Communication Metrics Research Articles

Is internet a missed opportunity? Evaluating radon websites from a stakeholder engagement perspective

Exposure to indoor radon, a naturally occurring radioactive gas, is one of the main causes of lung cancer worldwide. Although radon tests are easily accessible in most countries, and protective actions are effective and relatively easy to apply, the levels of radon testing and subsequent home remediation remain lower than aimed for. Public engagement, particularly through internet, may contribute to addressing this value-action gap. Given their role as common interaction points between citizens and public services, this research analyzed radon websites from a stakeholder engagement perspective. The rich database assembled, of websites in eight European countries with highly radon prone areas, provides for the empirical novelty of the study. The website evaluation relied on internet communication metrics adapted for radon risk mitigation. This included availability of radon information, accessibility, stakeholder interaction, dialogue, responsiveness, content and design, and transparency and openness. Unexpectedly, results show that availability of radon information on the internet in radon prone areas is often limited and poor, as for instance only three internet pages dedicated to radon have been found. Radon websites should be improved with consistent information supported by engaging stories, provide for personalized features, support stakeholder feedback and dialogue, and include the use of social media. We conclude by consolidating the analysis into a list of recommendations for health communication practitioners, which should support radon risk mitigation, and contribute to improving public health, particularly decreasing the numbers of lung cancers. The effect of radon information available on internet pages on changing protective behaviors is suggested for future research.

Supporting informed decision-making about vaccination: an analysis of two official websites

ObjectiveTo analyze the content of two official French-speaking websites that are used to inform the general public about recommended vaccines in France and Quebec. Study designQualitative content analysis. MethodsAll pages that inform and educate parents regarding childhood vaccination were downloaded and analyzed according to evidence-informed risk communication metrics. ResultsA total of 32 webpages, 14 videos, and two infographics were included in the analysis. The following were the most frequent risk communication approaches: ‘debunking common misconceptions about vaccination’ or ‘answering common questions about vaccines.’ Harm and benefit information focused primarily on the risks of vaccine-preventable diseases and the risks of adverse events after immunization. Most materials used qualitative terminology to describe the risk (e.g., vaccines are among the safest tools, adverse events are rare). Very few materials provided numeric likelihood of harms and benefits. When numeric information was stated, they were only presenting the risks of the diseases or number of cases in an outbreak. The approaches used to debunk misconceptions generally focused on the myth itself rather than the correct information. Few materials used visual aids (e.g., graphics, pictures, icons arrays, etc.) to convey important information. ConclusionsIt is often assumed that misinformation and rumors about vaccination found online is a leading cause of the increase in vaccine hesitancy. Existing communication materials could be improved to better align with best practices in risk communication. Given the availability of confusing and conflicting vaccine narratives, it is crucial that authoritative communication materials aim to build trust and support informed choices about vaccination.

Deciphering well connectivity with diagnostic signal processing techniques

Data mining has become increasingly crucial in deciphering reservoir dynamics, given that operators currently acquire an enormous amount of data. These data contain valuable information about subsurface processes. Interwell connectivity is one of the most significant aspects of subsurface characterization that can impact a project's success. In this study, we present novel techniques to quantify and monitor interwell communication by applying signal processing methods to observe and derive well-based measurements. A large dataset from the Permian Basin constituted the primary content of this investigation.We constructed a suite of realistic reservoir models under varying conditions involving multiple producing and water injection wells. More than 40 static and dynamic parameters including permeability, porosity, water saturation, fluid properties, and rock-fluid interaction terms are varied using experimental designs to capture realistic uncertainty. Waterflood scenarios are modeled using streamline simulation to infer injector-producer pair connectivity, pattern allocations, drainage efficiency, and their evolution period. These injector-producer variables are analyzed using numerous signal processing methods, including cross-correlation, time-lag correlation coefficient, coherence, and periodogram, among others. Well variables examined involve pressure, rate, and their derivative functions.The objectives of this study include: (1) Examining and devising several signal-processing techniques; (2) Identifying informative well data to provide information of communication between injectors and producers over time; (3) Deducing connectivity measures and systematically evaluate their efficacy in characterizing subsurface connectivity picture.The approaches reveal new insights into determining reservoir communication metrics. The proposed methods have the potential for implementation in the automated virtual flow-metering system. These methods also helped identifying the predominant injector-producer pairs and making operational decisions at any stage of any waterflood and enhanced recovery projects.

Design of a Physical Layer Encryption Scheme for Rate Compatible Modulation

Spectral efficiency and transmission security are both essential metrics for wireless communication. Rate compatible modulation (RCM) is an adaptive transmission scheme to improve the spectral efficiency. However, the mapping matrix of RCM is fixed. Once the mapping matrix is known to eavesdroppers, information will be leaked. Physical layer encryption (PLE) is a secure approach to enhance the security using encryption at physical layer. In this paper, we propose a secure transmission scheme for RCM, namely, secure RCM (S-RCM). The construction method of RCM mapping matrix is of great random. Combined with PLE, S-RCM mainly uses the secret key extracted from the channel information to generate mapping matrix. Due to the randomness of channel, the mapping matrix will also be random. Security analysis shows that the demapping of S-RCM must be based on the right mapping matrix. It also shows that S-RCM owns extremely large cipher mapping matrix space, which makes it impossible for eavesdropper to guess the mapping matrix. Furthermore, known-plaintext attack (KPA) is hardly impossible to get the mapping matrix due to the high calculations and multiple possibilities. Simulation result shows that the S-RCM have the same throughput performance and bit error rate (BER) performance as RCM. In addition, the simulation results also show that eavesdropper faces extremely high complexity, which is thought safe.

Beamforming Galvanic Coupling Signals for IoMT Implant-to-Relay Communication

Implants are poised to revolutionize personalized healthcare by monitoring and actuating physiological functions. Such implants operate under challenging constraints of the limited battery energy, heterogeneous tissue-dependent channel conditions, and human-safety regulations. To address these issues, we propose a new cross-layer protocol for galvanic coupled implants, wherein the weak electrical currents are used in place of classical radio frequency links. As the first step, we devise a method that allows multiple implants to communicate individual sensed data to each other through code division multiple access, combined with compressive sensing method to lower the transmission time and save energy, as well as delegates the computational burden of dispreading and decoding only to the on-body surface relays. Then, we devise a distributed beamforming approach that allows coordinated transmissions from the implants to the relays by considering the specific tissue path chosen and tissue heating-related safety constraints. We then proceed to implement distributed beamforming on a phantom of human tissue and prove an increase in received signal strength and a decrease in BER due to constructive interference of the signals of each implant. Our contributions are twofold: First, we devise a collision-free protocol that prevents undue interference at neighboring implants, especially for multiple deployments. Second, this is the first application of near-field distributed beamforming in human tissue. Simulation results reveal significant improvement in the network lifetime for implants of up to 79% compared to the galvanic coupled links without beamforming. In addition, the implementation of phantom tissue proves improved communication metrics when beamforming is used.

A Hash-Based RFID Authentication Mechanism for Context-Aware Management in IoT-Based Multimedia Systems.

With the technological advances in the areas of Machine-To-Machine (M2M) and Device-To-Device (D2D) communication, various smart computing devices now integrate a set of multimedia sensors such as accelerometers, barometers, cameras, fingerprint sensors, gestures, iris scanners, etc., to infer the environmental status. These devices are generally identified using radio-frequency identification (RFID) to transfer the collected data to other local or remote objects over a geographical location. To enable automatic data collection and transition, a valid RFID embedded object is highly recommended. It is used to authorize the devices at various communication phases. In smart application devices, RFID-based authentication is enabled to provide short-range operation. On the other hand, it does not require the communication device to be in line-of-sight to gain server access like bar-code systems. However, in existing authentication schemes, an adversary may capture private user data to create a forgery problem. Also, another issue is the high computation cost. Thus, several studies have addressed the usage of context-aware authentication schemes for multimedia device management systems. The security objective is to determine the user authenticity in order to withhold the eavesdropping and tracing. Lately, RFID has played a significant for the context-aware sensor management systems (CASMS) as it can reduce the complexity of the sensor systems, it can be available in access control, sensor monitoring, real time inventory and security-aware management systems. Lately, this technology has opened up its wings for CASMS, where the challenging issues are tag-anonymity, mutual authentication and untraceability. Thus, this paper proposes a secure hash-based RFID mechanism for CASMS. This proposed protocol is based on the hash operation with the synchronized secret session-key to withstand any attacks, such as desynchronization, replay and man-in-the-middle. Importantly, the security and performance analysis proves that the proposed hash-based protocol achieves better security and performance efficiencies than other related schemes. From the simulation results, it is observed that the proposed scheme is secure, robust and less expensive while achieving better communication metrics such as packet delivery ratio, end-to-end delay and throughput rate.

Genetic algorithm based adaptive offloading for improving IoT device communication efficiency

Improving the communication of Internet of Things (IoT) network is a challenging task as it connects a wide-range of heterogeneous mobile devices. With an extended support from cloud network, the mobile IoT devices demand flexibility and scalability in communication. Increase in density of communicating devices and user request, traffic handling and delay-less service are unenviable. This manuscript introduces genetic algorithm based adaptive offloading (GA-OA) for effective traffic handling in IoT-infrastructure-cloud environment. The process of offloading is designed to mitigate unnecessary delays in request process and to improve the success rate of the IoT requests. The fitness process of GA is distributed among the gateways and infrastructure to handle requests satisfying different communication metrics. The process of GA balances between the optimal and sub-optimal solutions generated to improve the rate of request response. Experimental results prove the consistency of the proposed GA-OA by improving request success ratio, achieving lesser complexity, delay and processing time.

On the Strength of Privacy Metrics for Vehicular Communication

Vehicular communication plays a key role in near-future automotive transport, promising features such as increased traffic safety and wireless software updates. However, vehicular communication can expose drivers' locations and thus poses privacy risks. Many schemes have been proposed to protect privacy in vehicular communication, and their effectiveness is usually evaluated with privacy metrics. However, to the best of our knowledge, (1) different privacy metrics have never been compared to each other, and (2) it is unknown how strong the metrics are. In this paper, we evaluate and compare the strength of 41 privacy metrics in terms of four novel criteria: Privacy metrics should be monotonic, i.e., indicate decreasing privacy for increasing adversary strength; their values should be spread evenly over a large value range to support within-scenario comparability; and they should share a large portion of their value range between traffic conditions to support between-scenario comparability. We evaluate all four criteria on real and synthetic traffic with state-of-the-art adversary models and create a ranking of privacy metrics. Our results indicate that no single metric dominates across all criteria and traffic conditions. We therefore recommend to use metrics suites, i.e., combinations of privacy metrics, when evaluating new privacy-enhancing technologies.

Self-Sustainable Dense Cellular M2M System With Hybrid Energy Harvesting and High Sensitivity Rectenna

The Internet of Things (IoT) is envisioned as an essential enabler of the smart city, which 5G small cell is going to cover. In this paper, we model the dense cellular M2M communication system using a Ginibre determinant point process and study the corresponding green communication metrics, including grid energy consumption and grid energy efficiency (EE). A dedicated millimeter-wave-based hybrid energy harvesting (EH) mechanism is proposed to maintain self-sustainable communication. Two EH modes are discussed, of which Mode 1 is suitable for long-term operation, while Mode 2 is preferred in dealing with a temporary energy shortage. We first minimize the average grid energy consumption by solving a large-scale linear programming problem. When the battery at machine device is charged with sufficient energy at the initial time, closed-form formula describing the average grid energy consumption of both the modes can be derived under moderate throughput constraints, which is proved to have clear relationship with 1) initial battery energy level at machine gateway and machine device; 2) specific hybrid EH time-division strategy; 3) system operation time; and 4) static power consumption at machine gateway and machine device. The numerical solutions are obtained using the interior-point method, and the results are illustrated and discussed. When dealing with the originally non-convex EE maximization problem, we first transform it into a series of sub-problems using the successive convex approximation method and then iteratively solve them with a trick combining Taylor expansion and square error minimization. Non-orthogonal multi-access (NOMA) transmission is investigated in our model to further improve the EE performance. The experiments show that NOMA achieves nearly three times throughput promotion and two times EE improvement.

Opportunities and Challenges in Health Sensing for Extreme Industrial Environment: Perspectives From Underground Mines

Occupational health and safety hazards in the extreme work environment of underground mines remained a serious concern for both mine management and regulatory agency. Miners are often employed to perform different mining activities across the mine and are always exposed to health risks such as lung cancer. With the technology advancements, it is now possible to keep track of mine individuals and their health parameters. The current practice of health analysis is periodic in nature and is highly dependent on voluntary participation. Wearable health sensing system is an alternative solution to overcome these challenges and is able to provide insights on miners’ health conditions. Timely analysis of physiological parameters of the miners is immensely helpful to minimize the injuries and can also provide preventive measures for potential health hazards. In this paper, we propose a wireless health monitoring system, especially for underground mines. The contributions of this paper are twofold. First, it presents and discusses our proposed system architecture and solution followed by challenges of such system in the context of underground mines. Second, as a preliminary analysis, detailed discussion on the wireless link behavior for reliable data transmission and communication are presented. We performed real-world experimental measurements in an operational underground coal mine considering several deployment settings in straight, near face and curved mine galleries. The communication metrics (e.g., received signal strength and packet reception rate) are extensively evaluated.

Nursing Unit Communication During a US Public Health Emergency: Natural Experiment.

BackgroundIn the second half of 2014, the first case of Ebola virus disease (EVD) was diagnosed in the United States. During this time period, we were collecting data for the Measuring Network Stability and Fit (NetFIT) longitudinal study, which used social network analysis (SNA) to study relationships between nursing staff communication patterns and patient outcomes. One of the data collection sites was a few blocks away from where the initial EVD diagnosis was made. The EVD public health emergency during the NetFIT data collection time period resulted in the occurrence of a natural experiment.ObjectiveThe objectives of the NetFIT study were to examine the structure of nursing unit decision-making and information-sharing networks, identify a parsimonious set of network metrics that can be used to measure the longitudinal stability of these networks, examine the relationship between the contextual features of a unit and network metrics, and identify relationships between key network measures and nursing-sensitive patient-safety and quality outcomes. This paper reports on unit communication and outcome changes that occurred during the EVD natural disaster time period on the 10 hospital units that had data collected before, during, and after the crisis period.MethodsFor the NetFIT study, data were collected from nursing staff working on 25 patient care units, in three hospitals, and at four data collection points over a 7-month period: Baseline, Month 1, Month 4, and Month 7. Data collection was staggered by hospital and unit. To evaluate the influence of this public health emergency on nursing unit outcomes and communication characteristics, this paper focuses on a subsample of 10 units from two hospitals where data were collected before, during, and after the EVD crisis period. No data were collected from Hospital B during the crisis period. Network data from individual staff were aggregated to the nursing unit level to create 24-hour networks and three unit-level safety outcome measures—fall rate, medication errors, and hospital-acquired pressure ulcers—were collected.ResultsThis analysis includes 40 data collection points and 608 staff members who completed questionnaires. Participants (N=608) included registered nurses (431, 70.9%), licensed vocational nurses (3, 0.5%), patient care technicians (133, 21.9%), unit clerks (28, 4.6%), and monitor watchers (13, 2.1%). Changes in SNA metrics associated with communication (ie, average distance, diffusion, and density) were noted in units that had changes in patient safety outcome measures.ConclusionsUnits in the hospital site in the same city as the EVD case exhibited multiple changes in patient outcomes, network communication metrics, and response rates. Future research using SNA to examine the influence of public health emergencies on hospital communication networks and relationships to patient outcomes is warranted.

A Softwarized Paradigm for Mobile Virtual Networks: Overcoming a Lack of Access Infrastructure

Market analysis reports suggest that the mobile virtual network operator (MVNO) market will experience subscriber growth at a compound annual growth rate (CAGR) of 10.7% from 2014 to 2020. This optimistic news presents great opportunities as well as many challenges. The major issue lies in the MVNOs' lack of spectrum allocation and an end-to-end network infrastructure, which means they must rely on mobile network operators (MNOs) for wireless access network connectivity to service their customers. In this article, we propose an approach that provides alternative wireless access methods to enable MVNOs to minimize their dependency on MNO networks. This leverages the fifth-generation (5G) softwarization technologies to provide selective multipath device-to-infrastructure (D2I) connections and service assortments. Supervised by software-defined networking (SDN)-based edge controllers, the multipath D2I connections provide flexible user data delivery over available communication resources without strict consideration of the MNO's infrastructure restraints. Additionally, a priority-based classification policy is applied to user data providing service assortments before it reaches the network infrastructure. Multiple pilot scenarios are implemented to verify the feasibility and performance tradeoff between the communication metrics of the proposed approach.

Experimental investigation of wind and temperature induced scintillation effect on optical wireless communication link

Atmospheric disturbances due to randomly distributed wind flow and temperature results in fluctuation of intensity as well as in the phase of the received light signal, impairing an optical wireless link performance. In this work, turbulence-induced scintillation on Optical Wireless Communication (OWC) is investigated experimentally on the basis of optimized signal wavelength, link length and launched power level. To mimic the outdoor environmental conditions, an indoor chamber equipped with fans and heating coil is made up, which gives manual control of the temperature and wind velocity within the chamber. The received signal bearing data rate of 100 Mbps is measured after traversing through the designed chamber and used to characterize the turbulence strength in terms of scintillation index (S.I.). To establish a long-range OWC link, the atmospheric channel length is increased using round-trip reflection by placing plane front surface mirrors at both ends of the chamber, also front concave mirror is used to collect distributed irradiance onto aperture area of the detector at the receiver. Experimentally, we have tried to characterize the combined effect of the wind and the temperature on the free space communication system. Various communication metrics like bit error rate (BER), signal to noise ratio (SNR) and Q factor have been evaluated and it is reported that the BER performance of an OWC link having wind flow of 15 km/h gets degraded by 109 as compared to still air.

57 Improving the Safety and Quality of Inter-Hospital Transfer for Nontraumatic Intracerebral and Subarachnoid Hemorrhage

Patients with nontraumatic intracranial hemorrhage (ICH, including intracerebral or subarachnoid hemorrhage) often require inter-hospital transfer (IHT) for subspecialty care. IHT involves multiple care transitions that harbor safety threats and quality gaps, yet few studies have implemented and evaluated interventions to improve this process. We re-engineered the IHT process at our institution for patients with nontraumatic ICH and implemented a multi-modal intervention that standardized clinical care goals and enhanced inter-disciplinary communication. We examined the impact of this intervention on process metrics, communication during transition periods, and the timeliness/effectiveness of care. Robust pre-intervention problem analysis identified several safety threats in this patient population. Guided by these results, we instituted a multi-modal intervention in May 2017 that included: 1) statewide clinical guideline dissemination, 2) standardization of the IHT acceptance process, 3) implementation of a patient arrival notification system, and 4) EMR enhancements. The intervention was evaluated through an EMR-based dashboard, case-by-case audit and feedback, and content analysis of IHT calls. We performed pre/post-intervention descriptive statistics analysis. The primary outcomes were a set of quality and safety measures: 1) process outcomes (ED length of stay [LOS], time to admit order, and ED boarding), 2) inter-departmental coordination/communication (% of times consulting services were notified upon patient arrival, % of times an ED attending to NICU attending conversation occurred), and 3) timeliness/effectiveness outcomes (adequate blood pressure control, and time to reversal of anticoagulation). The interventions resulted in significant improvements in the process of care: ED LOS (300 to 149 minutes, p<.01), ED time to admission order (66 to 20 minutes, p<.05) and ED boarding time (218 to 92 minutes, p<.01). Inter-departmental communication was enhanced: the percentage of IHT in which consult services were notified upon patient arrival improved from 38% to 91% (p < .05); additionally, a NICU attending discussed the care plan with the ED attending before the patient arrived in 64% of transfers post-intervention compared to 10% pre-intervention (p < .05). Timeliness/effectiveness improvements were noted in the reduction of time to anticoagulation reversal, though this was not statistically significant (217 to 165 minutes, p = 0.53). There was no significant difference in blood pressure control (86% to 80% with adequate BP control, p = 1). Decreased mortality was noted, though this was not statistically significant (27% to 14%, p = 0.26) The implementation of a large-scale multi-modal intervention significantly improved process and communication metrics associated with IHT for patients with nontraumatic ICH and resulted in a trend towards improvement in the timeliness and effectiveness of clinical care. Future research should explore the relationship between process improvement and more rare clinical outcomes, as our study was not powered to detect such differences. Our approach may be scalable to other critical care entities and achieve greater impact on the overall safety and quality threats related to the IHT process at large.

Receiver Techniques for Diffusion-Based Molecular Nano Communications Using an Adaptive Neuro-Fuzzy-Based Multivariate Polynomial Approximation

Molecular communication (MC) nanonetworks, the interconnection of biological nanomachines (Bio-NMs), are envisaged to significantly expand the applications of nano-technology in the areas of the biomedical, material science, and electrical engineering. In this paper, we consider the scenario of a diffusion-based molecular communication (DMC) system that is a promising bio-inspired approach to implementing nanonetwork systems. Considering the limited computation capability, ultra-low energy assumption, and expensive information exchange cost among Bio-NMs, this paper proposes a pulse-based demodulation scheme in three biologically inspired techniques for the detection of the molecular pulses: 1) a multivariate polynomial approximation (MPA) scheme; 2) an adaptive fuzzy threshold-based detection (AFTD) scheme; and 3) an adaptive neuro-fuzzy-based MPA (ANF-MPA) scheme. These methods are suitable for binary ON- OFF keying (BOOK signaling), where the Rx Bio-NM adapts the 1/0-bit detection threshold based on the previously received bits that help to alleviate the inter-symbol interference (ISI) problem resulting from residual (tail) diffusion molecules arriving at the receiver due to past bit transmissions and reception noise. To evaluate the performance of DMC systems, the essential communication metrics in each detection scheme are identified, and the numerical results are obtained and validated by MATLAB simulation. Moreover, the complexity of the proposed schemes is calculated, and the performance evaluation in various noisy channel sources shows a promising improvement in the un-coded bit error rate (BER) performance compared with the threshold detection schemes in the literature. These results provide insights that may guide the implementation of future DMC nanonetworks.

Communication training for inter‐specialty clinicians

Inter-specialty clinicians often co-lead family conferences for hospitalised patients. Families frequently report receiving different messages from different clinicians. We developed a communication training workshop that crosses disciplines and co-trains clinicians in one setting to create a culture of delivering a unified message. We developed a 2-day paediatric communication skills workshop to teach the skills necessary to conduct a family conference. The workshop was targeted at nurse-practitioners and faculty clinicians representing the different specialties that co-manage children in an intensive care unit. Our primary outcomes were learner self-assessment of skills attainmentand workshop satisfaction. We also evaluated the feasibility ofrecruiting busy clinicians. Fifteen clinicians, including eight critical care faculty members (80% of eligible participants), three subspecialty faculty members (100% of eligible participants) and four nurse-practitioners (100% of eligible participants), participated. Learners' self-reported confidence improved in all communication metrics assessed. From pre- to post-workshop, confidence increased from 39% to 94% for 'giving bad news' (p < 0.05), from 50% to 83% for 'conducting a family conference' (p < 0.05), and from 39% to 100% for 'eliciting a family's values/preferences (p < 0.05). Every learner rated the workshop as important to their clinical practice and 100% would strongly recommend it to others. All reported the time commitment was not burdensome and 74% would choose this 2-day format over shorter formats. When clinicians learn together, they are more likely to speak the same language when communicating with each other, and ultimately to deliver the same message to families CONCLUSIONS: An inter-specialty communication training workshop for different types of clinician was well received. It is feasible to co-train different types of clinician in a joint session. When clinicians learn together, they are more likely to speak the same language when communicating with each other, and ultimately to deliver the same message to families.

Modeling a Composite Molecular Communication Channel

This paper deals with development of diffusive propagation model for molecular communication in composite biological microenvironments with multiple regions (or layers) each with distinct diffusion properties to understand the transport of information molecules. We propose generalized analytical and simulation approaches for modeling a composite, diffusive, and molecular communication channel for arbitrary placement of the transmitting and receiving nano-machines. We derive a generalized closed-form expression for the channel impulse response of a three dimensionally (3-D) diffusive medium that has “N” regions. The results from the proposed particle-based simulator are validated with the exact analytical solution. The pulse peak amplitude, pulse peak time, and pulse width are derived to evaluate the system performance using both analytical and simulation approaches. It is shown that the channel impulse response and other communication metrics are significantly affected by the diffusion coefficients, region thickness, interface properties, and the positions of transmitter and receiver nano-machines with respect to the interfaces.

Measuring regional impact: The case for bigger data

Measuring regional impact: The case for bigger data

Towards automated assessment of team performance by mimicking expert observers\u2019 ratings

Automation is the holy grail of performance assessment. Cheap and reliable automated systems that produce consistent feedback on performance. Many such systems have been proposed that accurately measure the state of a product or the outcome of a process. Procedural faults can be detected and even mitigated without the need for human interference. In production industry and professional sports, this is a natural part of business. However, in macrocognitive team performance studies, human appraisal is still king. This study investigates the reliability of human observers as assessors of performance among virtual teams, and what they base their assessments on when only able to monitor one of the team members at a time. The results show that expert observers put a lot of emphasis on task outcomes and on communication and are generally reliable raters of team performance, but there are several aspects that they cannot rate reliably under these circumstances, e.g., team workload, stress, and collaborative problem-solving. Through simple algorithms, this study shows that by capturing task scores and different quantitative communication metrics, team performance ratings can be estimated to closely match how the expert observers assess team performance in a virtual team setting. The implication of the study is that numeric team performance estimations can be acquired by automated systems, with reasonable accuracy and reliability compared to observer ratings.

Understanding Performance and Verbal-Communication of Children with ASD in a Collaborative Virtual Environment.

Collaborative virtual environments (CVEs), which allow naturalistic communication between two or more individuals in a shared virtual environment, hold promise as a tool for measuring and promoting social communication between peers. In this work, a CVE platform and a set of CVE-based collaborative games are designed for children with autism spectrum disorder (ASD). Two groups (7 ASD/TD pairs; 7 TD/TD pairs) participated in a pilot study to establish system feasibility and tolerability. We also designed a methodology for capturing meaningful metrics of social communication. Based on these metrics, we found improved game performance and trends in communication of these participants over time. Although preliminary, these results provide important insights on CVE-based interaction for ASD intervention.