Data Dissemination for Industry 4.0 Applications in Internet of Vehicles Based on Short-term Traffic Prediction

As a key use case of Industry 4.0 and the Smart City, the Internet of Vehicles (IoV) provides an efficient way for city managers to regulate the traffic flow, improve the commuting performance, reduce the transportation facility cost, alleviate the traffic jam, and so on. In fact, the significant development of Internet of Vehicles has boosted the emergence of a variety of Industry 4.0 applications, e.g., smart logistics, intelligent transforation, and autonomous driving. The prerequisite of deploying these applications is the design of efficient data dissemination schemes by which the interactive information could be effectively exchanged. However, in Internet of Vehicles, an efficient data scheme should adapt to the high node movement and frequent network changing. To achieve the objective, the ability to predict short-term traffic is crucial for making optimal policy in advance. In this article, we propose a novel data dissemination scheme by exploring short-term traffic prediction for Industry 4.0 applications enabled in Internet of Vehicles. First, we present a three-tier network architecture with the aim to simply network management and reduce communication overheads. To capture dynamic network changing, a deep learning network is employed by the controller in this architecture to predict short-term traffic with the availability of enormous traffic data. Based on the traffic prediction, each road segment can be assigned a weight through the built two-dimensional delay model, enabling the controller to make routing decisions in advance. With the global weight information, the controller leverages the ant colony optimization algorithm to find the optimal routing path with minimum delay. Extensive simulations are carried out to demonstrate the accuracy of the traffic prediction model and the superiority of the proposed data dissemination scheme for Industry 4.0 applications.

Derived blockchain architecture for security-conscious data dissemination in edge-envisioned Internet of Drones ecosystem

Internet of Drones (IoD) facilitates the autonomous operations of drones into every application (warfare, surveillance, photography, etc) across the world. The transmission of data (to and fro) related to these applications occur between the drones and the other infrastructure over wireless channels that must abide to the stringent latency restrictions. However, relaying this data to the core cloud infrastructure may lead to a higher round trip delay. Thus, we utilize the cloud close to the ground, i.e., edge computing to realize an edge-envisioned IoD ecosystem. However, as this data is relayed over an open communication channel, it is often prone to different types of attacks due to it wider attack surface. Thus, we need to find a robust solution that can maintain the confidentiality, integrity, and authenticity of the data while providing desired services. Blockchain technology is capable to handle these challenges owing to the distributed ledger that store the data immutably. However, the conventional block architecture pose several challenges because of limited computational capabilities of drones. As the size of blockchain increases, the data flow also increases and so does the associated challenges. Hence, to overcome these challenges, in this work, we have proposed a derived blockchain architecture that decouples the data part (or block ledger) from the block header and shifts it to off-chain storage. In our approach, the registration of a new drone is performed to enable legitimate access control thus ensuring identity management and traceability. Further, the interactions happen in the form of transactions of the blockchain. We propose a lightweight consensus mechanism based on the stochastic selection followed by a transaction signing process to ensure that each drone is in control of its block. The proposed scheme also handles the expanding storage requirements with the help of data compression using a shrinking block mechanism. Lastly, the problem of additional delay anticipated due to drone mobility is handled using a multi-level caching mechanism. The proposed work has been validated in a simulated Gazebo environment and the results are promising in terms of different metrics. We have also provided numerical validations in context of complexity, communication overheads and computation costs.

Data dissemination by Uganda Bureau of Statistics

Data plays a big role in educating the population on various issues that contribute to development. One of the major activities conducted after data collection is, dissemination of the data to different stakeholders. Uganda Bureau of Statistics disseminates data to its users through a number of channels. This paper discusses each method in detail and how it's used during this process. The major channel of sharing data with users is through dissemination workshops and the website. Other channels used for dissemination include the library and resource centre, social media and physical delivery to stakeholders in district public libraries. Having the above-mentioned channels of data dissemination in place, has helped UBOS remain the centre of excellence in dissemination of data to users, countrywide and in Africa.

Security Improvements for Connected Vehicles Position-Based Routing

The constant growing on the number of vehicles is increasing the complexity of traffic in urban and highway environments. It is paramount to improve traffic management to guarantee better road usage and people’s safety. Through efficient communications, Vehicular Ad hoc Networks (VANETs) can provide enough information for traffic safety initiatives, daily traffic data processing, and entertainment information. However, VANETs are vulnerable to malicious nodes applying different types of net-work attacks, where an attacker can, for instance, forge its position to receive the data packet and drop the message. This can lead vehicles and authorities to make incorrect assumptions and decisions, which can result in dangerous situations. Therefore, any data dissemination protocol designed for VANET should consider security issues when selecting the next-hop forwarding node. In this paper, we propose a security scheme designed for position-based routing algorithms, which analyzes nodes position, transmission range, and hello packet interval. The scheme deals with malicious nodes performing network attacks, faking their positions forcing packets to be dropped. We used the Simulation of Urban MObility (SUMO) and Network Simulator-version 3 (NS-3) to compare our proposed scheme integrated with two well-known position-based algorithms. The results were collected in an urban Manhattan grid environment varying the number of nodes, the number of malicious nodes, as well as the number of source-destination pairs. The results show that the proposed security scheme can successfully improve the packet delivery ratio while maintaining low average end-to-end delay of the algorithms.

Vascular Access Teams: A Global Outlook on Challenges, Benefits, Opportunities, and Future Perspectives

Highlights Abstract Background: Specialized vascular access training for medical professionals organized into vascular access teams (VATs) was shown to improve patient outcomes, clinical efficiency, and cost savings. Professional perspectives on VAT benefits, organization, challenges, and opportunities on a global scale remain inadequately explored. Using detailed perspectives, in this study, we explored the global VAT landscape, including challenges faced, clinical and clinico-economic impacts of VATs, with emphasis on underresearched facets of VAT initiation, data dissemination, and metrics or benchmarks for VAT success. Methods: Semistructured in-depth interviews of 14 VAT professionals from 9 countries and 5 continents were used to elicit qualitative and quantitative information. Results: Catheter insertions (100%) and training (86%) were the most performed VAT functions. Based on a 1–7 scale evaluating observed impacts of VATs, patient satisfaction (6.5) and institutional costs (6.2) were ranked the highest. VAT co-initiatives, advanced technology utilization (6.6), and ongoing member training (6.3) distinctly impacted VAT endeavors. Most institutions (64%) did not have routine mechanisms for recording VAT-related data; however, all participants (100%) stated the importance of sharing data to demonstrate VAT impacts. Time constraints (57%) emerged as one of the major deterrents to data collection or dissemination. The majority (64%) experienced an increased demand or workload for VAT services during the COVID-19 pandemic. Conclusions: Despite the global variances in VATs and gaps in VAT-related data, all participants unanimously endorsed the benefits of VAT programs. Evaluating the impact of VATs, disseminating VAT-related data, and forging specialized institutional partnerships for data sharing and training are potential strategies to tackle the hurdles surrounding VAT formation and sustenance.

Frequent-Pattern-Based Broadcast Scheduling for Conflict Avoidance in Multichannel Data Dissemination Systems

With the popularity of mobile devices, using the traditional client-server model to handle a large number of requests is very challenging. Wireless data broadcasting can be used to provide services to many users at the same time, so reducing the average access time has become a popular research topic. For example, some location-based services (LBS) consider using multiple channels to disseminate information to reduce access time. However, data conflicts may occur when multiple channels are used, where multiple data items associated with the request are broadcasted at about the same time. In this article, we consider the channel switching time and identify the data conflict issue in an on-demand multichannel dissemination system. We model the considered problem as a data broadcast with conflict avoidance (DBCA) problem and prove it is NP-complete. We hence propose the frequent-pattern-based broadcast scheduling (FPBS), which provides a new variant of the frequent pattern tree, FP ∗ -tree, to schedule the requested data. Using FPBS, the system can avoid data conflicts when assigning data items to time slots in the channels. In the simulation, we discussed two modes of FPBS: online and offline. The results show that, compared with the existing heuristic methods, FPBS can shorten the average access time by 30%.

ISRO’s Geostationary data products archival & dissemination – Retrospect and prospect

Natural extreme weather events have been causing excessive damage to life and property across the globe since time immemorial. Space based techniques and instruments have been improvised and utilised over the years to generate and collect earth observations data. Although a significant amount of research has led to meaningful forecasts of extreme weather events leading to minimising of the loss of life and property, the analytical approaches in this field need to be further studied and explored. Also, since every instance of earth observation is significant in multiple time domains (current as well as past which is required for climatology studies), it needs to be archived and disseminated in an organised and holistic manner. For long time preservation, modern infrastructure and underlying cutting edge technologies need to be adapted. With missions like GISAT, where the volume of data handled per day will be around 200 Mega bytes per second, multi level strategic approach for archival and high speed bandwidth for near real time data dissemination on public networks should be complemented with data broadcast to strategic users, using satellite communications. This paper describes the current infrastructure established for archival and dissemination and archival of ISRO’s Met-Ocean data observations and the future road map in the area of instantaneous data and weather alerts dissemination through an Indian broadcasting system (IMETCAST). This is to ensure timely delivery of satellite data to end users to facilitate near real time analysis of weather events.

Identifying patients with psychosocial problems in general practice: a scoping review protocol

IntroductionPsychosocial problems (PSPs) are common issues associated with negative health outcomes. Since general practitioners are the first point of contact for any health-related concern, understanding their options to recognise patients with PSPs plays an important role as it is essential for early intervention and can prevent serious conditions. The objective of our scoping review is to map published evidence on the usage of instruments to identify patients with PSPs in general practice.Methods and analysisWe will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist and the Joanna Briggs Institute Reviewer’s Manual on scoping reviews. A systematic search of four electronic databases (Medline (Ovid), Web of Science Core Collection, PsycInfo, Cochrane Library) will be conducted for quantitative and qualitative studies published in English, Spanish, French and German. Main study characteristics as well as information on identification instruments will be extracted and visualised in structured tables to map the available evidence. The protocol has been registered with Open Science Framework, https://osfio/c2m6z.Ethics and disseminationThis study does not require ethical approval as we will not collect personal data. Dissemination will consist of publications, presentations and other knowledge translation activities.