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Background The widespread nature of coronavirus disease 2019 (COVID-19) has been unprecedented. We sought to analyze its global impact with a survey on colorectal cancer (CRC) care during the pandemic. Methods The impact of COVID-19 on preoperative assessment, elective surgery, and postoperative management of CRC patients was explored by a 35-item survey, which was distributed worldwide to members of surgical societies with an interest in CRC care. Respondents were divided into two comparator groups: 1) ‘delay’ group: CRC care affected by the pandemic; 2) ‘no delay’ group: unaltered CRC practice. Results A total of 1,051 respondents from 84 countries completed the survey. No substantial differences in demographics were found between the ‘delay’ (745, 70.9%) and ‘no delay’ (306, 29.1%) groups. Suspension of multidisciplinary team meetings, staff members quarantined or relocated to COVID-19 units, units fully dedicated to COVID-19 care, personal protective equipment not readily available were factors significantly associated to delays in endoscopy, radiology, surgery, histopathology and prolonged chemoradiation therapy-to-surgery intervals. In the ‘delay’ group, 48.9% of respondents reported a change in the initial surgical plan and 26.3% reported a shift from elective to urgent operations. Recovery of CRC care was associated with the status of the outbreak. Practicing in COVID-free units, no change in operative slots and staff members not relocated to COVID-19 units were statistically associated with unaltered CRC care in the ‘no delay’ group, while the geographical distribution was not. Conclusions Global changes in diagnostic and therapeutic CRC practices were evident. Changes were associated with differences in health-care delivery systems, hospital’s preparedness, resources availability, and local COVID-19 prevalence rather than geographical factors. Strategic planning is required to optimize CRC care., Global changes in both diagnostic and therapeutic practices in colorectal cancer care were evident in this survey conducted to analyze the impact of COVID-19 outbreak. The importance of this finding is that changes were associated with differences in health care delivery systems, hospital’s preparedness, resources availability, and local COVID-19 prevalence rather than geographical variations.

Wireless sensor networks comprising nodes equipped with cameras have become common in many scenarios, providing valuable visual data for some relevant services such as localization, tracking, patterns identification and emergencies detection. In this context, algorithms and optimization approaches have been designed to perform different types of quality assessment or performance enhancement tasks, addressing challenging issues such as networking, compression, availability, reliability, security, energy efficiency and virtually any subject related to the operational challenges of those networks. However, the dynamics of coverage failures have not been properly modelled in visual sensor networks, resulting in unrealistic perceptions when optimizing or assessing quality in most visual sensing scenarios. Particularly, the Field of View of visual sensors will be affected by occlusion caused by obstacles in the monitored field, which may turn such sensors inadequate for the expected monitoring services of the considered network. Therefore, this article proposes a mathematical model to assess occlusion caused by mobile obstacles such as vehicles on a road or forklifts in an industrial plant, aiming at the selection of the visual sensor nodes that will not have their coverage significantly restricted by those obstacles. Doing so, the proposed model can be exploited by any optimization or quality assessment approach in wireless visual sensor networks, providing a preprocessing method when selecting visual nodes.

In this paper, the RT-WiFi architecture is proposed to handle real-time (RT) communication in infrastructured IEEE 802.11 networks operating in high density industrial environments. This architecture is composed of a time division multiple access (TDMA)-based coordination layer that schedules the medium access of RT traffic flows, and an underlying traffic separation mechanism that is able do handle the coexistence of RT and non-RT traffic sources in the same communication environment. The simulation assessment considers an overlapping basic service set (OBSS), where a set of RT and non-RT stations share the same frequency band. The performance assessment compares the behaviour of the RT-WiFi architecture vs. the behaviour of standard distributed coordination function (DCF), point coordination function (PCF), enhanced distributed channel access (EDCA), and hybrid coordination function (HCF) controlled channel access (HCCA) medium access control mechanisms. A realistic error-prone model has been used to measure the impact of message losses in the RT-WiFi architecture. It is shown that the proposed RT-WiFi architecture offers a significantly enhanced behaviour when compared with the use of IEEE 802.11 standard mechanisms, in what concerns average deadline misses and average access delays. Moreover, it also offers an almost constant access delay, which is a relevant characteristic when supporting RT applications.

In critical industrial monitoring and control applications, dependability evaluation will be usually required. For wireless sensor networks deployed in industrial plants, dependability evaluation can provide valuable information, enabling proper preventive or contingency measures to assure their correct and safe operation. However, when employing sensor nodes equipped with cameras, visual coverage failures may have a deep impact on the perceived quality of industrial applications, besides the already expected impacts of hardware and connectivity failures. This article proposes a comprehensive mathematical model for dependability evaluation centered on the concept of Quality of Monitoring (QoM), processing availability, reliability and effective coverage parameters in a combined way. Practical evaluation issues are discussed and simulation results are presented to demonstrate how the proposed model can be applied in wireless industrial sensor networks when assessing and enhancing their dependability.

Availability is a major design issue that should play an important role when deploying and operating wireless sensor networks, specially for critical monitoring applications. Actually, sensing redundancy can be exploited to enhance the attainable availability level of sensor networks, since redundant nodes can replace faulty nodes. When employing camera-enabled sensors, the perception of sensing redundancy is considerably changed when compared to scalar sensors, with direct impact on network availability. In such way, some characteristics as deployment density, viewing angle and sensing range should be properly evaluated in wireless visual sensor networks, in order to better estimate the network availability. Nevertheless, when deploying visual sensors on occluded environments, viewed areas and resulted overlapping may be significantly altered, redefining sensing redundancy. We then propose an algorithm to automatically select redundant nodes in wireless visual sensor networks deployed on areas with occlusion, according to network configurations and application availability requirements. Additionally, an algorithm to adjust cameras’ orientations in occluded environments is also proposed. Mathematical assessment of the proposed algorithms are performed, allowing the discussion of how parameters of deployed networks can influence applications monitoring availability.

The adoption of emergency alerting systems can bring countless benefits when managing urban areas, industrial plants, farms, roads and virtually any area that is subject to the occurrence of critical events, supporting in rescue operations and reducing their negative impacts. For such systems, a promising approach is to exploit scalar sensors to detect events of interest, allowing for the distributed monitoring of different variables. However, the use of cameras as visual sensors can enhance the detection of critical events, which can be employed along with scalar sensors for a more comprehensive perception of the environment. Although the particularities of visual sensing may be challenging in some scenarios, the combination of scalar and visual sensors for the early detection of emergency situations can be valuable for many scenarios, such as smart cities and industry 4.0, bringing promising results. Therefore, in this article, we extend a sensors-based emergency detection and alerting system to also exploit visual monitoring when identifying critical events. Implementation and experimental details are provided to reinforce the use of cameras as a relevant sensor unit, bringing promising results for emergencies management.

Wireless sensor networks have been considered as an effective solution to a wide range of applications due to their prominent characteristics concerning information retrieving and distributed processing. When visual information can be also retrieved by sensor nodes, applications acquire a more comprehensive perception of monitored environments, fostering the creation of wireless visual sensor networks. As such networks are being more often considered for critical monitoring and control applications, usually related to catastrophic situation prevention, security enhancement and crises management, fault tolerance becomes a major expected service for visual sensor networks. A way to address this issue is to evaluate the system dependability through quantitative attributes (e.g., reliability and availability), which require a proper modeling strategy to describe the system behavior. That way, in this paper, we propose a methodology to model and evaluate the dependability of wireless visual sensor networks using Fault Tree Analysis and Markov Chains. The proposed modeling strategy considers hardware, battery, link and coverage failures, besides considering routing protocols on the network communication behavior. The methodology is automated by a framework developed and integrated with the SHARPE (Symbolic Hierarchical Automated Reliability and Performance Evaluator) tool. The achieved results show that this methodology is useful to compare different network implementations and the corresponding dependability, enabling the uncovering of potentially weak points in the network behavior.

The operation of Wireless Sensor Networks (WSNs) is subject to multiple constraints, among which one of the most critical is available energy. Sensor nodes are typically powered by electrochemical batteries. The stored energy in battery devices is easily influenced by the operating temperature and the discharge current values. Therefore, it becomes difficult to estimate their voltage/charge behavior over time, which are relevant variables for the implementation of energy-aware policies. Nowadays, there are hardware and/or software approaches that can provide information about the battery operating conditions. However, this type of hardware-based approach increases the battery production cost, which may impair its use for sensor node implementations. The objective of this work is to propose a software-based approach to estimate both the state of charge and the voltage of batteries inWSN nodes based on the use of a temperature-dependent analytical battery model. The achieved results demonstrate the feasibility of using embedded analytical battery models to estimate the lifetime of batteries, without affecting the tasks performed by the WSN nodes.

Energy consumption is a major issue in Wireless Sensor Networks (WSNs), as nodes are powered by chemical batteries with an upper bounded lifetime. Estimating the lifetime of batteries is a difficult task, as it depends on several factors, such as operating temperatures and discharge rates. Analytical battery models can be used for estimating both the battery lifetime and the voltage behavior over time. Still, available models usually do not consider the impact of operating temperatures on the battery behavior. The target of this work is to extend the widely-used Kinetic Battery Model (KiBaM) to include the effect of temperature on the battery behavior. The proposed Temperature-Dependent KiBaM (T-KiBaM) is able to handle operating temperatures, providing better estimates for the battery lifetime and voltage behavior. The performed experimental validation shows that T-KiBaM achieves an average accuracy error smaller than 0.33%, when estimating the lifetime of Ni-MH batteries for different temperature conditions. In addition, T-KiBaM significantly improves the original KiBaM voltage model. The proposed model can be easily adapted to handle other battery technologies, enabling the consideration of different WSN deployments.

This paper proposes a real-time communication scheme for wireless local area network (WLAN) infrastructure. This strategy was called Group Sequential Communication (GSC). The GSC has the main goal to reduce the network overhead due to the Polling, Ack and QoS Null Frames of Hybrid Coordination Function Controlled Channel Access (HCCA) in IEEE 802.11e, because it uses a Virtual Token Passing procedure to priority the real-time communication over WLAN. In order to improve the confiability of the new scheme is presented a fault-tolerant mechanism based on Block-Ack strategy to avoid missing real-time messages. The GSC was implemented in NS2 and simulation results have proved the superior performance of GSC in comparison with HCCA for real-time industrial communications.

In this paper, a new Traffic Separation mechanism (TSm) is proposed for CSMA-based networks. The TSm mechanism is intended to be used as an underlying traffic separation mechanism, able to prioritize traffic in CSMA-based networks. It allows the coexistence of standard CSMA (non-modified) stations with TSm (modified) stations in the same communication domain. When a station implementing the TSm mechanism has a high-priority message to transfer, it will impose its transfer prior to any message from standard CSMA stations. This behavior guarantees the highest transmitting probability to the TSm-enabled station in open communication environments. Therefore, the TSm approach can be used as an underlying mechanism to build real-time communication systems upon CSMA-based networks. The behavior of the TSm mechanism was assessed by simulation in the case of a relevant CSMA-based network (IEEE 802.11). The simulation analysis shows that the TSm mechanism guarantees values for both the throughput and the average access delay that significantly improve the results obtained for standard IEEE 802.11 stations.

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X-by-wire applications have extremely demanding reliability requirements that are increasingly being addressed through the adoption of distributed and fault-tolerant architectures. The development of these applications is facilitated by the availability of high-level services such as agreement or reliable broadcast (RB). Some dependable communication buses, e.g., TTP-C, already provide these services, whereas FlexRay does not. In this paper, we present an approach to evaluate the reliability of a family of RB protocols implemented both on top of FlexRay and on top of ordinary time-division multiple access (TDMA). In particular, we evaluate the impact of the acknowledgment policy on the reliability of these protocols. We express the reliability as the probability of violation of the agreement and validity properties of the protocol during a mission. For that, we develop an analytical model based on discrete-time Markov chains, which considers a comprehensive set of faults (permanent, transient, omissive, and asymmetric) affecting both nodes and channels, and their effects on the protocol execution. The structure of the model is quite flexible and easily adaptable to other TDMA-based protocols. To assess the sensitivity of the protocol to both internal and external factors, we carried out a large number of experiments considering several network configurations and fault rates. The results show that for FlexRay, the negative-acknowledgment policy provides the same reliability as the positive-acknowledgment policy. However, for TDMA-based protocols that lack FlexRay's ability to distinguish silence from the loss of a message, the negative-acknowledgment policy leads to lower reliability, and its fitness for safety-critical applications depends on the system configuration and environment conditions.

Currently, there is a trend towards the implementation of industrial communication systems using wireless networks. However, keeping up with the timing constraints of real-time traffic in wireless environments is a hard task. The main reason is that real-time devices must share the same communication medium with timing unconstrained devices. The VTP-CSMA architecture has been proposed to deal with this problem. It considers an unified wireless system in one frequency band, where the communication bandwidth is shared by real-time and non-real-time communicating devices. The proposed architecture is based on a virtual token passing (VTP) procedure that circulates a virtual token among real-time devices. This virtual token is complemented by an underlying traffic separation mechanism that prioritizes the real-time traffic over the non-real-time traffic. This is one of the most innovative aspects of the proposed architecture, as most part of real-time communication approaches are not able to handle timing unconstrained traffic sharing the same communication medium. A ring management procedure for the VTP-CSMA architecture is also proposed, allowing real-time stations to adequately join/leave the virtual ring.

The objective of this work was to evaluate the NPK influence on yield and oil, proteins and phytochemical contents in sunflower grain and to explore the potential of mathematical model of marginal contributions of fertilization effects. The field experiment was conducted in 33 incomplete factorial model, in two randomized blocks, with 15 parcels for block. The treatments were zero, 30 and 60 kg ha-1 of N, P and K. The achene yield increased with fertilizer doses until 55 kg of N ha-1, 41 kg ha-1of K2O and 46 kg ha-1of P2O5. The achene oil content answered positively to increased K2O and P2O5. Proteins content decreases as K2O rate increases. No influence of the fertilization was observed in concentrations of chlorogenic acid, total sterols and total phosphorus on achene.O objetivo do trabalho foi avaliar a influência da adubação NPK na produtividade e teores de óleo, proteínas e fitoquímicos no girassol e explorar o potencial do modelo matemático nas contribuições marginais dos efeitos da adubação. O ensaio de campo foi conduzido em um modelo fatorial incompleto 33, em dois blocos casualizados, com 15 parcelas por bloco, onde se empregou os níveis zero, 30 e 60 kg ha-1 de N, P e K. Observou-se aumento de produtividade de aquênios com doses estimadas de até 55 kg de N ha-1, 41 kg ha-1 de K2O e 46 kg ha-1de P2O5. O teor de óleo nos aquênios aumentou com incremento de K2O e P2O5 e o teor de proteínas diminuiu com incremento de K2O. Não foram observadas influências da adubação sobre os teores de ácido clorogênio, esterois totais e fósforo total nos aquênios.

With the widespread deployment of wireless mesh networks (WMNs) in industrial environments, real-time (RT) communication may benefit from the multi-hop relaying infrastructure provided by WMNs. However, RT communication must be able to coexist with non-RT traffic sources that will interfere with RT communication. Within this context, this paper assesses the impact of interferences caused by non-RT traffic sources upon RT traffic in IEEE 802.11s mesh networks. Through an extensive set of simulations, we assess the impact of external traffic sources upon a set of RT message streams in different communication scenarios. According to the simulation results, we infer that RT traffic in 802.11s networks may be highly affected by external interferences, and therefore, such interferences must be taken into account when setting-up 802.11s networks. By varying the network load imposed by external interferences, we provide some useful hints about utilization thresholds above which the network can no longer reliably support RT traffic. We also present insights about the setting-up of some network parameters in order to optimize the RT communication performance.

Wireless sensor networks can provide valuable information for a lot of measurement, tracking, surveillance, automation, and general-purpose monitoring applications. Information as humidity, temperature, pressure, infrared images, and noises will be sensed and packetized for distribution over the network, but corruption during transmission may compromise the accuracy of the retrieved information and even put people in danger. In fact, the sensed data may have different relevancies for the applications, altering the impact of packet corruptions. We propose a relevance-based partially reliable transmission approach to provide data delivery with different reliability guaranties, exploiting the relevancies of transmitted data when choosing the proper error recovery service. In this context, some error scenarios are investigated, considering different configurations of error bursts. We expect that the proposed partially reliable transmission mechanism can save energy over the network while assuring acceptable quality for sensing monitoring.

Wireless visual sensor networks have been considered for a large set of monitoring applications related with surveillance, tracking and multipurpose visual monitoring. When sensors are deployed over a monitored field, permanent faults may happen during the network lifetime, reducing the monitoring quality or rendering parts or the entire network unavailable. In a different way from scalar sensor networks, camera-enabled sensors collect information following a directional sensing model, which changes the notions of vicinity and redundancy. Moreover, visual source nodes may have different relevancies for the applications, according to the monitoring requirements and cameras' poses. In this paper we discuss the most relevant availability issues related to wireless visual sensor networks, addressing availability evaluation and enhancement. Such discussions are valuable when designing, deploying and managing wireless visual sensor networks, bringing significant contributions to these networks.

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks.

In several monitoring applications, such as those that can be found in industrial factory floor, it may be necessary to obtain an uniform sensing coverage, providing as much as possible the same coverage degree for the entire network area. The IEEE 802.15.4 has become an important standard in wireless sensor networks. However, the use of cluster-tree topology in these networks hampers a fair and uniform coverage in the sensing area. Clusters more distant from the base station are eventually adversely affected, with messages from its sensors delayed and discarded. In this paper, we propose a framework, entitled GLHOVE, whose goal is to make a trade-off between a minimum and uniform coverage area and the energy consumption of the network. The simulation results show an increase up to 20% of the fairness metric (w.r.t. messages received by base station). (c) 2013 IEEE.

Camera networks have been considered for a large set of visual monitoring applications. For some of them, cameras may be continuously monitoring scenes or groups of targets, but some events may trigger a critical level of visual monitoring, as in public security, industrial automation, and response to natural disasters. In such way, some critical events as a bomb explosion, a volcanic eruption, forest wildfire, or a car accident must be captured with high relevance, potentially helping when identifying responsibilities and during rescue operations. New relevance levels, which can be reflected in higher quality of transmitted images or video streams or even higher priority during transmission over the network must be quickly assigned to cameras that can view the critical events. In this work we propose a methodology to dynamically assign relevancies to cameras that view the area of critical events, employing scalar sensors and a decentralized decision mechanism. The resulting multimodal camera network can considerably enhance the critical surveillance in different monitoring applications. We propose some optimizations that exploit the monitoring relevance in such scenarios.

This paper proposes a new real-time communication scheme for 802.11e wireless networks. This scheme is called Group Sequential Communication (GSC). The GSC improves the efficiency of the Hybrid Coordination Function Controlled Channel Access (HCCA) mechanism by reducing the protocol overheads of the 802.11e amendment. The GSC approach eliminates the polling scheme used in traditional scheduling algorithm, by means of a virtual token passing procedure among members of the real-time group to whom is granted a high-priority and sequential access to communication medium. In order to improve the reliability of the proposed scheme, it is also proposed an error recovery mechanism based on block acknowledgment. The GSC was implemented in network simulator software and the performance results were compared to HCCA scheme, showing the efficient of the proposed approach when dealing with traditional industrial communication scenarios.

Wireless sensor networks may be deployed to retrieve visual information from the monitored field, enriching monitoring and control applications. Whenever a set of camera-enabled sensor nodes are deployed for time-critical monitoring, visual information as still images and video streams may need to reach the sink as soon as possible, requiring a differentiated treating of the network when compared with non-critical visual data. In such way, considering that source nodes may have different sensing relevancies for the application, according to the desired monitoring tasks and the current sensors' poses and fields of view, we propose a delay-aware multihop routing mechanism where higher relevant visual data packets are routed through paths with lower end-to-end delay. As sensor nodes are expected to be energy-constrained, transmitting only high-relevant packets through shorter/faster paths may prolong their lifetime and assure longer time-critical delivering, with low impact to the overall monitoring quality.

We present reliability models for a group membership protocol designed for TDMA networks such as FlexRay, a protocol that is likely to become the de facto standard for next generation automotive networks. The models are based on discrete-time Markov chains and consider a comprehensive set of fault scenarios. Furthermore, they are parametric allowing for a sensitivity analysis. The results, obtained by a numeric solution of the models using the PRISM model-checker, show that they are computationally practical for realistic configurations and that the GMP can achieve reliability levels in the range required for safety critical applications.

The purpose of this paper is to survey the state-of-the-art on real-time (RT) communication in CSMA-based networks and to identify the most suitable approaches to deal with the requirements imposed by next generation communication environments. The paper focuses in the two of the most relevant solutions that operate in shared broadcast environments, according to the CSMA medium access protocol (IEEE 802.3/802.11). RT communication solutions are classified according to two classification axes. The first axis is related to how collisions are dealt with. A second classification axis is related to the compatibility degree achieved by each of the proposed approaches. Finally, a RT communication framework that is adequate to support RT communication in shared environments is briefly discussed.

In this paper, we propose the VOA algorithm (Variable Offset Algorithm) to deal with the optimization of communication efficiency in dense WSN s with star topologies. The use of the VOA algorithm has been assessed by means of an experimental setup. The results highlight that the use of the VOA algorithm, implemented as a light middleware at the application layer, clearly enhances the communication efficiency in a WSN with star topology. Â(c) 2010 IEEE.

Characterization of the behaviour of link-layer retransmissions is helpful when designing MAC protocols and scheduling algorithms for Factory Automation WLANs. In this paper, we measure retransmission rates and consecutive retransmission occurrences of IEEE 802.11g communication links in an industrial indoor environment. The employed wireless channel at 2.4 GHz is characterized. Experimental results show that the distribution of consecutive retransmission occurrences tends to concentrate around just one retry when devices operate within their transmission range. It is also shown that smaller frames result in fewer retransmissions.