Fallback Approach Research Articles

Capacity Analysis of LEO Mega-Constellation Networks

This paper proposes a complete network capacity analysis framework for low-earth-orbit (LEO) mega-constellations, where a network capacity estimation problem considering the link packet loss rate is formulated with the support of a time-variant network topology model and a task distribution model. This problem is solved in two steps. First, without considering the link packet loss rate, an improved fully polynomial-time approximation (IFPTA) algorithm is proposed to provide a sub-optimal solution to the multi-commodity flow (MCF) problem, in which a simpler definition of a commodity is given and proved to be equivalent to the original problem. Second, a Jackson-network-based capacity fallback approach is proposed to control the link packet loss rate below a given threshold. Numerical results illustrate the superiority of the proposed IFPTA algorithm in terms of accuracy and time complexity compared to existing solutions. In addition, the capacity characteristics of mega-constellations are analyzed by utilizing the proposed capacity analysis framework, including the relationship between constellation size and capacity, network capacity bottlenecks, and the influence of task distributions.

NADEEM: Neighbor node approaching distinct energy‐efficient mates for reliable data delivery in underwater WSNs

AbstractIn this research work, we propose three schemes: neighbor node approaching distinct energy‐efficient mates (NADEEM), fallback approach NADEEM (FA‐NADEEM), and transmission adjustment NADEEM (TA‐NADEEM). In NADEEM, immutable forwarder node selection is avoided with the help of three distinct selection parameters. Void hole is avoided using a fallback recovery mechanism to deliver data successfully at the destination. The transmission range is dynamically adjusted to resume greedy forwarding among the network nodes. The neighbor node is only eligible to become forwarder when it is not a void node. Additionally, linear programming–based feasible regions are computed for an optimal energy dissipation and network throughput improvement. Extensive simulations are conducted for three parameters: energy, packet delivery ratio (PDR), and fraction of void nodes. Further, an analysis is performed by varying transmission range and data rate for energy consumption and fraction of void node. The results clearly depict that our proposed schemes outperform the baseline scheme (GEDAR) in terms of energy consumption and fraction of void nodes.

An adaptive model predictive approach for automated vehicle control in fallback procedure based on virtual vehicle scheme

Purpose Automated driving systems (ADSs) are being developed to avoid human error and improve driving safety. However, limited focus has been given to the fallback behavior of automated vehicles, which act as a fail-safe mechanism to deal with safety issues resulting from sensor failure. Therefore, this study aims to establish a fallback control approach aimed at driving an automated vehicle to a safe parking lane under perceptive sensor malfunction. Design/methodology/approach Owing to an undetected area resulting from a front sensor malfunction, the proposed ADS first creates virtual vehicles to replace existing vehicles in the undetected area. Afterward, the virtual vehicles are assumed to perform the most hazardous driving behavior toward the host vehicle; an adaptive model predictive control algorithm is then presented to optimize the control task during the fallback procedure, avoiding potential collisions with surrounding vehicles. This fallback approach was tested in typical cases related to car-following and lane changes. Findings It is confirmed that the host vehicle avoid collision with the surrounding vehicles during the fallback procedure, revealing that the proposed method is effective for the test scenarios. Originality/value This study presents a model for the path-planning problem regarding an automated vehicle under perceptive sensor failure, and it proposes an original path-planning approach based on virtual vehicle scheme to improve the safety of an automated vehicle during a fallback procedure. This proposal gives a different view on the fallback safety problem from the normal strategy, in which the mode is switched to manual if a driver is available or the vehicle is instantly stopped.

Joint Relay-Spectrum Selection in Hybrid Millimeter-Microwave Cooperative (HMMC) Network Using Fall-Back Approach

The microwave ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> Wave) spectrum or low-frequency spectrum has become overcrowded due to the ever-increasing demand in bandwidth-intensive applications, such as video streaming and gaming. Owing to the fact that the spectral efficiency of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> Wave links is approaching its fundamental limits, there is a growing consensus in both industry and academia that millimeter wave (mmWave) will play an important role in increasing data rate and scarcity of spectrum. To redress the predicament and to ensure adequate availability of bandwidth, increasing attentions have been paid to the use of mmWave spectrum for future broadband wireless networks. The mmWave spectrum offers wider bandwidth compared to the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> Wave spectrum and a promising solution to overcome the scarcity of spectrum while providing gigabits per second (Gb/s) of data rates. To fully exploit the high potential rates of mmWave in mobile networks, a number of technical problems must be addressed. The mmWave signal transmission suffers from the issues of blockage and deafness. The former challenge is characterized by the loss of Quality of Service (QoS) in non-line-of-sight (NLOS) conditions, while the latter is characterized by the misalignment between the main lobe of transmitter and the receiver beam. Two strategies can be adopted to deal with the issues:1) relaying, use of another path with the help of relay(s) providing line-of-sight (LOS) link(s) and b) fall back, in the case of service interruption, switch back to the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> Wave spectrum-based transmission switching between mmWave and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> Wave frequency bands can support higher rates and QoS requirements. However, a tradeoff exists in employing any of the aforementioned strategies. In this paper, we study the joint spectrum allocation and relay selection problem to maximize the weighted sum rate relay selection (using resource block and time slot) along with a fallback approach for spectrum allocation in an HMMC network. A fallback approach is introduced to enable the hybrid transmission of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> Wave and mmWave, and an iterative bipartite relay-spectrum selection algorithm is proposed to solve the problem. The performance evaluation results show that the proposed fallback approach outperforms the conventional <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> Wave or mmWave transmission schemes in terms of data rate, transmit power, and the number of users.

Multiphase isenthalpic flash: General approach and its adaptation to thermal recovery of heavy oil

Isenthalpic flash is a basic equilibrium calculation in process simulation. The recent interest in isenthalpic multiphase flash is mainly caused by the need for simulating thermal recovery of heavy oil. We present here systematic solutions to multiphase isenthalpic flash with full thermodynamics (such as EoS models) or with correlations for K‐factors, and discuss how to tailor the general methods to systems encountered in thermal recovery of heavy oil. First, for the general situation with full thermodynamics we recommend a solution strategy which uses Newton's method for rapid convergence in the majority of cases and Q‐function maximization to safeguard convergence when Newton's method fails. The solution procedure is a generalization of Michelsen's state function based two‐phase flash to multiple phases. The general solution does not need special considerations for the components in the system and is not limited to the selected thermodynamic models and the number of phases. For thermal recovery processes where gas, oil, and aqueous phases are typically involved, the stability analysis and initialization steps are tailored to improve the efficiency. Second, as it is quite common in thermal reservoir simulators to describe phase equilibrium and heat properties with temperature‐dependent K‐factors and separate correlations for heat capacities, we propose a formulation as an extension of the ideal solution isothermal flash formulation to solve such problems. It uses a Newton–Raphson procedure to converge in the majority of cases and a nested loop procedure with the outer loop for a temperature search as a fallback approach for convergence. If the correlations for K‐factors and for heat capacities are thermodynamically consistent, the outer loop can be treated as a maximization. Finally, we present systematic tests of the proposed algorithms using examples with full thermodynamics or K‐factor based thermodynamics. The algorithms prove robust and efficient even in challenging cases including a narrow‐boiling system, a degenerate system, and a four‐phase system. The additional computational cost relative to the corresponding isothermal flash is modest and would be suitable for the purpose of thermal reservoir simulation. © 2018 American Institute of Chemical Engineers AIChE J, 65: 281–293, 2019

An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications

We developed a large-area preprocessing framework for multisensor Landsat data, capable of processing large data volumes. Cloud and cloud shadow detection is performed by a modified Fmask code. Surface reflectance is inferred from Tanre's formulation of the radiative transfer, including adjacency effect correction. A precompiled MODIS water vapor database provides daily or climatological fallback estimates. Aerosol optical depth (AOD) is estimated over dark objects (DOs) that are identified in a combined database and image-based approach, where information on their temporal persistency is utilized. AOD is inferred with consideration of the actual target reflectance and background contamination effect. In case of absent DOs in bright scenes, a fallback approach with a modeled AOD climatology is used instead. Topographic normalization is performed by a modified C-correction. The data are projected into a single coordinate system and are organized in a gridded data structure for simplified pixel-based access. We based the assessment of the produced data set on an exhaustive analysis of overlapping pixels: 98.8% of the redundant overlaps are in the range of the expected ±2.5% overall radiometric algorithm accuracy. AOD is in very good agreement with Aerosol Robotic Network sunphotometer data ( $R^{2}$ : 0.72 to 0.79, low intercepts, and slopes near unity). The uncertainty in using the water vapor fallback climatology is approximately ±2.8% for the TM SWIR1 band in the wet season. The topographic correction was considered successful by an investigation of the nonrelationship between the illumination angle and the corrected radiance.

Estimation of treatment effects in all-comers randomized clinical trials with a predictive marker.

Recent advances in genomics and biotechnologies have accelerated the development of molecularly targeted treatments and accompanying markers to predict treatment responsiveness. However, it is common at the initiation of a definitive phase III clinical trial that there is no compelling biological basis or early trial data for a candidate marker regarding its capability in predicting treatment effects. In this case, it is reasonable to include all patients as eligible for randomization, but to plan for prospective subgroup analysis based on the marker. One analysis plan in such all-comers designs is the so-called fallback approach that first tests for overall treatment efficacy and then proceeds to testing in a biomarker-positive subgroup if the first test is not significant. In this approach, owing to the adaptive nature of the analysis and a correlation between the two tests, a bias will arise in estimating the treatment effect in the biomarker-positive subgroup after a non-significant first overall test. In this article, we formulate the bias function and show a difficulty in obtaining unbiased estimators for a whole range of an associated parameter. To address this issue, we propose bias-corrected estimation methods, including those based on an approximation of the bias function under a bounded range of the parameter using polynomials. We also provide an interval estimation method based on a bivariate doubly truncated normal distribution. Simulation experiments demonstrated a success in bias reduction. Application to a phase III trial for lung cancer is provided.

Comparison of Statistical Analysis Plans in Randomize-All Phase III Trials with a Predictive Biomarker

When there are no compelling biologic or early trial data for a candidate predictive biomarker with regard to its ability to predict the effect of an anticancer treatment at the initiation of definitive phase III trials, it is generally reasonable to include all patients as eligible for randomization but to plan for a prospective subgroup analysis based on the biomarker. We assessed such statistical analysis plans, fixed-sequence, fallback, and treatment-by-biomarker interaction approaches, in terms of the probability of asserting treatment efficacy for either the overall patient population or a biomarker-positive subpopulation of patients. If there was some evidence that the treatment would work better in the biomarker-positive subgroup than the biomarker-negative subgroup, then the fixed-sequence approaches would be favored, whereas if evidence was weak that there would be much difference in responsiveness between the two subgroups, then the fallback approach would be favored. If there was substantial uncertainty in the difference in treatment effects between the two subgroups, the treatment-by-biomarker interaction approach could be a reasonable choice as this approach generally provided a high probability of asserting treatment efficacy for the right patient population under homogeneous treatment effects and a qualitative interaction over biomarker-based subgroups. Clin Cancer Res; 20(11); 2820-30. ©2014 AACR.

HIV Vaccine Development: Strategies for Preclinical and Clinical Investigation

This article discusses HIV vaccine discovery and candidate vaccine testing in the context of current realities of funding and clinical trial practice. Lacking perfect animal models for testing candidate HIV vaccines, clinical investigators have proposed a strategy of iterative exploratory clinical trials in the model of cancer chemotherapy development. Problems with the appropriateness of this model to HIV vaccine development are discussed. Also, the future feasibility of this strategy in the context of increasing clinical trial costs and emerging new, efficacious prevention modalities is questioned. Strategies for making better use of animal models are presented as an alternative to iterative exploratory clinical efficacy testing. Some ways in which better data from preclinical studies can refine clinical product development are described. Finally, development of an HIV vaccine under the FDA's "Animal Rule" pathway to licensure when human efficacy studies are not feasible is discussed as a fall-back approach. Not making a preventive vaccine against HIV infection is simply not an option because eradication of AIDS will require a preventive vaccine.

Generalized Multi-Constrained Path (G_MCP) QoS Routing Algorithm for Mobile Ad hoc Networks

In mobile ad hoc network, efficient routing protocol is required to perform route discovery and maintenance. These protocols can be classified into two main types which are proactive and reactive routing protocols. Most of them usually use the suboptimal path to reach destination without considering QoS parameters. This results in network congestion during high traffic load situation. Hence, many algorithms have been proposed to offer QoS routing to these protocols. However, most of them find the feasible path by using only one or two QoS metrics. This is not enough to support many applications with QoS guaranteed, especially multimedia applications since they have more stringent various QoS requirements. To provide QoS routing in ad hoc network based on such environment, we propose the effective algorithm called Generalized MCP (G_MCP) to find the feasible path based on proposed weighted Connectivity Index (combination of link connectivity and capacity) and non-linear cost (combination of multiple additive QoS metrics using non-linear function). We adopt the fall-back approach. That is, G_MCP will find the path from source to destination by considering weighted Connectivity Index first. If there is a tie, the path with least non-linear cost will be chosen. Based on this approach, G_MCP has the comparable time complexity with the Shortest-Widest Path algorithm. We construct the simulation in a number of scenarios based on proactive protocol called OLSR. According to the simulation results, it is obvious that G_MCP performances are superior than OLSR and Shortest-Widest Path algorithms in terms of throughput, packet delivery ratio, delay and success ratio. Therefore, it can be concluded that G_MCP is able to support various applications and be operated well in highly dynamic mobility environment

A Contextual Approach to Privacy Online

Recent media revelations have demonstrated the extent of third-party tracking and monitoring online, much of it spurred by data aggregation, profiling, and selective targeting. How to protect privacy online is a frequent question in public discourse and has reignited the interest of government actors. In the United States, notice-and-consent remains the fallback approach in online privacy policies, despite its weaknesses. This essay presents an alternative approach, rooted in the theory of contextual integrity. Proposals to improve and fortify notice-and-consent, such as clearer privacy policies and fairer information practices, will not overcome a fundamental flaw in the model, namely, its assumption that individuals can understand all facts relevant to true choice at the moment of pair-wise contracting between individuals and data gatherers. Instead, we must articulate a backdrop of context-specific substantive norms that constrain what information websites can collect, with whom they can share it, and under what conditions it can be shared. In developing this approach, the paper warns that the current bias in conceiving of the Net as a predominantly commercial enterprise seriously limits the privacy agenda.

Industrial noise control—Technical and economic feasibility

Industrial noise control is too often considered technically not possible or economically infeasible. The use of ear protection devices becomes the fallback approach to attempt to reduce the risk of worker hearing loss. In reality there are noise control opportunities in industrial settings than are low cost and provide significant noise reduction without affecting production and maintenance practices. This paper will present mechanical and pneumatic noise controls that can be successfully applied to industrial environments. This paper will also present information on OSHAs approach to determine whether engineering noise controls are considered economically feasible.

Talking Oneself Into Change: Motivational Interviewing, Stages of Change, and Therapeutic Process

Motivational interviewing (MI) is a directive, person-centered clinical method for helping clients resolve ambivalence and move ahead with change. It can be applied as a preparation for treatment, a freestanding brief intervention, an enduring clinical style, or a fallback approach when motivational obstacles are encountered. A psycholinguistic theory is emerging to account for the efficacy of MI that has been demonstrated in numerous clinical trials. For cognitive therapists, MI provides an evidence-based alternative to direct disputation of client cognitions.