and gaining community respect and pride. This was enhanced by community selection of the volunteers. Major challenges included incorrect community perceptions of CBSVs, problems with transportation and equipment, difficulties conducting both volunteer and farm work and late or lack of payment for ad hoc tasks such as National Immunization Days. Most CBSVs recognized that they were volunteers, understood the constraints of the health system and were not demanding remuneration. However, CBSVs strongly desired something tangible to show that their work is recognized and appreciated and described a number of low cost items that could be used. They also desired equipment such as raincoats and identifiers such as tee-shirts and certificates.
Full Text Available The inference of gene regulatory networks (GRNs from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN, to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only
Q Sue Huang
Full Text Available Background: Recent experience with pandemic influenza A(H1N1pdm09 highlighted the importance of global surveillance for severe respiratory disease to support pandemic preparedness and seasonal influenza control. Improved surveillance in the southern hemisphere is needed to provide critical data on influenza epidemiology, disease burden, circulating strains and effectiveness of influenza prevention and control measures. Hospital-based surveillance for severe acute respiratory infection (SARI cases was established in New Zealand on 30 April 2012. The aims were to measure incidence, prevalence, risk factors, clinical spectrum and outcomes for SARI and associated influenza and other respiratory pathogen cases as well as to understand influenza contribution to patients not meeting SARI case definition. Methods/Design: All inpatients with suspected respiratory infections who were admitted overnight to the study hospitals were screened daily. If a patient met the World Health Organization’s SARI case definition, a respiratory specimen was tested for influenza and other respiratory pathogens. A case report form captured demographics, history of presenting illness, co-morbidities, disease course and outcome and risk factors. These data were supplemented from electronic clinical records and other linked data sources. Discussion: Hospital-based SARI surveillance has been implemented and is fully functioning in New Zealand. Active, prospective, continuous, hospital-based SARI surveillance is useful in supporting pandemic preparedness for emerging influenza A(H7N9 virus infections and seasonal influenza prevention and control.
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)....
Full Text Available Tracking of a moving object is very important for video surveillance in a real time scenario. The proposedalgorithm uses dynamic probe window based approach & combines the conventional edge based and framedifferencing approach to achieve better algorithmic time complexity as well as improved results. First itcomputes the edge map of two consecutive frames with the help of first order differential sobel operator dueto its noise resistant attributes and applies the frame differencing method between the two consecutive edgemaps. Apart from the above optimization, our method doesn’t differentiate between the scenario when motionoccurs and when it doesn’t, that is, almost same computation overhead is required even if motion is not thereso it reduces the time complexity of the algorithm when no motion is detected. The effectiveness of theproposed motion detection algorithm is demonstrated in a real time environment and the evaluation resultsare reported.
Wiratsudakul, Anuwat; Paul, Mathilde Cécile; Bicout, Dominique Joseph; Tiensin, Thanawat; Triampo, Wannapong; Chalvet-Monfray, Karine
In Southeast Asia, traditional poultry marketing chains have been threatened by epidemics caused by the highly pathogenic avian influenza H5N1 (HPAI H5N1) virus. In Thailand, the trade of live backyard chickens is based on the activities of traders buying chickens from villages and supplying urban markets with chicken meat. This study aims to quantify the flows of chickens traded during a 1-year period in a province of Thailand. A compartmental stochastic dynamic model was constructed to illustrate trade flows of live chickens from villages to slaughterhouses. Live poultry movements present important temporal variations with increased activities during the 15 days preceding the Chinese New Year and, to a lesser extent, other festivals (Qingming Festival, Thai New Year, Hungry Ghost Festival, and International New Year). The average distance of poultry movements ranges from 4 to 25 km, defining a spatial scale for the risk of avian influenza that spread through traditional poultry marketing chains. Some characteristics of traditional poultry networks in Thailand, such as overlapping chicken supply zones, may facilitate disease diffusion over longer distances through combined expansion and relocation processes. This information may be of use in tailoring avian influenza and other emerging infectious poultry disease surveillance and control programs provided that the cost-effectiveness of such scenarios is also evaluated in further studies.
Hennenfent, Andrew; DelVento, Vito; Davies-Cole, John; Johnson-Clarke, Fern
To enhance the early detection of emerging infectious diseases and bioterrorism events using companion animal-based surveillance. Washington, DC, small animal veterinary facilities (n=17) were surveyed to determine interest in conducting infectious disease surveillance. Using these results, an electronic-based online reporting system was developed and launched in August 2015 to monitor rates of canine influenza, canine leptospirosis, antibiotic resistant infections, canine parvovirus, and syndromic disease trends. Nine of the 10 facilities that responded expressed interest conducting surveillance. In September 2015, 17 canine parvovirus cases were reported. In response, a campaign encouraging regular veterinary preventative care was launched and featured on local media platforms. Additionally, during the system's first year of operation it detected 5 canine leptospirosis cases and 2 antibiotic resistant infections. No canine influenza cases were reported and syndromic surveillance compliance varied, peaking during National Special Security Events. Small animal veterinarians and the general public are interested in companion animal disease surveillance. The system described can serve as a model for establishing similar systems to monitor disease trends of public health importance in pet populations and enhance biosurveillance capabilities. Copyright © 2017 Elsevier B.V. All rights reserved.
Huang, Jian; Hu, Weidong; Xin, Qin; Guo, Weiwei
The increasing amount of space debris threatens to seriously deteriorate and damage space-based instruments in Low Earth Orbit (LEO) environments. Therefore, LEO space debris surveillance systems must be developed to provide situational awareness in space and issue warnings of collisions with LEO space debris. In this paper, a double fence radar system is proposed as an emerging paradigm for LEO space debris surveillance. This system exhibits several unique and promising characteristics compared with existing surveillance systems. In this paper, we also investigate the data association scheme for LEO space debris surveillance based on a double fence radar system. We also perform a theoretical analysis of the performance of our proposed scheme. The superiority and the effectiveness of our novel data association scheme is demonstrated by experimental results. The data used in our experiments is the LEO space debris catalog produced by the North American Air Defense Command (NORAD) up to 2009, especially for scenarios with high densities of LEO space debris, which were primarily produced by the collisions between Iridium 33 and Cosmos 2251. We hope that our work will stimulate and benefit future work on LEO space debris surveillance approaches and enable construction of the double fence radar system.
Full Text Available The emergence and spread of multidrug resistant (MDR malaria caused by Plasmodium falciparum or Plasmodium vivax have become increasingly important in the Greater Mekong Subregion (GMS. MDR malaria is the heritable and hypermutable property of human malarial parasite populations that can decrease in vitro and in vivo susceptibility to proven antimalarial drugs as they exhibit dose-dependent drug resistance and delayed parasite clearance time in treated patients. MDR malaria risk situations reflect consequences of the national policy and strategy as this influences the ongoing national-level or subnational-level implementation of malaria control strategies in endemic GMS countries. Based on our experience along with current literature review, the design of ecotope-based entomological surveillance (EES and molecular xenomonitoring of MDR falciparum and vivax malaria parasites in Anopheles vectors is proposed to monitor infection pockets in transmission control areas of forest and forest fringe-related malaria, so as to bridge malaria landscape ecology (ecotope and ecotone and epidemiology. Malaria ecotope and ecotone are confined to a malaria transmission area geographically associated with the infestation of Anopheles vectors and particular environments to which human activities are related. This enables the EES to encompass mosquito collection and identification, salivary gland DNA extraction, Plasmodium- and species-specific identification, molecular marker-based PCR detection methods for putative drug resistance genes, and data management. The EES establishes strong evidence of Anopheles vectors carrying MDR P. vivax in infection pockets epidemiologically linked with other data obtained during which a course of follow-up treatment of the notified P. vivax patients receiving the first-line treatment was conducted. For regional and global perspectives, the EES would augment the epidemiological surveillance and monitoring of MDR falciparum and
ZHANG Jin-yu; LI Hong-hui; LIU Feng
This paper addresses a management model for IP network based on Next Generation Operation Support System (NGOSS). It makes the network management on the base of all the operation actions of ISP, It provides QoS to user service through the whole path by providing end-to-end Service Level Agreements (SLA) management through whole path. Based on web and coordination technology, this paper gives an implement architecture of this model.
Full Text Available This paper introduces an in-service transmission surveillance and protection-based approach for fiber failures/faults over fiber-to-the-home passive optical network (FTTH-PON with an excellent combination of Access Control System (ACS and Smart Access Network Testing, Analyzing and Database (SANTAD. Our hardware design works on a standard local area network (LAN using a specially designed hardware interfaced with a microcontroller integrated Ethernet to monitor the status of optical signals flow and provide the restoration against fiber failures/faults in FTTH-PON. We also introduce the centralized management and access control program by means of SANTAD. ACS is used to control the troubleshooting mechanism carried out by SANTAD. This design will be implemented at central office (CO for distant monitoring and remote controlling each optical fiber line’s status as well as for detecting any failures/faults that occurs in the network system downwardly from CO towards multiple optical network units (ONUs. The scope of this discussion only highlighted on the monitoring and controlling instead of the restoration scheme.
Drevers, Thomas; van de Meent, R.; Pras, Aiko; Harjo, J.; Moltchanov, D.; Silverajan, B.
Web services is one of the emerging approaches in network management. This paper describes the design and implementation of four Web services based network monitoring prototypes. Each prototype follows a speciï¿½ï¿½?c approach to retrieve management data, ranging from retrieving a single management
Full Text Available The last few years have seen an increased interest in the potential use of wireless sensor networks (WSNs in various fields like disaster management, battle field surveillance, and border security surveillance. In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomously. The process of dividing the network into interconnected substructures is called clustering and the interconnected substructures are called clusters. The cluster head (CH of each cluster act as a coordinator within the substructure. Each CH acts as a temporary base station within its zone or cluster. It also communicates with other CHs. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption. It can also increase network scalability. Researchers in all fields of wireless sensor network believe that nodes are homogeneous, but some nodes may be of different characteristics to prolong the lifetime of a WSN and its reliability. We have proposed an algorithm for better cluster head selection based on weights for different parameter that influence on energy consumption which includes distance from base station as a new parameter to reduce number of transmissions and reduce energy consumption by sensor nodes. Finally proposed algorithm compared with the WCA, IWCA algorithm in terms of number of clusters and energy consumption.
An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian
Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.
Talati, Mikita V.; Valiveti, Sharada; Kotecha, K.
Ad Hoc network often termed as an infrastructure-less, self- organized or spontaneous network.The execution and survival of an ad-hoc network is solely dependent upon the cooperative and trusting nature of its nodes. However, this naive dependency on intermediate nodes makes the ad-hoc network vulnerable to passive and active attacks by malicious nodes and cause inflict severe damage. A number of protocols have been developed to secure ad-hoc networks using cryptographic schemes, but all rely on the presence of trust authority. Due to mobility of nodes and limitation of resources in wireless network one interesting research area in MANET is routing. This paper offers various trust models and trust based routing protocols to improve the trustworthiness of the neighborhood.Thus it helps in selecting the most secure and trustworthy route from the available ones for the data transfer.
Garcia, Eloy; Montestruque, Luis A
This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled. The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control. Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...
Jianhui Wu; Kuntao Yang; Qiaolian Xiang; Nanyang Zhang
A new method is proposed for the object surveillance system based on the enhanced fish-eye lens and the high speed digital signal processor (DSP). The improved fish-eye lens images an ellipse picture on the charge-coupled device (CCD) surface, which increases both the utilization rate of the 4:3 rectangular CCD and the imaging resolution, and remains the view angle of 183°. The algorithm of auto-adapted renewal background subtraction (ARBS) is also explored to extract the object from the monitoring image. The experimental result shows that the ARBS algorithm has high anti-jamming ability and high resolution, leading to excellent object detecting ability from the enhanced elliptical fish-eye image under varies en-vironments. This system has potential applications in different security monitoring fields due to its wide monitoring space, simple structure, working stability, and reliability.
Stewar, Avaré; Diaz-Aviles, Ernesto; Dolog, Peter
In a typical Event-Based Surveillance setting, a stream of web documents is continuously monitored for disease reporting. A structured representation of the disease reporting events is extracted from the raw text, and the events are then aggregated to produce signals, which are intended to represent early warnings against potential public health threats. To public health officials, these warnings represent an overwhelming list of "one-size-fits-all" information for risk assessment. To reduce this overload, two techniques are proposed. First, filtering signals according to the user's preferences (e.g., location, disease, symptoms, etc.) helps reduce the undesired noise. Second, re-ranking the filtered signals, according to an individual's feedback and annotation, allows a user-specific, prioritized ranking of the most relevant warnings. We introduce an approach that takes into account this two-step process of: 1) filtering and 2) re-ranking the results of reporting signals. For this, Collaborative Filtering an...
The 45th Weather Squadron (45 WS) is replacing the Weather Surveillance Radar, Model 74C (WSR-74C) at Patrick Air Force Base (PAFB), with a Doppler, dual polarization radar, the Radtec 43/250. A new scan strategy is needed for the Radtec 43/250, to provide high vertical resolution data over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) launch pads, while taking advantage of the new radar's advanced capabilities for detecting severe weather phenomena associated with convection within the 45 WS area of responsibility. The Applied Meteorology Unit (AMU) developed several scan strategies customized for the operational needs of the 45 WS. The AMU also developed a plan for evaluating the scan strategies in the period prior to operational acceptance, currently scheduled for November 2008.
Wang, Ying; Le, Linh H; Wang, Xiaohang; Tao, Zhen; Druschel, Charlotte D; Cross, Philip K; Hwang, Syni-An
Geographic information systems (GIS) have been widely used in mapping health data and analyzing the geographic distribution of disease. Mapping and spatially analyzing data normally begins with geocoding, a process of assigning geographic coordinates to an address so that it can be displayed and analyzed on a map. The objectives of this project were to develop Web-based geocoding applications for the New York State birth defects surveillance system to geocode, both automatically and interactively, the birth defect cases of the Congenital Malformations Registry (CMR) and evaluate the geocoding results. Geocoding software, in conjunction with a Java-based development tool (J Server), was used to develop the Web-based applications on the New York State Department of Health's Health Commerce System. The Web-based geocoding applications have been developed and implemented for the New York State birth defects surveillance system. These menu-driven applications empower users to conduct geocoding activities using only a PC and a Web browser without the installation of any GIS software. These powerful tools provide automatic, real-time, street-level geocoding of the routinely collected birth defects records in the CMR. Up to 92% of the CMR records have been geocoded with addresses exactly matched to the reference addresses on house number, street name, and city or zip code.
Masuda, Naoki; Kori, Hiroshi
Determining the relative importance of nodes in directed networks is important in, for example, ranking websites, publications, and sports teams, and for understanding signal flows in systems biology. A prevailing centrality measure in this respect is the PageRank. In this work, we focus on another class of centrality derived from the Laplacian of the network. We extend the Laplacian-based centrality, which has mainly been applied to strongly connected networks, to the case of general directed networks such that we can quantitatively compare arbitrary nodes. Toward this end, we adopt the idea used in the PageRank to introduce global connectivity between all the pairs of nodes with a certain strength. Numerical simulations are carried out on some networks. We also offer interpretations of the Laplacian-based centrality for general directed networks in terms of various dynamical and structural properties of networks. Importantly, the Laplacian-based centrality defined as the stationary density of the continuous-time random walk with random jumps is shown to be equivalent to the absorption probability of the random walk with sinks at each node but without random jumps. Similarly, the proposed centrality represents the importance of nodes in dynamics on the original network supplied with sinks but not with random jumps.
Brookes, Victoria J.; Kennedy, Emma; Dhagapan, Phillipa; Ward, Michael P.
Given the proximity and recent spread of rabies in Indonesia, effective rabies surveillance in dogs is a priority in Northern Australia and Papua New Guinea (PNG). Reporting of potential cases requires community engagement; therefore, the value and acceptability of such a system is critical to ensure sustainable surveillance. We used qualitative research methods to identify factors that influence the acceptability and value of community-based rabies surveillance. Thirty-two semi-structured interviews were conducted with informants in 16 communities in East Arnhem, the Northern Peninsula Area, the Torres Strait in Australia, and in Western Province, PNG. Thematic analysis identified common themes including the importance of verbal communication, particularly via radio, community meetings, and direct conversation. We also found that dogs have high value to community members through connection to culture, economic (especially hunting), and companionship. The greatest barrier to the reporting of sick dogs was insufficient veterinary services and the subsequent lack of treatment response. In some regions, acceptance that sick dogs are a normal daily occurrence and lack of trust of authorities were also barriers to reporting. The findings from this study will be used to design sustainable rabies surveillance in Northern Australia and PNG by utilizing traditional communication channels and building on existing and valued animal-management services. The methods and findings of this study complement previous quantitative research, so as to target surveillance to high-risk areas within these regions. PMID:28275611
Brookes, Victoria J; Kennedy, Emma; Dhagapan, Phillipa; Ward, Michael P
Given the proximity and recent spread of rabies in Indonesia, effective rabies surveillance in dogs is a priority in Northern Australia and Papua New Guinea (PNG). Reporting of potential cases requires community engagement; therefore, the value and acceptability of such a system is critical to ensure sustainable surveillance. We used qualitative research methods to identify factors that influence the acceptability and value of community-based rabies surveillance. Thirty-two semi-structured interviews were conducted with informants in 16 communities in East Arnhem, the Northern Peninsula Area, the Torres Strait in Australia, and in Western Province, PNG. Thematic analysis identified common themes including the importance of verbal communication, particularly via radio, community meetings, and direct conversation. We also found that dogs have high value to community members through connection to culture, economic (especially hunting), and companionship. The greatest barrier to the reporting of sick dogs was insufficient veterinary services and the subsequent lack of treatment response. In some regions, acceptance that sick dogs are a normal daily occurrence and lack of trust of authorities were also barriers to reporting. The findings from this study will be used to design sustainable rabies surveillance in Northern Australia and PNG by utilizing traditional communication channels and building on existing and valued animal-management services. The methods and findings of this study complement previous quantitative research, so as to target surveillance to high-risk areas within these regions.
CHEN Ai-bin; CAI Zi-xing; HU De-wen
An on-demand distributed clustering algorithm based on neural network was proposed. The system parameters and the combined weight for each node were computed, and cluster-heads were chosen using the weighted clustering algorithm, then a training set was created and a neural network was trained. In this algorithm, several system parameters were taken into account, such as the ideal node-degree, the transmission power, the mobility and the battery power of the nodes. The algorithm can be used directly to test whether a node is a cluster-head or not. Moreover, the clusters recreation can be speeded up.
Panyasing, Y; Goodell, C; Kittawornrat, A; Wang, C; Levis, I; Desfresne, L; Rauh, R; Gauger, P C; Zhang, J; Lin, X; Azeem, S; Ghorbani-Nezami, S; Yoon, K-J; Zimmerman, J
Influenza A virus (IAV) surveillance using pre-weaning oral fluid samples from litters of piglets was evaluated in four ˜12 500 sow and IAV-vaccinated, breeding herds. Oral fluid samples were collected from 600 litters and serum samples from their dams at weaning. Litter oral fluid samples were tested for IAV by virus isolation, quantitative reverse transcription-polymerase chain reaction (qRT-PCR), RT-PCR subtyping and sequencing. Commercial nucleoprotein (NP) enzyme-linked immunosorbent assay (ELISA) kits and NP isotype-specific assays (IgM, IgA and IgG) were used to characterize NP antibody in litter oral fluid and sow serum. All litter oral fluid specimens (n = 600) were negative by virus isolation. Twenty-five oral fluid samples (25/600 = 4.2%) were qRT-PCR positive based on screening (Laboratory 1) and confirmatory testing (Laboratory 2). No hemagglutinin (HA) and neuraminidase (NA) gene sequences were obtained, but matrix (M) gene sequences were obtained for all qRT-PCR-positive samples submitted for sequencing (n = 18). Genetic analysis revealed that all M genes sequences were identical (GenBank accession no. KF487544) and belonged to the triple reassortant influenza A virus M gene (TRIG M) previously identified in swine. The proportion of IgM- and IgA-positive samples was significantly higher in sow serum and litter oral fluid samples, respectively (P oral fluids. This study supported the use of oral fluid sampling as a means of conducting IAV surveillance in pig populations and demonstrated the inapparent circulation of IAV in piglets. Future work on IAV oral fluid diagnostics should focus on improved procedures for virus isolation, subtyping and sequencing of HA and NA genes. The role of antibody in IAV surveillance remains to be elucidated, but longitudinal assessment of specific antibody has the potential to provide information regarding patterns of infection, vaccination status and herd immunity.
Full Text Available The meteorological surveillance of the four nuclear power plants in Switzerland is of first importance in a densely populated area such as the Swiss Plateau. The project "Centrales Nucléaires et Météorologie" CN-MET aimed at providing a new security tool based on one hand on the development of a high resolution numerical weather prediction (NWP model. The latter is providing essential nowcasting information in case of a radioactive release from a nuclear power plant in Switzerland. On the other hand, the model input over the Swiss Plateau is generated by a dedicated network of surface and upper air observations including remote sensing instruments (wind profilers and temperature/humidity passive microwave radiometers. This network is built upon three main sites ideally located for measuring the inflow/outflow and central conditions of the main wind field in the planetary boundary layer over the Swiss Plateau, as well as a number of surface automatic weather stations (AWS. The network data are assimilated in real-time into the fine grid NWP model using a rapid update cycle of eight runs per day (one forecast every three hours. This high resolution NWP model has replaced the former security tool based on in situ observations (in particular one meteorological mast at each of the power plants and a local dispersion model. It is used to forecast the dynamics of the atmosphere in the planetary boundary layer (typically the first 4 km above ground layer and over a time scale of 24 h. This tool provides at any time (e.g. starting at the initial time of a nuclear power plant release the best picture of the 24-h evolution of the air mass over the Swiss Plateau and furthermore generates the input data (in the form of simulated values substituting in situ observations required for the local dispersion model used at each of the nuclear power plants locations. This paper is presenting the concept and two validation studies as well as the results of an
Sea Shuan Luo
Full Text Available This paper presents a comparative study about the development of a network based laboratory environment in the “Unix introduction” course for the undergraduate students. The study results and the response from the students from 2005 to 2006 will be used to better understand what kind of method is more suitable for students. We also use the data collected to adjust our teaching strategy and try to build up a network based laboratory environment.
Roberts, Rhonda Sue; Foppa, Ivo M
Since the introduction of West Nile Virus (WNV) to the United States in 1999, the efficacy of dead bird surveillance for the prediction of human and veterinary WNV infection has been an issue of debate. We utilized South Carolina's Department of Health and Environmental Control surveillance data from 2003 to determine whether dead bird surveillance accurately predicts equine WNV infection on a county level. We adjusted for human population density as a potential confounder of an association between WNV-positive dead bird counts and mammalian WNV risk. We found a strong positive association between avian risk of WNV death and subsequent equine mortality due to WNV in South Carolina even after adjusting for human population density. Sensitivity of dead bird surveillance as a predictor of future equine WNV risk was far superior to mosquito surveillance (95% vs. 9.5%, respectively). A Poisson regression model of the equine WNV rate as a function of WNV-positive dead bird rate, adjusting for population density and taking into account effect modification by population density shows a good fit with the data. Unlike most previous studies, we control for potential confounding of the dead, WNVpositive bird-equine WNV infection association by human population density. Yet, the positive association between dead bird surveillance and equine WNV risk remains strong and statistically significant, indicating that dead bird surveillance remains a valuable tool of WNV surveillance.
Ali Safa Sadiq
Full Text Available This paper proposes an Advanced Mobility Handover (AMH scheme based on Wireless Local Area Networks (WLANs by developing a network layer handover procedure which triggers messages to be sent to the next access point. The proposed AMH scheme performs the network handover process, which is represented by binding update procedure in advance during the time mobile node is still connected to the current AP in the link layer. Furthermore, a unique home IPv6 address is developed to maintain an IP communication with other corresponding nodes without a care-of-address during mobile node$'$s roaming process. This can contribute significantly to reducing network layer handover delays and signaling costs by eliminate the process of obtaining a new care-of-address and processing the handover of network layer in advance while the mobile node is still communicating with the current access point. Eventually, the conducted OMNET++ simulated scenario shows that the proposed AMH scheme performs the best in terms of reducing the handover delay as compared to the state of the art.
New Network of Automatic Stations integrated in the CSNs Environmental Radiological Surveillance Network; Nueva Red de Estaciones Automaticas integrada en la Red de Vigilancia Radiologica Ambiental del CSN
Parages Perez del Yerro, C.; Garcia Cadierno, J. P.; Calvin Cuartero, M.
In 1992, the Council put into operation a network comprising 25 automatic stations for continuous monitoring of the radiological quality of the air and the detection of anomalous situations. It has now decided to undertake the renewal and modernisation of these installations, incorporating sensors and automatic connection and communication systems based on the best technology currently available. (Author)
Full Text Available Background The genetic epidemiology of ischemic stroke remains relatively unstudied, and information about the genetic epidemiology of ischemic stroke in populations with significant minority representation is currently unavailable. Methods The Brain Attack Surveillance in Corpus Christi project (BASIC is a population-based stroke surveillance study conducted in the bi-ethnic community of Nueces County, Texas, USA. Completed ischemic strokes were identified among patients 45 years or older seen at hospitals in the county between January 1, 2000 – December 31, 2002. A random sample of ischemic stroke patients underwent an in-person interview and detailed medical record abstraction (n = 400. Outcomes, including initial stroke severity (NIH stroke scale, age at stroke onset, 90-day mortality and functional outcome (modified Rankin scale ≥2, were studied for their association with family history of stroke among a first degree relative using multivariable logistic and linear regression. A chi-square test was used to test the association between family history of stroke and ischemic stroke subtype. Results The study population was 53.0% Mexican American and 58.4% female. Median age was 73.2 years. Forty percent reported a family history of stroke among a first degree relative. Family history of stroke was borderline significantly associated with stroke subtype (p = 0.0563. Family history was associated with poor functional outcome in the multivariable model (OR = 1.87; 95% CI: 1.14–3.09. Family history was not significantly related to initial stroke severity, age at stroke onset, or 90-day mortality. Conclusion Family history of stroke was related to ischemic stroke subtype and to functional status at discharge. More research is needed to understand whether stroke subtype would be a useful selection criterion for genetic association studies and to hypothesize about a possible genetic link to recovery following ischemic stroke.
Eric H Y Lau
Full Text Available BACKGROUND: Multiple sources of influenza surveillance data are becoming more available; however integration of these data streams for situational awareness of influenza activity is less explored. METHODS AND RESULTS: We applied multivariate time-series methods to sentinel outpatient and school absenteeism surveillance data in Hong Kong during 2004-2009. School absenteeism data and outpatient surveillance data experienced interruptions due to school holidays and changes in public health guidelines during the pandemic, including school closures and the establishment of special designated flu clinics, which in turn provided 'drop-in' fever counts surveillance data. A multivariate dynamic linear model was used to monitor influenza activity throughout epidemics based on all available data. The inferred level followed influenza activity closely at different times, while the inferred trend was less competent with low influenza activity. Correlations between inferred level and trend from the multivariate model and reference influenza activity, measured by the product of weekly laboratory influenza detection rates and weekly general practitioner influenza-like illness consultation rates, were calculated and compared with those from univariate models. Over the whole study period, there was a significantly higher correlation (ρ = 0.82, p≤0.02 for the inferred trend based on the multivariate model compared to other univariate models, while the inferred trend from the multivariate model performed as well as the best univariate model in the pre-pandemic and the pandemic period. The inferred trend and level from the multivariate model was able to match, if not outperform, the best univariate model albeit with missing data plus drop-in and drop-out of different surveillance data streams. An overall influenza index combining level and trend was constructed to demonstrate another potential use of the method. CONCLUSIONS: Our results demonstrate the
Wiggins, Lisa D.; Rice, Catherine E.; Baio, Jon
This study evaluated the phenomenon of autistic regression using population-based data. The sample comprised 285 children who met the autism spectrum disorder (ASD) case definition within an ongoing surveillance program. Results indicated that children with a previously documented ASD diagnosis had higher rates of autistic regression than children…
This technical report will cover the participation in the IEEE International Conference on Advanced Video and Signal based Surveillance in September 2007. The report will give a concise description of the most relevant topics presented at the conference, focusing on the work related to the HERMES...
Tejedor, Javier; Macias-Guarasa, Javier; Martins, Hugo F; Piote, Daniel; Pastor-Graells, Juan; Martin-Lopez, Sonia; Corredera, Pedro; Gonzalez-Herraez, Miguel
This paper presents a novel surveillance system aimed at the detection and classification of threats in the vicinity of a long gas pipeline. The sensing system is based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) technology for signal acquisition and pattern recognition strategies for threat identification. The proposal incorporates contextual information at the feature level and applies a system combination strategy for pattern classification. The contextual information at the feature level is based on the tandem approach (using feature representations produced by discriminatively-trained multi-layer perceptrons) by employing feature vectors that spread different temporal contexts. The system combination strategy is based on a posterior combination of likelihoods computed from different pattern classification processes. The system operates in two different modes: (1) machine + activity identification, which recognizes the activity being carried out by a certain machine, and (2) threat detection, aimed at detecting threats no matter what the real activity being conducted is. In comparison with a previous system based on the same rigorous experimental setup, the results show that the system combination from the contextual feature information improves the results for each individual class in both operational modes, as well as the overall classification accuracy, with statistically-significant improvements.
Full Text Available This paper presents a novel surveillance system aimed at the detection and classification of threats in the vicinity of a long gas pipeline. The sensing system is based on phase-sensitive optical time domain reflectometry (ϕ-OTDR technology for signal acquisition and pattern recognition strategies for threat identification. The proposal incorporates contextual information at the feature level and applies a system combination strategy for pattern classification. The contextual information at the feature level is based on the tandem approach (using feature representations produced by discriminatively-trained multi-layer perceptrons by employing feature vectors that spread different temporal contexts. The system combination strategy is based on a posterior combination of likelihoods computed from different pattern classification processes. The system operates in two different modes: (1 machine + activity identification, which recognizes the activity being carried out by a certain machine, and (2 threat detection, aimed at detecting threats no matter what the real activity being conducted is. In comparison with a previous system based on the same rigorous experimental setup, the results show that the system combination from the contextual feature information improves the results for each individual class in both operational modes, as well as the overall classification accuracy, with statistically-significant improvements.
Zhou, Kaixing; Sun, Xiucong; Huang, Hai; Wang, Xinsheng; Ren, Guangwei
The space-based Automatic Dependent Surveillance - Broadcast (ADS-B) is a new technology for air traffic management. The satellite equipped with spaceborne ADS-B system receives the broadcast signals from aircraft and transfers the message to ground stations, so as to extend the coverage area of terrestrial-based ADS-B. In this work, a novel satellite single-axis attitude determination solution based on the ADS-B receiving system is proposed. This solution utilizes the signal-to-noise ratio (SNR) measurement of the broadcast signals from aircraft to determine the boresight orientation of the ADS-B receiving antenna fixed on the satellite. The basic principle of this solution is described. The feasibility study of this new attitude determination solution is implemented, including the link budget and the access analysis. On this basis, the nonlinear least squares estimation based on the Levenberg-Marquardt method is applied to estimate the single-axis orientation. A full digital simulation has been carried out to verify the effectiveness and performance of this solution. Finally, the corresponding results are processed and presented minutely.
Tejedor, Javier; Macias-Guarasa, Javier; Martins, Hugo F.; Piote, Daniel; Pastor-Graells, Juan; Martin-Lopez, Sonia; Corredera, Pedro; Gonzalez-Herraez, Miguel
This paper presents a novel surveillance system aimed at the detection and classification of threats in the vicinity of a long gas pipeline. The sensing system is based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) technology for signal acquisition and pattern recognition strategies for threat identification. The proposal incorporates contextual information at the feature level and applies a system combination strategy for pattern classification. The contextual information at the feature level is based on the tandem approach (using feature representations produced by discriminatively-trained multi-layer perceptrons) by employing feature vectors that spread different temporal contexts. The system combination strategy is based on a posterior combination of likelihoods computed from different pattern classification processes. The system operates in two different modes: (1) machine + activity identification, which recognizes the activity being carried out by a certain machine, and (2) threat detection, aimed at detecting threats no matter what the real activity being conducted is. In comparison with a previous system based on the same rigorous experimental setup, the results show that the system combination from the contextual feature information improves the results for each individual class in both operational modes, as well as the overall classification accuracy, with statistically-significant improvements. PMID:28208687
The widespread relevance of increasingly complex networks requires methods to extract meaningful coarse-grained representations of such systems. For undirected graphs, standard community detection methods use criteria largely based on density of connections to provide such representations. We propose a method for grouping nodes in directed networks based on the role of the nodes in the network, understood in terms of patterns of incoming and outgoing flows. The role groupings are obtained through the clustering of a similarity matrix, formed by the distances between feature vectors that contain the number of in and out paths of all lengths for each node. Hence nodes operating in a similar flow environment are grouped together although they may not themselves be densely connected. Our method, which includes a scale factor that reveals robust groupings based on increasingly global structure, provides an alternative criterion to uncover structure in networks where there is an implicit flow transfer in the system...
Song, D. Y.; Lee, S. Y.; Ha, J. H.; Go, W. I.; Kim, H. D. [KAERI, Taejon (Korea, Republic of)
Unattended continuous surveillance systems for safeguards of nuclear facility result in large amounts of image and radiation data, which require much time and effort to inspect. Therefore, it is necessary to develop system that automatically pinpoints and diagnoses the anomalies from data. In this regards, this paper presents a novel concept of the continuous surveillance system that integrates visual image and radiation data by the use of neural networks based on self-organized feature mapping. This surveillance system is stably operating for safeguards of the DUPIC (DFDF) in KAERI.
Full Text Available Due to the unprecedented development of networks, manual network service provisioning is becoming increasingly risky, error-prone, expensive, and time-consuming. To solve this problem,rule-based methods can provide adequate leverage for automating various network management tasks. This paper presents a rule-based solution for automated network service provisioning. The proposed approach captures configuration data interdependencies using high-level, service-specific, user-configurable rules. We focus on the service validation task, which is illustrated by means of a case study.Based on numerical results, we analyse the influence of the network-level complexity factors and rule descriptive features on the rule efficiency. This analysis shows the operators how to increase rule efficiency while keeping the rules simple and the rule set compact. We present a technique that allows operators to increase the error coverage, and we show that high error coverage scales well when the complexity of networks and services increases.We reassess the correlation function between specific rule efficiency and rule complexity metrics found in previous work, and show that this correlation function holds for various sizes, types, and complexities of networks and services.
Herz, A.; Herz, E.; Center, K.; George, P.; Axelrad, P.; Mutschler, S.; Jones, B.
The Space Surveillance Network (SSN) is tasked with the increasingly difficult mission of detecting, tracking, cataloging and identifying artificial objects orbiting the Earth, including active and inactive satellites, spent rocket bodies, and fragmented debris. Much of the architecture and operations of the SSN are limited and outdated. Efforts are underway to modernize some elements of the systems. Even so, the ability to maintain the best current Space Situational Awareness (SSA) picture and identify emerging events in a timely fashion could be significantly improved by leveraging non-traditional sensor sites. Orbit Logic, the University of Colorado and the University of Texas at Austin are developing an innovative architecture and operations concept to coordinate the tasking and observation information processing of non - traditional assets based on information-theoretic approaches. These confirmed tasking schedules and the resulting data can then be used to "inform" the SSN tasking process. The 'Heimdall Web' system is comprised of core tasking optimization components and accompanying Web interfaces within a secure, split architecture that will for the first time allow non-traditional sensors to support SSA and improve SSN tasking. Heimdall Web application components appropriately score/prioritize space catalog objects based on covariance, priority, observability, expected information gain, and probability of detect - then coordinate an efficient sensor observation schedule for non-SSN sensors contributing to the overall SSA picture maintained by the Joint Space Operations Center (JSpOC). The Heimdall Web Ops concept supports sensor participation levels of "Scheduled", "Tasked" and "Contributing". Scheduled and Tasked sensors are provided optimized observation schedules or object tracking lists from central algorithms, while Contributing sensors review and select from a list of "desired track objects". All sensors are "Web Enabled" for tasking and feedback
Lowry, R Brian
Congenital anomalies (CA) are present in approximately 3% of all newborn babies and account for about 12% of paediatric hospital admissions. They represent an important public health problem. Surveillance is especially important so that preventive measures such as folic acid fortification can be properly assessed without resorting to a series of ad hoc studies. Canada's surveillance of CAs is weak, with only Alberta and British Columbia having established sytems. Most provinces have perinatal systems but their CA data are incomplete and they do not capture terminations of pregnancy. The same is true of the Public Health Agency of Canada's system. A new system, the Fetal Alert Network, has been proposed for Ontario, which represents a start but will require additional sources of ascertainment if it is to be a truly population-based system for Ontario.
Katz, Rebecca; May, Larissa; Baker, Julia; Test, Elisa
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. Copyright © 2011 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.
Nielsen, J.N.; Knudsen, Morten; Nielsen, Jens Frederik Dalsgaard
A course in database design and implementation has been de- signed, utilizing existing network facilities. The course is an elementary course for students of computer engineering. Its purpose is to give the students a theoretical database knowledge as well as practical experience with design...... and implementation. A tutorial relational database and the students self-designed databases are implemented on the UNIX system of Aalborg University, thus giving the teacher the possibility of live demonstrations in the lecture room, and the students the possibility of interactive learning in their working rooms...
Nielsen, J.N.; Knudsen, Morten; Nielsen, Jens Frederik Dalsgaard
A course in database design and implementation has been de- signed, utilizing existing network facilities. The course is an elementary course for students of computer engineering. Its purpose is to give the students a theoretical database knowledge as well as practical experience with design...... and implementation. A tutorial relational database and the students self-designed databases are implemented on the UNIX system of Aalborg University, thus giving the teacher the possibility of live demonstrations in the lecture room, and the students the possibility of interactive learning in their working rooms...
Full Text Available According to the 31th statistical reports of China Internet network information center (CNNIC, by the end of December 2012, the number of Chinese netizens has reached 564 million, and the scale of mobile Internet users also reached 420 million. But when the network brings great convenience to people's life, it also brings huge threat in the life of people. So through collecting and analyzing the information in the computer system or network we can detect any possible behaviors that can damage the availability, integrity and confidentiality of the computer resource, and make timely treatment to these behaviors which have important research significance to improve the operation environment of network and network service. At present, the Neural Network, Support Vector machine (SVM and Hidden Markov Model, Fuzzy inference and Genetic Algorithms are introduced into the research of network intrusion detection, trying to build a healthy and secure network operation environment. But most of these algorithms are based on the total sample and it also hypothesizes that the number of the sample is infinity. But in the field of network intrusion the collected data often cannot meet the above requirements. It often shows high latitudes, variability and small sample characteristics. For these data using traditional machine learning methods are hard to get ideal results. In view of this, this paper proposed a Generalized Multi-Kernel Learning method to applied to network intrusion detection. The Generalized Multi-Kernel Learning method can be well applied to large scale sample data, dimension complex, containing a large number of heterogeneous information and so on. The experimental results show that applying GMKL to network attack detection has high classification precision and low abnormal practical precision.
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...... 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)....
Full Text Available Abstract Background Surveillance data allow for analysis, providing public health officials and policy-makers with a basis for long-term priorities and timely information on possible outbreaks for rapid response (data for action. In this article we describe the considerations and technology behind a newly introduced public web tool in Sweden for easy retrieval of county and national surveillance data on communicable diseases. Methods The web service was designed to automatically present updated surveillance statistics of some 50 statutory notifiable diseases notified to the Swedish Institute for Infectious Disease Control (SMI. The surveillance data is based on clinical notifications from the physician having treated the patient and laboratory notifications, merged into cases using a unique personal identification number issued to all Swedish residents. The web service use notification data from 1997 onwards, stored in a relational database at the SMI. Results The web service presents surveillance data to the user in various ways; tabulated data containing yearly and monthly disease data per county, age and sex distribution, interactive maps illustrating the total number of cases and the incidence per county and time period, graphs showing the total number of cases per week and graphs illustrating trends in the disease data. The system design encompasses the database (storing the data, the web server (holding the web service and an in-the-middle computer (to ensure good security standards. Conclusions The web service has provided the health community, the media, and the public with easy access to both timely and detailed surveillance data presented in various forms. Since it was introduced in May 2003, the system has been accessed more than 1,000,000 times, by more than 10,000 different viewers (over 12.600 unique IP-numbers.
Laupland Kevin B
Full Text Available Abstract Background Hospital-based series have characterized Hafnia alvei primarily as an infrequent agent of polymicrobial nosocomial infections in males with underlying illness. Methods We conducted population-based laboratory surveillance in the Calgary Health Region during 2000–2005 to define the incidence, demographic risk factors for acquisition, and anti-microbial susceptibilities of Hafnia alvei isolates. Results A total of 138 patients with Hafnia alvei isolates were identified (2.1/100,000/year and two-thirds were of community onset. Older age and female gender were important risk factors for acquisition. The most common focus of isolation was urine in 112 (81%, followed by lower respiratory tract in 10 (7%, and soft tissue in 5 (4%, and the majority (94; 68% were mono-microbial. Most isolates were resistant to ampicillin (111;80%, cephalothin (106; 77%, amoxicillin/clavulanate (98; 71%, and cefazolin (95; 69% but none to imipenem or ciprofloxacin. Conclusion Hafnia alvei was most commonly isolated as a mono-microbial etiology from the urinary tract in women from the community. This study highlights the importance of population-based studies in accurately defining the epidemiology of an infectious disease.
Kaliraj, Kalirajan; Manimaran, Sudha
Robust skin color-based moving object detection for video surveillance is proposed. The objective of the proposed algorithm is to detect and track the target under complex situations. The proposed framework comprises four stages, which include preprocessing, skin color-based feature detection, feature classification, and target localization and tracking. In the preprocessing stage, the input image frame is smoothed using averaging filter and transformed into YCrCb color space. In skin color detection, skin color regions are detected using Otsu's method of global thresholding. In the feature classification, histograms of both skin and nonskin regions are constructed and the features are classified into foregrounds and backgrounds based on Bayesian skin color classifier. The foreground skin regions are localized by a connected component labeling process. Finally, the localized foreground skin regions are confirmed as a target by verifying the region properties, and nontarget regions are rejected using the Euler method. At last, the target is tracked by enclosing the bounding box around the target region in all video frames. The experiment was conducted on various publicly available data sets and the performance was evaluated with baseline methods. It evidently shows that the proposed algorithm works well against slowly varying illumination, target rotations, scaling, fast, and abrupt motion changes.
Full Text Available Diatoms are an important group of eukaryotic phytoplankton, responsible for about 20% of global primary productivity. Study of the functional role of chemical signaling within phytoplankton assemblages is still in its infancy although recent reports in diatoms suggest the existence of chemical-based defense strategies. Here, we demonstrate how the accurate perception of diatom-derived reactive aldehydes can determine cell fate in diatoms. In particular, the aldehyde (2E,4E/Z-decadienal (DD can trigger intracellular calcium transients and the generation of nitric oxide (NO by a calcium-dependent NO synthase-like activity, which results in cell death. However, pretreatment of cells with sublethal doses of aldehyde can induce resistance to subsequent lethal doses, which is reflected in an altered calcium signature and kinetics of NO production. We also present evidence for a DD-derived NO-based intercellular signaling system for the perception of stressed bystander cells. Based on these findings, we propose the existence of a sophisticated stress surveillance system in diatoms, which has important implications for understanding the cellular mechanisms responsible for acclimation versus death during phytoplankton bloom successions.
Zhang, Weizhe; Li, Xiaoqiang; He, Hui; Wang, Xing
Public opinion emergencies have important effect on social activities. Recognition of special communities like opinion leaders can contribute to a comprehensive understanding of the development trend of public opinion. In this paper, a network opinion leader recognition method based on relational data was put forward, and an opinion leader recognition system integrating public opinion data acquisition module, data characteristic selection, and fusion module as well as opinion leader discovery module based on Markov Logic Networks was designed. The designed opinion leader recognition system not only can overcome the incomplete data acquisition and isolated task of traditional methods, but also can recognize opinion leaders comprehensively with considerations to multiple problems by using the relational model. Experimental results demonstrated that, compared with the traditional methods, the proposed method can provide a more accurate opinion leader recognition and has good noise immunity.
Li, Yangyang; Wu, Yunhui; Jiao, Lc; Wu, Jianshe
With the development of society, handwritten digits recognition technique has been widely applied to production and daily life. It is a very difficult task to solve these problems in the field of pattern recognition. In this paper, a new method is presented for handwritten digit recognition. The digit samples firstly are processed and features extraction. Based on these features, a novel immune network classification algorithm is designed and implemented to the handwritten digits recognition. The proposed algorithm is developed by Jerne's immune network model for feature selection and KNN method for classification. Its characteristic is the novel network with parallel commutating and learning. The performance of the proposed method is experimented to the handwritten number datasets MNIST and compared with some other recognition algorithms-KNN, ANN and SVM algorithm. The result shows that the novel classification algorithm based on immune network gives promising performance and stable behavior for handwritten digits recognition.
Li Fei; Li Zhi-tang
The Novel Interconnection Network (NIN)based on inverted-graph topology and crossbar switch is a kind of lower latency and higher throughput interconnection network. But it bas a vital disadvantage, high hardware complexity. In order to reduce system hardware cost, an improved NIN (ININ) structure is proposed. As same as NIN,ININ has constant network diameter. Besides of keeping ad vantages of NIN, hardware cost of ININ is lower than NIN.Furthermore, we design a new deadlock-free routing algorithm for the improved NIN.
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
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.
Jurdak, Raja; Elfes, Alberto; Kusy, Branislav; Tews, Ashley; Hu, Wen; Hernandez, Emili; Kottege, Navinda; Sikka, Pavan
The global movement of people and goods has increased the risk of biosecurity threats and their potential to incur large economic, social, and environmental costs. Conventional manual biosecurity surveillance methods are limited by their scalability in space and time. This article focuses on autonomous surveillance systems, comprising sensor networks, robots, and intelligent algorithms, and their applicability to biosecurity threats. We discuss the spatial and temporal attributes of autonomous surveillance technologies and map them to three broad categories of biosecurity threat: (i) vector-borne diseases; (ii) plant pests; and (iii) aquatic pests. Our discussion reveals a broad range of opportunities to serve biosecurity needs through autonomous surveillance. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.
Eke, Paul I; Page, Roy C; Wei, Liang; Thornton-Evans, Gina; Genco, Robert J
This report adds a new definition for mild periodontitis that allows for better descriptions of the overall prevalence of periodontitis in populations. In 2007, the Centers for Disease Control and Prevention in partnership with the American Academy of Periodontology developed and reported standard case definitions for surveillance of moderate and severe periodontitis based on measurements of probing depth (PD) and clinical attachment loss (AL) at interproximal sites. However, combined cases of moderate and severe periodontitis are insufficient to determine the total prevalence of periodontitis in populations. The authors proposed a definition for mild periodontitis as ≥ 2 interproximal sites with AL ≥ 3 mm and ≥ 2 interproximal sites with PD ≥ 4 mm (not on the same tooth) or one site with PD ≥ 5 mm . The effect of the proposed definition on the total burden of periodontitis was assessed in a convenience sample of 456 adults ≥ 35 years old and compared with other previously reported definitions for similar categories of periodontitis. Addition of mild periodontitis increases the total prevalence of periodontitis by ≈31% in this sample when compared with the prevalence of severe and moderate disease. Total periodontitis using the case definitions in this study should be based on the sum of mild, moderate, and severe periodontitis.
Shoemaker, M.; Shroyer, L.
In the spirit of the 50th anniversary of the launch of the first man-made satellite, an historical overview of ground-based optical space surveillance systems is provided. Specific emphasis is given on gathering metrics to analyze design trends. The subject of space surveillance spans the history of spaceflight: from the early tracking cameras at missile ranges, the first observations of Sputnik, to the evolution towards highly capable commercial off-the-shelf (COTS) systems, and much in between. Whereas previous reviews in the literature have been limited in scope to specific time periods, operational programs, countries, etc., a broad overview of a wide range of sources is presented. This review is focused on systems whose primary design purpose can be classified as Space Object Identification (SOI) or Orbit Determination (OD). SOI systems are those that capture images or data to determine information about the satellite itself, such as attitude, features, and material composition. OD systems are those that produce estimates of the satellite position, usually in the form of orbital elements or a time history of tracking angles. Systems are also categorized based on the orbital regime in which their targets reside, which has been simplified in this study to either Low Earth Orbit (LEO) or Geosynchronous Earth Orbit (GEO). The systems are further classified depending on the industry segment (government/commercial or academic), and whether the program is foreign or domestic. In addition to gathering metrics on systems designed solely for man-made satellite observations, it is interesting to find examples of other systems being similarly used. Examples include large astronomical telescopes being used for GEO debris surveys and anomaly resolution for deep-space probes. Another interesting development is the increase in number and capability of COTS systems, some of which are specifically marketed to consumers as satellite trackers. After describing the results of the
Survivability is one of the important issues in ATM-based networks since even a single network element failure may cause a serious data loss. This paper introduces a new restoration mechanism based on multi-layer ATM survivable network management architecture. This mechanism integrates the general control and restoration control by establishing the Working VPs logical network, Backup VPs logical network and spare logical network in order to optimally utilize the network resources while maintaining the restoration requirements.
Campbell, Carlene E-A; Khan, Shafiullah; Singh, Dhananjay; Loo, Kok-Keong
The next generation surveillance and multimedia systems will become increasingly deployed as wireless sensor networks in order to monitor parks, public places and for business usage. The convergence of data and telecommunication over IP-based networks has paved the way for wireless networks. Functions are becoming more intertwined by the compelling force of innovation and technology. For example, many closed-circuit TV premises surveillance systems now rely on transmitting their images and data over IP networks instead of standalone video circuits. These systems will increase their reliability in the future on wireless networks and on IEEE 802.11 networks. However, due to limited non-overlapping channels, delay, and congestion there will be problems at sink nodes. In this paper we provide necessary conditions to verify the feasibility of round robin technique in these networks at the sink nodes by using a technique to regulate multi-radio multichannel assignment. We demonstrate through simulations that dynamic channel assignment scheme using multi-radio, and multichannel configuration at a single sink node can perform close to optimal on the average while multiple sink node assignment also performs well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives.
Full Text Available The next generation surveillance and multimedia systems will become increasingly deployed as wireless sensor networks in order to monitor parks, public places and for business usage. The convergence of data and telecommunication over IP-based networks has paved the way for wireless networks. Functions are becoming more intertwined by the compelling force of innovation and technology. For example, many closed-circuit TV premises surveillance systems now rely on transmitting their images and data over IP networks instead of standalone video circuits. These systems will increase their reliability in the future on wireless networks and on IEEE 802.11 networks. However, due to limited non-overlapping channels, delay, and congestion there will be problems at sink nodes. In this paper we provide necessary conditions to verify the feasibility of round robin technique in these networks at the sink nodes by using a technique to regulate multi-radio multichannel assignment. We demonstrate through simulations that dynamic channel assignment scheme using multi-radio, and multichannel configuration at a single sink node can perform close to optimal on the average while multiple sink node assignment also performs well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives.
Full Text Available Abstract Background A crucial goal of infectious disease surveillance is the early detection of epidemics, which is essential for disease control. In China, the current surveillance system is based on confirmed case reports. In rural China, it is not practical for health units to perform laboratory tests to confirm disease and people are more likely to get 'old' and emerging infectious diseases due to poor living conditions and closer contacts with wild animals and poultry. Syndromic surveillance, which collects non-specific syndromes before diagnosis, has great advantages in promoting the early detection of epidemics and reducing the necessities of disease confirmation. It will be especially effective for surveillance in resource poor settings. Methods/Design This is a field experimental study. The experimental tool is an innovative electronic surveillance system, combining syndromic surveillance with the existing case report surveillance in four selected counties in China. In the added syndromic surveillance, three types of data are collected including patients' major symptoms from health clinics, pharmaceutical sales from pharmacies and absenteeism information from primary school. In order to evaluate the early warning capability of the new added syndromic surveillance, the timelines and validity of the alert signals will be analyzed in comparison with the traditional case reporting system. The acceptability, feasibility and economic evaluation of the whole integrated surveillance system will be conducted in a before and after study design. Discussions Although syndromic surveillance system has mostly been established in developed areas, there are opportunities and advantages of developing it in rural China. The project will contribute to knowledge, experience and evidence on the establishment of an integrated surveillance system, which aims to provide early warning of disease epidemics in developing countries.
Unemo, Magnus; Ison, Catherine A; Cole, Michelle; Spiteri, Gianfranco; van de Laar, Marita; Khotenashvili, Lali
Antimicrobial resistance (AMR) in Neisseria gonorrhoeae has emerged for essentially all antimicrobials following their introduction into clinical practice. During the latest decade, susceptibility to the last remaining options for antimicrobial monotherapy, the extended-spectrum cephalosporins (ESC), has markedly decreased internationally and treatment failures with these ESCs have been verified. In response to this developing situation, WHO and the European Centre for Disease Prevention and Control (ECDC) have published global and region-specific response plans, respectively. One main component of these action/response plans is to enhance the surveillance of AMR and treatment failures. This paper describes the perspectives from the diverse WHO European Region (53 countries), including the independent countries of the former Soviet Union, regarding gonococcal AMR surveillance networks. The WHO European Region has a high prevalence of resistance to all previously recommended antimicrobials, and most of the first strictly verified treatment failures with cefixime and ceftriaxone were also reported from Europe. In the European Union/European Economic Area (EU/EEA), the European gonococcal antimicrobial surveillance programme (Euro-GASP) funded by the ECDC is running. In 2011, the Euro-GASP included 21/31 (68%) EU/EEA countries, and the programme is further strengthened annually. However, in the non-EU/EEA countries, internationally reported and quality assured gonococcal AMR data are lacking in 87% of the countries and, worryingly, appropriate support for establishment of a GASP is still lacking. Accordingly, national and international support, including political and financial commitment, for gonococcal AMR surveillance in the non-EU/EEA countries of the WHO European Region is essential.
Wang, Ying; O'Leary, Leslie A; Rickard, Russel S; Mason, Craig A
A Web-based survey focusing on geocoding of birth defects data was developed and administrated to gain an understanding of the capacity of state birth defects programs to geocode maternal residence and to identify barriers to geocoding birth defects data. The survey consisted of 21 questions related to geocoding of maternal residence, type of software used, barriers to geocoding, and data linkage. In August 2007, an e-mail with a Web link to the survey was sent to all state birth defects program contacts in the United States, including the District of Columbia, Puerto Rico, and the Centers for Disease Control and Prevention (CDC) requesting they complete the online survey. By October 2007, 39 (74%) out of 53 birth defects program contacts completed the survey. Although nearly all birth defects programs collect maternal residential data, many are not currently geocoding that data. Results indicated that 97% of the programs that completed the survey reported they collected data on maternal residence, 53% of which reported that the birth defects surveillance data were geocoded to the street address level using maternal residential address at delivery. Twenty six percent of the programs that do not currently geocode the data identified "Software and address reference file are not available" as the most significant barrier to geocoding; another 16% chose "Lack of funding" as the most significant barrier to geocoding. Since geocoding is an important component of spatial analyses used to detect potential clusters of birth defects, leveraging resources to overcome the barriers that prevent programs from geocoding is important.
Bose, Anindya Sekhar; Jafari, Hamid; Sosler, Stephen; Narula, Arvinder Pal Singh; Kulkarni, V. M.; Ramamurty, Nalini; Oommen, John; Jadi, Ramesh S.; Banpel, R. V.; Henao-Restrepo, Ana Maria
Background According to WHO estimates, 35% of global measles deaths in 2011 occurred in India. In 2013, India committed to a goal of measles elimination by 2020. Laboratory supported case based measles surveillance is an essential component of measles elimination strategies. Results from a case-based measles surveillance system in Pune district (November 2009 through December 2011) are reported here with wider implications for measles elimination efforts in India. Methods Standard protocols were followed for case identification, investigation and classification. Suspected measles cases were confirmed through serology (IgM) or epidemiological linkage or clinical presentation. Data regarding age, sex, vaccination status were collected and annualized incidence rates for measles and rubella cases calculated. Results Of the 1011 suspected measles cases reported to the surveillance system, 76% were confirmed measles, 6% were confirmed rubella, and 17% were non-measles, non-rubella cases. Of the confirmed measles cases, 95% were less than 15 years of age. Annual measles incidence rate was more than 250 per million persons and nearly half were associated with outbreaks. Thirty-nine per cent of the confirmed measles cases were vaccinated with one dose of measles vaccine (MCV1). Conclusion Surveillance demonstrated high measles incidence and frequent outbreaks in Pune where MCV1 coverage in infants was above 90%. Results indicate that even high coverage with a single dose of measles vaccine was insufficient to provide population protection and prevent measles outbreaks. An effective measles and rubella surveillance system provides essential information to plan, implement and evaluate measles immunization strategies and monitor progress towards measles elimination. PMID:25290339
Anindya Sekhar Bose
Full Text Available BACKGROUND: According to WHO estimates, 35% of global measles deaths in 2011 occurred in India. In 2013, India committed to a goal of measles elimination by 2020. Laboratory supported case based measles surveillance is an essential component of measles elimination strategies. Results from a case-based measles surveillance system in Pune district (November 2009 through December 2011 are reported here with wider implications for measles elimination efforts in India. METHODS: Standard protocols were followed for case identification, investigation and classification. Suspected measles cases were confirmed through serology (IgM or epidemiological linkage or clinical presentation. Data regarding age, sex, vaccination status were collected and annualized incidence rates for measles and rubella cases calculated. RESULTS: Of the 1011 suspected measles cases reported to the surveillance system, 76% were confirmed measles, 6% were confirmed rubella, and 17% were non-measles, non-rubella cases. Of the confirmed measles cases, 95% were less than 15 years of age. Annual measles incidence rate was more than 250 per million persons and nearly half were associated with outbreaks. Thirty-nine per cent of the confirmed measles cases were vaccinated with one dose of measles vaccine (MCV1. CONCLUSION: Surveillance demonstrated high measles incidence and frequent outbreaks in Pune where MCV1 coverage in infants was above 90%. Results indicate that even high coverage with a single dose of measles vaccine was insufficient to provide population protection and prevent measles outbreaks. An effective measles and rubella surveillance system provides essential information to plan, implement and evaluate measles immunization strategies and monitor progress towards measles elimination.
Nolte, Kurt B; Fischer, Marc; Reagan, Sarah; Lynfield, Ruth
Medical examiners and coroners investigate deaths that are sudden, unexplained, and violent. Oftentimes these deaths are a consequence of infections, many of which have public health consequences. Additionally, because deaths from bioterrorism are homicides, they fall under the jurisdiction of medical examiners and coroners. Surveillance for infectious disease-related deaths can enhance the opportunities to recognize these deaths. Beginning in 2000, the New Mexico Office of the Medical Investigator developed and tested a medical examiner surveillance model for bioterrorism and infectious disease mortality ("Med-X") using a set of symptoms to determine which cases should receive an autopsy and a set of pathology-based syndromes for early reporting of cases to public health authorities. This model demonstrated that many of the symptoms had a high predictive value for infections and were useful criteria for autopsy performance. The causative organism was identified for 81% of infections of which 58% were notifiable conditions by public health standards. Uniform criteria for performing autopsies and reporting cases to public health authorities enhance surveillance for notifiable infectious diseases and increase the probability of recognizing fatalities related to bioterrorism. We have developed guidelines for medical examiners, coroners and their public health partners to use in implementing Med-X surveillance in their jurisdictions. These guidelines encompass definitions of symptoms and syndromes, specimen collection and storage procedures, laboratory diagnostic approaches, and processes for case flow, case reporting, and data collection. We also suggest resources for autopsy biosafety information and funding.
Ranking players or teams in sports is of practical interests. From the viewpoint of networks, a ranking system is equivalent a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score (i.e., strength) of a player, for example, depends on time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. Our ranking system, also interpreted as a centrality measure for directed temporal networks, has two parameters. One parameter represents the exponential decay rate of the past score, and the other parameter controls the effect of indirect wins on the score. We derive a set of linear online update equ...
王伶; 焦李成; 陶海红; 刘芳
Multiple access interference (MAI) and near-far problem are two major obstacles in DS-CDMA systems.Combining wavelet neural networks and two matched filters, the novel multiuser detector, which is based on multiple variable function estimation wavelet networks over single path asynchronous channel and space-time channel respectively is presented. Excellent localization characteristics of wavelet functions in both time and frequency domains allowed hierarchical multiple resolution learning of input-output data mapping. The mathematic frame of the neural networks and error back ward propagation algorithm are introduced. The complexity of the multiuser detector only depends on that of wavelet networks. With numerical simulations and performance analysis, it indicates that the multiuser detector has excellent performance in eliminating MAI and near-far resistance.
Full Text Available This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D surface reconstruction model. The neural network combines the diffuse and specular components into a hybrid model. The proposed model considers the characteristics of each point and the variant albedo to prevent the reconstructed surface from being distorted. The neural network inputs are the pixel values of the two-dimensional images to be reconstructed. The normal vectors of the surface can then be obtained from the output of the neural network after supervised learning, where the illuminant direction does not have to be known in advance. Finally, the obtained normal vectors can be applied to integration method when reconstructing 3-D objects. Facial images were used for training in the proposed approach
Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz
Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....
LI Ji; WANG Bing-Hong; WANG Wen-Xu; ZHOU Tao
A definition of network entropy is presented, and as an example, the relationship between the value of network entropy of ER network model and the connect probability p as well as the total nodes N is discussed. The theoretical result and the simulation result based on the network entropy of the ER network are in agreement well with each other. The result indicated that different from the other network entropy reported before, the network entropy defined here has an obvious difference from different type of random networks or networks having different total nodes. Thus, this network entropy may portray the characters of complex networks better. It is also pointed out that, with the aid of network entropy defined, the concept of equilibrium networks and the concept of non-equilibrium networks may be introduced, and a quantitative measurement to describe the deviation to equilibrium state of a complex network is carried out.
Renga, Alfredo; Graziano, Maria D.; D'Errico, M.; Moccia, A.; Cecchini, A.
Maritime surveillance problems are drawing the attention of multiple institutional actors. National and international security agencies are interested in matters like maritime traffic security, maritime pollution control, monitoring migration flows and detection of illegal fishing activities. Satellite imaging is a good way to identify ships but, characterized by large swaths, it is likely that the imaged scenes contain a large number of ships, with the vast majority, hopefully, performing legal activities. Therefore, the imaging system needs a supporting system which identifies legal ships and limits the number of potential alarms to be further monitored by patrol boats or aircrafts. In this framework, spaceborne Synthetic Aperture Radar (SAR) sensors, terrestrial AIS and the ongoing satellite AIS systems can represent a great potential synergy for maritime security. Starting from this idea the paper develops different designs for an AIS constellation able to reduce the time lag between SAR image and AIS data acquisition. An analysis of SAR-based ship detection algorithms is also reported and candidate algorithms identified.
黄中文; 戚飞虎; 岑峰
A new real-time algorithm is proposed in this paper for detecting moving object in color image sequences taken from stationary cameras. This algorithm combines a temporal difference with an adaptive background subtraction where the combination is novel. When changes occur, the background is automatically adapted to suit the new conditions. For the background model, a new model is proposed with each frame decomposed into regions and the model is based not only upon single pixel but also on the characteristic of a region. The hybrid presentation includes a model for single pixel information and a model for the pixel's neighboring area information.This new model of background can both improve the accuracy of segmentation due to that spatial information is taken into account and saliently speed up the processing procedure because portion of neighboring pixel can be selected into modeling. The algorithm was successfully used in a video surveillance system and the experiment result shows it can obtain a clearer foreground than the single frame difference or background subtraction method.
Wagner, Laurie; Rechtman, Lindsay; Jordan, Heather; Ritsick, Maggie; Sanchez, Marchelle; Sorenson, Eric; Kaye, Wendy
Our objective was to develop state and metropolitan area-based surveillance projects to describe the characteristics of those with ALS and to assist with evaluating the completeness of the National ALS Registry. Because the literature suggested that ethnic/racial minorities have lower incidence of ALS, three state and eight metropolitan areas were selected to over-represent ethnic/racial minorities to have a sufficient number of minority patients. Project activities relied on reports from medical providers and medical records abstraction. The project areas represented approximately 27% of the U.S. The combined racial and ethnic distribution of these areas is 64.4% white, 16.0% African-American, 6.7% Asian, and 28.3% Hispanic. Most neurologists did not diagnose or provide care for ALS patients. The number of unique patients reported was close to expected (5883 vs. 6673). Age and gender distribution of patients was similar to the literature. The crude average annual incidence rate was 1.52 per 100,000 person-years, CI 1.44-1.61, and the 2009 prevalence rate was 3.84 per 100,000 population, CI 3.70-3.97. In conclusion, this study represents the largest number of clinically diagnosed ALS patients reported by neurologists in the U.S. Comparison of these data with those in the National ALS Registry will help evaluate the completeness of administrative databases.
Detection of vehicle events is a research hotspot in digital traffic.In this paper,an approach is proposed to detect vehicle events with semantic analysis of traffic surveillance video using spatio-velocity statistic models.The approach includes two successive phases:trajectory clustering and semantic events detection.For trajectory clustering,a statistic model of vehicle trajectories are presented,for which a spatio-velocity model is trained by analyzing the trajectories of moving vehicles in the scene.Based on the trajectory,which represents both the position of the vehicle and its instantaneous velocity,a trajectory similarity measure is proposed.Then,an improved hierarchical clustering algorithm is adopted to cluster the trajectories according to different spatial and velocity distributions.In each cluster,trajectories that are spatially close have similar velocities of motion and represent one type of activity pattern.For the semantic events detection phase,statistic models of semantic regions in the scene are generated by estimating the probability density and velocity distributions of each type of activity pattern.Finally,semantic events are detected by the proposed spatio-velocity statistic models.The paper also presents experiments using real video sequence to verify the effectiveness of the proposed method.
Full Text Available With the continuous expansion of the amount of data with time in mobile video applications such as cloud video surveillance (CVS, the increasing energy consumption in video data centers has drawn widespread attention for the past several years. Addressing the issue of reducing energy consumption, we propose a low energy consumption storage method specially designed for CVS systems based onthe service level agreement (SLA classification. A novel SLA with an extra parameter of access time period is proposed and then utilized as a criterion for dividing virtual machines (VMs and data storage nodes into different classifications. Tasks can be scheduled in real time for running on the homologous VMs and data storage nodes according to their access time periods. Any nodes whose access time periods do not encompass the current time will be placed into the energy saving state while others are in normal state with the capability of undertaking tasks. As a result, overall electric energy consumption in data centers is reduced while the SLA is fulfilled. To evaluate the performance, we compare the method with two related approaches using the Hadoop Distributed File System (HDFS. The results show the superiority and effectiveness of our method.
Sonia M. Orlando Gibelli
Full Text Available In this work, Probabilistic Safety Assessment (PSA is used to evaluate Allowed Outage Times (AOT and Surveillance Test Intervals (STI extensions for three Angra 1 nuclear power plant safety systems. The interest in such an analysis lies on the fact that PSA comprises a risk-based tool for safety evaluation and has been increasingly applied to support both the regulatory and the operational decision-making processes. Regarding Angra 1, among other applications, PSA is meant to be an additional method that can be used by the utility to justify Technical Specification relaxation to the Brazilian regulatory body. The risk measure used in this work is the Core Damage Frequency, obtained from the Angra 1 Level 1 PSA study. AOT and STI extensions are evaluated for the Safety Injection, Service Water and Auxiliary Feedwater Systems using the SAPHIRE code. In order to compensate for the risk increase caused by the extensions, compensatory measures as (1 test of redundant train prior to entering maintenance and (2 staggered test strategy are proposed. Results have shown that the proposed AOT extensions are acceptable for two of the systems with the implementation of compensatory measures whereas STI extensions are acceptable for all three systems.
Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.
Gastanaduy, Paul A.; Islam, Khaleda; Rahman, Mahmudur; Rahman, Mustafizur; Luby, Stephen P.; Heffelfinger, James D.; Parashar, Umesh D.; Gurley, Emily S.
Background: In anticipation of introduction of a rotavirus vaccine into the national immunization program of Bangladesh, active hospital-based surveillance was initiated to provide prevaccine baseline data on rotavirus disease. Methods: Children 5 years of age and younger admitted with acute gastroenteritis (AGE) (≥3 watery or looser-than-normal stools or ≥1 episode of forceful vomiting) at 7 hospitals throughout Bangladesh were identified. Clinical information and stool specimens were collected from every 4th patient. Specimens were tested for rotavirus antigen by enzyme immunoassays; 25% of detected rotaviruses were genotyped. Results: From July 2012 to June 2015, rotavirus was detected in 2432 (64%) of 3783 children hospitalized for AGE. Eight enrolled children died, including 4 (50%) who were rotavirus positive. Rotavirus was detected year-round in Bangladesh with peak detection rates of >80% during November–February. Most (86%) rotavirus AGE cases were 6–23 months of age. Sixty-nine percent of children with rotavirus had severe disease (Vesikari score, ≥11). Among 543 strains genotyped, G1P (31%) and G12P (29%) were the most common. Conclusions: Rotavirus is a major cause of morbidity in Bangladeshi children, accounting for nearly two-thirds of AGE hospitalizations. These data highlight the potential value of rotavirus vaccination in Bangladesh, and will be the key for future measurement of vaccine impact. PMID:27798545
Uter, Wolfgang; Gefeller, Olaf; Giménez-Arnau, Ana
from 63 530 consultations collected by 53 departments from 12 countries participating in the European Surveillance System on Contact Allergies (ESSCA) ( www.essca-dc.org) between 2009 and 2012. RESULTS: Considerable variation in the prevalence of the MOAHLFA factors between departments was found...
Utzmann, Jens; Flohrer, Tim; Schildknecht, Thomas; Wagner, Axel; Silha, Jiri; Willemsen, Philip; Teston, Frederic
This paper presents the capabilities of a Space-Based Space Surveillance (SBSS) demonstration mission for Space Surveillance and Tracking (SST) based on a micro-satellite platform. The results have been produced in the frame of ESA’s "Assessment Study for Space Based Space Surveillance Demonstration Mission" performed by the Airbus Defence and Space consortium. Space Surveillance and Tracking is part of Space Situational Awareness (SSA) and covers the detection, tracking and cataloguing of space debris and satellites. Derived SST services comprise a catalogue of these man-made objects, collision warning, detection and characterisation of in-orbit fragmentations, sub-catalogue debris characterisation, etc. The assessment of SBSS in a SST system architecture has shown that both an operational SBSS and also already a well-designed space-based demonstrator can provide substantial performance in terms of surveillance and tracking of beyond-LEO objects. Especially the early deployment of a demonstrator, possible by using standard equipment, could boost initial operating capability and create a self-maintained object catalogue. Furthermore, unique statistical information about small-size LEO debris (mm size) can be collected in-situ. Unlike classical technology demonstration missions, the primary goal is the demonstration and optimisation of the functional elements in a complex end-to-end chain (mission planning, observation strategies, data acquisition, processing and fusion, etc.) until the final products can be offered to the users. Also past and current missions by the US (SBV, SBSS) and Canada (Sapphire, NEOSSat) underline the advantages of space-based space surveillance. The presented SBSS system concept takes the ESA SST System Requirements (derived within the ESA SSA Preparatory Program) into account and aims at fulfilling SST core requirements in a stand-alone manner. Additionally, requirments for detection and characterisation of small-sized LEO debris are
Coebergh, Jan Willem; van den Hurk, Corina; Louwman, Marieke; Comber, Harry; Rosso, Stefano; Zanetti, Roberto; Sacchetto, Lidia; Storm, Hans; van Veen, Evert-Ben; Siesling, Sabine; van den Eijnden-van Raaij, Janny
provide only incidence and survival data. If they are unable to do so because POs and stakeholders do not demand it, they might also be inhibited by data protection restrictions, especially in German and French speaking countries. The value of population-based studies of quality of oncologic care and mass screening and the flawless reputation with regard to data protection of intensively used CRs in the northwest of Europe offered a sharp contrast, although they also follow the 1995 EU guideline on data protection. CRs thus offer a perfect example of what can be done with sensitive and minimal data, also when enriched by linkages to other databases. Intensive use of the data has allowed CR research departments to take on a visible expertise-based profile but a neutral in many public controversies in preventive oncology. Their management and fundability also appeared to benefit from externally classifying the wide array of tumour- or tract-specific intelligence and research activities for the various users in oncology and public health and also patients - who are the source of the data - are better informed. Transparency on what CRs enable may also improve through programmes of research have been deemed essential to our funding POs (ministries, cancer charities, cancer centres or public health institutes) who might benefit from some guidance to - often suboptimal -governance. Therefore, a metaphoric RegisTree has been developed for self-assessment and to clarify CR working methods and domain-specific performance to stakeholders and funding agencies, showing much room for development in many CRs. All in all, CRs are likely to remain unique sources of independent expert information on the burden of cancer, indispensable for cancer surveillance, with increased attention to cancer survivors, up to 4% of the population. Investments in the expanding CR network across Europe offer an excellent way forward for comparative future cancer surveillance with so many epidemiologic and
Torner, Nuria; Baricot, Maretva; Martínez, Ana; Toledo, Diana; Godoy, Pere; Dominguez, Ángela
The aim of this study was to evaluate the outcome of a collaborative action between Public Health services and Primary Care in the context of a case-control study on effectiveness of pharmaceutical and non-pharmaceutical measures to prevent hospitalization in a pandemic situation. To carry out this research the collaborative action of the primary care physicians members of the Influenza surveillance network was needed, they had to recall clinical information from influenza A(H1N1)pmd09 confirmed outpatient cases and negative outpatient controls matching their corresponding hospitalized confirmed case. A survey questionnaire to assess involvement of Influenza Sentinel Surveillance Primary care physicians' Network of Catalonia (PIDIRAC) regarding the outpatient case and control outreach during the pandemic influenza season was performed. A total of 71,1% of completed surveys were received. Perception of pandemic activity was considered to be similar to seasonal influenza activity in 43.8% or higher but not unbearable in 37.5% of the replies. There was no nuisance reported from patients regarding neither the questions nor the surveyor. Collaborative research between Public Health services and Primary Care physicians enhances Public Health actions and research.
Full Text Available With the rapid rise of Internet of Things in public domain, people expect fast, reliable and on-demand home security via the Internet. However, existing remote home surveillance systems place a very rigid constraint on authentication and require customized hardware and software. In this paper we have proposed an ingenious and reliable internet based, home access system for smart homes that can be easily deployed on generic hardware. The proposed architecture uses popular email service providers to notify and update the user about the home access. It sends an email to the owner with the attached picture of the person who is at the door. It also incorporates a protected mechanism to give access of the door to a remote user by responding to that email. It essentially means that we can view and give access to the person at our door via sending and receiving an email. Furthermore, an image processing based mechanism has also been incorporated to provide access without email, to few selected personnel who are trusted by the owner. It works by capturing and comparing the visitor's image with the stored images in the database. Perceptual hashing or fingerprint matching algorithm is used for comparison purposes. Similarity percentage based on hamming distance was evaluated, and the similarity threshold for providing access was set. The simulations were performed in rigorous environment. The efficiency of the hashing algorithm was found to be 97% at the similarity threshold of 95%. The results validate that the average latency is only 155 ms with low standard deviation. The CPU utilization remained quite low with a minimum value of 10 MHz and a maximum value of 30 MHz when the payload size of the sent mail was increased to 1500 kB. Thus, the proposed system can be used for developing a larger low power infrastructure.
Grolinger, Katarina; Jerbic, Bojan; Vranjes, Bozo
The purpose of autonomous robot is to solve various tasks while adapting its behavior to the variable environment, expecting it is able to navigate much like a human would, including handling uncertain and unexpected obstacles. To achieve this the robot has to be able to find solution to unknown situations, to learn experienced knowledge, that means action procedure together with corresponding knowledge on the work space structure, and to recognize working environment. The planning of the intelligent robot behavior presented in this paper implements the reinforcement learning based on strategic and random attempts for finding solution and neural network approach for memorizing and recognizing work space structure (structural assignment problem). Some of the well known neural networks based on unsupervised learning are considered with regard to the structural assignment problem. The adaptive fuzzy shadowed neural network is developed. It has the additional shadowed hidden layer, specific learning rule and initialization phase. The developed neural network combines advantages of networks based on the Adaptive Resonance Theory and using shadowed hidden layer provides ability to recognize lightly translated or rotated obstacles in any direction.
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
Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin
Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.
release, distribution unlimited. 13. SUPPLEMENTARY NOTES The original document contains color images. 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY ...material is based upon work funded and supported by Department of Homeland Security Department of Defense under Contract No. FA8721-05-C-0003 with...Corruption #6 UDP: DNS DoS/DDoS Floods #8 DP: Remote Connections DoS/D,DoS Crashes #7 UDP: VoiiP Q I e Software Engineering Institute I Carnegie Mellon Uni
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.
Malone, J B; Bergquist, N R; Huh, O K; Bavia, M E; Bernardi, M; El Bahy, M M; Fuentes, M V; Kristensen, T K; McCarroll, J C; Yilma, J M; Zhou, X N
At a team residency sponsored by the Rockefeller Foundation in Bellagio, Italy, 10-14 April 2000 an organizational plan was conceived to create a global network of collaborating health workers and earth scientists dedicated to the development of computer-based models that can be used for improved control programs for schistosomiasis and other snail-borne diseases of medical and veterinary importance. The models will be assembled using GIS methods, global climate model data, sensor data from earth observing satellites, disease prevalence data, the distribution and abundance of snail hosts, and digital maps of key environmental factors that affect development and propagation of snail-borne disease agents. A work plan was developed for research collaboration and data sharing, recruitment of new contributing researchers, and means of access of other medical scientists and national control program managers to GIS models that may be used for more effective control of snail-borne disease. Agreement was reached on the use of compatible GIS formats, software, methods and data resources, including the definition of a 'minimum medical database' to enable seamless incorporation of results from each regional GIS project into a global model. The collaboration plan calls for linking a 'central resource group' at the World Health Organization, the Food and Agriculture Organization, Louisiana State University and the Danish Bilharziasis Laboratory with regional GIS networks to be initiated in Eastern Africa, Southern Africa, West Africa, Latin America and Southern Asia. An Internet site, www.gnosisGIS.org, (GIS Network On Snail-borne Infections with special reference to Schistosomiasis), has been initiated to allow interaction of team members as a 'virtual research group'. When completed, the site will point users to a toolbox of common resources resident on computers at member organizations, provide assistance on routine use of GIS health maps in selected national disease control
Broek, I.V.F. van den; Verheij, R.A.; Dijk, C. van; Koedijk, F.D.H.; Sande, M.A.B. van der; Bergen, J.E.A.M. van
Background: Sexually transmitted infections (STI) care in the Netherlands is primarily provided by general practitioners (GPs) and specialized STI centers. STI surveillance is based on data from STI centers, which show increasing numbers of clients. Data from a GP morbidity surveillance network were
Braeken, An; Porambage, Pawani; Gurtov, Andrei; Ylianttila, Mika
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. PMID:26729130
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.
张凤斌; 杨永田; 江子扬; 孙冰心
Because currently intrusion detection systems cannot detect undefined intrusion behavior effectively,according to the robustness and adaptability of the genetic algorithms, this paper integrates the genetic algorithms into an intrusion detection system, and a detection algorithm based on network traffic is proposed. This algorithm is a real-time and self-study algorithm and can detect undefined intrusion behaviors effectively.
Klein Wolterink, W.
In this thesis we focus on location-based message forwarding in vehicular networks to support intelligent transportation systems (ITSs). ITSs are transport systems that utilise information and communication technologies to increase their level of automation, in this way levering the performance of
and leisure have not been studied with the same intensity as e.g. policing, civil liberties and social sorting. This paper offers a study of trends in surveillance pleasures, i.e. watching and eavesdropping in popular culture. My focus is the existential aspects and ethical dilemmas of surveillance...
Full Text Available This study presents a new method of Synthetic Aperture Radar (SAR image target recognition based on a convolutional neural network. First, we introduce a class separability measure into the cost function to improve this network’s ability to distinguish between categories. Then, we extract SAR image features using the improved convolutional neural network and classify these features using a support vector machine. Experimental results using moving and stationary target acquisition and recognition SAR datasets prove the validity of this method.
Colson, Philippe; Rolain, Jean-Marc; Abat, Cédric; Charrel, Rémi; Fournier, Pierre-Edouard; Raoult, Didier
Infectious diseases (IDs) are major causes of morbidity and mortality and their surveillance is critical. In 2002, we implemented a simple and versatile homemade tool, named EPIMIC, for the real-time systematic automated surveillance of IDs at Marseille university hospitals, based on the data from our clinical microbiology laboratory, including clinical samples, tests and diagnoses. This tool was specifically designed to detect abnormal events as IDs are rarely predicted and modeled. EPIMIC operates using Microsoft Excel software and requires no particular computer skills or resources. An abnormal event corresponds to an increase above, or a decrease below threshold values calculated based on the mean of historical data plus or minus 2 standard deviations, respectively. Between November 2002 and October 2013 (11 years), 293 items were surveyed weekly, including 38 clinical samples, 86 pathogens, 79 diagnosis tests, and 39 antibacterial resistance patterns. The mean duration of surveillance was 7.6 years (range, 1 month-10.9 years). A total of 108,427 Microsoft Excel file cells were filled with counts of clinical samples, and 110,017 cells were filled with counts of diagnoses. A total of 1,390,689 samples were analyzed. Among them, 172,180 were found to be positive for a pathogen. EPIMIC generated a mean number of 0.5 alert/week on abnormal events. EPIMIC proved to be efficient for real-time automated laboratory-based surveillance and alerting at our university hospital clinical microbiology laboratory-scale. It is freely downloadable from the following URL: http://www.mediterranee-infection.com/article.php?larub=157&titre=bulletin-epidemiologique (last accessed: 20/11/2015).
Australia's geography and technology base got it off to a flying start in the early days of surveillance of space, starting with CSIRO's first radio telescope in the 1940's and climaxing in NASA's establishment of station 43 in the Deep Space Network at Tidbinbilla in 1965. But Britain's exit from space and the subsequent closure of the Woomera launch range and associated space tracking facilities in the early 1970's saw the start of a long draw-down of capability. Programs such as CSIRO's radio astronomy telescopes, Electro-Optic Systems' adoption of laser technology for satellite laser ranging and tracking system, and the exploration of the use of technology developed in Australia's over-the-horizon-radar program for surveillance of space, kept some interest in the problem alive, but there has been no serious national investment in the area for the last thirty years. Recently, however, increased awareness of the vulnerability of space systems and the need to include potential opponents' space capabilities in operations planning has led to a revival of interest in space situational awareness within the Australian Defence Organisation. While firm commitments to new systems must wait on the next Defence White Paper due out at the end of 2007 and the policy directions it formally endorses, discussions have already started with the US on participating in the Space Surveillance Network (SSN) and developing a comprehensive space situational awareness capability. In support of these initiatives the Defence Science and Technology Organisation (DSTO) is drawing up an inventory of relevant Australian capabilities, technologies and activities: the paper will describe the findings of this inventory, and in particular local technologies and systems that might be deployed in Australia to contribute to the SSN. In the optical regime the available options are rather limited; they centre primarily on the satellite laser ranging technology developed by Electro-Optic Systems and
Flohrer, T.; Krag, H.; Klinkrad, H.; Schildknecht, T.
Under ESA contract an industrial consortium including Aboa Space Research Oy (ASRO), the Astronomical Institute of the University of Bern (AIUB), and the Dutch National Aerospace Laboratory (NLR), proposed the observation concept, developed a suitable sensor architecture, and assessed the performance of a space-based optical (SBO) telescope in 2005. The goal of the SBO study was to analyse how the existing knowledge gap in the space debris population in the millimetre and centimetre regime may be closed by means of a passive optical instrument. The SBO instrument was requested to provide statistical information on the space debris population in terms of number of objects and size distribution. The SBO instrument was considered to be a cost-efficient with 20 cm aperture and 6° field-of-view and having flexible integration requirements. It should be possible to integrate the SBO instrument easily as a secondary payload on satellites launched into low-Earth orbits (LEO), or into geostationary orbit (GEO). Thus the selected mission concept only allowed for fix-mounted telescopes, and the pointing direction could be requested freely. Since 2007 ESA focuses space surveillance and tracking activities in the Space Situational Awareness (SSA) preparatory program. Ground-based radars and optical telescopes are studied for the build-up and maintenance of a catalogue of objects. In this paper we analyse how the proposed SBO architecture could contribute to the space surveillance tasks survey and tracking. We assume that the SBO instrumentation is placed into a circular sun-synchronous orbit at 800 km altitude. We discuss the observation conditions of objects at higher altitude, and select an orbit close to the terminator plane. A pointing of the sensor orthogonal to the orbital plane with optimal elevation slightly in positive direction (0° and +5°) is found optimal for accessing the entire GEO regime within one day, implying a very good coverage of controlled objects in
Commentary on "Surveillance guidelines based on recurrence patterns after radical cystectomy for bladder cancer: the Canadian Bladder Cancer Network experience." Yafi FA, Aprikian AG, Fradet Y, Chin JL, Izawa J, Rendon R, Estey E, Fairey A, Cagiannos I, Lacombe L, Lattouf JB, Bell D, Saad F, Drachenberg D, Kassouf W. Department of Surgery (Urology), McGill University, Quebec, Canada: BJU Int 2012;110(9):1317-23 [Epub 2012 Apr 13].
Kamat, Ashish M
≥ T3N0 tumours and p ≤ T2N0 tumours (5-yr RFS 25% vs. 44% vs. 66% respectively, P < 0.001). Similarly, pTxN+ tumours had a shorter median time to recurrence (9 months, range 1-72 months) than p ≥ T3N0 tumours (10 months, range 1-70 months) or p ≤ T2N0 tumours (14 months, range 1-192 months, P < 0.001). Differences in recurrence patterns after RC suggest the need for varied follow-up protocols for each group. We propose a stage-based protocol for surveillance of patients with BC treated with RC that captures most recurrences while limiting over-investigation. Copyright © 2013. Published by Elsevier Inc.
Full Text Available Abstract Background Japanese encephalitis (JE is presumed to be endemic throughout Asia, yet only a few cases have been reported in tropical Asian countries such as Indonesia, Malaysia and the Philippines. To estimate the true disease burden due to JE in this region, we conducted a prospective, hospital-based surveillance with a catchment population of 599,120 children less than 12 years of age in Bali, Indonesia, from July 2001 through December 2003. Methods Balinese children presenting to any health care facility with acute viral encephalitis or aseptic meningitis were enrolled. A "confirmed" diagnosis of JE required the detection of JE virus (JEV-specific IgM in cerebrospinal fluid, whereas a diagnosis of "probable JE" was assigned to those cases in which JEV-specific IgM was detected only in serum. Results In all, 86 confirmed and 4 probable JE cases were identified. The annualized JE incidence rate was 7.1 and adjusted to 8.2 per 100,000 for children less than 10 years of age over the 2.5 consecutive years of study. Only one JE case was found among 96,920 children 10–11 years old (0.4 per 100,000. Nine children (10% died and 33 (37% of the survivors had neurological sequelae at discharge. JEV was transmitted in Bali year-round with 70% of cases in the rainy season. Conclusion JE incidence and case-fatality rates in Bali were comparable to those of other JE-endemic countries of Asia. Our findings contradict the common wisdom that JE is rare in tropical Asia. Hence, the geographical range of endemic JE is broader than previously described. The results of the study support the need to introduce JE vaccination into Bali.
Ramos, Antonio L. L.; Shao, Zhili; Holthe, Aleksander; Sandli, Mathias F.
The introduction of the System-on-Chip (SoC) technology has brought exciting new opportunities for the development of smart low cost embedded systems spanning a wide range of applications. Currently available SoC devices are capable of performing high speed digital signal processing tasks in software while featuring relatively low development costs and reduced time-to-market. Unmanned aerial vehicles (UAV) are an application example that has shown tremendous potential in an increasing number of scenarios, ranging from leisure to surveillance as well as in search and rescue missions. Video capturing from UAV platforms is a relatively straightforward task that requires almost no preprocessing. However, that does not apply to audio signals, especially in cases where the data is to be used to support real-time decision making. In fact, the enormous amount of acoustic interference from the surroundings, including the noise from the UAVs propellers, becomes a huge problem. This paper discusses a real-time implementation of the NLMS adaptive filtering algorithm applied to enhancing acoustic signals captured from UAV platforms. The model relies on a combination of acoustic sensors and a computational inexpensive algorithm running on a digital signal processor. Given its simplicity, this solution can be incorporated into the main processing system of an UAV using the SoC technology, and run concurrently with other required tasks, such as flight control and communications. Simulations and real-time DSP-based implementations have shown significant signal enhancement results by efficiently mitigating the interference from the noise generated by the UAVs propellers as well as from other external noise sources.
In the first decade of the 21st century, New Product Development has undergone major changes in the way NPD is managed and organised. This is due to changes in technology, market demands, and in the competencies of companies. As a result NPD organised in different forms of networks is predicted...... to be of ever-increasing importance to many different kinds of companies. This happens at the same times as the share of new products of total turnover and earnings is increasing at unprecedented speed in many firms and industries. The latter results in the need for very fast innovation and product development...... - a need that can almost only be resolved by organising NPD in some form of network configuration. The work of Peter Lindgren is on several aspects of network based high speed product innovation and contributes to a descriptive understanding of this phenomenon as well as with normative theory on how NPD...
Ritter, Stephan; Bochmann, Joerg; Figueroa, Eden; Hahn, Carolin; Kalb, Norbert; Muecke, Martin; Neuzner, Andreas; Noelleke, Christian; Reiserer, Andreas; Uphoff, Manuel; Rempe, Gerhard [Max-Planck-Institut fuer Quantenoptik, Hans-Kopfermann-Strasse 1, 85748 Garching (Germany)
Quantum repeaters require an efficient interface between stationary quantum memories and flying photons. Single atoms in optical cavities are ideally suited as universal quantum network nodes that are capable of sending, storing, retrieving, and even processing quantum information. We demonstrate this by presenting an elementary version of a quantum network based on two identical nodes in remote, independent laboratories. The reversible exchange of quantum information and the creation of remote entanglement are achieved by exchange of a single photon. Quantum teleportation is implemented using a time-resolved photonic Bell-state measurement. Quantum control over all degrees of freedom of the single atom also allows for the nondestructive detection of flying photons and the implementation of a quantum gate between the spin state of the atom and the polarization of a photon upon its reflection from the cavity. Our approach to quantum networking offers a clear perspective for scalability and provides the essential components for the realization of a quantum repeater.
Kurt Derr; Milos Manic
Location Based Services (LBS), context aware applications, and people and object tracking depend on the ability to locate mobile devices, also known as localization, in the wireless landscape. Localization enables a diverse set of applications that include, but are not limited to, vehicle guidance in an industrial environment, security monitoring, self-guided tours, personalized communications services, resource tracking, mobile commerce services, guiding emergency workers during fire emergencies, habitat monitoring, environmental surveillance, and receiving alerts. This paper presents a new neural network approach (LENSR) based on a competitive topological Counter Propagation Network (CPN) with k-nearest neighborhood vector mapping, for indoor location estimation based on received signal strength. The advantage of this approach is both speed and accuracy. The tested accuracy of the algorithm was 90.6% within 1 meter and 96.4% within 1.5 meters. Several approaches for location estimation using WLAN technology were reviewed for comparison of results.
Full Text Available Central American countries face a major challenge in the control of Triatoma dimidiata, a widespread vector of Chagas disease that cannot be eliminated. The key to maintaining the risk of transmission of Trypanosoma cruzi at lowest levels is to sustain surveillance throughout endemic areas. Guatemala, El Salvador, and Honduras integrated community-based vector surveillance into local health systems. Community participation was effective in detection of the vector, but some health services had difficulty sustaining their response to reports of vectors from the population. To date, no research has investigated how best to maintain and reinforce health service responsiveness, especially in resource-limited settings.We reviewed surveillance and response records of 12 health centers in Guatemala, El Salvador, and Honduras from 2008 to 2012 and analyzed the data in relation to the volume of reports of vector infestation, local geography, demography, human resources, managerial approach, and results of interviews with health workers. Health service responsiveness was defined as the percentage of households that reported vector infestation for which the local health service provided indoor residual spraying of insecticide or educational advice. Eight potential determinants of responsiveness were evaluated by linear and mixed-effects multi-linear regression. Health service responsiveness (overall 77.4% was significantly associated with quarterly monitoring by departmental health offices. Other potential determinants of responsiveness were not found to be significant, partly because of short- and long-term strategies, such as temporary adjustments in manpower and redistribution of tasks among local participants in the effort.Consistent monitoring within the local health system contributes to sustainability of health service responsiveness in community-based vector surveillance of Chagas disease. Even with limited resources, countries can improve health
Hashimoto, Ken; Zúniga, Concepción; Romero, Eduardo; Morales, Zoraida; Maguire, James H
Central American countries face a major challenge in the control of Triatoma dimidiata, a widespread vector of Chagas disease that cannot be eliminated. The key to maintaining the risk of transmission of Trypanosoma cruzi at lowest levels is to sustain surveillance throughout endemic areas. Guatemala, El Salvador, and Honduras integrated community-based vector surveillance into local health systems. Community participation was effective in detection of the vector, but some health services had difficulty sustaining their response to reports of vectors from the population. To date, no research has investigated how best to maintain and reinforce health service responsiveness, especially in resource-limited settings. We reviewed surveillance and response records of 12 health centers in Guatemala, El Salvador, and Honduras from 2008 to 2012 and analyzed the data in relation to the volume of reports of vector infestation, local geography, demography, human resources, managerial approach, and results of interviews with health workers. Health service responsiveness was defined as the percentage of households that reported vector infestation for which the local health service provided indoor residual spraying of insecticide or educational advice. Eight potential determinants of responsiveness were evaluated by linear and mixed-effects multi-linear regression. Health service responsiveness (overall 77.4%) was significantly associated with quarterly monitoring by departmental health offices. Other potential determinants of responsiveness were not found to be significant, partly because of short- and long-term strategies, such as temporary adjustments in manpower and redistribution of tasks among local participants in the effort. Consistent monitoring within the local health system contributes to sustainability of health service responsiveness in community-based vector surveillance of Chagas disease. Even with limited resources, countries can improve health service
Well-designed network topology provides vital support for routing, data fusion, and target tracking in wireless sensor networks (WSNs). Self-organization feature map (SOFM) neural network is a major branch of artificial neural networks, which has self-organizing and self-learning features. In this paper, we propose a cluster-based topology control algorithm for WSNs, named SOFMHTC, which uses SOFM neural network to form a hierarchical network structure, completes cluster head selection by the...
John Sherck, MD
Full Text Available Introduction: Every year in the United States, thousands of young children are injured by passengervehicles in driveways or parking areas. Little is known about risk factors, and incidence rates aredifficult to estimate because ascertainment using police collision reports or media sources isincomplete. This study used surveillance at trauma centers to identify incidents and parent interviewsto obtain detailed information on incidents, vehicles, and children.Methods: Eight California trauma centers conducted surveillance of nontraffic pedestrian collisioninjury to children aged 14 years or younger from January 2005 to July 2007. Three of these centersconducted follow-up interviews with family members.Results: Ninety-four injured children were identified. Nine children (10% suffered fatal injury. Seventychildren (74% were 4 years old or younger. Family members of 21 victims from this study (23%completed an interview. Of these 21 interviewed victims, 17 (81% were male and 13 (62% were 1 or 2years old. In 13 cases (62%, the child was backed over, and the driver was the mother or father in 11cases (52%. Fifteen cases (71% involved a sport utility vehicle, pickup truck, or van. Most collisionsoccurred in a residential driveway.Conclusion: Trauma center surveillance can be used for case ascertainment and for collectinginformation on circumstances of nontraffic pedestrian injuries. Adoption of a specific external cause-ofinjurycode would allow passive surveillance of these injuries. Research is needed to understand thecontributions of family, vehicular, and environmental characteristics and injury risk to inform preventionefforts.
Wang, Yanqing; Chen, Min; Liang, Yaowen; Jiang, Yu
Lots of researches have showed that plagiarism becomes a severe problem in higher education around the world, especially in programming learning for its essence. Therefore, an effective strategy for plagiarism surveillance in program learning is much essential. Some literature focus on code similarity algorithm and the related tools can help to…
Full Text Available The risk of adverse pregnancy outcomes can be minimized through the adoption of healthy lifestyles before pregnancy by women of childbearing age. Initiatives for promotion of preconception health may be difficult to implement. Internet can be used to build tailored health interventions through identification of the public's information needs. To this aim, we developed a semi-automatic web-based system for monitoring Google searches, web pages and activity on social networks, regarding preconception health.Based on the American College of Obstetricians and Gynecologists guidelines and on the actual search behaviors of Italian Internet users, we defined a set of keywords targeting preconception care topics. Using these keywords, we analyzed the usage of Google search engine and identified web pages containing preconception care recommendations. We also monitored how the selected web pages were shared on social networks. We analyzed discrepancies between searched and published information and the sharing pattern of the topics.We identified 1,807 Google search queries which generated a total of 1,995,030 searches during the study period. Less than 10% of the reviewed pages contained preconception care information and in 42.8% information was consistent with ACOG guidelines. Facebook was the most used social network for sharing. Nutrition, Chronic Diseases and Infectious Diseases were the most published and searched topics. Regarding Genetic Risk and Folic Acid, a high search volume was not associated to a high web page production, while Medication pages were more frequently published than searched. Vaccinations elicited high sharing although web page production was low; this effect was quite variable in time.Our study represent a resource to prioritize communication on specific topics on the web, to address misconceptions, and to tailor interventions to specific populations.
Dompier, Thomas P.; Marshall, Stephen W.; Kerr, Zachary Y.; Hayden, Ross
Context Previous epidemiologic researchers have examined time-loss (TL) injuries in high school student-athletes, but little is known about the frequency of non–time-loss (NTL) injuries in these athletes. Objective To describe the methods of the National Athletic Treatment, Injury and Outcomes Network (NATION) Surveillance Program and provide descriptive epidemiology of TL and NTL injuries across athletes in 27 high school sports. Design Descriptive epidemiology study. Setting Aggregate injury and exposure data collected from 147 high schools in 26 states. Patients or Other Participants High school student-athletes participating in 13 boys' sports and 14 girls' sports during the 2011–2012 through 2013–2014 academic years. Main Outcome Measure(s) Athletic trainers documented injuries and exposures using commercially available injury-tracking software packages. Standard injury-tracking software was modified by the software vendors to conform to the surveillance needs of this project. The modified software exported a set of common data elements, stripped of personally identifiable information, to a centralized automated verification and validation system before they were included in the centralized research database. Dependent measures were injury and exposure frequencies and injury rates with 95% confidence intervals stratified by sport, sex, and injury type (TL or NTL). Results Over the 3-year period, a total of 2337 team seasons across 27 sports resulted in 47 014 injuries and 5 146 355 athlete-exposures. The NTL injuries accounted for 38 765 (82.45%) and TL injuries for 8249 (17.55%) of the total. Conclusions The NTL injuries accounted for a substantial amount of the total number of injuries sustained by high school student-athletes. This project demonstrates the feasibility of creating large-scale injury surveillance systems using commercially available injury-tracking software. PMID:26067620
Dai, Ting-ting; Shan, Chang-ji; Dong, Yan-shou
As a new subject, the research of complex networks has attracted the attention of researchers from different disciplines. Community structure is one of the key structures of complex networks, so it is a very important task to analyze the community structure of complex networks accurately. In this paper, we study the problem of extracting the community structure of complex networks, and propose a continuous neural network (CNN) algorithm. It is proved that for any given initial value, the continuous neural network algorithm converges to the eigenvector of the maximum eigenvalue of the network modularity matrix. Therefore, according to the stability of the evolution of the network symbol will be able to get two community structure.
Full Text Available Abstract Background The health impacts of heat waves are serious and have prompted the development of heat wave response plans. Even when they are efficient, these plans are developed to limit the health effects of heat waves. This study was designed to determine relevant indicators related to health effects of heat waves and to evaluate the ability of a syndromic surveillance system to monitor variations in the activity of emergency departments over time. The study uses data collected during the summer 2006 when a new heat wave occurred in France. Methods Data recorded from 49 emergency departments since July 2004, were transmitted daily via the Internet to the French Institute for Public Health Surveillance. Items collected on patients included diagnosis (ICD10 codes, outcome, and age. Statistical t-tests were used to compare, for several health conditions, the daily averages of patients within different age groups and periods (whether 'on alert' or 'off alert'. Results A limited number of adverse health conditions occurred more frequently during hot period: dehydration, hyperthermia, malaise, hyponatremia, renal colic, and renal failure. Over all health conditions, the total number of patients per day remained equal between the 'on alert' and 'off alert' periods (4,557.7/day vs. 4,511.2/day, but the number of elderly patients increased significantly during the 'on alert' period relative to the 'off alert' period (476.7/day vs. 446.2/day p Conclusion Our results show the interest to monitor specific indicators during hot periods and to focus surveillance efforts on the elderly. Syndromic surveillance allowed the collection of data in real time and the subsequent optimization of the response by public health agencies. This method of surveillance should therefore be considered as an essential part of efforts to prevent the health effects of heat waves.
Chen, Zixuan; Wang, Xuewen; Xu, Zekai; Hou, Wenguang
DEM super resolution is proposed in our previous publication to improve the resolution for a DEM on basis of some learning examples. Meanwhile, the nonlocal algorithm is introduced to deal with it and lots of experiments show that the strategy is feasible. In our publication, the learning examples are defined as the partial original DEM and their related high measurements due to this way can avoid the incompatibility between the data to be processed and the learning examples. To further extent the applications of this new strategy, the learning examples should be diverse and easy to obtain. Yet, it may cause the problem of incompatibility and unrobustness. To overcome it, we intend to investigate a convolutional neural network based method. The input of the convolutional neural network is a low resolution DEM and the output is expected to be its high resolution one. A three layers model will be adopted. The first layer is used to detect some features from the input, the second integrates the detected features to some compressed ones and the final step transforms the compressed features as a new DEM. According to this designed structure, some learning DEMs will be taken to train it. Specifically, the designed network will be optimized by minimizing the error of the output and its expected high resolution DEM. In practical applications, a testing DEM will be input to the convolutional neural network and a super resolution will be obtained. Many experiments show that the CNN based method can obtain better reconstructions than many classic interpolation methods.
Politis, C; Wiersum, J C; Richardson, C; Robillard, P; Jorgensen, J; Renaudier, P; Faber, J-C; Wood, E M
The International Haemovigilance Network's ISTARE is an online database for surveillance of all adverse reactions (ARs) and adverse events (AEs) associated with donation of blood and transfusion of blood components, irrespective of severity or the harm caused. ISTARE aims to unify the collection and sharing of information with a view to harmonizing best practices for haemovigilance systems around the world. Adverse reactionss and adverse events are recorded by blood component, type of reaction, severity and imputability to transfusion, using internationally agreed standard definitions. From 2006 to 2012, 125 national sets of annual aggregated data were received from 25 countries, covering 132.8 million blood components issued. The incidence of all ARs was 77.5 per 100 000 components issued, of which 25% were severe (19.1 per 100 000). Of 349 deaths (0.26 per 100 000), 58% were due to the three ARs related to the respiratory system: transfusion-associated circulatory overload (TACO, 27%), transfusion-associated acute lung injury (TRALI, 19%) and transfusion-associated dyspnoea (TAD, 12%). Cumulatively, 594 477 donor complications were reported (rate 660 per 100 000), of which 2.9% were severe. ISTARE is a well-established surveillance tool offering important contributions to international efforts to maximize transfusion safety. © 2016 International Society of Blood Transfusion.
Full Text Available An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona network because the properties of the IB model more closely matched those of the e-mail URV network than the other models
Economopoulou, A; Kinross, P; Domanovic, D; Coulombier, D
In 2012, London hosted the Olympic and Paralympic Games (the Games), with events occurring throughout the United Kingdom (UK) between 27 July and 9 September 2012. Public health surveillance was performed by the Health Protection Agency (HPA). Collaboration between the HPA and the European Centre for Disease Prevention and Control (ECDC) was established for the detection and assessment of significant infectious disease events (SIDEs) occurring outside the UK during the time of the Games. Additionally, ECDC undertook an internal prioritisation exercise to facilitate ECDC’s decisions on which SIDEs should have preferentially enhanced monitoring through epidemic intelligence activities for detection and reporting in daily surveillance in the European Union (EU). A team of ECDC experts evaluated potential public health risks to the Games, selecting and prioritising SIDEs for event-based surveillance with regard to their potential for importation to the Games, occurrence during the Games or export to the EU/European Economic Area from the Games. The team opted for a multilevel approach including comprehensive disease selection, development and use of a qualitative matrix scoring system and a Delphi method for disease prioritisation. The experts selected 71 infectious diseases to enter the prioritisation exercise of which 27 were considered as priority for epidemic intelligence activities by ECDC for the EU for the Games.
Yu, Fei; Gillard, Sebastien; Medo, Matus
Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use - such as the possible influence of recommendation on the evolution of systems that use it - and finally discuss open research directions and challenges.
Yu, Fei; Zeng, An; Gillard, Sébastien; Medo, Matúš
Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use-such as the possible influence of recommendation on the evolution of systems that use it-and finally discuss open research directions and challenges.
Inference of the network structure (e.g., routing topology) and dynamics (e.g., link performance) is an essential component in many network design and management tasks. In this paper we propose a new, general framework for analyzing and designing routing topology and link performance inference algorithms using ideas and tools from phylogenetic inference in evolutionary biology. The framework is applicable to a variety of measurement techniques. Based on the framework we introduce and develop several polynomial-time distance-based inference algorithms with provable performance. We provide sufficient conditions for the correctness of the algorithms. We show that the algorithms are consistent (return correct topology and link performance with an increasing sample size) and robust (can tolerate a certain level of measurement errors). In addition, we establish certain optimality properties of the algorithms (i.e., they achieve the optimal $l_\\infty$-radius) and demonstrate their effectiveness via model simulation.
Preciosa M Coloma
Full Text Available BACKGROUND: Drug-related adverse events remain an important cause of morbidity and mortality and impose huge burden on healthcare costs. Routinely collected electronic healthcare data give a good snapshot of how drugs are being used in 'real-world' settings. OBJECTIVE: To describe a strategy that identifies potentially drug-induced acute myocardial infarction (AMI from a large international healthcare data network. METHODS: Post-marketing safety surveillance was conducted in seven population-based healthcare databases in three countries (Denmark, Italy, and the Netherlands using anonymised demographic, clinical, and prescription/dispensing data representing 21,171,291 individuals with 154,474,063 person-years of follow-up in the period 1996-2010. Primary care physicians' medical records and administrative claims containing reimbursements for filled prescriptions, laboratory tests, and hospitalisations were evaluated using a three-tier triage system of detection, filtering, and substantiation that generated a list of drugs potentially associated with AMI. Outcome of interest was statistically significant increased risk of AMI during drug exposure that has not been previously described in current literature and is biologically plausible. RESULTS: Overall, 163 drugs were identified to be associated with increased risk of AMI during preliminary screening. Of these, 124 drugs were eliminated after adjustment for possible bias and confounding. With subsequent application of criteria for novelty and biological plausibility, association with AMI remained for nine drugs ('prime suspects': azithromycin; erythromycin; roxithromycin; metoclopramide; cisapride; domperidone; betamethasone; fluconazole; and megestrol acetate. LIMITATIONS: Although global health status, co-morbidities, and time-invariant factors were adjusted for, residual confounding cannot be ruled out. CONCLUSION: A strategy to identify potentially drug-induced AMI from electronic healthcare
Frosch, Peter J; Duus Johansen, Jeanne; Schuttelaar, Marie-Louise A;
of patients consecutively patch tested between 2009 and 2012 in 12 European countries with fragrance allergens contained in the baseline series were collected by the European Surveillance System on Contact Allergies network and descriptively analysed. Four departments used the TRUE Test(®) system. RESULTS......BACKGROUND: Contact allergy to fragrances is common, and impairs quality of life, particularly in young women. OBJECTIVE: To provide current results on the prevalences of sensitization to fragrance allergens used as markers in the baseline series of most European countries. METHODS: Data......: Contact allergy to fragrances is common throughout Europe, with regional variation probably being explained by patch test technique, and differences in exposure and referral patterns. The current basic markers of fragrance sensitivity in the baseline series should be supplemented with additional fragrance...
Neural Network-Based Hyperspectral Algorithms Walter F. Smith, Jr. and Juanita Sandidge Naval Research Laboratory Code 7340, Bldg 1105 Stennis Space...our effort is development of robust numerical inversion algorithms , which will retrieve inherent optical properties of the water column as well as...validate the resulting inversion algorithms with in-situ data and provide estimates of the error bounds associated with the inversion algorithm . APPROACH
Samuel A. Iverson
Full Text Available Emerging infectious diseases are a growing concern in wildlife conservation. Documenting outbreak patterns and determining the ecological drivers of transmission risk are fundamental to predicting disease spread and assessing potential impacts on population viability. However, evaluating disease in wildlife populations requires expansive surveillance networks that often do not exist in remote and developing areas. Here, we describe the results of a community-based research initiative conducted in collaboration with indigenous harvesters, the Inuit, in response to a new series of Avian Cholera outbreaks affecting Common Eiders (Somateria mollissima and other comingling species in the Canadian Arctic. Avian Cholera is a virulent disease of birds caused by the bacterium Pasteurella multocida. Common Eiders are a valuable subsistence resource for Inuit, who hunt the birds for meat and visit breeding colonies during the summer to collect eggs and feather down for use in clothing and blankets. We compiled the observations of harvesters about the growing epidemic and with their assistance undertook field investigation of 131 colonies distributed over >1200 km of coastline in the affected region. Thirteen locations were identified where Avian Cholera outbreaks have occurred since 2004. Mortality rates ranged from 1% to 43% of the local breeding population at these locations. Using a species-habitat model (Maxent, we determined that the distribution of outbreak events has not been random within the study area and that colony size, vegetation cover, and a measure of host crowding in shared wetlands were significantly correlated to outbreak risk. In addition, outbreak locations have been spatially structured with respect to hypothesized introduction foci and clustered along the migration corridor linking Arctic breeding areas with wintering areas in Atlantic Canada. At present, Avian Cholera remains a localized threat to Common Eider populations in the
Zhao, H; Green, H; Lackenby, A; Donati, M; Ellis, J; Thompson, C; Bermingham, A; Field, J; Sebastianpillai, P; Zambon, M; Watson, Jm; Pebody, R
During the 2009 influenza A(H1N1) pandemic, a new laboratory-based virological sentinel surveillance system, the Respiratory DataMart System (RDMS), was established in a network of 14 Health Protection Agency (now Public Health England (PHE)) and National Health Service (NHS) laboratories in England. Laboratory results (both positive and negative) were systematically collected from all routinely tested clinical respiratory samples for a range of respiratory viruses including influenza, respiratory syncytial virus (RSV), rhinovirus, parainfluenza virus, adenovirus and human metapneumovirus (hMPV). The RDMS also monitored the occurrence of antiviral resistance of influenza viruses. Data from the RDMS for the 2009–2012 period showed that the 2009 pandemic influenza virus caused three waves of activity with different intensities during the pandemic and post pandemic periods. Peaks in influenza A(H1N1)pdm09 positivity (defined as number of positive samples per total number of samples tested) were seen in summer and autumn in 2009, with slightly higher peak positivity observed in the first post-pandemic season in 2010/2011. The influenza A(H1N1)pdm09 virus strain almost completely disappeared in the second postpandemic season in 2011/2012. The RDMS findings are consistent with other existing community-based virological and clinical surveillance systems. With a large sample size, this new system provides a robust supplementary mechanism, through the collection of routinely available laboratory data at minimum extra cost, to monitor influenza as well as other respiratory virus activity. A near real-time, daily reporting mechanism in the RDMS was established during the London 2012 Olympic and Paralympic Games. Furthermore, this system can be quickly adapted and used to monitor future influenza pandemics and other major outbreaks of respiratory infectious disease, including novel pathogens.
Heryanto M Ary
Full Text Available UAVs are mostly used for surveillance, inspection and data acquisition. We have developed a Quadrotor UAV that is constructed based on a four motors with a lift-generating propeller at each motors. In this paper, we discuss the development of a quadrotor and its neural networks direct inverse control model using the actual flight data. To obtain a better performance of the control system of the UAV, we proposed an Optimized Direct Inverse controller based on re-training the neural networks with the new data generated from optimal maneuvers of the quadrotor. Through simulation of the quadrotor using the developed DIC and Optimized DIC model, results show that both models have the ability to stabilize the quadrotor with a good tracking performance. The optimized DIC model, however, has shown a better performance, especially in the settling time parameter.
Chow, C B; Leung, M; Lai, Adela; Chow, Y H; Chung, Joanne; Tong, K M; Lit, Albert
To describe the experience in the development of an electronic emergency department (ED)-based injury surveillance (IS) system in Hong Kong using data-mining and geo-spatial information technology (IT) for a Safe Community setup. This paper described the phased development of an emergency department-based IS system based on World Health Organization (WHO) injury surveillance Guideline to support safety promotion and injury prevention in a Safe Community in Hong Kong starting 2002. The initial ED data-based only collected data on name, sex, age, address, eight general categories of injury types (traffic, domestic, common assault, indecent assault, batter, industrial, self-harm and sports) and disposal from ED. Phase 1--manual data collection on International Classification of External Causes of Injury pre-event data; Phase 2--manual form was converted to electronic format using web-based data mining technology with built in data quality monitoring mechanism; Phase 3--integration of injury surveillance-data with in-patient hospital information; and Phase 4--geo-spatial information and body mapping were introduced to geo-code exact place of injury in an electronic map and site of injury on body map. It was feasible to develop a geo-spatial IS system at busy ED to collect valuable information for safety promotion and injury prevention at Safe Community setting. The keys for successful development and implementation involves engagement of all stakeholders at design and implementation of the system with injury prevention as ultimate goal, detail workflow planning at front end, support from the management, building on exiting system and appropriate utilisation of modern technology. Copyright © 2011 Elsevier Ltd. All rights reserved.
We propose a new method for detecting communities based on the concept of communicability between nodes in a complex network. This method, designated as N-ComBa K-means, uses a normalized version of the adjacency matrix to build the communicability matrix and then applies K-means clustering to find the communities in a graph. We analyze how this method performs for some pathological cases found in the analysis of the detection limit of communities and propose some possible solutions on the basis of the analysis of the ratio of local to global densities in graphs. We use four different quality criteria for detecting the best clustering and compare the new approach with the Girvan-Newman algorithm for the analysis of two "classical" networks: karate club and bottlenose dolphins. Finally, we analyze the more challenging case of homogeneous networks with community structure, for which the Girvan-Newman completely fails in detecting any clustering. The N-ComBa K-means approach performs very well in these situations and we applied it to detect the community structure in an international trade network of miscellaneous manufactures of metal having these characteristics. Some final remarks about the general philosophy of community detection are also discussed.
Rajkumar, Sunanda; Sistla, Sujatha; Manoharan, Meerabai; Sugumar, Madhan; Nagasundaram, Niveditha; Parija, Subhash Chandra; Ray, Pallab; Bakthavatchalam, Yamuna Devi; Veeraraghavan, Balaji; Kapil, Arti; Walia, Kamini; Ohri, V C
Routine surveillance of antimicrobial resistance (AMR) is an essential component of measures aimed to tackle the growing threat of resistant microbes in public health. This study presents a 1-year multicentre report on AMR in Staphylococcus species as part of Indian Council of Medical Research-AMR surveillance network. Staphylococcus species was routinely collected in the nodal and regional centres of the network and antimicrobial susceptibility testing was performed against a panel of antimicrobials. Minimum inhibitory concentration (MIC) values of vancomycin (VAN), daptomycin, tigecycline and linezolid (LNZ) against selected methicillin-resistant Staphylococcus aureus(MRSA) isolates were determined by E-test and MIC creep, if any, was determined. Resistant genotypes were determined by polymerase chain reaction for those isolates showing phenotypic resistance. The prevalence of MRSA was found to be range from moderate (21%) to high (45%) among the centres with an overall prevalence of 37.3%. High prevalence of resistance was observed with commonly used antimicrobials such as ciprofloxacin and erythromycin in all the centres. Resistance to LNZ was not encountered except for a single case. Full-blown resistance to VAN in S. aureus was not observed; however, a few VAN-intermediate S. aureus isolates were documented. The most common species of coagulase negative staphylococci (CoNS) identified was Staphylococcus haemolyticus and Staphylococcus epidermidis. Resistance among CoNS was relatively higher than S. aureus. Most phenotypically resistant organisms possessed the corresponding resistance genes. There were localised differences in the prevalence of resistance between the centres. The efficacy of the anti-MRSA antimicrobials was very high; however, almost all these antimicrobials showed evidence of creeping MIC.
Full Text Available Plasmodium malariae is a slow-growing parasite with a wide geographic distribution. Although generally regarded as a benign cause of malaria, it has been associated with nephrotic syndrome, particularly in young children, and can persist in the host for years. Morbidity associated with P. malariae infection has received relatively little attention, and the risk of P. malariae-associated nephrotic syndrome is unknown.We used data from a very large hospital-based surveillance system incorporating information on clinical diagnoses, blood cell parameters and treatment to describe the demographic distribution, morbidity and mortality associated with P. malariae infection in southern Papua, Indonesia. Between April 2004 and December 2013 there were 1,054,674 patient presentations to Mitra Masyarakat Hospital of which 196,380 (18.6% were associated with malaria and 5,097 were with P. malariae infection (constituting 2.6% of all malaria cases. The proportion of malaria cases attributable to P. malariae increased with age from 0.9% for patients under one year old to 3.1% for patients older than 15 years. Overall, 8.5% of patients with P. malariae infection required admission to hospital and the median length of stay for these patients was 2.5 days (Interquartile Range: 2.0-4.0 days. Patients with P. malariae infection had a lower mean hemoglobin concentration (9.0 g/dL than patients with P. falciparum (9.5 g/dL, P. vivax (9.6g/dL and mixed species infections (9.3g/dL. There were four cases of nephrotic syndrome recorded in patients with P. malariae infection, three of which were in children younger than 5 years old, giving a risk in this age group of 0.47% (95% Confidence Interval; 0.10% to 1.4%. Overall, 2.4% (n = 16 of patients hospitalized with P. malariae infection subsequently died in hospital, similar to the proportions for the other endemic Plasmodium species (range: 0% for P. ovale to 1.6% for P. falciparum.Plasmodium malariae infection is
Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.
Umeh, Chukwuemeka Anthony; Onyi, Stella Chioma
Introduction. Rubella infection has the potential of causing severe fetal birth defects collectively called congenital rubella syndrome (CRS) if the mother is infected early in pregnancy. However, little is known about rubella and CRS epidemiology in Nigeria and rubella vaccines are still not part of routine childhood immunization in Nigeria. Methods. Analysis of confirmed cases of rubella in Abia State, Nigeria from 2007 to 2011 detected through Abia State Integrated Disease Surveillance and Response system. Results. Of the 757 febrile rash cases, 81(10.7%) tested positive for rubella immunoglobulin M (IgM). New rubella infection decreased from 6.81/1,000,000 population in 2007 to 2.28/1,000,000 in 2009 and increased to 6.34/1,000,000 in 2011. The relative risk of rubella was 1.5 (CI [0.98-2.28]) times as high in females compared to males and 1.6 times (CI [0.90-2.91]) as high in rural areas compared to urban areas. Eighty six percent of rubella infections occurred in children less than 15 years with a high proportion of cases occurring between 5 and 14 years. Conclusion. Rubella infection in Abia State, Nigeria is predominantly in those who are younger than 15 years old. It is also more prevalent in females and in those living in rural areas of the state. Unfortunately, there is no surveillance of CRS in Nigeria and so the public health impact of rubella infection in the state is not known. Efforts should be made to expand the rubella surveillance in Nigeria to incorporate surveillance for CRS.
Le Roux, WH
Full Text Available activity recognition framework for maritime applications (Adapted from ) III. APPLYING THE FRAMEWORK A. Use Cases Use cases  are valuable means of capturing transactions between users and systems. In the maritime surveillance environment, a.... D. Vessel Capabilities In terms of capabilities, the design, deployment and devel- opment sub-elements have to be estimated from information and data sources. To establish that a vessel is engaged in illegal fishing activities, basic criteria...
Full Text Available Mobile ad-hoc network has challenge of the limited power to prolong the lifetime of the network, because power is a valuable resource in mobile ad-hoc network. The status of power consumption should be continuously monitored after network deployment. In this paper, we propose coverage aware neural network based power control routing with the objective of maximizing the network lifetime. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage. The simulation results show that the proposed scheme can be used in wide area of applications in mobile ad-hoc network.
Yang, Hongyong; Lu, Lan; Liu, Qiming
Recently, the studies of the complex network have gone deep into many scientific fields, such as computer science, physics, mathematics, sociology, etc. These researches enrich the realization for complex network, and increase understands for the new characteristic of complex network. Based on the evolvement characteristic of the author collaboration in the scientific thesis, a self-organized network model of the scientific cooperation network is presented by module emerging. By applying the theoretical analysis, it is shown that this network model is a scale-free network, and the strength degree distribution and the module degree distribution of the network nodes have the same power law. In order to make sure the validity of the theoretical analysis for the network model, we create the computer simulation and demonstration collaboration network. By analyzing the data of the network, the results of the demonstration network and the computer simulation are consistent with that of the theoretical analysis of the model.
Full Text Available During their task accomplishment, autonomous unmanned aerial vehicles are facing more and more threats coming from both ground and air. In such adversarial environments, with no a priori information about the threats, a flying robot in charge with surveilling a specified 3D sector must perform its tasks by evolving on misleading and unpredictable trajectories to cope with enemy entities. In our view, the chaotic dynamics can be the cornerstone in designing unpredictable paths for such missions, even though this solution was not exploited until now by researchers in the 3D context. This paper addresses the flight path-planning issue for surveilling a given volume in adversarial conditions by proposing a proficient approach that uses the chaotic behaviour exhibited by the 3D Arnold’s cat map. By knowing the exact location of the volume under surveillance before take-off, the flying robot will generate the successive chaotic waypoints only with onboard resources, in an efficient manner. The method is validated by simulation in a realistic scenario using a detailed Simulink model for the X-4 Flyer quadcopter.
Prattley, D J; Morris, R S; Stevenson, M A; Thornton, R
Distribution of finite levels of resources between multiple competing tasks can be a challenging problem. Resources need to be distributed across time periods and geographic locations to increase the probability of detection of a disease incursion or significant change in disease pattern. Efforts should focus primarily on areas and populations where risk factors for a given disease reach relatively high levels. In order to target resources into these areas, the overall risk level can be evaluated periodically across locations to create a dynamic national risk landscape. Methods are described to integrate the levels of various risk factors into an overall risk score for each area, to account for the certainty or variability around those measures and then to allocate surveillance resources across this risk landscape. In addition to targeting resources into high risk areas, surveillance continues in lower risk areas where there is a small yet positive chance of disease occurrence. In this paper we describe the application of portfolio theory concepts, routinely used in finance, to design surveillance portfolios for a series of examples. The appropriate level of resource investment is chosen for each disease or geographical area and time period given the degree of disease risk and uncertainty present.
van den Hurk, Andrew F; Hall-Mendelin, Sonja; Townsend, Michael; Kurucz, Nina; Edwards, Jim; Ehlers, Gerhard; Rodwell, Chris; Moore, Frederick A; McMahon, Jamie L; Northill, Judith A; Simmons, Russell J; Cortis, Giles; Melville, Lorna; Whelan, Peter I; Ritchie, Scott A
Effective arbovirus surveillance is essential to ensure the implementation of control strategies, such as mosquito suppression, vaccination, or dissemination of public warnings. Traditional strategies employed for arbovirus surveillance, such as detection of virus or virus-specific antibodies in sentinel animals, or detection of virus in hematophagous arthropods, have limitations as an early-warning system. A system was recently developed that involves collecting mosquitoes in CO2-baited traps, where the insects expectorate virus on sugar-baited nucleic acid preservation cards. The cards are then submitted for virus detection using molecular assays. We report the application of this system for detecting flaviviruses and alphaviruses in wild mosquito populations in northern Australia. This study was the first to employ nonpowered passive box traps (PBTs) that were designed to house cards baited with honey as the sugar source. Overall, 20/144 (13.9%) of PBTs from different weeks contained at least one virus-positive card. West Nile virus Kunjin subtype (WNVKUN), Ross River virus (RRV), and Barmah Forest virus (BFV) were detected, being identified in 13/20, 5/20, and 2/20 of positive PBTs, respectively. Importantly, sentinel chickens deployed to detect flavivirus activity did not seroconvert at two Northern Territory sites where four PBTs yielded WNVKUN. Sufficient WNVKUN and RRV RNA was expectorated onto some of the honey-soaked cards to provide a template for gene sequencing, enhancing the utility of the sugar-bait surveillance system for investigating the ecology, emergence, and movement of arboviruses.
Manning, J; Broughton, V; McConnell, E A
The challenge in nursing education is to create a learning environment that enables students to learn new knowledge, access previously acquired information from a variety of disciplines, and apply this newly constructed knowledge to the complex and constantly changing world of practice. Faculty at the University of South Australia, School of Nursing, City Campus describe the use of reality based scenarios to acquire domain-specific knowledge and develop well connected associative knowledge networks, both of which facilitate theory based practice and the student's transition to the role of registered nurse.
Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur
This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.
Zhai, Yinhu; Wang, Shaohui
We introduce an informative labeling algorithm for the vertices of a family of Koch networks. Each of the labels is consisted of two parts, the precise position and the time adding to Koch networks. The shortest path routing between any two vertices is determined only on the basis of their labels, and the routing is calculated only by few computations. The rigorous solutions of betweenness centrality for every node and edge are also derived by the help of their labels. Furthermore, the community structure in Koch networks is studied by the current and voltage characteristics of its resistor networks.
The main task of network administrators is to ensure that their network functions properly. Whether they manage a telecommunication or a road network, they generally base their decisions on the analysis of measurement data. Inspired by such network control applications, this dissertation investigate
This dissertation addresses the problem of optimizing maintenance, repair and reconstruction decisions for bridge networks. Incorporating network topologies into bridge management problems is computationally difficult. Because of the interdependencies among networked bridges, they have to be analyzed together. Simulation-based numerical optimization techniques adopted in past research are limited to networks of moderate sizes. In this dissertation, novel approaches are developed to dete...
With the digital information and application requirement on the Internet increasing fleetly nowadays,it is urgent to work out a network storage system with a large capacity, a high availability and scalability. To solve the above-mentioned issues, a NAS-based storage network ( for short NASSN) has been designed. Firstly,the NASSN integrates multi-NAS,iNAS (an iSCSI-based NAS) and enterprise SAN with the help of storage virtualization, which can provide a greater capacity and better scalability. Secondly, the NASSN can provide high availability with the help of server and storage subsystem redundancy technologies. Thirdly, the NASSN simultaneously serves for both the file I/O and the block L/O with the help of an iSCSI module, which has the advantages of NAS and SAN. Finally, the NASSN can provide higher I/O speed by a high network-attached channel which implements the direct data transfer between the storage device and client. In the experiments, the NASSN has ultra-high-throughput for both of the file I/O requests and the block I/O requests.
Full Text Available BACKGROUND: Dengue vaccines are now in late-stage development, and evaluation and robust estimates of dengue disease burden are needed to facilitate further development and introduction. In Cambodia, the national dengue case-definition only allows reporting of children less than 16 years of age, and little is known about dengue burden in rural areas and among older persons. To estimate the true burden of dengue in the largest province of Cambodia, Kampong Cham, we conducted community-based active dengue fever surveillance among the 0-to-19-year age group in rural villages and urban areas during 2006-2008. METHODS AND FINDINGS: Active surveillance for febrile illness was conducted in 32 villages and 10 urban areas by mothers trained to use digital thermometers combined with weekly home visits to identify persons with fever. An investigation team visited families with febrile persons to obtain informed consent for participation in the follow-up study, which included collection of personal data and blood specimens. Dengue-related febrile illness was defined using molecular and serological testing of paired acute and convalescent blood samples. Over the three years of surveillance, 6,121 fever episodes were identified with 736 laboratory-confirmed dengue virus (DENV infections for incidences of 13.4-57.8/1,000 person-seasons. Average incidence was highest among children less than 7 years of age (41.1/1,000 person-seasons and lowest among the 16-to-19-year age group (11.3/1,000 person-seasons. The distribution of dengue was highly focal, with incidence rates in villages and urban areas ranging from 1.5-211.5/1,000 person-seasons (median 36.5. During a DENV-3 outbreak in 2007, rural areas were affected more than urban areas (incidence 71 vs. 17/1,000 person-seasons, p<0.001. CONCLUSION: The large-scale active surveillance study for dengue fever in Cambodia found a higher disease incidence than reported to the national surveillance system, particularly
Gilani, Syed Sherjeel Ahmad; Zubair, Muhammad; Khan, Zeeshan Shafi
Infrastructure-based Wireless Mesh Networks are emerging as an affordable, robust, flexible and scalable technology. With the advent of Wireless Mesh Networks (WMNs) the dream of connecting multiple technology based networks seems to come true. A fully secure WMN is still a challenge for the researchers. In infrastructure-based WMNs almost all types of existing Wireless Networks like Wi-Fi, Cellular, WiMAX, and Sensor etc can be connected through Wireless Mesh Routers (WMRs). This situation can lead to a security problem. Some nodes can be part of the network with high processing power, large memory and least energy issues while others may belong to a network having low processing power, small memory and serious energy limitations. The later type of the nodes is very much vulnerable to targeted attacks. In our research we have suggested to set some rules on the WMR to mitigate these kinds of targeted flooding attacks. The WMR will then share those set of rules with other WMRs for Effective Utilization of Resources.
CHEN Xiao-lin; ZHOU Jing-yang; DAI Han; LU Sang-lu; CHEN Gui-hai
We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallelly processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.
Sarigöl, Emre; Scholtes, Ingo; Garas, Antonios; Schweitzer, Frank
We address the question to what extent the success of scientific articles is due to social influence. Analyzing a data set of over 100000 publications from the field of Computer Science, we study how centrality in the coauthorship network differs between authors who have highly cited papers and those who do not. We further show that a machine learning classifier, based only on coauthorship network centrality measures at time of publication, is able to predict with high precision whether an article will be highly cited five years after publication. By this we provide quantitative insight into the social dimension of scientific publishing - challenging the perception of citations as an objective, socially unbiased measure of scientific success.
费翔; 何小燕; 罗军舟; 吴介一; 顾冠群
Congestion control is one of the key problems in high-speed networks, such as ATM. In this paper, a kind of traffic prediction and preventive congestion control scheme is proposed using neural network approach. Traditional predictor using BP neural network has suffered from long convergence time and dissatisfying error. Fuzzy neural network developed in this paper can solve these problems satisfactorily. Simulations show the comparison among no-feedback control scheme,reactive control scheme and neural network based control scheme.
LIU Su-ping; DING Yong-sheng
Traditional SNMP-based network management can not deal with the task of managing large-scaled distributed network,while policy-based management is one of the effective solutions in network and distributed systems management. However,cross-vendor hardware compatibility is one of the limitations in policy-based management. Devices existing in current network mostly support SNMP rather than Common Open Policy Service (COPS) protocol. By analyzing traditional network management and policy-based network management, a scalable network management framework is proposed. It is combined with Internet Engineering Task Force (IETF) framework for policybased management and SNMP-based network management. By interpreting and translating policy decision to SNMP message,policy can be executed in traditional SNMP-based device.
Roer, Louise; Hansen, Frank; Thomsen, Martin Christen Frølund
To evaluate a genome-based surveillance of all Danish third-generation cephalosporin-resistant Escherichia coli (3GC-R Ec ) from bloodstream infections between 2014 and 2015, focusing on horizontally transferable resistance mechanisms. A collection of 552 3GC-R Ec isolates were whole....... The majority of the 552 isolates were ESBL producers (89%), with bla CTX-M-15 being the most prevalent (50%) gene, followed by bla CTX-M-14 (14%), bla CTX-M-27 (11%) and bla CTX-M-101 (5%). ST131 was detected in 50% of the E. coli isolates, with the remaining isolates belonging to 73 other STs, including...
Yu, Ping; de Courten, Maximilian; Pan, Elaine;
EpiData and Epi Info are often used together by public health agencies around the world, particularly in developing countries, to meet their needs of low-cost public health data management; however, the current open source data management technology lacks a mobile component to meet the needs...... of mobile public health data collectors. The goal of this project is to explore the opportunity of filling this gap through developing and trial of a personal digital assistant (PDA) based data collection/entry system. It evaluated whether such a system could increase efficiency and reduce data...... transcription errors for public surveillance data collection in developing countries represented by Fiji....
Velasquez, Daniel E.; Arvelo, Wences; Cama, Vitaliano A.; López, Beatriz; Reyes, Lissette; Roellig, Dawn M.; Kahn, Geoffrey D.; Lindblade, Kimberly A.
We molecularly characterized samples with Giardia, Cryptosporidium, and soil-transmitted helminths from a facility-based surveillance system for diarrhea in Santa Rosa, Guatemala. The DNA sequence analysis determined the presence of Giardia assemblages A (N = 7) and B (N = 12) and, Cryptosporidium hominis (N = 2) and Cryptosporidium parvum (N = 2), suggestive of different transmission cycles. All 41 samples with soil-transmitted helminths did not have the β-tubulin mutation described for benzimidazole resistance, suggesting potential usefulness in mass drug administration campaigns. PMID:22144459
Jeffrey Joseph; Roshan Gajanan Patil; Skanda Kumar Kaipu Narahari; Yogish Didagi; Jyotsna Bapat; Debabrata Das
... system. Wireless Sensor Networks are one such class of networks, which meet these criteria. These networks consist of spatially distributed sensor motes which work in a co-operative manner to sense and control the environment...
Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.
Church, Earnie Mitchell, Jr.
In the last couple of years, a new aspect of online social networking has emerged, in which the strength of social network connections is based not on social ties but mutually shared interests. This dissertation studies these "curation-based" online social networks (CBN) and their suitability for the diffusion of electronic word-of-mouth…
Full Text Available In this article a number of neural networks based on self-organizing maps, that can be successfully used for dynamic object identification, is described. Unique SOM-based modular neural networks with vector quantized associative memory and recurrent self-organizing maps as modules are presented. The structured algorithms of learning and operation of such SOM-based neural networks are described in details, also some experimental results and comparison with some other neural networks are given.
Rashid Uz Zaman
Full Text Available BACKGROUND: Recent population-based estimates in a Dhaka low-income community suggest that influenza was prevalent among children. To explore the epidemiology and seasonality of influenza throughout the country and among all age groups, we established nationally representative hospital-based surveillance necessary to guide influenza prevention and control efforts. METHODOLOGY/PRINCIPAL FINDINGS: We conducted influenza-like illness and severe acute respiratory illness sentinel surveillance in 12 hospitals across Bangladesh during May 2007-December 2008. We collected specimens from 3,699 patients, 385 (10% which were influenza positive by real time RT-PCR. Among the sample-positive patients, 192 (51% were type A and 188 (49% were type B. Hemagglutinin subtyping of type A viruses detected 137 (71% A/H1 and 55 (29% A/H3, but no A/H5 or other novel influenza strains. The frequency of influenza cases was highest among children aged under 5 years (44%, while the proportions of laboratory confirmed cases was highest among participants aged 11-15 (18%. We applied kriging, a geo-statistical technique, to explore the spatial and temporal spread of influenza and found that, during 2008, influenza was first identified in large port cities and then gradually spread to other parts of the country. We identified a distinct influenza peak during the rainy season (May-September. CONCLUSIONS/SIGNIFICANCE: Our surveillance data confirms that influenza is prevalent throughout Bangladesh, affecting a wide range of ages and causing considerable morbidity and hospital care. A unimodal influenza seasonality may allow Bangladesh to time annual influenza prevention messages and vaccination campaigns to reduce the national influenza burden. To scale-up such national interventions, we need to quantify the national rates of influenza and the economic burden associated with this disease through further studies.
Smartt, H.; Martinez, R.; Caskey, S. [Sandia National Laboratories (United States); Honkamaa, T.; Ilander, T.; Poellaenen, R. [Radiation and Nuclear Safety Authority, Helsinki (Finland); Jeremica, N.; Ford, G. [Nokia (Finland)
One of the primary concerns of employing remote monitoring technologies for IAEA safeguards applications is the high cost of data transmission. Transmitting data over the Internet has been shown often to be less expensive than other data transmission methods. However, data security of the Internet is often considered to be at a low level. Virtual Private Networks has emerged as a solution to this problem. A field demonstration was implemented to evaluate the use of Virtual Private Networks (via the Internet) as a means for data transmission. Evaluation points included security, reliability and cost. The existing Finnish Remote Environmental Monitoring System, located at the STUK facility in Helsinki, Finland, served as the field demonstration system. Sandia National Laboratories (SNL) established a Virtual Private Network between STUK (Radiation and Nuclear Safety Authority) Headquarters in Helsinki, Finland, and IAEA Headquarters in Vienna, Austria. Data from the existing STUK Remote Monitoring System was viewed at the IAEA via this network. The Virtual Private Network link was established in a proper manner, which guarantees the data security. Encryption was verified using a network sniffer. No problems were? encountered during the test. In the test system, fixed costs were higher than in the previous system, which utilized telephone lines. On the other hand transmission and operating costs are very low. Therefore, with low data amounts, the test system is not cost-effective, but if the data amount is tens of Megabytes per day the use of Virtual Private Networks and Internet will be economically justifiable. A cost-benefit analysis should be performed for each site due to significant variables. (orig.)
Impact of population on the environment, and conversely, is obvious and represents a real challenge for Public Health since 2000. It has been shown an increase in cancer prevalence, respiratory disease or even reproductive disorders, for which multifactorial origins are strongly suspected. In this context, surveillance has become an essential tool to decision making in public health, and surveillance networks of health events are multiplying, giving rise to numerous databases (sometimes consi...
Hernández-Ávila, Juan Eugenio; Rodríguez, Mario-Henry; Santos-Luna, René; Sánchez-Castañeda, Veronica; Román-Pérez, Susana; Ríos-Salgado, Víctor Hugo; Salas-Sarmiento, Jesús Alberto
Dengue fever incidence and its geographical distribution are increasing throughout the world. Quality and timely information is essential for its prevention and control. A web based, geographically enabled, dengue integral surveillance system (Dengue-GIS) was developed for the nation-wide collection, integration, analysis and reporting of geo-referenced epidemiologic, entomologic, and control interventions data. Consensus in the design and practical operation of the system was a key factor for its acceptance. Working with information systems already implemented as a starting point facilitated its acceptance by officials and operative personnel. Dengue-GIS provides the geographical detail needed to plan, asses and evaluate the impact of control activities. The system is beginning to be adopted as a knowledge base by vector control programs. It is used to generate evidence on impact and cost-effectiveness of control activities, promoting the use of information for decision making at all levels of the vector control program. Dengue-GIS has also been used as a hypothesis generator for the academic community. This GIS-based model system for dengue surveillance and the experience gathered during its development and implementation could be useful in other dengue endemic countries and extended to other infectious or chronic diseases.
Juan Eugenio Hernández-Ávila
Full Text Available Dengue fever incidence and its geographical distribution are increasing throughout the world. Quality and timely information is essential for its prevention and control. A web based, geographically enabled, dengue integral surveillance system (Dengue-GIS was developed for the nation-wide collection, integration, analysis and reporting of geo-referenced epidemiologic, entomologic, and control interventions data. Consensus in the design and practical operation of the system was a key factor for its acceptance. Working with information systems already implemented as a starting point facilitated its acceptance by officials and operative personnel. Dengue-GIS provides the geographical detail needed to plan, asses and evaluate the impact of control activities. The system is beginning to be adopted as a knowledge base by vector control programs. It is used to generate evidence on impact and cost-effectiveness of control activities, promoting the use of information for decision making at all levels of the vector control program. Dengue-GIS has also been used as a hypothesis generator for the academic community. This GIS-based model system for dengue surveillance and the experience gathered during its development and implementation could be useful in other dengue endemic countries and extended to other infectious or chronic diseases.
Zhao, Yongli; He, Ruiying; Chen, Haoran; Zhang, Jie; Ji, Yuefeng; Zheng, Haomian; Lin, Yi; Wang, Xinbo
Software defined networking (SDN) has become the focus in the current information and communication technology area because of its flexibility and programmability. It has been introduced into various network scenarios, such as datacenter networks, carrier networks, and wireless networks. Optical transport network is also regarded as an important application scenario for SDN, which is adopted as the enabling technology of data communication networks (DCN) instead of general multi-protocol label switching (GMPLS). However, the practical performance of SDN based DCN for large scale optical networks, which is very important for the technology selection in the future optical network deployment, has not been evaluated up to now. In this paper we have built a large scale flexi-grid optical network testbed with 1000 virtual optical transport nodes to evaluate the performance of SDN based DCN, including network scalability, DCN bandwidth limitation, and restoration time. A series of network performance parameters including blocking probability, bandwidth utilization, average lightpath provisioning time, and failure restoration time have been demonstrated under various network environments, such as with different traffic loads and different DCN bandwidths. The demonstration in this work can be taken as a proof for the future network deployment.
Morisada, Naoya; Nozu, Kandai; Iijima, Kazumoto
Branchio-oto-renal (BOR) syndrome is an autosomal dominant disorder characterized by branchiogenic malformation, hearing loss and renal anomalies. The prevalence of BOR syndrome is 1/40,000 in Western countries, and nationwide surveillance in 2009-2010 identified approximately 250 BOR patients in Japan. Three causative genes for BOR syndrome have been reported thus far: EYA1, SIX1, and SIX5, but the causative genes for approximately half of all BOR patients remain unknown. This review article discusses the epidemiology, clinical symptoms, genetic background and management of BOR syndrome. © 2014 Japan Pediatric Society.
Ana Maria Passos-Castilho
Full Text Available INTRODUCTION: Data on hepatitis E virus (HEV in Brazil are limited. We analyzed 15 years of HEV surveillance data in a major clinical laboratory in São Paulo, Brazil. METHODS: The seroprevalence of HEV of 2,271 patients subjected to anti-HEV tests from 1998 to 2013 were analyzed. RESULTS: HEV seroprevalence was 2.1%, and the anti-HEV IgM positivity rate was 4.9%. Six hepatitis E patients were identified. CONCLUSIONS: HEV seroprevalence and detection rates appear to have increased in recent years. Hepatitis E should be investigated further and included in the differential diagnosis of hepatitis in Brazil.
Ana Maria Passos-Castilho; Anne de Sena; Mônica Renata Reinaldo; Celso Francisco Hernandes Granato
INTRODUCTION: Data on hepatitis E virus (HEV) in Brazil are limited. We analyzed 15 years of HEV surveillance data in a major clinical laboratory in São Paulo, Brazil. METHODS: The seroprevalence of HEV of 2,271 patients subjected to anti-HEV tests from 1998 to 2013 were analyzed. RESULTS: HEV seroprevalence was 2.1%, and the anti-HEV IgM positivity rate was 4.9%. Six hepatitis E patients were identified. CONCLUSIONS: HEV seroprevalence and detection rates appear to have increased in recent y...
Full Text Available A Bayesian Network based mathematical model has been used for modelling Extreme Programmingsoftware development process. The model is capable of predicting the expected finish time and theexpected defect rate for each XP release. Therefore, it can be used to determine the success/failure of anyXP Project. The model takes into account the effect of three XP practices, namely: Pair Programming,Test Driven Development and Onsite Customer practices. The model’s predictions were validated againsttwo case studies. Results show the precision of our model especially in predicting the project finish time.
Full Text Available This paper presents multiphase sinusoidal oscillators (MSOs using operational transresistance amplifier (OTRA based all pass networks. Both even and odd phase oscillations of equal amplitudes which are equally spaced in phase can be produced using single all pass section per phase. The proposed MSOs provide voltage output and can readily be used for driving voltage input circuits without increasing component count. The effect of nonideality of OTRA on the circuit performance is also analysed. The functionality of the proposed circuit is verified through PSPICE simulations.
Full Text Available As a result of developing on Internet and computer fields, web based education becomes one of the area that many improving and research studies are done. In this study, web based education materials have been explained for multimedia animation and simulation aided Computer Networks course in Technical Education Faculties. Course content is formed by use of university course books, web based education materials and technology web pages of companies. Course content is formed by texts, pictures and figures to increase motivation of students and facilities of learning some topics are supported by animations. Furthermore to help working principles of routing algorithms and congestion control algorithms simulators are constructed in order to interactive learning
Based on social network theoy, this article investigates the distribution of networking roles and responsibilities in entrepreneurial founding teams. Its focus is on the team as a collection of individuals, thus allowing the research to address differences in networking patterns. It identifies six...... central networking activities and shows that not all founding team members are equally active 'networkers'. The analyses show that team members prioritize different networking activities and that one member in particular has extensive networking activities whereas other memebrs of the team are more...
Hu Hai-Bo; Guo Jin-Li; Chen Jun
We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation,preferential acceptance,and preferential attachment.Based on the linear preference,we propose an analyzable model,which illustrates the mechanism of network growth and reproduces the process of network evolution.Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network.This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks.
Sørensen, John Aasted
A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization of...
Surita Fernanda G
Full Text Available Abstract Background It has been suggested that the study of women who survive life-threatening complications related to pregnancy (maternal near-miss cases may represent a practical alternative to surveillance of maternal morbidity/mortality since the number of cases is higher and the woman herself is able to provide information on the difficulties she faced and the long-term repercussions of the event. These repercussions, which may include sexual dysfunction, postpartum depression and posttraumatic stress disorder, may persist for prolonged periods of time, affecting women's quality of life and resulting in adverse effects to them and their babies. Objective The aims of the present study are to create a nationwide network of scientific cooperation to carry out surveillance and estimate the frequency of maternal near-miss cases, to perform a multicenter investigation into the quality of care for women with severe complications of pregnancy, and to carry out a multidimensional evaluation of these women up to six months. Methods/Design This project has two components: a multicenter, cross-sectional study to be implemented in 27 referral obstetric units in different geographical regions of Brazil, and a concurrent cohort study of multidimensional analysis. Over 12 months, investigators will perform prospective surveillance to identify all maternal complications. The population of the cross-sectional component will consist of all women surviving potentially life-threatening conditions (severe maternal complications or life-threatening conditions (the maternal near miss criteria and maternal deaths according to the new WHO definition and criteria. Data analysis will be performed in case subgroups according to the moment of occurrence and determining cause. Frequencies of near-miss and other severe maternal morbidity and the association between organ dysfunction and maternal death will be estimated. A proportion of cases identified in the cross
Cecatti, Jose G; Souza, João P; Parpinelli, Mary A; Haddad, Samira M; Camargo, Rodrigo S; Pacagnella, Rodolfo C; Silveira, Carla; Zanardi, Dulce T; Costa, Maria L; Pinto e Silva, João L; Passini, Renato; Surita, Fernanda G; Sousa, Maria H; Calderon, Iracema M P; Say, Lale; Pattinson, Robert C
It has been suggested that the study of women who survive life-threatening complications related to pregnancy (maternal near-miss cases) may represent a practical alternative to surveillance of maternal morbidity/mortality since the number of cases is higher and the woman herself is able to provide information on the difficulties she faced and the long-term repercussions of the event. These repercussions, which may include sexual dysfunction, postpartum depression and posttraumatic stress disorder, may persist for prolonged periods of time, affecting women's quality of life and resulting in adverse effects to them and their babies. The aims of the present study are to create a nationwide network of scientific cooperation to carry out surveillance and estimate the frequency of maternal near-miss cases, to perform a multicenter investigation into the quality of care for women with severe complications of pregnancy, and to carry out a multidimensional evaluation of these women up to six months. This project has two components: a multicenter, cross-sectional study to be implemented in 27 referral obstetric units in different geographical regions of Brazil, and a concurrent cohort study of multidimensional analysis. Over 12 months, investigators will perform prospective surveillance to identify all maternal complications. The population of the cross-sectional component will consist of all women surviving potentially life-threatening conditions (severe maternal complications) or life-threatening conditions (the maternal near miss criteria) and maternal deaths according to the new WHO definition and criteria. Data analysis will be performed in case subgroups according to the moment of occurrence and determining cause. Frequencies of near-miss and other severe maternal morbidity and the association between organ dysfunction and maternal death will be estimated. A proportion of cases identified in the cross-sectional study will comprise the cohort of women for the
Full Text Available In order to temporally recover the information network infrastructure in disaster areas from the Great East Japan Earthquake in 2011, various wireless network technologies such as satellite IP network, 3G, and Wi-Fi were effectively used. However, since those wireless networks are individually introduced and installed but not totally integrated, some of networks were congested due to the sudden network traffic generation and unbalanced traffic distribution, and eventually the total network could not effectively function. In this paper, we propose a disaster resilient network which integrates various wireless networks into a cognitive wireless network that users can use as an access network to the Internet at the serious disaster occurrence. We designed and developed the disaster resilient network based on software defined network (SDN technology to automatically select the best network link and route among the possible access networks to the Internet by periodically monitoring their network states and evaluate those using extended AHP method. In order to verify the usefulness of our proposed system, a prototype system is constructed and its performance is evaluated.
Full Text Available This paper presents an automated surveillance system that exploits the Fisher Kernel representation in the context of multiple-instance object retrieval task. The proposed algorithm has the main purpose of tracking a list of persons in several video sources, using only few training examples. In the first step, the Fisher Kernel representation describes a set of features as the derivative with respect to the log-likelihood of the generative probability distribution that models the feature distribution. Then, we learn the generative probability distribution over all features extracted from a reduced set of relevant frames. The proposed approach shows significant improvements and we demonstrate that Fisher kernels are well suited for this task. We demonstrate the generality of our approach in terms of features by conducting an extensive evaluation with a broad range of keypoints features. Also, we evaluate our method on two standard video surveillance datasets attaining superior results comparing to state-of-the-art object recognition algorithms.
Janiec, J; Evans, M R; Thomas, D R; Davies, G H; Lewis, H
Laboratory data are the cornerstone in surveillance of infectious disease. We investigated whether changes in reported incidence of Campylobacter and Salmonella infection might be explained by changes in stool sampling rates. Data were extracted from a national database on 585 843 patient stool samples tested by microbiology laboratories in Wales between 1998 and 2008. Salmonella incidence fell from 43 to 19 episodes/100 000 population but Campylobacter incidence after declining from 111/100 000 in 1998 to 84/100 000 in 2003 rose to 119/100 000 in 2008. The proportion of the population sampled rose from 2·0% in 1998 to 2·8% in 2008, mostly due to increases in samples from hospital patients and older adults. The proportion of positive samples declined for both Salmonella and Campylobacter from 3·1% to 1·1% and from 8·9% to 7·5%, respectively. The decline in Salmonella incidence is so substantial that it is not masked even by increased stool sampling, but the recent rise in Campylobacter incidence may be a surveillance artefact largely due to the increase in stool sampling in older people.
Josseran, Loïc; Caillère, Nadège; Brun-Ney, Dominique; Rottner, Jean; Filleul, Laurent; Brucker, Gilles; Astagneau, Pascal
The health impacts of heat waves are serious and have prompted the development of heat wave response plans. Even when they are efficient, these plans are developed to limit the health effects of heat waves. This study was designed to determine relevant indicators related to health effects of heat waves and to evaluate the ability of a syndromic surveillance system to monitor variations in the activity of emergency departments over time. The study uses data collected during the summer 2006 when a new heat wave occurred in France. Data recorded from 49 emergency departments since July 2004, were transmitted daily via the Internet to the French Institute for Public Health Surveillance. Items collected on patients included diagnosis (ICD10 codes), outcome, and age. Statistical t-tests were used to compare, for several health conditions, the daily averages of patients within different age groups and periods (whether 'on alert' or 'off alert'). A limited number of adverse health conditions occurred more frequently during hot period: dehydration, hyperthermia, malaise, hyponatremia, renal colic, and renal failure. Over all health conditions, the total number of patients per day remained equal between the 'on alert' and 'off alert' periods (4,557.7/day vs. 4,511.2/day), but the number of elderly patients increased significantly during the 'on alert' period relative to the 'off alert' period (476.7/day vs. 446.2/day p waves.
Effect of mobility models on infrastructure based wireless networks. ... In this paper, the effect of handoff procedure on the performance of random mobile nodes in wireless networks was investigated. Mobility of node is defined ... Article Metrics.
Henry N Njuguna
Full Text Available BACKGROUND: Worldwide, Shigella causes an estimated 160 million infections and >1 million deaths annually. However, limited incidence data are available from African urban slums. We investigated the epidemiology of shigellosis and drug susceptibility patterns within a densely populated urban settlement in Nairobi, Kenya through population-based surveillance. METHODS: Surveillance participants were interviewed in their homes every 2 weeks by community interviewers. Participants also had free access to a designated study clinic in the surveillance area where stool specimens were collected from patients with diarrhea (≥3 loose stools within 24 hours or dysentery (≥1 stool with visible blood during previous 24 hours. We adjusted crude incidence rates for participants meeting stool collection criteria at household visits who reported visiting another clinic. RESULTS: Shigella species were isolated from 262 (24% of 1,096 stool specimens [corrected]. The overall adjusted incidence rate was 408/100,000 person years of observation (PYO with highest rates among adults 34-49 years old (1,575/100,000 PYO. Isolates were: Shigella flexneri (64%, S. dysenteriae (11%, S. sonnei (9%, and S. boydii (5%. Over 90% of all Shigella isolates were resistant to trimethoprim-sulfamethoxazole and sulfisoxazole. Additional resistance included nalidixic acid (3%, ciprofloxacin (1% and ceftriaxone (1%. CONCLUSION: More than 1 of every 200 persons experience shigellosis each year in this Kenyan urban slum, yielding rates similar to those in some Asian countries. Provision of safe drinking water, improved sanitation, and hygiene in urban slums are needed to reduce disease burden, in addition to development of effective Shigella vaccines.
Holt, Martin; Lea, Toby; Mao, Limin; Zablotska, Iryna; Lee, Evelyn; de Wit, John B F; Prestage, Garrett
Background: In Australia, the preventative use of antiretroviral drugs [pre-exposure prophylaxis (PrEP) and treatment as prevention] is being embraced to protect individuals at high risk of HIV and reduce onward transmission. Methods: The adaptation of a behavioural surveillance system, the Gay Community Periodic Surveys, was reviewed to monitor the uptake and effect of new prevention strategies in Australia's primary HIV-affected population (gay and bisexual men, GBM). The national trends in key indicators during 2000-15 were reviewed and a new measure to take account of antiretroviral-based prevention was developed. Results: Between 2000 and 2015, there were significant increases (PBehavioural surveillance can be successfully adapted to follow the effect of antiretroviral-based prevention. It is anticipated that HIV testing and HIV treatment will continue to increase among Australian GBM, but to prevent new infections, intervention in the growing proportion of GBM who have condomless sex with casual partners is needed. For PrEP to have its desired effect, condom use needs to be sustained.
Pérez-Lago, L; Martínez Lirola, M; Herranz, M; Comas, I; Bouza, E; García-de-Viedma, D
Molecular epidemiology has transformed our knowledge of how tuberculosis (TB) is transmitted. Whole genome sequencing (WGS) has reached unprecedented levels of accuracy. However, it has increased technical requirements and costs, and analysis of data delays results. Our objective was to find a way to reconcile speed and ease of implementation with the high resolution of WGS. The targeted regional allele-specific oligonucleotide PCR (TRAP) assay presented here is based on allele-specific PCR targeting strain-specific single nucleotide polymorphisms, identified from WGS, and makes it possible to track actively transmitted Mycobacterium tuberculosis strains. A TRAP assay was optimized to track the most actively transmitted strains in a population in Almería, Southeast Spain, with high rates of TB. TRAP was transferred to the local laboratory where transmission was occurring. It performed well from cultured isolates and directly from sputa, enabling new secondary cases of infection from the actively transmitted strains to be detected. TRAP constitutes a fast, simple and low-cost tool that could modify surveillance of TB transmission. This pilot study could help to define a new model to survey TB transmission based on a decentralized multinodal network of local laboratories applying fast and low-cost TRAPs, which are developed by central reference centres, tailored to the specific demands of transmission at each local node.
Cornaglia, G; Hryniewicz, W; Jarlier, V; Kahlmeter, G; Mittermayer, H; Stratchounski, L; Baquero, F
The problem of antimicrobial resistance surveillance in Europe has been debated extensively in many excellent documents issued by national committees that often assume the value of national guidelines. However, a comprehensive document addressing the whole matter from a European perspective, as well as reviewing its present status and drafting future perspectives, has been lacking. The present recommendations have been produced by the ESCMID Study Group for Antimicrobial Resistance Surveillance (ESGARS) through a consensus process involving all members of the Study Group. The recommendations focus on the detection of bacterial resistance and its reporting to clinicians, public health officers and a wider-and ever-increasing-audience. The leading concept is that the basis for resistance monitoring is microbiological diagnostics. The prerequisites for resistance monitoring are findings of adequate quality and quantity, which have been recorded properly and evaluated correctly. Different types of surveillance studies should fulfil different requirements with regard to data collection and reporting, the expected use of data, and the prerequisites for networking such activities. To generate relevant indicators, bacterial resistance data should be reported using adequate denominators and stratification. Reporting of antimicrobial resistance data is necessary for selection of empirical therapy at the local level, for assessing the scale of the resistance problem at the local, national or international levels, for monitoring changes in resistance rates, and for detecting the emergence and spread of new resistances types. Any type of surveillance study should conclude, where appropriate, with a proposal for intervention based on the data obtained.
Pardee, Keith; Green, Alexander A.; Ferrante, Tom; Cameron, D. Ewen; DaleyKeyser, Ajay; Yin, Peng; Collins, James J.
Synthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides a new venue for synthetic biologists to operate, and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze-dried onto paper, enabling the inexpensive, sterile and abiotic distribution of synthetic biology-based technologies for the clinic, global health, industry, research and education. For field use, we create circuits with colorimetric outputs for detection by eye, and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors. PMID:25417167
Edilberto Alves Rocha Filho
Full Text Available Objective. To assess occurrence of severe maternal complications associated with ectopic pregnancy (EP. Method. A multicenter cross-sectional study was conducted, with prospective surveillance of potentially life-threatening conditions (PLTC, maternal near miss (MNM, and maternal death (MD. EP complications, patient sociodemographic/obstetric characteristics, and conditions of severity management were assessed, estimating prevalence ratios with respective 95% CI. Factors independently associated with greater severity were identified using multiple regression analysis. Results. Of the 9.555 severe maternal morbidity patients, 312 women (3.3% had complications after EP: 286 (91.7% PLTC, 25 (8.0% MNM, and 1 (0.3% MD. Severe maternal outcome ratio (SMOR was 0.3/1000 LB among EP cases and 10.8/1000 LB among other causes. Complicated EP patients faced a higher risk of blood transfusion, laparotomy, and lower risk of ICU admission and prolonged hospitalization than women developing complications resulting from other causes. Substandard care was the most common in more severe maternal morbidity and EP cases (22.7% MNM and MD versus 15% PLTC, although not significant. Conclusion. Increased maternal morbidity due to EP raised awareness about the condition and its impact on female reproductive life. No important risk factors for greater severity were identified. Care providers should develop specific guidelines and interventions to prevent severe maternal morbidity.
Souli S. Sameh
Full Text Available In this paper, we propose a robust environmental sound spectrogram classification approach. Its purpose is surveillance and security applications based on the reassignment method and log-Gabor filters. Besides, the reassignment method is applied to the spectrogram to improve the readability of the time-frequency representation, and to assure a better localization of the signal components. Our approach includes three methods. In the first two methods, the reassigned spectrograms are passed through appropriate log-Gabor filter banks and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criterion. The third method uses the same steps but applied only to three patches extracted from each reassigned spectrogram. The proposed approach is tested on a large database consists of 1000 sounds belonging to ten classes. The recognition is based on Multiclass Support Vector Machines.
Vong, Sirenda; Khieu, Virak; Glass, Olivier; Ly, Sowath; Duong, Veasna; Huy, Rekol; Ngan, Chantha; Wichmann, Ole; Letson, G. William; Margolis, Harold S.; Buchy, Philippe
Background Dengue vaccines are now in late-stage development, and evaluation and robust estimates of dengue disease burden are needed to facilitate further development and introduction. In Cambodia, the national dengue case-definition only allows reporting of children less than 16 years of age, and little is known about dengue burden in rural areas and among older persons. To estimate the true burden of dengue in the largest province of Cambodia, Kampong Cham, we conducted community-based active dengue fever surveillance among the 0-to-19–year age group in rural villages and urban areas during 2006–2008. Methods and Findings Active surveillance for febrile illness was conducted in 32 villages and 10 urban areas by mothers trained to use digital thermometers combined with weekly home visits to identify persons with fever. An investigation team visited families with febrile persons to obtain informed consent for participation in the follow-up study, which included collection of personal data and blood specimens. Dengue-related febrile illness was defined using molecular and serological testing of paired acute and convalescent blood samples. Over the three years of surveillance, 6,121 fever episodes were identified with 736 laboratory-confirmed dengue virus (DENV) infections for incidences of 13.4–57.8/1,000 person-seasons. Average incidence was highest among children less than 7 years of age (41.1/1,000 person-seasons) and lowest among the 16-to-19–year age group (11.3/1,000 person-seasons). The distribution of dengue was highly focal, with incidence rates in villages and urban areas ranging from 1.5–211.5/1,000 person-seasons (median 36.5). During a DENV-3 outbreak in 2007, rural areas were affected more than urban areas (incidence 71 vs. 17/1,000 person-seasons, pdengue fever in Cambodia found a higher disease incidence than reported to the national surveillance system, particularly in preschool children and that disease incidence was high in both rural
Vong, Sirenda; Khieu, Virak; Glass, Olivier; Ly, Sowath; Duong, Veasna; Huy, Rekol; Ngan, Chantha; Wichmann, Ole; Letson, G William; Margolis, Harold S; Buchy, Philippe
Dengue vaccines are now in late-stage development, and evaluation and robust estimates of dengue disease burden are needed to facilitate further development and introduction. In Cambodia, the national dengue case-definition only allows reporting of children less than 16 years of age, and little is known about dengue burden in rural areas and among older persons. To estimate the true burden of dengue in the largest province of Cambodia, Kampong Cham, we conducted community-based active dengue fever surveillance among the 0-to-19-year age group in rural villages and urban areas during 2006-2008. Active surveillance for febrile illness was conducted in 32 villages and 10 urban areas by mothers trained to use digital thermometers combined with weekly home visits to identify persons with fever. An investigation team visited families with febrile persons to obtain informed consent for participation in the follow-up study, which included collection of personal data and blood specimens. Dengue-related febrile illness was defined using molecular and serological testing of paired acute and convalescent blood samples. Over the three years of surveillance, 6,121 fever episodes were identified with 736 laboratory-confirmed dengue virus (DENV) infections for incidences of 13.4-57.8/1,000 person-seasons. Average incidence was highest among children less than 7 years of age (41.1/1,000 person-seasons) and lowest among the 16-to-19-year age group (11.3/1,000 person-seasons). The distribution of dengue was highly focal, with incidence rates in villages and urban areas ranging from 1.5-211.5/1,000 person-seasons (median 36.5). During a DENV-3 outbreak in 2007, rural areas were affected more than urban areas (incidence 71 vs. 17/1,000 person-seasons, pdengue fever in Cambodia found a higher disease incidence than reported to the national surveillance system, particularly in preschool children and that disease incidence was high in both rural and urban areas. It also confirmed the
Ponce-Espinosa, Hiram; Molina, Arturo
This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: · approximation; · inference; · clustering; · control; · class...
Boyle, Coleen A.; Bertrand, Jacquelyn; Yeargin-Allsopp, Marshalyn
This article describes the autism surveillance activities of the Center for Disease Control and Prevention. It considers why surveillance to track prevalence of autistic disorders is needed, how such surveillance is conducted, and the special challenges of autism surveillance. (DB)
Mohamed A. Ahmed
Full Text Available Nowadays, with large-scale offshore wind power farms (WPFs becoming a reality, more efforts are needed to maintain a reliable communication network for WPF monitoring. Deployment topologies, redundancy, and network availability are the main items to enhance the communication reliability between wind turbines (WTs and control centers. Traditional communication networks for monitoring and control (i.e., supervisory control and data acquisition (SCADA systems using switched gigabit Ethernet will not be sufficient for the huge amount of data passing through the network. In this paper, the optical power budget, optical path loss, reliability, and network cost of the proposed Ethernet Passive Optical Network (EPON-based communication network for small-size offshore WPFs have been evaluated for five different network architectures. The proposed network model consists of an optical network unit device (ONU deployed on the WT side for collecting data from different internal networks. All ONUs from different WTs are connected to a central optical line terminal (OLT, placed in the control center. There are no active electronic elements used between the ONUs and the OLT, which reduces the costs and complexity of maintenance and deployment. As fiber access networks without any protection are characterized by poor reliability, three different protection schemes have been configured, explained, and discussed. Considering the cost of network components, the total implementation expense of different architectures with, or without, protection have been calculated and compared. The proposed network model can significantly contribute to the communication network architecture for next generation WPFs.
Fayçal, Marguerite; Serhrouchni, Ahmed
P2P networks lay over existing IP networks and infrastructure. This chapter investigates the relation between both layers, details the motivations for network awareness in P2P systems, and elucidates the requirements P2P systems have to meet for efficient network awareness. Since new P2P systems are mostly based on DHTs, we also present and analyse DHT-based architectures. And after a brief presentation of different existing network-awareness solutions, the chapter goes on effective cooperation between P2P traffic and network providers' business agreements, and introduces emerging DHT-based P2P systems that are network aware through a semantic defined for resource sharing. These new systems ensure also a certain context-awareness. So, they are analyzed and compared before an open end on prospects of network awareness in P2P systems.
Networks, based upon informal relationships, have ensured that care was delivered to patients for many years. This informal organisation of care, based upon personal relationships, ensures that where the bureaucratic organisation fails the patient, health professionals' work together to network the resources the patient needs. Networks are not new. Formalising networks and recognising their potential to deliver seamless care is new. The NHS must ensure that networks are developed, allowing them freedom from bureaucracy to reach their potential. The Northern and Yorkshire Learning Alliance (NYLA) was established as part of the Northern and Yorkshire health community's efforts to radically improve care. The NYLA operates as a network with a small team of change experts working to develop change management and service improvement capacity across 10,000 square miles. As a network based organisation the team has learned many lessons, which may inform the development of clinical networks in England.
Bhattacharyya, Dhruba Kumar
With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents mach
Hanafusa, Shigeki; Muhadir, Andi; Santoso, Hari; Tanaka, Kohtaroh; Anwar, Muhammad; Sulistyo, Erwan Tri; Hachiya, Masahiko
The government of Indonesia and the Japan International Cooperation Agency launched a three-year project (2008–2011) to strengthen the surveillance of human avian influenza cases through a comprehensive surveillance system of local-priority communicable diseases in South Sulawesi Province. Based on findings from preliminary and baseline surveys, the project developed a technical protocol for surveillance and response activities in local settings, consistent with national guidelines. District surveillance officers (DSOs) and rapid-response-team members underwent training to improve surveillance and response skills. A network-based early warning and response system for weekly reports and a short message service (SMS) gateway for outbreak reports, both encompassing more than 20 probable outbreak diseases, were introduced to support existing paper-based systems. Two further strategies were implemented to optimize project outputs: a simulation exercise and a DSO-centered model. As a result, the timeliness of weekly reports improved from 33% in 2009 to 82% in 2011. In 2011, 65 outbreaks were reported using the SMS, with 64 subsequent paper-based reports. All suspected human avian influenza outbreaks up to September 2011 were reported in the stipulated format. A crosscutting approach using human avian influenza as the core disease for coordinating surveillance activities improved the overall surveillance system for communicable diseases. PMID:23532690
An adaptive control model and its algorithms based on simple diagonal recurrent neural networks are presented for the dynamic congestion control in broadband ATM networks.Two simple dynamic queuing models of real networks are used to test the performance of the suggested control scheme.
XU Liang; LIANG Xiong-jian; HUANG Xiu-qing
In this paper, according to the practical condition of local fixed telecom network, based on the method of the realistic total element long-run incremental cost, the practical methods of dividing the network elements, calculating the cost of network elements and services are given, to provide reference for the cost calculation in telecom industry.
Zhao Qigang; Li Qunzhan; He Zhengyou
By using netflow traffic collecting technology, some traffic data for analysis are collected from a next generation network (NGN) operator. To build a wavelet basis neural network (NN), the Sigmoid function is replaced with the wavelet in NN. Then the wavelet multiresolution analysis method is used to decompose the traffic signal, and the decomposed component sequences are employed to train the NN. By using the methods, an NGN traffic prediction model is built to predict one day's traffic. The experimental results show that the traffic prediction method of wavelet NN is more accurate than that without using wavelet in the NGN traffic forecasting.
Full Text Available The ability to detect and track object of interest from sequence of frames is a critical and vital problem of many vision systems developed as yet. This paper presents a smart surveillance system that tracks objects of interest in a sequence of frames in their own defined respective boundaries. The objects of interest are registered or saved within the system. We have proposed a unique tracking algorithm using combination of SURF feature matching, Kalman filtering and template matching approach. Moreover, an efficient technique is proposed that is used to refine registered object image, extract object of interest and remove extraneous image area from it. The system will track registered objects in their respective boundaries using real time video generated through two IP cameras positioned in front of each other.
Ana Maria Passos-Castilho
Full Text Available INTRODUCTION:Data on hepatitis E virus (HEV in Brazil are limited. We analyzed 15 years of HEV surveillance data in a major clinical laboratory in São Paulo, Brazil.METHODS:The seroprevalence of HEV of 2,271 patients subjected to anti-HEV tests from 1998 to 2013 were analyzed.RESULTS:HEV seroprevalence was 2.1%, and the anti-HEV IgM positivity rate was 4.9%. Six hepatitis E patients were identified.CONCLUSIONS:HEV seroprevalence and detection rates appear to have increased in recent years. Hepatitis E should be investigated further and included in the differential diagnosis of hepatitis in Brazil.
Full Text Available Abstract Background Little is known about HIV-1 subtype distribution in Morocco. Some data suggest an emergence of new HIV subtypes. We conducted phylogenetic analysis on a nationally representative sample of 60 HIV-1 viral specimens collected during 2004-2005 through the Morocco national HIV sentinel surveillance survey. Results While subtype B is still the most prevalent, 23.3% of samples represented non-B subtypes, the majority of which were classified as CRF02_AG (15%. Molecular clock analysis confirmed that the initial introduction of HIV-1B in Morocco probably came from Europe in the early 1980s. In contrast, the CRF02_AG strain appeared to be introduced from sub-Saharan Africa in two separate events in the 1990s. Conclusions Subtype CRF02_AG has been emerging in Morocco since the 1990s. More information about the factors introducing HIV subtype-specific transmission will inform the prevention strategy in the region.
Full Text Available Currently, schistosomiasis in China provides an excellent example of many of the challenges of moving from low transmission to the elimination of transmission for infectious diseases generally. In response to the surveillance dimension of these challenges, we here explore two strategic approaches to inform priorities for the development of improved methods addressed specifically to schistosomiasis in the low transmission environment. We utilize an individually-based model and the exposure data used earlier to explore surveillance strategies, one focused on exposure assessment and the second on our estimates of variability in individual susceptibility in the practical context of the current situation in China and the theoretical context of the behavior of transmission dynamics near the zero state. Our findings suggest that individual susceptibility is the major single determinant of infection intensity in both the low and medium risk environments. We conclude that there is considerable motivation to search for a biomarker of susceptibility to infection in humans, but that there would also be value in a method for monitoring surface waters for the free-swimming forms of the parasite in endemic or formerly endemic environments as an early warning of infection risk.
Fleming, Douglas M; Durnall, Hayley
We review experience in England of the swine flu pandemic between May 2009 and April 2010. The surveillance data from the Royal College of General Practitioners Weekly Returns Service and the linked virological data collected in the integrated program with the Health Protection Agency are used as a reference frame to consider issues emerging during the pandemic. Ten lessons are summarized. (1) Delay between illness onset in the first worldwide cases and virological diagnosis restricted opportunities for containment by regional prophylaxis. (2) Pandemic vaccines are unlikely to be available for effective prevention during the first wave of a pandemic. (3) Open, realistic and continuing communication with the public is important. (4) Surveillance programs should be continued through summer as well as winter. (5) Severity of illness should be incorporated in pandemic definition. (6) The reliability of diagnostic tests as used in routine clinical practice calls for further investigation. (7) Evidence from serological studies is not consistent with evidence based on health care requests made by sick persons and is thus of limited value in cost effectiveness studies. (8) Pregnancy is an important risk factor. (9) New strategies for administering vaccines need to be explored. (10) Acceptance by the public and by health professionals of influenza vaccination as the major plank on which the impact of influenza is controlled has still not been achieved.
Full Text Available To identify the features of Chinese genetic prion diseases.Suspected Creutzfeldt-Jakob disease (CJD cases that were reported under CJD surveillance were diagnosed and subtyped using the diagnostic criteria issued by the WHO. The general information concerning the patient, their clinical, MRI and EEG data, and the results of CSF 14-3-3 and PRNP sequencing were carefully collected from the database of the national CJD surveillance program and analyzed using the SPSS 11.5 statistical software program.Since 2006, 69 patients were diagnosed with genetic prion diseases and as having 15 different mutations. The median age of the 69 patients at disease onset was 53.5 years, varying from 19 to 80 years. The majority of patients displaying clinical symptoms were in the 50-59 years of age. FFI, T188K gCJD and E200K were the three most common subtypes. The disease appeared in the family histories of 43.48% of the patients. The clinical manifestations varied considerably among the various diseases. Patients who carried mutations in the N-terminus displayed a younger age of onset, were CSF 14-3-3 negative, had a family history of the condition, and experienced a longer duration of the condition. The clinical courses of T188K were significantly shorter than those of FFI and E200K gCJD, while the symptoms in the FFI group appeared at a younger age and for a longer duration. Moreover, the time intervals between the initial neurologist visit to the final diagnosis were similar among patients with FFI, T188K gCJD, E200K gCJD and other diseases.The features of Chinese genetic prion diseases are different from those seen in Europe and other Asian countries.
Full Text Available Background & objectives: Dengue is currently one of the most important arthropod-borne diseasesand may be caused by four different dengue virus serotypes (DENV-1 to DENV-4, transmittedmainly by Aedes aegypti (Diptera: Culicidae mosquitoes. With the lack of a dengue vaccine,vector control strategies constitute a crucial mode to prevent or reduce disease transmission. Inthis context, DENV detection in natural Ae. aegypti populations may serve as a potential additionaltool for early prediction systems of dengue outbreaks, leading to an intensification of vector controlmeasures, aimed at reducing disease transmission. In Brazil, this type of surveillance has beenperformed sporadically by a few groups and has not been incorporated as a routine activity incontrol programs. This study aimed at detecting DENV in natural Ae. aegypti from Recife,Pernambuco, to check the circulating serotypes and the occurrence of transovarial transmission inlocal mosquito populations.Methods: From January 2005 to June 2006, mosquitoes (adults and eggs were collected in houseswhere people with clinical suspicion of dengue infection lived at. RNA was extracted from pooledmosquitoes and RT-PCR was performed in these samples for detection of the four DENV serotypes.Results & conclusion: Out of 83 pools of adult mosquitoes collected in the field, nine were positivefor DENV: five for DENV-1, two for DENV-2 and two for DENV-3. From 139 pools of adultmosquitoes reared from collected eggs, there were 17 positive pools: three for DENV-1, 10 forDENV-2, and four for DENV-3. These results are discussed in the paper in regard to the localdengue epidemiological data. The conclusions clearly point to the informative power and sensitivityof DENV entomological surveillance and to the importance of including mosquito immature formsin this strategy.
Han, Ruisong; Yang, Wei; You, Kaiming
Safety production of coalmines is a task of top priority which plays an important role in guaranteeing, supporting and promoting the continuous development of the coal industry. Since traditional wireless sensor networks (WSNs) cannot fully meet the requirements of comprehensive environment monitoring of underground coalmines, wireless multimedia sensor networks (WMSNs), enabling the retrieval of multimedia information, are introduced to realize fine-grained and precise environment surveillance. In this paper, a framework for designing underground coalmine WMSNs based on Multi-Band Orthogonal Frequency-Division Multiplexing Ultra-wide Band (MB-OFDM-UWB) is presented. The selection of MB-OFDM-UWB wireless transmission solution is based on the characteristics of underground coalmines. Network structure and design challenges are analyzed first, which is the foundation for further discussion. Then, key supporting technologies and open research areas in different layers are surveyed, and we provide a detailed literature review of the state of the art strategies, algorithms and general solutions in these issues. Finally, other research issues like localization, information processing, and network management are discussed. PMID:27999258
Han, Ruisong; Yang, Wei; You, Kaiming
Safety production of coalmines is a task of top priority which plays an important role in guaranteeing, supporting and promoting the continuous development of the coal industry. Since traditional wireless sensor networks (WSNs) cannot fully meet the requirements of comprehensive environment monitoring of underground coalmines, wireless multimedia sensor networks (WMSNs), enabling the retrieval of multimedia information, are introduced to realize fine-grained and precise environment surveillance. In this paper, a framework for designing underground coalmine WMSNs based on Multi-Band Orthogonal Frequency-Division Multiplexing Ultra-wide Band (MB-OFDM-UWB) is presented. The selection of MB-OFDM-UWB wireless transmission solution is based on the characteristics of underground coalmines. Network structure and design challenges are analyzed first, which is the foundation for further discussion. Then, key supporting technologies and open research areas in different layers are surveyed, and we provide a detailed literature review of the state of the art strategies, algorithms and general solutions in these issues. Finally, other research issues like localization, information processing, and network management are discussed.
Full Text Available We introduce and develop a new network-based and binless methodology to perform frequency analyses and produce histograms. In contrast with traditional frequency analysis techniques that use fixed intervals to bin values, we place a range ±ζ around each individual value in a data set and count the number of values within that range, which allows us to compare every single value of a data set with one another. In essence, the methodology is identical to the construction of a network, where two values are connected if they lie within a given a range (±ζ. The value with the highest degree (i.e., most connections is therefore assimilated to the mode of the distribution. To select an optimal range, we look at the stability of the proportion of nodes in the largest cluster. The methodology is validated by sampling 12 typical distributions, and it is applied to a number of real-world data sets with both spatial and temporal components. The methodology can be applied to any data set and provides a robust means to uncover meaningful patterns and trends. A free python script and a tutorial are also made available to facilitate the application of the method.
Zhang, Zhengbing; Deng, Huiping; Xia, Zhenhua
Video systems have been widely used in many fields such as conferences, public security, military affairs and medical treatment. With the rapid development of FPGA, SOPC has been paid great attentions in the area of image and video processing in recent years. A network video transmission system based on SOPC is proposed in this paper for the purpose of video acquisition, video encoding and network transmission. The hardware platform utilized to design the system is an SOPC board of model Altera's DE2, which includes an FPGA chip of model EP2C35F672C6, an Ethernet controller and a video I/O interface. An IP core, known as Nios II embedded processor, is used as the CPU of the system. In addition, a hardware module for format conversion of video data, and another module to realize Motion-JPEG have been designed with Verilog HDL. These two modules are attached to the Nios II processor as peripheral equipments through the Avalon bus. Simulation results show that these two modules work as expected. Uclinux including TCP/IP protocol as well as the driver of Ethernet controller is chosen as the embedded operating system and an application program scheme is proposed.
National Aeronautics and Space Administration — The Innovation Laboratory, Inc. builds a control system which controls the topology of an air traffic flow network and the network flow properties which enables Air...
洪炳镕; 金飞虎; 郭琦
Hopfield neural network is a single layer feedforward neural network. Hopfield network requires some control parameters to be carefully selected, else the network is apt to converge to local minimum. An ant system is a nature inspired meta heuristic algorithm. It has been applied to several combinatorial optimization problems such as Traveling Salesman Problem, Scheduling Problems, etc. This paper will show an ant system may be used in tuning the network control parameters by a group of cooperated ants. The major advantage of this network is to adjust the network parameters automatically, avoiding a blind search for the set of control parameters.This network was tested on two TSP problems, 5 cities and 10 cities. The results have shown an obvious improvement.
Erler, Janine Terra; Linding, Rune
The structure and dynamics of protein signalling networks governs cell decision processes and the formation of tissue boundaries. Complex diseases such as cancer and diabetes are diseases of such networks. Therefore approaches that can give insight into how these networks change during disease pr...... associated technologies. We then focus on the multivariate nature of cellular networks and how this has implications for biomarker and drug discovery using cancer metastasis as an example....
The mobile agent technology can be employed effectively for the decentralized management of complex networks. We show how the integration of mobile agent with legacy management protocol, such as simple network management protocol (SNMP), leads to decentralized management architecture. HostWatcher is a framework that allows mobile agents to roam network, collect and process data, and perform certain adaptive actions. A prototype system is built and a quantitative analysis underlines the benefits in respect to reducing network load.
Full Text Available This paper proposes Web Service based network management. The Web Service based network management system is analyzed. It consists of network management layer, collaborative management implementation layer, and management function layer mainly. The complex management network tasks can be accomplished respectively by more than one Web Service distributed on Internet and the Web Services interchange information based on XML message. The SNMP/XML gateway and the translation between GDMO/ASN.1 and XML/Schema are designed and implemented to implement the integration between the legacy network management systems and the network management developed by Web Service technologies. The service management in Web Service based network management is discussed. Service composition/re-composition in Web Service based network management is analyzed based on the QoS requirements negotiation between the network management requirements and the statement of Web Service and network, OWL-S being used to described the network management requirements to discover the suitable Web Service, BPEL being used to describe the Web Service composition.
van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.
Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more
Zwaag, van der B.J.; Slump, C.H.; Spaanenburg, L.
Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more
Robin, Xavier; Creixell, Pau; Radetskaya, Oxana;
Network medicine aims at unraveling cell signaling networks to propose personalized treatments for patients suffering from complex diseases. In this short review, we show the relevance of network medicine to cancer treatment by outlining the potential convergence points of the most recent technol...
Full Text Available Problem statement: Wireless sensor networks have been used in many applications, such as home automation, military surveillances and entity tracking systems. The sensor nodes have low computational capabilities and are highly resource constrained. Routing protocols of wireless sensor networks are prone to various routing attacks, such as black hole, rushing, wormhole, Sybil and denial of service attacks. Approach: The objective of this study was to examine the effects of wormhole in conjunction with Sybil attack on a location based-Geographic Multicast Routing (GMR protocol. Results: The NS-2 based simulation was used in analyzing the wormhole in conjunction with Sybil attack on GMR. Conclusion: It is found that, the Sybil attack degrades the network performance by 24% and the wormhole attack by 20%.
Full Text Available Many complex systems can be described as networks to comprehend both the structure and the function. Community structure is one of the most important properties of complex networks. Detecting overlapping communities in networks have been more attention in recent years, but the most of approaches to this problem have been applied to the undirected networks. This paper presents a novel approach based on link partition to detect overlapping communities structure in directed networks. In contrast to previous researches focused on grouping nodes, our algorithm defines communities as groups of directed links rather than nodes with the purpose of nodes naturally belong to more than one community. This approach can identify a suitable number of overlapping communities without any prior knowledge about the community in directed networks. We evaluate our algorithm on a simple artificial network and several real-networks. Experimental results demonstrate that the algorithm proposed is efficient for detecting overlapping communities in directed networks.
A new industry Internet system structure, "M&C Network Node" is presented and designed to construct an M&C network based on the Internet. The "M&C Network Node" has powerful communication and control abilities referring to the wide and complicate M&C network. By using the largely invisible and highly reliable field bus LonWorks, all the local M&C stations installed in the industrial field are integrated into one "M&C Network Node". For connecting the heterogeneous PLC instruments to the LonWorks network a serial adapter (RS232 standard) is designed. The adapter can be seen as the internal communication interface of the "M&C Network Node".The Ethernet interface of the "M&C Network Node" is realized by an Ethernet adapter, which is also designed. The hardware components and the two kinds communication interfaces of this"M&C Network Node" are described in detail in this paper.
Bloom, Niels; Theune, Mariet; de Jong, Franciska M.G.
Associative networks are a connectionist language model with the ability to categorize large sets of documents. In this research we combine monolingual associative networks based on Wikipedia to create a larger, multilingual associative network, using the cross-lingual connections between Wikipedia
Bloom, Niels; Theune, Mariet; de Jong, Franciska M.G.
Associative networks are a connectionist language model with the ability to categorize large sets of documents. In this research we combine monolingual associative networks based on Wikipedia to create a larger, multilingual associative network, using the cross-lingual connections between Wikipedia
Bloom, Niels; Theune, Mariët; Jong, de Franciska
Associative networks are a connectionist language model with the ability to categorize large sets of documents. In this research we combine monolingual associative networks based on Wikipedia to create a larger, multilingual associative network, using the cross-lingual connections between Wikipedia
For the redundant manipulators, neural network is used to tackle the velocity inverse kinematics of robot manipulators. The neural networks utilized are multi-layered perceptions with a back-propagation training algorithm. The weight table is used to save the weights solving the inverse kinematics based on the different optimization performance criteria. Simulations verify the effectiveness of using neural network.
A direct feedback control system based on fuzzy-recurrent neural network is proposed, and a method of training weights of fuzzy-recurrent neural network was designed by applying modified contract mapping genetic algorithm. Computer simul ation results indicate that fuzzy-recurrent neural network controller has perfect dynamic and static performances .
Shen Liqun [School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001 (China)], E-mail: email@example.com; Wang Mao [Space Control and Inertia Technology Research Center, Harbin Institute of Technology, Harbin 150001 (China); Liu Wanyu [School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001 (China); Sun Guanghui [Space Control and Inertia Technology Research Center, Harbin Institute of Technology, Harbin 150001 (China)
In this Letter, a new chaos control scheme based on chaos prediction is proposed. To perform chaos prediction, a new neural network architecture for complex nonlinear approximation is proposed. And the difficulty in building and training the neural network is also reduced. Simulation results of Logistic map and Lorenz system show the effectiveness of the proposed chaos control scheme and the proposed neural network.
Study Objective:Throughout the world,political developments have brought new demands to communities to prevent and intervene in the incidence of infectious and noninfectious conditions.Historically,these developments have required new and more effective public health surveillance ac-tivities.This report describes public health surveillance practice in the People's Republic of China,making comparisons with selected aspects of surveillance in the United States with respect to collec-tion,analysis,dissemination,and use of data.Main results:In both the People's Republc of China and the United States.political change has affected health,and multiple surveillance system are used in public health practice.Surveillance of acute infectious diseases based on the reporting of legally notifiable diseases and the use of vital records for surveillance have the longest established history in both countries.In both countries,da-ta from the surveillance systems have been used to affect public health policy.Conclusions:in comparing surveillance practices in these countries,we find similarities in con-ditions reported and in the dissemination of the data.At the same time,legal,social,cultural,and economic differences between the nations have affected the practice of surveillance in analysis and evaluation.We make explicit recommendations for improement and evaluation of systems in both countries,including sentinel surveillance system and data quality measures in China and computer networking and data analysis in the United States.
Chiueh, T D; Tsai, H K
A multivalued neural associative memory model based on a recurrent network structure is proposed. This model adopts the same principle proposed in the authors' previous work, the exponential correlation associative memories (ECAM). The model also has a very high storage capacity and strong error-correction capability. The major components of the new model include a weighted average process and some similarity-measure computation. As in ECAM, in order to enhance the differences among the weights and make the largest weights more overwhelming, the new model incorporates a nonlinear function in the calculation of weights. Several possible similarity measures suitable for this model are suggested. Simulation results of the performance of the new model with different measures show that, loaded with 500 64-component patterns, the model can sustain noise with power about one fifth to three fifths of the average signal power.
In order to overcome the effect of the assumption between emissivity and wavelength on the measurement of true temperature and spectral emissivity for most engineering materials, a neural network based method is proposed for data processing while a blackbody furnace and three optical filters with known spectral transmittance curves were used to make up a true target. The experimental results show that the calculated temperatures are in good agreement with the temperature of the blackbody furnace, and the calculated spectral emissivity curves are in good agreement with the spectral transmittance curves of the filters. The method proposed has been proved to be an effective method for solving the problem of true temperature and emissivity measurement, and it can overcome the effect of the assumption between emissivity and wavelength on the measurement of true temperature and spectral emissivity for most engineering materials.
Full Text Available We investigate a sequence of dynamic criminal networks on a time series based on the dynamic network analysis (DNA. According to the change of networks’ structure, networks’ variation trend is analyzed to forecast its future structure. Finally, an optimal arresting time and priority list are designed based on our analysis. Better results can be expected than that based on social network analysis (SNA.
Alba, Anna; Morrison, Robert E; Cheeran, Ann; Rovira, Albert; Alvarez, Julio; Perez, Andres M
Porcine reproductive and respiratory syndrome virus (PRRSv) infection causes a devastating economic impact to the swine industry. Active surveillance is routinely conducted in many swine herds to demonstrate freedom from PRRSv infection. The design of efficient active surveillance sampling schemes is challenging because optimum surveillance strategies may differ depending on infection status, herd structure, management, or resources for conducting sampling. Here, we present an open web-based application, named 'OptisampleTM', designed to optimize herd sampling strategies to substantiate freedom of infection considering also costs of testing. In addition to herd size, expected prevalence, test sensitivity, and desired level of confidence, the model takes into account the presumed risk of pathogen introduction between samples, the structure of the herd, and the process to select the samples over time. We illustrate the functionality and capacity of 'OptisampleTM' through its application to active surveillance of PRRSv in hypothetical swine herds under disparate epidemiological situations. Diverse sampling schemes were simulated and compared for each herd to identify effective strategies at low costs. The model results show that to demonstrate freedom from disease, it is important to consider both the epidemiological situation of the herd and the sample selected. The approach illustrated here for PRRSv may be easily extended to other animal disease surveillance systems using the web-based application available at http://stemma.ahc.umn.edu/optisample.
SHANG Rui-qiang; ZHAO Jian-li; SUN Qiu-xia; WANG Guang-xing
A hierarchical sensor network is proposed which places the sensing and routing capacity at different layer nodes.It thus simplifies the hardware design and reduces cost. Adopting Voronoi diagram in the partition of backbone network,a mathematical model of data aggregation based on hierarchical architecture is given. Simulation shows that the number of transmission data packages is sharply cut down in the network, thus reducing the needs in the bandwidth and energy resources and is thus well adapted to sensor networks.
Huang, Ying; Wang, Pei
Biological networks, such as genetic regulatory networks and protein interaction networks, provide important information for studying gene/protein activities. In this paper, we propose a new method, NetBoosting, for incorporating a priori biological network information in analyzing high dimensional genomics data. Specially, we are interested in constructing prediction models for disease phenotypes of interest based on genomics data, and at the same time identifying disease susceptible genes. ...
Fernandes, Roberta Zanelli Sartori; Vilela, Maria Filomena de Gouveia
Mother and infant mortality has been the scope of analysis throughout the history of public health in Brazil and various strategies to tackle the issue have been proposed to date. The Ministry of Health has been working on this and the Rede Cegonha strategy is the most recent policy in this context. Given the principle of comprehensive health care and the structure of the Unified Health System in c