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Routing protocols for underwater wireless sensor networks (UWSN) and underwater Internet of Things (IoT_UWSN) networks have expanded significantly. DBR routing protocol is one of the most critical routing protocols in UWSNs. In this routing protocol, the energy consumption of the nodes, the rate of loss of sent packets, and the rate of drop of routing packets due to node shutdown have created significant challenges. For this purpose, in a new scenario called FB-DBR, clustering is performed, and fuzzy logic and bloom filter are used in each cluster's new routing protocol in underwater wireless sensor networks. Due to the fuzzy nature of the parameters used in DBR, better results are obtained and bloom filters are used in routing tables to compensate for the deceleration. as the average number of accesses to routing table entries, dead nodes, Number of Packets Sent to Base Station (BS), Number of Packets Received at BS, Packet Dropped, and Remaining Energy has improved significantly., Competing Interests: The authors have declared that no competing interests exist.

Abstract: Medical data sharing, anti-tampering, and leakage prevention have always been severe problems that plagued the pharmaceutical industry. When a patient is referred, he often cannot provide information about previous visits because the medical information of each hospital cannot be shared in most cases, but only through Medical records, test sheets, and other easily lost paper information are used to share some medical information. At the same time, patient medical information is easily leaked, and the medical information provided in the event of a medical dispute cannot guarantee authenticity and impartiality. This article designs a consortium medical blockchain system based on a Possible Byzantine Fault Tolerance algorithm. This system is a medical system that is maintained and shared by multiple nodes and can prevent medical data from being tampered with or leaked. It can be used to solve these medical problems. Compared with the existing medical blockchain system, this system has certain advantages and better applicability., Competing Interests: The author has no conflicts of interest to disclose., (Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.)

Cloud computing has evolved the big data technologies to a consolidated paradigm with SPaaS (Streaming processing-as-a-service). With a number of enterprises offering cloud-based solutions to end-users and other small enterprises, there has been a boom in the volume of data, creating interest of both industry and academia in big data analytics, streaming applications, and social networking applications. With the companies shifting to cloud-based solutions as a service paradigm, the competition grows in the market. Good quality of service (QoS) is a must for the enterprises, as they strive to survive in a competitive environment. However, achieving reasonable QoS goals to meet SLA agreement cost-effectively is challenging due to variation in workload over time. This problem can be solved if the system has the ability to predict the workload for the near future. In this paper, we present a novel topology-refining scheme based on a workload prediction mechanism. Predictions are made through a model based on a combination of SVR, autoregressive, and moving average model with a feedback mechanism. Our streaming system is designed to increase the overall performance by making the topology refining robust to the incoming workload on the fly, while still being able to achieve QoS goals of SLA constraints. Apache Flink distributed processing engine is used as a testbed in the paper. The result shows that the prediction scheme works well for both workloads, i.e., synthetic as well as real traces of data., Competing Interests: The authors have declared that no competing interests exist.

Methods: The aim of the paper is twofold. First, we present Starviewer, a DICOM viewer developed in C++ with a core component built on top of open-source libraries. The viewer supports extensions that implement functionalities and front-ends for specific use cases. Second, we propose an adaptable evaluation framework based on a set of criteria weighted according to user needs. The framework can consider different user profiles and allow criteria to be decomposed in subcriteria and grouped in more general categories making a multi-level hierarchical structure that can be analysed at different levels of detail to make scores interpretation more comprehensible., Results: Different examples to illustrate Starviewer functionalities and its extensions are presented. In addition, the proposed evaluation framework is used to compare Starviewer with four open-source viewers regarding their functionalities for daily clinical practice. In a range from 0 to 10, the final scores are: Horos (7.7), Starviewer (6.2), Weasis (6.0), Ginkgo CADx (4.1), and medInria (3.8)., Conclusions: Starviewer provides basic and advanced features for daily image diagnosis needs as well as a modular design that enables the development of custom extensions. The evaluation framework is useful to understand and prioritize new development goals, and can be easily adapted to express different needs by altering the weights. Moreover, it can be used as a complement to maturity models., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The US Food and Drug Administration (FDA) Sentinel System uses a distributed data network, a common data model, curated real-world data, and distributed analytic tools to generate evidence for FDA decision-making. Sentinel system needs include analytic flexibility, transparency, and reproducibility while protecting patient privacy. Based on over a decade of experience, a critical system limitation is the inability to identify enough medical conditions of interest in observational data to a satisfactory level of accuracy. Improving the system's ability to use computable phenotypes will require an "all of the above" approach that improves use of electronic health data while incorporating the growing array of complementary electronic health record data sources. FDA recently funded a Sentinel System Innovation Center and a Community Building and Outreach Center that will provide a platform for collaboration across disciplines to promote better use of real-world data for decision-making., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: A large quantity of data is collected during the delivery of cancer care. However, once collected, these data are difficult for health professionals to access to support clinical decision making and performance review. There is a need for innovative tools that make clinical data more accessible to support health professionals in these activities. One approach for providing health professionals with access to clinical data is to create the infrastructure and interface for a clinical dashboard to make data accessible in a timely and relevant manner., Objective: This study aimed to develop and evaluate 2 prototype dashboards for displaying data on the identification and management of lymphedema., Methods: The study used a co-design framework to develop 2 prototype dashboards for use by health professionals delivering breast cancer care. The key feature of these dashboards was an approach for visualizing lymphedema patient cohort and individual patient data. This project began with 2 focus group sessions conducted with members of a breast cancer multidisciplinary team (n=33) and a breast cancer consumer (n=1) to establish clinically relevant and appropriate data for presentation and the visualization requirements for a dashboard. A series of fortnightly meetings over 6 months with an Advisory Committee (n=10) occurred to inform and refine the development of a static mock-up dashboard. This mock-up was then presented to representatives of the multidisciplinary team (n=3) to get preliminary feedback about the design and use of such dashboards. Feedback from these presentations was reviewed and used to inform the development of the interactive prototypes. A structured evaluation was conducted on the prototypes, using Think Aloud Protocol and semistructured interviews with representatives of the multidisciplinary team (n=5)., Results: Lymphedema was selected as a clinically relevant area for the prototype dashboards. A qualitative evaluation is reported for 5 health professionals. These participants were selected from 3 specialties: surgery (n=1), radiation oncology (n=2), and occupational therapy (n=2). Participants were able to complete the majority of tasks on the dashboard. Semistructured interview themes were categorized into engagement or enthusiasm for the dashboard, user experience, and data quality and completeness., Conclusions: Findings from this study constitute the first report of a co-design process for creating a lymphedema dashboard for breast cancer health professionals. Health professionals are interested in the use of data visualization tools to make routinely collected clinical data more accessible. To be used effectively, dashboards need to be reliable and sourced from accurate and comprehensive data sets. While the co-design process used to develop the visualization tool proved effective for designing an individual patient dashboard, the complexity and accessibility of the data required for a cohort dashboard remained a challenge., (©Anna Janssen, Candice Donnelly, Judy Kay, Peter Thiem, Aldo Saavedra, Nirmala Pathmanathan, Elisabeth Elder, Phuong Dinh, Masrura Kabir, Kirsten Jackson, Paul Harnett, Tim Shaw. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 21.04.2020.)

Objective: The study sought to design, pilot, and evaluate a federated data completeness tracking system (CTX) for assessing completeness in research data extracted from electronic health record data across the Accessible Research Commons for Health (ARCH) Clinical Data Research Network., Materials and Methods: The CTX applies a systems-based approach to design workflow and technology for assessing completeness across distributed electronic health record data repositories participating in a queryable, federated network. The CTX invokes 2 positive feedback loops that utilize open source tools (DQe-c and Vue) to integrate technology and human actors in a system geared for increasing capacity and taking action. A pilot implementation of the system involved 6 ARCH partner sites between January 2017 and May 2018., Results: The ARCH CTX has enabled the network to monitor and, if needed, adjust its data management processes to maintain complete datasets for secondary use. The system allows the network and its partner sites to profile data completeness both at the network and partner site levels. Interactive visualizations presenting the current state of completeness in the context of the entire network as well as changes in completeness across time were valued among the CTX user base., Discussion: Distributed clinical data networks are complex systems. Top-down approaches that solely rely on technology to report data completeness may be necessary but not sufficient for improving completeness (and quality) of data in large-scale clinical data networks. Improving and maintaining complete (high-quality) data in such complex environments entails sociotechnical systems that exploit technology and empower human actors to engage in the process of high-quality data curating., Conclusions: The CTX has increased the network's capacity to rapidly identify data completeness issues and empowered ARCH partner sites to get involved in improving the completeness of respective data in their repositories., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Distributed ledger technology (DLT) holds great potential to improve health information exchange. However, the immutable and transparent character of this technology may conflict with data privacy regulations and data processing best practices., Objective: The aim of this paper is to develop a proof-of-concept system for immutable, interoperable, and General Data Protection Regulation (GDPR)-compliant exchange of blood glucose data., Methods: Given that there is no ideal design for a DLT-based patient-provider data exchange solution, we proposed two different variations for our proof-of-concept system. One design was based purely on the public IOTA distributed ledger (a directed acyclic graph-based DLT) and the second used the same public IOTA ledger in combination with a private InterPlanetary File System (IPFS) cluster. Both designs were assessed according to (1) data reversal risk, (2) data linkability risks, (3) processing time, (4) file size compatibility, and (5) overall system complexity., Results: The public IOTA design slightly increased the risk of personal data linkability, had an overall low processing time (requiring mean 6.1, SD 1.9 seconds to upload one blood glucose data sample into the DLT), and was relatively simple to implement. The combination of the public IOTA with a private IPFS cluster minimized both reversal and linkability risks, allowed for the exchange of large files (3 months of blood glucose data were uploaded into the DLT in mean 38.1, SD 13.4 seconds), but involved a relatively higher setup complexity., Conclusions: For the specific use case of blood glucose explored in this study, both designs presented a suitable performance in enabling the interoperable exchange of data between patients and providers. Additionally, both systems were designed considering the latest guidelines on personal data processing, thereby maximizing the alignment with recent GDPR requirements. For future works, these results suggest that the conflict between DLT and data privacy regulations can be addressed if careful considerations are made regarding the use case and the design of the data exchange system., (©David Hawig, Chao Zhou, Sebastian Fuhrhop, Andre S Fialho, Navin Ramachandran. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 14.06.2019.)

Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represents a data architecture, whose application goes far beyond Bitcoin - the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as 'revolutionary' and 'disruptive', is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is 'fit-for-purpose' is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.

The accuracy and diversity of recommendation algorithms have always been the research hotspot of recommender systems. A good recommender system should not only have high accuracy and diversity, but also have adequate robustness against spammer attacks. However, the issue of recommendation robustness has received relatively little attention in the literature. In this paper, we systematically study the influences of different spammer behaviors on the recommendation results in various recommendation algorithms. We further propose an improved algorithm by incorporating the inner-similarity of user's purchased items in the classic KNN approach. The new algorithm effectively enhances the robustness against spammer attacks and thus outperforms traditional algorithms in recommendation accuracy and diversity when spammers exist in the online commercial systems., Competing Interests: Authors Zhang C, Han T and Ge X are paid employees of ShuKun BeiJing Network Technology Co., Limited. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

As the number of elderly persons with chronic illnesses increases, a new public infrastructure for their care is becoming increasingly necessary. In particular, technologies that can monitoring bio-signals in real-time have been receiving significant attention. Currently, most healthcare monitoring services are implemented by wireless carrier through centralized servers. These services are vulnerable to data concentration because all data are sent to a remote server. To solve these problems, we propose self-organizing P2P middleware for healthcare monitoring that enables a real-time multi bio-signal streaming without any central server by connecting the caregiver and care recipient. To verify the performance of the proposed middleware, we evaluated the monitoring service matching time based on a monitoring request. We also confirmed that it is possible to provide an effective monitoring service by evaluating the connectivity between Peer-to-Peer and average jitter., Competing Interests: The authors declare no conflict of interest.

In the existing centralized location services system structure, the server is easily attracted and be the communication bottleneck. It caused the disclosure of users' location. For this, we presented a new distributed collaborative recommendation strategy that is based on the distributed system. In this strategy, each node establishes profiles of their own location information. When requests for location services appear, the user can obtain the corresponding location services according to the recommendation of the neighboring users' location information profiles. If no suitable recommended location service results are obtained, then the user can send a service request to the server according to the construction of a k-anonymous data set with a centroid position of the neighbors. In this strategy, we designed a new model of distributed collaborative recommendation location service based on the users' location information profiles and used generalization and encryption to ensure the safety of the user's location information privacy. Finally, we used the real location data set to make theoretical and experimental analysis. And the results show that the strategy proposed in this paper is capable of reducing the frequency of access to the location server, providing better location services and protecting better the user's location privacy., Competing Interests: The authors have declared that no competing interests exist.

Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks.

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc.

Software methods that enable navigation of radiology cases on various digital platforms differ between handheld devices and desktop computers. This has resulted in poor compatibility of online radiology teaching files across mobile smartphones, tablets, and desktop computers. A standardized, platform-independent, or "agnostic" approach for presenting online radiology content was produced in this work by leveraging modern hypertext markup language (HTML) and JavaScript web software technology. We describe the design and evaluation of this software, demonstrate its use across multiple viewing platforms, and make it publicly available as a model for future development efforts.

Objective: To introduce and evaluate a method that uses electronic medical record (EMR) data to measure the effects of computer system downtime on clinical processes associated with pathology testing and results reporting., Materials and Methods: A matched case-control design was used to examine the effects of five downtime events over 11-months, ranging from 5 to 300min. Four indicator tests representing different laboratory workflows were selected to measure delays and errors: potassium, haemoglobon, troponin and activated partial thromboplastin time. Tests exposed to a downtime were matched to tests during unaffected control periods by test type, time of day and day of week. Measures included clinician read time (CRT), laboratory turnaround time (LTAT), and rates of missed reads, futile searches, duplicate orders, and missing test results., Results: The effects of downtime varied with the type of IT problem. When clinicians could not logon to a results reporting system for 17-min, the CRT for potassium and haemoglobon tests was five (10.3 vs. 2.0days) and six times (13.4 vs. 2.1days) longer than control (p=0.01-0.04; p=0.0001-0.003). Clinician follow-up of tests was also delayed by another downtime involving a power outage with a small effect. In contrast, laboratory processing of troponin tests was unaffected by network services and routing problems. Errors including missed reads, futile searches, duplicate orders and missing test results could not be examined because the sample size of affected tests was not sufficient for statistical testing., Conclusion: This study demonstrates the feasibility of using routinely collected EMR data with a matched case-control design to measure the effects of downtime on clinical processes. Even brief system downtimes may impact patient care. The methodology has potential to be applied to other clinical processes with established workflows where tasks are pre-defined such as medications management., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Today, security is a prominent issue when any type of communication is being undertaken. Like traditional networks, supervisory control and data acquisition (SCADA) systems suffer from a number of vulnerabilities. Numerous end-to-end security mechanisms have been proposed for the resolution of SCADA-system security issues, but due to insecure real-time protocol use and the reliance upon open protocols during Internet-based communication, these SCADA systems can still be compromised by security challenges. This study reviews the security challenges and issues that are commonly raised during SCADA/protocol transmissions and proposes a secure distributed-network protocol version 3 (DNP3) design, and the implementation of the security solution using a cryptography mechanism. Due to the insecurities found within SCADA protocols, the new development consists of a DNP3 protocol that has been designed as a part of the SCADA system, and the cryptographically derived security is deployed within the application layer as a part of the DNP3 stack.

Background: The universal qPCR data exchange file format RDML is today well accepted by the scientific community, part of the MIQE guidelines and implemented in many qPCR instruments. With the increased use of RDML new challenges emerge. The flexibility of the RDML format resulted in some implementations that did not meet the expectations of the consortium in the level of support or the use of elements., Results: In the current RDML version 1.2 the description of the elements was sharpened. The open source editor RDML-Ninja was released (http://sourceforge.net/projects/qpcr-ninja/). RDML-Ninja allows to visualize, edit and validate RDML files and thus clarifies the use of RDML elements. Furthermore RDML-Ninja serves as reference implementation for RDML and enables migration between RDML versions independent of the instrument software. The database RDMLdb will serve as an online repository for RDML files and facilitate the exchange of RDML data (http://www.rdmldb.org). Authors can upload their RDML files and reference them in publications by the unique identifier provided by RDMLdb. The MIQE guidelines propose a rich set of information required to document each qPCR run. RDML provides the vehicle to store and maintain this information and current development aims at further integration of MIQE requirements into the RDML format., Conclusions: The editor RDML-Ninja and the database RDMLdb enable scientists to evaluate and exchange qPCR data in the instrument-independent RDML format. We are confident that this infrastructure will build the foundation for standardized qPCR data exchange among scientists, research groups, and during publication.

Services composition is fundamental to software development in multi-service wireless sensor networks (WSNs). The quality of service (QoS) of services composition applications (SCAs) are confronted with severe challenges due to the open, dynamic, and complex natures of WSNs. Most previous research separated various QoS indices into different fields and studied them individually due to the computational complexity. This approach ignores the mutual influence between these QoS indices, and leads to a non-comprehensive and inaccurate analysis result. The universal generating function (UGF) shows the speediness and precision in QoS analysis. However, only one QoS index at a time can be analyzed by the classic UGF. In order to efficiently analyze the comprehensive QoS of SCAs, this paper proposes an improved UGF technique-vector universal generating function (VUGF)-which considers the relationship between multiple QoS indices, including security, and can simultaneously analyze multiple QoS indices. The numerical examples demonstrate that it can be used for the evaluation of the comprehensive QoS of SCAs subjected to the security constraint in WSNs. Therefore, it can be effectively applied to the optimal design of multi-service WSNs.

Objective: This paper describes Health Level 7 (HL7) V.3 Care Transfer, Care Record Query, and Care Record messages. This is the core of the Care Provision Domain in the HL7 standard which became normative at the end of 2012 and is an American National Standards Institute (ANSI)-approved HL7 standard., Background and Significance: Using a message is somewhat different from the approach offered in the current HL7 Clinical Document Architecture (CDA). The overall advantage is human-to-human communication and system-to-system processing of structured data through electronic messages, supporting continuity of care and interactive structured data exchange through querying., Materials and Methods: The Care Provision Domain Model in HL7 was developed based on use cases from several projects internationally. Use case and information analysis, model building, HL7 consensus methods (eg, working group meetings), conference calls, balloting, a draft standard for trial use, pilot implementations, and subsequent evaluation were applied., Results: The membership and pilot implementers gave feedback to improve the draft standard. After the formal ballot process, HL7 membership accepted it as a normative standard and it is now ANSI approved. The Care Provision Domain Model defines the structure (data exchanged) and dynamics (workflow and communications) of the Care Record, Care Record Query, and Care Transfer., Discussion and Conclusions: The HL7 V3 Care Provision Domain differs from the HL7 CDA regarding support of the dynamics of care (eg, for continuity of care) as provided through a series of interactions and queries, but is similar with respect to the data and their organization., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Nowadays, quality of service (QoS) is very popular in various research areas like distributed systems, multimedia real-time applications and networking. The requirements of these systems are to satisfy reliability, uptime, security constraints and throughput as well as application specific requirements. The real-time multimedia applications are commonly distributed over the network and meet various time constraints across networks without creating any intervention over control flows. In particular, video compressors make variable bit-rate streams that mismatch the constant-bit-rate channels typically provided by classical real-time protocols, severely reducing the efficiency of network utilization. Thus, it is necessary to enlarge the communication bandwidth to transfer the compressed multimedia streams using Flexible Time Triggered- Enhanced Switched Ethernet (FTT-ESE) protocol. FTT-ESE provides automation to calculate the compression level and change the bandwidth of the stream. This paper focuses on low-latency multimedia transmission over Ethernet with dynamic quality-of-service (QoS) management. This proposed framework deals with a dynamic QoS for multimedia transmission over Ethernet with FTT-ESE protocol. This paper also presents distinct QoS metrics based both on the image quality and network features. Some experiments with recorded and live video streams show the advantages of the proposed framework. To validate the solution we have designed and implemented a simulator based on the Matlab/Simulink, which is a tool to evaluate different network architecture using Simulink blocks.

Providing patients and clinicians with self-contained PACS viewer on CD format is a common and necessary tool to share vital imaging data. However, to be useful, this tool should be reliable, robust, and convenient. Numerous PACS viewer options are available, often without empirical data to guide in choosing one for routine use. To assist in making a standardized choice for our institution, we chose four common viewers, benchmarked on four different workstations reflecting the variety of environments used by non-radiologist clinicians who would receive a CD. Four CD-based DICOM viewers from eFilm, Philips, Pacsgear Gearview, and iSite were examed on two radiology PACS workstations, a standard desktop computer, and a laptop using a test case consisting of a multi-series CTA with 13 series and 3,035 total images. Multiple objective measures, subjective measures, and presence of key features were evaluated including program time to load, image time to load, cine/movie mode, ability to adequately window and level, pan and zoom functionality, basic measurement tools, and perceived lag when scrolling through a multi-image series. Substantial differences in speed of operation and behavior on multiple systems were documented, which could potentially add several minutes to the time required to open and view a patient's imaging data. The eFilm and iSite viewers operated consistently and reliably across all tested computer environments. The iSite viewer, having among the quickest load times in the group tested and consistently low subjective scroll lag during series viewing, and also beneficially allowing partial viewing while images load in the background, was found to generate the best overall user experience. Because of these significant differences, we have recommended that our institution standardize all patient imaging CD creation using the iSite viewer.

Information technology (IT) is pushing ahead with drastic reforms of modern life for improvement of human welfare. Objects constitute "Information Networks" through smart, self-regulated information gathering that also recognizes and controls current information states in Wireless Sensor Networks (WSNs). Information observed from sensor networks in real-time is used to increase quality of life (QoL) in various industries and daily life. One of the key challenges of the WSNs is how to achieve lossless data transmission. Although nowadays sensor nodes have enhanced capacities, it is hard to assure lossless and reliable end-to-end data transmission in WSNs due to the unstable wireless links and low hard ware resources to satisfy high quality of service (QoS) requirements. We propose a node and path traffic prediction model to predict and minimize the congestion. This solution includes prediction of packet generation due to network congestion from both periodic and event data generation. Simulation using NS-2 and Matlab is used to demonstrate the effectiveness of the proposed solution.

Traceback schemes have been proposed to trace the sources of attacks that usually hide by spoofing their IP addresses. Among these methods, schemes using packet logging can achieve single-packet traceback. But packet logging demands high storage on routers and therefore makes IP traceback impractical. For lower storage requirement, packet logging and packet marking are fused to make hybrid single-packet IP traceback. Despite such attempts, their storage still increases with packet numbers. That is why RIHT bounds its storage with path numbers to guarantee low storage. RIHT uses IP header's ID and offset fields to mark packets, so it inevitably suffers from fragment and drop issues for its packet reassembly. Although the 16-bit hybrid IP traceback schemes, for example, MORE, can mitigate the fragment problem, their storage requirement grows up with packet numbers. To solve the storage and fragment problems in one shot, we propose a single-packet IP traceback scheme that only uses packets' ID field for marking. Our major contributions are as follows: (1) our fragmented packets with tracing marks can be reassembled; (2) our storage is not affected by packet numbers; (3) it is the first hybrid single-packet IP traceback scheme to achieve zero false positive and zero false negative rates.

Vehicular ad hoc networks (VANETs) are emerging as new research area and attracting an increasing attention from both industry and research communities. In this context, a dynamic resource allocation policy that maximizes the use of available resources and meets the quality of service (QoS) requirement of constraining applications is proposed. It is a combination of a fair packet scheduling policy and a new adaptive QoS oriented call admission control (CAC) scheme based on the vehicle density variation. This scheme decides whether the connection request is to be admitted into the system, while providing fair access and guaranteeing the desired throughput. The proposed algorithm showed good performance in testing in real world environment.

Both reliable detection of the primary signal in a noisy and fading environment and nullifying the effect of unauthorized users are important tasks in cognitive radio networks. To address these issues, we consider a cooperative spectrum sensing approach where each user is assigned nonuniform reliability based on the sensing performance. Users with poor channel or faulty sensor are assigned low reliability. The nonuniform reliabilities serve as identification tags and are used to isolate users with malicious behavior. We consider a link layer attack similar to the Byzantine attack, which falsifies the spectrum sensing data. Three different strategies are presented in this paper to ignore unreliable and malicious users in the network. Considering only reliable users for global decision improves sensing time and decreases collisions in the control channel. The fusion center uses the degree of reliability as a weighting factor to determine the global decision in scheme I. Schemes II and III consider the unreliability of users, which makes the computations even simpler. The proposed schemes reduce the number of sensing reports and increase the inference accuracy. The advantages of our proposed schemes over conventional cooperative spectrum sensing and the Chair-Varshney optimum rule are demonstrated through simulations.

We propose a novel protocol for controlled bidirectional quantum secure communication based on a nonlocal swap gate scheme. Our proposed protocol would be applied to a system in which a controller (supervisor/Charlie) controls the bidirectional communication with quantum information or secret messages between legitimate users (Alice and Bob). In this system, the legitimate users must obtain permission from the controller in order to exchange their respective quantum information or secret messages simultaneously; the controller is unable to obtain any quantum information or secret messages from the decoding process. Moreover, the presence of the controller also avoids the problem of one legitimate user receiving the quantum information or secret message before the other, and then refusing to help the other user decode the quantum information or secret message. Our proposed protocol is aimed at protecting against external and participant attacks on such a system, and the cost of transmitting quantum bits using our protocol is less than that achieved in other studies. Based on the nonlocal swap gate scheme, the legitimate users exchange their quantum information or secret messages without transmission in a public channel, thus protecting against eavesdroppers stealing the secret messages.

Objectives: To compare the usability of different Picture Archiving and Communication System (PACS) workstations, determine whether a usability test has added value with respect to the traditional way of comparing PACSs based on functional requirements, and to evaluate the appropriateness of a task-based methodology for a PACS usability test., Methods: A task-based usability test of four PACS workstations was performed. Radiologists' subjective responses to the PACSs and their performance on the tasks were measured. To mimic the traditional PACS selection process, two functional requirements were defined which the PACSs met in varying degrees. The focus of the usability test was on the aspects of the PACS related to these requirements. The usability results were compared to the PACSs' ability to meet the functional requirements., Results: One PACS outperformed the other PACSs both in terms of subjective preference and task performance, indicating its superior usability. There were differences in usability between PACSs with identical functionality. Also, a PACS with theoretically advantageous functionality for a given task did not necessarily have better usability for this task than a PACS without this functionality. There was a discrepancy between participants' subjective preferences and their task performance, which indicates that it is vital to include performance measures in the usability assessment so that it accurately reflects the efficiency of interaction., Conclusions: The differences in usability between PACSs with identical functionality indicate that functional requirements alone are insufficient to determine a PACS's overall quality. A usability test should therefore be used in addition to a functional requirement list in a PACS selection process to ensure that a hospital buys the PACS with the highest quality. A task-based usability evaluation methodology, which yields both subjective preference data and objective performance data of radiologists interacting with the PACS, is very suitable for such a usability test., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

We revisit the SM2 protocol, which is widely used in Chinese commercial applications and by Chinese government agencies. Although it is by now standard practice for protocol designers to provide security proofs in widely accepted security models in order to assure protocol implementers of their security properties, the SM2 protocol does not have a proof of security. In this paper, we prove the security of the SM2 protocol in the widely accepted indistinguishability-based Bellare-Rogaway model under the elliptic curve discrete logarithm problem (ECDLP) assumption. We also present a simplified and more efficient version of the SM2 protocol with an accompanying security proof.

On the basis of Evalvid tool integrated in NS2 (Network Simulator version 2), the paper gets new set of tools, myEvalvid, to establish the simulation and evaluation platform for multimedia transmission. Then the paper investigates the effects of various influence factors when multimedia information is transmitted in the network and the relationships among these factors. Based on the analysis, the paper gets different evaluation models, respectively. In this paper, we study the impact on performance of several basic source and network parameters of video streams, namely, GOP (Group of Pictures) pattern, compression quantitative parameters, packet length, and packet error rate. Simulation results show that different parameters lead to different distortion levels which are calculated according to the reconstruction images at the receiver and the original images. The experimental results show that the video transmission and quality evaluation model we designed can evaluate multimedia transmission performance over complex environment very well.

The behaviour of the routers' buffer may affect the quality of service (QoS) of network services under certain conditions, since it may modify some traffic characteristics, as delay or jitter, and may also drop packets. As a consequence, the characterization of the buffer is interesting, especially when multimedia flows are transmitted and even more if they transport information with real-time requirements. This work presents a new methodology with the aim of determining the technical and functional characteristics of real buffers (i.e., behaviour, size, limits, and input and output rate) of a network path. It permits the characterization of intermediate buffers of different devices in a network path across the Internet.

Even though existing low-power listening (LPL) protocols have enabled ultra-low-power operation in wireless sensor networks (WSN), they do not address trade-off between energy and delay, since they focused only on energy aspect. However, in recent years, a growing interest in various WSN applications is requiring new design factors, such as minimum delay and higher reliability, as well as energy efficiency. Therefore, in this paper we propose a novel sensor multiple access control (MAC) protocol, transmission rate based adaptive low-power listening MAC protocol (TRA-MAC), which is a kind of preamble-based LPL but is capable of controlling preamble sensing cycle adaptively to transmission rates. Through experiments, it is demonstrated that TRA-MAC enables LPL cycle (LC) and preamble transmission length to adapt dynamically to varying transmission rates, compensating trade-off between energy and response time.

Despite the convenience, ubiquitous computing suffers from many threats and security risks. Security considerations in the ubiquitous network are required to create enriched and more secure ubiquitous environments. The address resolution protocol (ARP) is a protocol used to identify the IP address and the physical address of the associated network card. ARP is designed to work without problems in general environments. However, since it does not include security measures against malicious attacks, in its design, an attacker can impersonate another host using ARP spoofing or access important information. In this paper, we propose a new detection scheme for ARP spoofing attacks using a routing trace, which can be used to protect the internal network. Tracing routing can find the change of network movement path. The proposed scheme provides high constancy and compatibility because it does not alter the ARP protocol. In addition, it is simple and stable, as it does not use a complex algorithm or impose extra load on the computer system.

Authenticated key exchange protocols are of fundamental importance in securing communications and are now extensively deployed for use in various real-world network applications. In this work, we reveal major previously unpublished security vulnerabilities in the password-based authenticated three-party key exchange protocol according to Lee and Hwang (2010): (1) the Lee-Hwang protocol is susceptible to a man-in-the-middle attack and thus fails to achieve implicit key authentication; (2) the protocol cannot protect clients' passwords against an offline dictionary attack; and (3) the indistinguishability-based security of the protocol can be easily broken even in the presence of a passive adversary. We also propose an improved password-based authenticated three-party key exchange protocol that addresses the security vulnerabilities identified in the Lee-Hwang protocol.

Mobile ad hoc networks (MANETs) are a collection of mobile nodes with a dynamic topology. MANETs work under scalable conditions for many applications and pose different security challenges. Due to the nomadic nature of nodes, detecting misbehaviour is a complex problem. Nodes also share routing information among the neighbours in order to find the route to the destination. This requires nodes to trust each other. Thus we can state that trust is a key concept in secure routing mechanisms. A number of cryptographic protection techniques based on trust have been proposed. Q-learning is a recently used technique, to achieve adaptive trust in MANETs. In comparison to other machine learning computational intelligence techniques, Q-learning achieves optimal results. Our work focuses on computing a score using Q-learning to weigh the trust of a particular node over associativity based routing (ABR) protocol. Thus secure and stable route is calculated as a weighted average of the trust value of the nodes in the route and associativity ticks ensure the stability of the route. Simulation results show that Q-learning based trust ABR protocol improves packet delivery ratio by 27% and reduces the route selection time by 40% over ABR protocol without trust calculation.

The existence of malicious participants is a major threat for authenticated group key exchange (AGKE) protocols. Typically, there are two detecting ways (passive and active) to resist malicious participants in AGKE protocols. In 2012, the revocable identity- (ID-) based public key system (R-IDPKS) was proposed to solve the revocation problem in the ID-based public key system (IDPKS). Afterwards, based on the R-IDPKS, Wu et al. proposed a revocable ID-based AGKE (RID-AGKE) protocol, which adopted a passive detecting way to resist malicious participants. However, it needs three rounds and cannot identify malicious participants. In this paper, we fuse a noninteractive confirmed computation technique to propose the first two-round RID-AGKE protocol with identifying malicious participants, which is an active detecting way. We demonstrate that our protocol is a provably secure AGKE protocol with forward secrecy and can identify malicious participants. When compared with the recently proposed ID/RID-AGKE protocols, our protocol possesses better performance and more robust security properties.

Spectrum allocation is one of the key issues to improve spectrum efficiency and has become the hot topic in the research of cognitive wireless network. This paper discusses the real-time feature and efficiency of dynamic spectrum allocation and presents a new spectrum allocation algorithm based on the master-slave parallel immune optimization model. The algorithm designs a new encoding scheme for the antibody based on the demand for convergence rate and population diversity. For improving the calculating efficiency, the antibody affinity in the population is calculated in multiple computing nodes at the same time. Simulation results show that the algorithm reduces the total spectrum allocation time and can achieve higher network profits. Compared with traditional serial algorithms, the algorithm proposed in this paper has better speedup ratio and parallel efficiency.

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network-complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each sensor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly.

The paper outlines a bioinspired approach named "network nervous system" and methods of simulation of infrastructure attacks and protection mechanisms based on this approach. The protection mechanisms based on this approach consist of distributed procedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine necessary countermeasures. Attacks and protection mechanisms are specified as structural models using a set-theoretic approach. An environment for simulation of protection mechanisms based on the biological metaphor is considered; the experiments demonstrating the effectiveness of the protection mechanisms are described.

Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user's background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1) to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2) to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance.

Understanding how to govern emerging distributed research networks is essential to their success. Distributed research networks aggregate patient medical data from many institutions leaving data within the local provider security system. While much is known about patients' views on secondary medical research, little is known about their views on governance of research networks. We conducted six focus groups with patients from three medical centers across the U.S. to understand their perspectives on privacy, consent, and ethical concerns of sharing their data as part of research networks. Participants positively endorsed sharing their health data with these networks believing that doing so could advance healthcare knowledge. However, patients expressed several concerns regarding security and broader ethical issues such as commercialism, public benefit, and social responsibility. We suggest that network governance guidelines move beyond strict technical requirements and address wider socio-ethical concerns by fully including patients in governance processes.

Distance has been one of the basic factors in manufacturing and control fields, and ultrasonic distance sensors have been widely used as a low-cost measuring tool. However, the propagation of ultrasonic waves is greatly affected by environmental factors such as temperature, humidity and atmospheric pressure. In order to solve the problem of inaccurate measurement, which is significant within industry, this paper presents a novel ultrasonic distance sensor model using networked error correction (NEC) trained on experimental data. This is more accurate than other existing approaches because it uses information from indirect association with neighboring sensors, which has not been considered before. The NEC technique, focusing on optimization of the relationship of the topological structure of sensor arrays, is implemented for the compensation of erroneous measurements caused by the environment. We apply the maximum likelihood method to determine the optimal fusion data set and use a neighbor discovery algorithm to identify neighbor nodes at the top speed. Furthermore, we adopt the NEC optimization algorithm, which takes full advantage of the correlation coefficients for neighbor sensors. The experimental results demonstrate that the ranging errors of the NEC system are within 2.20%; furthermore, the mean absolute percentage error is reduced to 0.01% after three iterations of this method, which means that the proposed method performs extremely well. The optimized method of distance measurement we propose, with the capability of NEC, would bring a significant advantage for intelligent industrial automation.

Typically, commercial sensor nodes are equipped with MCUsclocked at a low-frequency (i.e., within the 4-12 MHz range). Consequently, executing cryptographic algorithms in those MCUs generally requires a huge amount of time. In this respect, the required energy consumption can be higher than using a separate accelerator based on a Field-programmable Gate Array (FPGA) that is switched on when needed. In this manuscript, we present the design of a cryptographic accelerator suitable for an FPGA-based sensor node and compliant with the IEEE802.15.4 standard. All the embedded resources of the target platform (Xilinx Artix-7) have been maximized in order to provide a cost-effective solution. Moreover, we have added key negotiation capabilities to the IEEE 802.15.4 security suite based on Elliptic Curve Cryptography (ECC). Our results suggest that tailored accelerators based on FPGA can behave better in terms of energy than contemporary software solutions for motes, such as the TinyECC and NanoECC libraries. In this regard, a point multiplication (PM) can be performed between 8.58- and 15.4-times faster, 3.40- to 23.59-times faster (Elliptic Curve Diffie-Hellman, ECDH) and between 5.45- and 34.26-times faster (Elliptic Curve Integrated Encryption Scheme, ECIES). Moreover, the energy consumption was also improved with a factor of 8.96 (PM).

Despite advancements in the development of the artificial pancreas, barriers in the form of proprietary data and communication protocols of diabetes devices have made the integration of these components challenging. The Artificial Pancreas Standards and Technical Platform Project is an initiative funded by the JDRF Canadian Clinical Trial Network with the goal of developing device communication standards for the interoperability of diabetes devices. Stakeholders from academia, industry, regulatory agencies, and medical and patient communities have been engaged in advancing this effort. In this article, we describe this initiative along with the process involved in working with the standards organizations and stakeholders that are key to ensuring effective standards are developed and adopted. Discussion from a special session of the 12th Annual Diabetes Technology Meeting is also provided., (© 2013 Diabetes Technology Society.)

Statistical channel models for 60 GHz communications systems in hospital environments are validated using channel capacity and throughput of a physical layer as figures of merit. The channel models are validated by comparing the performance figures with channels from the measurements and the channel models. The throughput evaluation is based on system specifications given by the IEEE 802.15.3 c standard for high data rate wireless personal area networks, namely orthogonal frequency division multiplexing and single carrier transmissions. The channel capacity serves as a metric of the potential of the two transmission schemes since it defines the upper bound of the throughput. The capacity is derived based on the signal formats of the transmission schemes. The capacity shows that 97 % of the measurement results are within 2σ range of the modeled results. The throughput shows that the channel models predict the maximum achievable throughput of the measured channels precisely, while the mean throughput in some cases shows difference because of the interpolation effect of the small-scale fading in the statistical channel models. Due to the interpolation effect, the channel model is more suitable for a precise analysis of the outage performance than the measurements where the number of channel samples is limited and the worst faded channels are not necessarily included.