Multi-measure Method Research Articles

A Direct Discrimination Packet Flow Based Improving Security against Reactive Traffic Attacks in Wireless Communication

The wireless networks is most difficult of selective filling attacks. If jammer localizations and resistance routing are left alone, both are very promising, and the service overhead is still below the real-time requirements. To propose a new Direct Discriminant Packet Flow Exploration [DDPFE] algorithm based on network utility maximization (NUM) to resolve the centralized reaction disturbance optimization problem in multi-source network without any lose to send the data. The impact of the networks is estimated through interference and combine these estimates with the ability to assign problems in this type of attacks. To overcome this type of physical-layer characterization of cryptographic primitives attacks using a Cooperative Crypto Riddle Hiding Algorithm (CCRHA) for the control channel jamming problem in-network, which takes advantage of the transfer the data using the Ad-hoc network. The resolution to detect the schema attacks and isolate the nodes for the threshold. CCRHA Presenting to find selectively invasive attackers in wireless networks. Multiple metrics are measured to detect areas of interference of the wireless network. Multi-measurement method considered Packet Delivery Ratio (PDR) and signals strength variation as parameters to detect the selective jamming attacks.

Assessing the safety criticality of driver behavior toward cyclists at intersections

Objective: Detailed analyses of car-to-cyclist accidents show that drivers intending to turn right at T-junctions collide more often with cyclists crossing from the right side on the bicycle lane than drivers intending to turn left. This fact has led to numerous studies examining the behavior of drivers turning left and right. However, the most essential question still has not been sufficiently answered: is the behavior of drivers intending to turn right generally more safety critical than the behavior of those intending to turn left? The purpose of this article is to provide a method that allows to determine whether a driver’s behavior toward cyclists can retrospectively be assessed as critical or non-critical.Methods: Several theoretical considerations enriched by findings of experimental studies were employed to devise a multi-measure method. This method was applied to a dataset containing real-world approaching behavior of 48 drivers turning right and left at four T-junctions with different sight obstructions. For each driver a behavior-specific criticality was defined based on both, their driving and gaze behavior. Moreover, based on the behavior-specific criticality of each driver, the required field of view to see a cyclist from the right was defined and was set into relation with the available field of view of the T-junction.Results: The results show that only a small portion of the drivers within the dataset would have posed an actual risk to cyclists crossing from the right side. Those situations with a higher safety criticality did not only arise when drivers intended to turn right, but also left.Conclusion: Therefore, the analysis can only provide an explanation for the higher proportion of accidents between drivers turning right and cyclists crossing from the right side in certain situations. Further research, for example analyses of exposure data regarding the frequency of turning manoeuvers at T-junctions, is needed in order to explain the higher proportion of accidents between drivers turning right and cyclists crossing from the right side.

Multiple measures-based chaotic time series for traffic flow prediction based on Bayesian theory

Considering the chaotic characteristics of traffic flow, this study proposes a Bayesian theory-based multiple measures chaotic time series prediction algorithm. In particular, a time series of three traffic measures, i.e., speed, occupancy, and flow, obtained from different sources is used to reconstruct the phase space using the phase space reconstruction theory. Then, data from the multiple sources are combined using Bayesian estimation theory to identify the chaotic characteristics of traffic flow. In addition, a radial basis function (RBF) neural network is designed to predict the traffic flow. Compared to the consideration of a single source, results from numerical experiments demonstrate the improved effectiveness of the proposed multi-measure method in terms of accuracy and timeliness for the short-term traffic flow prediction.

Water planning: From what Time Perspective?

Integrative planning for water technology and infrastructure depends on various social, behavioral and environmental factors. Since water is a common-pool resource, water planning commonly involves addressing the views of diverse groups of people on multiple levels. Inter-group differences, especially if they go unrecognized, can be problematic for planning processes. Research into the Time Perspectives of people fulfilling different roles in the water sector worldwide revealed fascinating differences in how people perceive the Foreseeable Future. The aim was to characterize the heterogeneity so that it might be explicitly accounted for in planning. One-on-one interviews were held with 309 managers, practical workers, and scientists in the Netherlands, Ghana, Brazil, and Japan. Each interviewee's Time Perspective was characterized using a multi-measure method. The most noteworthy conclusions concern differences in the temporal extent of the goals and events that motivate people. Scientists are motivated by objects that lie furthest into the future followed by managers and then practical workers (Group medians: 8.4, 3.5, 1.7 yrs). Across national cultures, the time horizons of the Japanese and Brazilian interviewees are longest. These conclusions are important because the time horizons considered in planning influence what problems are perceived, what questions are asked, and what solutions are sought.

Delineating reservoir fluid variations in the Bossier Formation using an integrated multi-measurement method

Delineating reservoir fluid variations in the Bossier Formation using an integrated multi-measurement method

Diversity - An End in Itself?

The scope of this article is methodological, focusing on the measurement of programme diversity on television. In recent research literature programme diversity has been understood too narrowly. In order to avoid typical pitfalls of diversity studies, the article discusses the concept and dimensions of diversity and, then, develops four parallel measures of breadth of programming and difference between channels, applicable for the analysis of both individual channels and the channel system as a whole. These measures (channel diversity, system diversity, deviation and choice options) are tested in a longitudinal analysis of Finnish television schedules. The article demonstrates that since shifts in the different dimensions of diversity are not necessarily unilinear, the multi-measure method tends to provide a more versatile picture of the developments in programme schedules than the traditional diversity analysis can do.