The Delay Measurement and Analysis of Unreachable Hosts of Internet

Delay related metrics are significant quality of service criteria for the performance evaluation of networks. Almost all delay related measurement and analysis studies take into consideration the reachable sources of Internet. However, unreachable sources might also shed light upon some problems such as worm propagation. In this study, we carry out a delay measurement study of unreachable destinations and analyse the delay dynamics of unreachable nodes. 2. Internet Control Message Protocol (ICMP) destination unreachable Internet Control Message Protocol-Destination Unreachable (ICMP T3) packets are considered for the delay measurement according to their code types which shows network un reach ability, host un reach ability, port un reach ability, etc. Measurement results show that unreachable sources exhibit totally different delay behaviour compared to reachable IP hosts. A significant part of the unreachable hosts experiences extra 3 seconds Round Trip Time (RTT) delay compared to accessible hosts mostly due to host un reach ability. It is also seen that, approximately 79% of destination un reach ability causes from host un reach ability. Obtained Hurst parameter estimation results reveal that unreachable host RTTs show lower Hurst degree compared to reachable hosts which is approximately a random behaviour. Unreachable sources exhibit totally different distributional characteristic compared to accessible ones which is best fitted with Phased Bi-Exponential distribution.

Female forest owners as a market segment? Results from a marketing experiment in the context of a small forest service enterprise

Broad social changes are reflected in the forest owner structure, which has become increasingly diverse both demographically and in terms of objectives and values. This naturally also impacts forest owners’ interest towards using their forests as well as to their interest in purchasing various forest management services. This development highlights the need for service providers to better segment their clientele and plan their market communication accordingly. However, a surprisingly small amount of research has focused on the impact of marketing arguments for various forest owner segments. This study provides a first attempt to analyse, through a real-life marketing intervention, how effective marketing arguments are at promoting first thinning to female forest owners. For this, three marketing messages were created and sent out to 300 forest owners in Finland. One message explained the importance of first thinning to provide maximal economic income from forests, one explained the importance of first thinning in relation to biodiversity protection and climate change mitigation, and a control message included no value arguments. The results indicate that contrary to our hypothesis, the marketing message with the economic arguments raised more interest towards the first thinning service among female forest owners than the one with biodiversity protection and climate change mitigation values. The results further show that the control message was found to generate the least interest towards first thinning. This indicates that incorporating value arguments do improve the impact of a marketing message. Key words Market segmentation, female forest owner, marketing argument, economic values, biodiversity values

Smurf as Spoof Type Attacking Activity on Network and Neutralization

Reliable and timely detection of cyberattacks is becoming indispensable for securing networks and systems. Internet Control Message Protocol (ICMP) flood attacks continue to be one of the most serious threats in both IPv4 and IPv6 networks. There are various types of cybersecurity attacks based on ICMP protocols. Many ICMP protocols are very similar, so security managers might think they might have the same impact on the victim’s computer systems or servers.

Influences of study design on the effectiveness of consensus messaging: The case of medicinal cannabis

This study examines to what extent study design decisions influence the perceived efficacy of consensus messaging, using medicinal cannabis as the context. We find that researchers’ decisions about study design matter. A modified Solomon Group Design was used in which participants were either assigned to a group that had a pretest (within-subjects design) or a posttest only group (between-subjects design). Furthermore, participants were exposed to one of three messages—one of two consensus messages or a control message—attributed to the National Academies of Sciences, Engineering and Medicine. A consensus message describing a percent (97%) of agreeing scientists was more effective at shifting public attitudes than a consensus message citing substantial evidence, but this was only true in the between-subject comparisons. Participants tested before and after exposure to a message demonstrated pre-sensitization effects that undermined the goals of the messages. Our results identify these nuances to the effectiveness of scientific consensus messaging, while serving to reinforce the importance of study design.

Tense of Psychological Distancing Self Talk and Test Performance Among GT High School Students

Test taking is ubiquitous in academic life. Often, a student’s desire to perform well in these evaluative situations leads them to experience test-anxiety. However, test-anxiety has been repeatedly correlated with reduced test performance. Research suggests that reappraisal interventions promote the reduction of test anxiety which may result in improved test performance. But can linguistic tense mediate the effect of these interventions? If so, are these interventions helpful for GT students for whom test anxiety is a significant concern? This intervention study tested whether reading a message containing a type of reappraisal technique, objective psychological distancing, in a certain linguistic tense could reduce test anxiety and improve test performance for high school GT algebra students. Two hours before taking an exam, students read one of three messages: a first-person distancing, a third-person distancing, or a control message. There existed a slight improvement in student test performance from the control condition to the distancing conditions, yet this trend was not statistically significant.

Investigating the Potential of Inoculation Messages and Self-Affirmation in Reducing the Effects of Health Misinformation

We investigated the effectiveness of inoculation and self-affirmation interventions in neutralizing effects of health misinformation. Women ( N=854) recruited via Prolific were randomly assigned to self-affirm (or not) and read an inoculation (versus control) message detailing five common attributes of misinformation. All participants read an article with misinformation about breast cancer screening and reported their reactions to the article. The inoculation (vs control) message reduced the negative effects of misinformation, as assessed by resistance-related measures, attitudes, and intentions. Experimentally induced self-affirmation did not show protective effects against misinformation, but the inoculation intervention was stronger among participants higher in self-reported spontaneous self-affirmation.

A Decentralized Economic Load-Balancing Framework among Federated Cloudlets

Edge computing servers like cloudlets from different service providers compensate scarce computational and storage resources of mobile devices, are distributed across access networks. However, the dynamically varying computational requirements of associated mobile devices make cloudlets either overloaded or under-loaded. Hence, load balancing among neighboring cloudlets appears to be an essential research problem. Especially, the load balancing problem among federated cloudlets from the same as well as different service providers for low-latency applications needs significant attention. Thus, in this paper, we propose a decentralized load balancing framework among federated cloudlets for low-latency applications that focuses on latency bound rather than latency minimization. In this framework, we employ dynamic processor slicing for handling heterogeneous classes of job requests. We propose a continuous-action reinforcement learning automata-based algorithm that enables cloudlets to independently compute the load balancing strategies in a completely distributed network setting without any exhaustive control message exchange. To capture the economic interaction among federated cloudlets, we model this load balancing problem as an economic and non-cooperative game and by scaffolding the properties of the game formulation, we achieve faster convergence of the reinforcement learning automata. Furthermore, through extensive simulations, we study the impacts of exploration and exploitation on learning accuracy.

A Decentralized Economic Load-Balancing Framework among Federated Cloudlets

Edge computing servers like cloudlets from different service providers compensate scarce computational and storage resources of mobile devices, are distributed across access networks. However, the dynamically varying computational requirements of associated mobile devices make cloudlets either overloaded or under-loaded. Hence, load balancing among neighboring cloudlets appears to be an essential research problem. Especially, the load balancing problem among federated cloudlets from the same as well as different service providers for low-latency applications needs significant attention. Thus, in this paper, we propose a decentralized load balancing framework among federated cloudlets for low-latency applications that focuses on latency bound rather than latency minimization. In this framework, we employ dynamic processor slicing for handling heterogeneous classes of job requests. We propose a continuous-action reinforcement learning automata-based algorithm that enables cloudlets to independently compute the load balancing strategies in a completely distributed network setting without any exhaustive control message exchange. To capture the economic interaction among federated cloudlets, we model this load balancing problem as an economic and non-cooperative game and by scaffolding the properties of the game formulation, we achieve faster convergence of the reinforcement learning automata. Furthermore, through extensive simulations, we study the impacts of exploration and exploitation on learning accuracy.

Reducing false reassurance following negative results from asymptomatic coronavirus (Covid-19) testing: an online experiment

Objectives. Individuals who receive a negative lateral flow coronavirus (Covid-19) test result may misunderstand it as meaning no risk of infectiousness, giving false reassurance. This experiment tested the impact of adding information to negative test result messages about (a) residual risk and (b) need to continue protective behaviours. Design. 4 (residual risk) x 2 (post-test result behaviours) between-subjects design. Setting. Online. Participants. 1200 adults from a representative UK sample recruited via Prolific (12-15 March 2021). Interventions. Participants were randomly allocated to one of eight messages. Residual risk messages were: 1) 'Your coronavirus test result is negative' (control); 2) Message 1 plus 'It's likely you were not infectious when the test was done' (Current NHS Test and Trace); 3) Message 2 plus 'But there is still a chance you may be infectious' (Elaborated NHS Test and Trace); 4) Message 3 plus infographic depicting residual risk (Elaborated NHS Test and Trace + infographic). Each message contained either no additional information or information about behaviour, i.e. the need to continue following guidelines and protective behaviours. Outcome measures. (i) proportion understanding residual risk of infectiousness and (ii) likelihood of engaging in protective behaviours (score range 0-7). Results. The control message decreased understanding relative to the current NHS T&T message: 54% vs 71% (AOR=0.37 95% CI [0.22, 0.61], p<.001). Understanding increased with the elaborated NHS T&T (89%; AOR=3.27 95% CI [1.78, 6.02], p<.001) and elaborated NHS T&T + infographic (91%; AOR=4.03 95% CI [2.14, 7.58], p<.001) compared to current NHS T&T message. Likelihood of engaging in protective behaviours was unaffected by information (F(1,1192)=0.43, p=.513), being high (M=6.4, SD=0.9) across the sample. Conclusions. The addition of a single sentence ('But there is still a chance you may be infectious') to current NHS Test and Trace wording increased understanding of the residual risk of infection. Trial registration. Open Science Framework: https://osf.io/byfz3/