A Service Approach for Architecting Application Independent Wireless Sensor Networks

The current sensor networks are assumed to be designed for specific applications, having data communication protocols strongly coupled to applications. The future sensor networks are envisioned as comprising heterogeneous devices assisting to a large range of applications. To achieve this goal, a new architecture approach is needed, having application specific features separated from the data communication protocol, while influencing its behavior. We propose a Web Services approach for the design of sensor network, in which sensor nodes are service providers and applications are clients of such services. Our main goal is to enable a flexible architecture in which sensor networks data can be accessed by users spread all over the world.     

大数据时代下的生态系统观测发展趋势与挑战

随着观测技术的发展, 生态学研究尺度不断扩大。生态系统观测从小规模合作、短时间个人观测向大规模、长时间、跨学科、多因子联合观测转变。传感器技术的革新带来了生态观测在时空尺度的扩展与精确度上的提升, 致使生态学观测数据的容量、产生速度与数据种类飞速增长。对生态系统数据获取、存储与管理的传统方法无疑不再能满足现代生态学研究的要求。因此, 我们建议以大数据时代的数据存储、管理与处理技术为基础, 整合生态物联观测网络(Internet of Ecology)、公民科学观测网络以及基于标准化数据管理的研究者网络互联, 建立整合生态系统观测平台来应对这一困境。为生态学研究者打造一站式生态观测服务, 是大数据时代下生态系统观测的大势所趋。     

Beyond the benchtop and the benthos: Dataset management planning and design for time series of ocean carbonate chemistry associated with Durafet®-based pH sensors

To better understand the impact of ocean acidification on marine ecosystems, an important ongoing research priority for marine scientists is to characterize present-day pH variability. Following recent technological advances, autonomous pH sensor deployments in shallow coastal marine environments have revealed that pH dynamics in coastal oceans are more variable in space and time than the discrete, open-ocean measurements that are used for ocean acidification projections. Data from these types of deployments will benefit the research community by facilitating the improved design of ocean acidification studies as well as the identification or evaluation of natural and human-influenced pH variability. Importantly, the collection of ecologically relevant pH data and a cohesive, user-friendly integration of results across sites and regions requires (1) effective sensor operation to ensure high-quality pH data collection and (2) efficient data management for accessibility and broad reuse by the marine science community. Here, we review the best practices for deployment, calibration, and data processing and quality control, using our experience with Durafet®-based pH sensors as a model. Next, we describe information management practices for streamlining preservation and distribution of data and for cataloging different types of pH sensor data, developed in collaboration with two U.S. Long Term Ecological Research (LTER) sites. Finally, we assess sensor performance and data recovery from 73 SeaFET deployments in the Santa Barbara Channel using our quality control guidelines and data management tools, and offer recommendations for improved data yields. Our experience provides a template for other groups contemplating using SeaFET technology as well as general steps that may be helpful for the design of data management for other complex sensors.     

我国医疗服务数据中心发展现状

医疗服务数据中心能够通过对医疗数据的采集、存储、维护和分析,在评价和提升患者安全、助力医疗质量管理、为患者就医提供导向、推动生物银行的建设发展等方面发挥着非常重要的作用。尽管相比发达国家,我国的国家医疗服务数据中心的建设起步较晚,但已在指导医疗服务和服务医疗管理方面取得了一定的成绩。     

Implementation of load management application system using smart grid privacy policy in energy management service environment

As the Smart grid is intelligent power grid, combining information Technology to the existing power grid. Electricity suppliers and consumers exchange real-time information to two-way and is a next-generation power grid to optimize energy efficiency. This paper suggests the implementation of load management application system using smart grid privacy policy in energy management service in energy management service environment. The structure of the privacy policy-based protection system using load management system in the smart grid environment is the structure that serves data in the load management system to the web through the application service network. For this, the privacy policy-based protection system suggested and developed the smart grid privacy policy-based protection system which controls service access by protecting items related to the personal information of the user and setting the privacy protection level for each item.     

Cyberinfrastructure for sourcing and processing ecological data

Cyberinfrastructure is a product of the information age that provides a framework for informing adaptive management of ecological entities under the impact of regional and global change. It supports proximity monitoring, user-friendly data management, knowledge discovery by data synthesis, and decision making by forecasting.A workflow is proposed that suits the iterative nature of adaptive management. It takes advantage of novel sensor, genomics, and communication technology for ecological monitoring, of ontologies, semantic webs and blockchain for data management, of hybrid, machine and deep learning concepts for data synthesis and forecasting. Forecasting at different time horizons is guiding decision making for adjusting management and continuing monitoring.This review aims to make researchers, decision makers and stakeholders aware of currently existing technology to make better use of ecological data and models for timely and evidence-based decisions.     

Staying afloat in the sensor data deluge

Developments in sensor design, electronics, computer technology and networking have converged to provide new ways of collecting environmental data at rates hitherto impossible to achieve. To translate this 'data deluge' into scientific knowledge requires comparable advances in our ability to integrate, process and analyze massive data sets. We review the experience of one large project in ingesting and analyzing sensor data from global lakes and provide a synopsis of innovative approaches being used to confront the information management and analytical challenges posed by massive volumes of data.     

基于Android系统的医院设备共享服务管理系统

为了提高设备利用率,大多医院将部分设备集中放置于病区服务中心,供全院科室共享使用,但是设备的借用、归还登记依然采用手工模式,这种模式工作效率低下且数据统计难度大。为了解决该问题,本文设计开发了一套基于Android系统的医院设备共享服务管理系统。该系统利用二维码作为设备唯一识别标识,利用Android移动终端软件扫描设备二维码获取该设备基础信息,并通过Web Service接口从数据服务器中获取设备详细信息后进行共享服务管理操作。该软件系统采用Java+MVC框架开发,利用SQL Server 2008实现设备信息存储、共享。通过对徐州医科大学附属医院病区服务中心200余台设备的日常共享服务管理的实际应用与测试,该系统能很好的优化医院设备共享服务管理流程,提高了设备管理人员工作效率。     

Energy and QoS Aware Routing in Wireless Sensor Networks

Many new routing protocols have been proposed for wireless sensor networks in recent years. Almost all of the routing protocols considered energy efficiency as the ultimate objective since energy is a very scarce resource for sensor nodes. However, the introduction imaging sensors has posed additional challenges. Transmission of imaging data requires both energy and QoS aware routing in order to ensure efficient usage of the sensors and effective access to the gathered measurements. In this paper, we propose an energy-aware QoS routing protocol for sensor networks which can also run efficiently with best-effort traffic. The protocol finds a least-cost, delay-constrained path for real-time data in terms of link cost that captures nodes energy reserve, transmission energy, error rate and other communication parameters. Moreover, the throughput for non-real-time data is maximized by adjusting the service rate for both real-time and non-real-time data at the sensor nodes. Such adjustment of service rate is done by using two different mechanisms. Simulation results have demonstrated the effectiveness of our approach for different metrics with respect to the baseline approach where same link cost function is used without any service differentiation mechanism.Kemal Akkaya received his B.S. degree in Computer Science from Bilkent University, Ankara, Turkey in 1997 and MS degree in Computer Science from Ortadogu Technical University (ODTU), Ankara, Turkey in 1999. He worked as a software developer at an automation project of Siemens and World Bank in Ankara, Turkey in 2000. He is currently a Ph.D. candidate at University of Maryland, Baltimore County (UMBC), Baltimore, MD. His research interests include energy aware routing, security and quality of service issues in ad hoc wireless networks.Mohamed F. Younis received B.S. degree in computer science and M.S. in engineering mathematics from Alexandria University in Egypt in 1987 and 1992, respectively. In 1996, he received his Ph.D. in computer science from New Jersey Institute of Technology. He is currently an assistant professor in the department of computer science and electrical engineering at the university of Maryland Baltimore County (UMBC). Before joining UMBC, he was with the Advanced Systems Technology Group, an Aerospace Electronic Systems R&D organization of Honeywell International Inc. While at Honeywell he led multiple projects for building integrated fault tolerant avionics, in which a novel architecture and an operating system were developed. This new technology has been incorporated by Honeywell in multiple products and has received worldwide recognition by both the research and the engineering communities. He also participated in the development the Redundancy Management System, which is a key component of the Vehicle and Mission Computer for NASAs X-33 space launch vehicle. Dr. Younis technical interest includes network architectures and protocols, embedded systems, fault tolerant computing and distributed real-time systems. Dr. Younis has four granted and three pending patents. He served on multiple technical committees and published over 40 technical papers in refereed conferences and journals.     

江苏农业种质资源平台运行管理信息系统建设

为促进农业种质资源开放共享,江苏省于2005年启动农业种质资源保护与利用平台建设,经过十多年的努力,初步建成了“四位一体”“库圃结合”的农业种质资源保护与利用体系,涵盖农作物、林木、水产和家养动物4大类共计30个省级种质库(圃),有力地支撑了江苏现代农业品种创新与产业发展.由于平台跨学科、跨行业建设,种质库(圃)遍布全...     

Wildlife tracking data management: a new vision

To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioural data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals'' environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.     

An autonomic routing framework for sensor networks

Current routing services for sensor networks are often designed for specific applications and network conditions, thus have difficulty in adapting to application and network dynamics. This paper proposes an autonomic framework to promote the adaptivity of routing services in sensor networks. The key idea of this framework is to maintain some feature functions that are decoupled from originally-integrated routing services. This separation enables significant service changes to be done by only tuning these functions. Measures including parameterization are taken to save the energy for changing these functions. Further, this framework includes a monitoring module to support a policy-based collaborative adaptation. This paper shows an example autonomic routing service conforming to this framework. Some of this work was done while the author was at ISI     

On the Potential of Surfers to Monitor Environmental Indicators in the Coastal Zone

The social and economic benefits of the coastal zone make it one of the most treasured environments on our planet. Yet it is vulnerable to increasing anthropogenic pressure and climate change. Coastal management aims to mitigate these pressures while augmenting the socio-economic benefits the coastal region has to offer. However, coastal management is challenged by inadequate sampling of key environmental indicators, partly due to issues relating to cost of data collection. Here, we investigate the use of recreational surfers as platforms to improve sampling coverage of environmental indicators in the coastal zone. We equipped a recreational surfer, based in the south west United Kingdom (UK), with a temperature sensor and Global Positioning System (GPS) device that they used when surfing for a period of one year (85 surfing sessions). The temperature sensor was used to derive estimates of sea-surface temperature (SST), an important environmental indicator, and the GPS device used to provide sample location and to extract information on surfer performance. SST data acquired by the surfer were compared with data from an oceanographic station in the south west UK and with satellite observations. Our results demonstrate: (i) high-quality SST data can be acquired by surfers using low cost sensors; and (ii) GPS data can provide information on surfing performance that may help motivate data collection by surfers. Using recent estimates of the UK surfing population, and frequency of surfer participation, we speculate around 40 million measurements on environmental indicators per year could be acquired at the UK coastline by surfers. This quantity of data is likely to enhance coastal monitoring and aid UK coastal management. Considering surfing is a world-wide sport, our results have global implications and the approach could be expanded to other popular marine recreational activities for coastal monitoring of environmental indicators.     

Information management at the North Temperate Lakes Long-term Ecological Research site — Successful support of research in a large,diverse, and long running project

Information management has been an integral part of the research process at the North Temperate Lakes Long-term Ecological Research (NTL LTER) program for over 30 years. A combination of factors has made the information management system (IMS) at NTL very successful. Significant resources have been invested in the IMS from the beginning, the Information Manager has been part of the leadership team at NTL and later in various roles at the LTER network level; the NTL IMS was a very early adopter of database systems, standardized metadata, and a data delivery system based on those metadata. This approach has made data easily accessible to NTL researchers and the broader scientific community. Data management workflows have become increasingly more automated with adoption of modern technologies as they became available, making the system efficient enough to handle core data as well as all one-time research data generated within NTL and several related projects. More than three decades of core data from eleven lakes are reused extensively as critical background information and as the limnological go-to site for many synthesis projects within and beyond LTER.The NTL IMS continues to implement new technologies for improving data management efficiency, discovery, access, integration, and synthesis. Accordingly, the functionality of the original online data access system programmed in Java and JavaServer Pages (JSP) was ported to the modern content management system, Drupal and integrated into LTER's Drupal Ecological Information Management System (DEIMS). NTL has invested in sensor technology for studying lake conditions over the long term, which necessitated a sophisticated management system tailored to high frequency data streams. Several technologies have been used at different times for automation of management, quality control and archiving of these high volume data. Near real time lake conditions can be accessed on the NTL website and smart phone Apps.Easy access to long-term and sensor data in the NTL IMS has led NTL researchers to develop new analytical methods and the publication of several R statistical packages. Recent graduate students are now employed as data scientists helping define a new career path inspired by the availability of data.The NTL project has amassed one of the world's most comprehensive long-term datasets on lakes and their surrounding landscapes. The NTL IMS facilitates the use of these data by multiple groups for research, education, and communication of science to the public.     

Distinct ecosystem types respond differentially to grazing exclosure

Here, we evaluate the ecosystem functioning and the ecosystems services supply of different vegetation types (grasslands, shrublands and woodlands) under contrasting management regimes by comparing a protected area with the surrounding landscape, which has been subjected to human disturbance in the Eastern Hills of Uruguay. We propose, based on functional attributes and vegetation physiognomy, a State and Transition Model for the dynamics of the grassland–woodland mosaic. We used remote sensing techniques to: (i) develop a land‐cover map of the study area based on supervised Landsat imagery classification, and (ii) compare attributes of the ecosystem functioning (productivity and seasonality) and service supply derived from the Normalized Difference Vegetation Index (NDVI) images provided by the moderate resolution imaging spectroradiometer (MODIS) sensor. The land‐cover map showed that grasslands and shrublands were the most extensive land covers in the study area. These vegetation types presented higher productivity, seasonality and ecosystem service supply, outside the protected area than inside it. On the other hand, woodlands showed higher productivity, ecosystem service supply and lower seasonality inside the protected area than outside of it. Two axes represented the grassland–woodland mosaic dynamic: (i) the mean annual and (ii) the intra‐annual coefficient of variation of the NDVI. Our results highlight that conservation of grasslands, shrublands and woodlands require different management strategies based on particular disturbance regimes like moderate grazing and controlled burns. Moderate disturbances may help to preserve ecosystem services provisioning in grasslands and shrublands. On the contrary, woodland conservation requires a more rigorous regime of protection against disturbances.     

Mobile healthcare application with EMR interoperability for diabetes patients

With digitalization of medical information and rapid distribution of smart devices, currently, healthcare service is actively planned and developed based on smart devices. By 2015, 500 million smartphone users are expected to use a mobile health application, especially for exercise, diet, and chronic disease management. Unlike other chronic diseases, diabetes can be managed by the patient. Therefore smart mobile device can be a universal tool for self-diabetes management because of its high penetration and functions. A mobile healthcare application for Android OS was developed to provide self-diabetes management. The application consists of Diabetes management, Weight management, Cardio-cerebrovascular risk evaluation, Stress and depression evaluation and Exercise management. The application synchronizes data with hospital’s EMR database to provide accurate data with minimized process of data input. This paper introduces detailed structure and functionalities of the application with EMR data synchronization aspect.     

Modelling home care organisations from an operations management perspective

Home Care (HC) service consists of providing care to patients in their homes. During the last decade, the HC service industry experienced significant growth in many European countries. This growth stems from several factors, such as governmental pressure to reduce healthcare costs, demographic changes related to population ageing, social changes, an increase in the number of patients that suffer from chronic illnesses, and the development of new home-based services and technologies. This study proposes a framework that will enable HC service providers to better understand HC operations and their management. The study identifies the main processes and decisions that relate to the field of HC operations management. Hence, an IDEF0 (Integrated Definition for Function Modelling) activity-based model describes the most relevant clinical, logistical and organisational processes associated with HC operations. A hierarchical framework for operations management decisions is also proposed. This analysis is derived from data that was collected by nine HC service providers, which are located in France and Italy, and focuses on the manner in which operations are run, as well as associated constraints, inputs and outputs. The most challenging research areas in the field of HC operations management are also discussed.     

Hierarchical semantic information modeling and ontology for bird ecology

Birds have become an increasing concern for ecological preservation and safety. This paper proposes hierarchical architecture of semantic sensing information for bird acoustic data representation in bird ecological environment. This architecture provides various real-time sensing data such as bird calls using acoustic sensors in sensor networks. In this paper, we implement an ontology structure of hierarchical semantic information representation in bird’s ecological environment. Information of this architecture supports to recognize bird calls, identify birds, classify species, and to track a bird behavior in bird ecological environment. All of this would indicate that we suggest relationship between phenomenon data to service/semantic information in bird ecology.     

Using Trust to Secure Geographic and Energy Aware Routing against Multiple Attacks

To address the vulnerability of geographic routing to multiple security threats such as false routing information, selective forwarding and the Sybil attack in wireless sensor networks, this paper proposes a trust-based defending model against above-mentioned multiple attacks. Considering the characteristics of resource-constrained sensor nodes, trust values of neighboring nodes on the routing path can be calculated through the Dirichlet distribution function, which is based on data packets'' acknowledgements in a certain period instead of energy-consuming monitoring. Trust is combined with the cost of geographic and energy aware routing for selecting the next hop of routing. At the same time, the initial trust is dynamically determined, service requests are restricted for malicious nodes in accordance with trust values, and the impact of node mobility is weakened by the trust evolution. The simulation results and analysis show that the proposed model under multiple attacks has advantages in packet delivery ratio and network lifetime over the existing models.     

M@CBETH: a microarray classification benchmarking tool

Microarray classification can be useful to support clinical management decisions for individual patients in, for example, oncology. However, comparing classifiers and selecting the best for each microarray dataset can be a tedious and non-straightforward task. The M@CBETH (a MicroArray Classification BEnchmarking Tool on a Host server) web service offers the microarray community a simple tool for making optimal two-class predictions. M@CBETH aims at finding the best prediction among different classification methods by using randomizations of the benchmarking dataset. The M@CBETH web service intends to introduce an optimal use of clinical microarray data classification.