Low Loss Probability Research Articles

Wavelength-division multiplexing (WDM) FSO communications with soliton microcombs

This study highlights the benefits of soliton microcombs (SMCs) in FSO communication systems. By employing a microring resonator coupled with an add/drop filter, we achieved soliton microcombs with a precise Free Spectral Range (FSR) of 1870 pm and a Full Width at Half Maximum (FWHM) of 60 pm, tailored for Wavelength Division Multiplexing (WDM) channels. The system utilized 100 lines for the WDM channel with an inter-channel spacing of 0.5 nm and PolSK modulation to encode the data. This combination achieved a bit error rate (BER) of 10 − 9 , significantly lower than the 10 − 7 observed with traditional systems. For performance simulation, the channel was characterized using the gamma-gamma model, which assessed the impact of atmospheric turbulence on data transmission. The results show a high channel capacity ( 10 3 Gbit/s) and a low loss probability ( 10 − 8 ), ensuring reliable data transmission even in the presence of atmospheric disturbances. This methodology provides substantial improvements in stability and efficiency for FSO networks.

Determination of iron in water by flame atomic absorption spectrometry with sorption preconcentration

Determination and monitoring of pollutants in the natural environment is an urgent task because of their impact on living organisms as a result of numerous anthropogenic impacts. For this reason, a large number of publications are devoted to the development, modification or optimization of analytical methods that can solve these problems. When determining trace elements present in various samples, such as natural and waste water, biological samples and alloy samples, direct determination by various instrumental methods is often impossible due to the matrix effect and rather low concentration of metal ions in the sample. The atomic absorption method is one of the methods widely used for the determination of iron ions, which has such advantages as simplified sample preparation, low probability of contamination and loss of elements, increased analytical productivity, the detection limit of components in the analyzed mixture reduced by several orders of magnitude, and the ability to determine trace amounts of elements in small samples. The aim of the study was to develop a technique for the preliminary concentration of Fe (III) ions in waters of various origins using a sorbent immobilized with sulfosalicylic acid and their further determination by flame atomic absorption spectrometry. Sorbents obtained on the basis of polyacrylonitrile modified with polyethylene polyamine (PPF-1 and PPA-1) with sulfosalicylic acid immobilized on their surface were used for selective sorption of Fe (III) ions. Optimal conditions for the immobilization of sulfosalicylic acid on sorbents and the formation of complexes with Fe (III) ions were studied. The developed sorption-atomic absorption technique provided determination of low concentrations of Fe (III) ions in various waters. The use of PPF-1 as a sorbent with immobilized sulfosalicylic acid for pre-concentration of iron has a number of advantages compared to traditional atomic absorption procedure, i.e., the simplicity, high degree of iron extraction, high sensitivity and selectivity of iron determination, as well as a low cost. The detection limit of iron ions is 0.01 μg/L, Sr does not exceed 0.033.

Designing the Distribution Network of Essential Items in the Critical Conditions of Earthquakes and COVID-19 Simultaneously

Current societies must make the necessary plans for effective responses and to reduce the destructive effects of disasters. For this reason, this research has developed a mathematical programming model under uncertainty for earthquake relief and response during COVID-19. In the presented model, the possibility of facility failure is considered according to the intensity of the earthquake and COVID-19 to increase reliability. The simultaneous occurrence of these disasters presents unique challenges in ensuring the timely delivery of essential supplies to affected regions. Distribution centers (DCs) are considered to be of two types: the first type is local DCs, which use public centers and are close to accident points. These types of centers are prone to failure because they use public facilities. Another type is the reliable DCs built outside the disrupted area, which have a very low probability of loss due to spending more money to build them. In addition, to consider the reliability capabilities, the new model has tried to provide a complete model for transportation planning by considering the multi-trip mode of vehicles. Moreover, this model considers distance restriction at the demand point for the first time because of COVID-19 during the earthquake. The proposed network design aims to offer effective solutions in promptly delivering essential items to affected areas, thereby enhancing disaster management strategies and minimizing the impact of these crises on vulnerable populations. Uncertainty is presented using the probability approach based on the modeling scenario and a case study from the city of Istanbul to illustrate the performance of the suggested model. Finally, the suggested mode is solved with an Lp-metric and goal programming (GP) approach. The results show that in this case, the proposed model shows that effective and efficient aid delivery is possible in terms of time and cost. Therefore, it can help crisis managers respond by providing the required budget and appropriate logistics planning.

Blockchain‐oriented location privacy preserving for cooperative spectrum sensing in 6G wireless networks

AbstractIn this article, the authors proposed a novel blockchain‐oriented location privacy‐preserving (BoLPP) for the Cooperative Spectrum Sensing (CSS) in 6G networks. In order to attain the sustainability of privacy and security for 6G wireless networks, it is a great challenge in this sensing as it faces various malicious attacks while the secondary user (SU) is active. To tackle these issues, the authors proposed a novel framework for blockchain‐oriented Cognitive Radio Networks (CRNs) for CSS using an energy detection technique. Moreover, the authors implemented another novel paradigm BoLPP, to attain the privacy of SUs location for CSS in 6G networks. This approach preserves the SUs’ location and makes the BoLPP framework immune to all malicious attackers. The simulation results have been undergone based on the performance metrics such as response time, consistency, probability of false alarm, frame loss (%), average network throughput, energy efficiency, and security. The outcomes reveal that the proposed scheme achieves high security, privacy, energy efficiency, average network throughput, and low probability of false alarm and frame loss (%) when compared with the existing frameworks such as Friend or Foe (FoF) and Tidal Trust Algorithm (TTA) mechanisms. It is observed that the proposed BoLPP mechanism provides better security and privacy in 6G wireless networks.

Application of Internet of Things Energy System in Dynamic Risk Assessment of Composite Fault of Transmission Line

In order to study the application of Internet of things energy system in complex fault risk dynamic assessment of transmission line. Firstly, the concept of power grid dynamic risk assessment is introduced, and the process of power grid dynamic risk assessment system based on Internet of things is designed. Then, it puts forward how to use the ubiquitous Internet of things multisource data to solve the key problems such as dynamic perception of fault probability, dynamic selection of fault set, dynamic generation of post fault state, and dynamic risk assessment of operation process. Finally, taking the maximum operation mode of a provincial power grid in summer 2013 as an example, this paper selects key 500 kV transmission lines for risk assessment, and the actual power grid example shows that. The power grid comprehensive risk assessment system considering the fault characteristics of transmission lines can effectively predict the fault probability of transmission lines; distinguish the two risks of high loss, low probability, and low loss and high probability; and provide guidance for operators. It is practical and effective.

Risking Everything in Obsessive-Compulsive Disorder: An Analogue Decision-Making Study.

An experiment examined decision-making processes among nonclinical participants with low or high levels of OCD symptomatology (N = 303). To better simulate the decision environments that are most likely to be problematic for clients with OCD, we employed decision tasks that incorporated “black swan” options that have a very low probability but involve substantial loss. When faced with a choice between a safer option that involved no risk of loss or a riskier alternative with a very low probability of substantial loss, most participants chose the safer option regardless of OCD symptom level. However, when faced with choices between options that had similar expected values to the previous choices, but where each option had some low risk of a substantial loss, there was a significant shift towards riskier decisions. These effects were stronger when the task involved a contamination based, health-relevant decision task as compared to one with financial outcomes. The results suggest that both low and high symptom OC participants approach decisions involving risk-free options and decisions involving risky alternatives in qualitatively different ways. There was some evidence that measures of impulsivity were better predictors of the shift to risky decision making than OCD symptomatology.

Tail index-linked annuity: A longevity risk sharing retirement plan

This paper proposes an innovative retirement product focusing on longevity risk sharing, a contract we refer to as tail index-linked annuity (TILA). Specifically, the proposed TILA pays out variable annual payments, which will be equal to a regular nominal amount when a reference survival index is lower than a predetermined threshold (i.e. normal evolution of longevity risk), and a reduced, index-dependent payment when the threshold is passed (i.e. highly unfavorable evolution of longevity risk). The proposed TILA aims at not only improving the benefits of the policyholders, which has been the focus in recent literature on innovative retirement products, but also reducing the longevity risk exposure of the insurer, particularly for advanced retirement ages. Using real-world mortality data and a stochastic multi-population mortality model, we find that the proposed TILA leads to higher expected lifetime utility than regular annuities for policyholders with different degrees of risk aversions. Meanwhile, numerical analysis shows that the proposed TILA could greatly mitigate the solvency risk of the insurer, leading to a substantially lower loss probability and expected (tail-) loss than regular annuities in the presence of a longevity shock, and therefore could reduce the insurer's required solvency capital under the latest solvency regulations.

Robust Adaptive Beam Tracking for Mobile Millimetre Wave Communications

Millimetre wave (mmWave) beam tracking is a challenging task because tracking algorithms are required to provide consistent high accuracy with low probability of loss of track and minimal overhead. To meet these requirements, we propose in this article a new cost-effective analog beam tracking framework namely Adaptive Tracking with Stochastic Control (ATSC). Under this framework, beam direction updates are made using a novel mechanism based on measurements taken from only two beam directions perturbed from the current data beam. To achieve high tracking accuracy and reliability, we provide a systematic approach to jointly optimise the algorithm parameters. The complete framework includes a method for adapting the tracking rate together with a criterion for realignment (perceived loss of track). ATSC adapts the amount of tracking overhead that matches well to the mobility level, without incurring frequent loss of track, as verified by an extensive set of experiments under both representative statistical channel models as well as realistic urban scenarios simulated by ray-tracing software. In particular, numerical results show that ATSC can track dominant channel directions with high accuracy for vehicles moving at 72 km/hour in complicated urban scenarios, with an overhead of less than 1%.

A Low-Cost Multi-Failure Resilient Replication Scheme for High-Data Availability in Cloud Storage

Data availability is one of the most important performance factors in cloud storage systems. To enhance data availability, replication is a common approach to handle the machine failures. However, previously proposed replication schemes cannot effectively handle both correlated and non-correlated machine failures, especially while increasing the data availability with limited resources. The schemes for correlated machine failures must create a constant number of replicas for each data object, which often neglects diverse data popularities and does not utilize the resource to maximize the expected data availability. Also, the previous schemes neglect the consistency maintenance cost and the storage cost caused by replication. It is critical for cloud providers to maximize data availability (hence minimize SLA violations) while minimizing costs caused by replication in order to maximize the revenue. In this paper, we build a nonlinear integer programming model to maximize data availability in both types of failures, and therefore minimize the cost caused by replication. Based on the model's solution for the replication degree of each data object, we propose a low-cost multi-failure (correlated and non-correlated machine failures) resilient replication scheme (MRR). MRR can effectively handle both correlated and non-correlated machine failures, considers data popularities to enhance data availability, and also tries to minimize consistency maintenance and storage cost. Extensive numerical results from trace parameters and experiments from real-world Amazon S3 demonstrate that MRR achieves high data availability, low data loss probability and low consistency maintenance and storage costs when compared to previous replication schemes.

SAT459 - HBV RNA decline without concomitant HBsAg decrease is associated with a low probability of sustained response and HBsAg loss

SAT459 - HBV RNA decline without concomitant HBsAg decrease is associated with a low probability of sustained response and HBsAg loss

Towards the implementation of advanced random access schemes for satellite IoT

SummaryMachine‐to‐machine (M2M) communications being pivotal for internet of things (IoT) networks are characterized by low‐cost, low complexity, and often energy constrained terminals with low traffic duty cycle. Satellite networks provide an attractive low‐cost solution for such application, in particular when the terminals (both fixed and mobile) are distributed over a wide geographical area not well served by terrestrial infrastructure. An ALOHA random access (RA) scheme is a natural candidate for M2M communications since it is well matched to sporadic traffic, and it requires little terminals coordination. However, the classical ALOHA scheme suffers from a low throughput when operated in a load region requiring low probability of packet loss. To overcome this intrinsic ALOHA limitation, in the last decade, a lot of effort has been devoted to the investigation of evolutions of the ALOHA scheme reducing the probability of destructive packet collisions thus making it more attractive for satellite IoT. In such context, the Contention Resolution Diversity ALOHA (CRDSA) scheme and the Asynchronous Contention Resolution Diversity ALOHA (ACRDA) have emerged as promising solutions thanks to their high spectral efficiency achievable with low packet loss probability. The results reported in literature are however assuming ideal demodulator performance. This paper investigates the design and optimization of RA burst demodulator algorithms for single‐frequency and multifrequency CRDSA and ACRDA. It evaluates the performance of such algorithms in a number of system scenarios of practical interest and studies the impact of relevant system parameters on several performance metrics.

Managing Genetic Diversity and Extinction Risk for a Rare Plains Bison (Bison bison bison) Population.

Unfenced plains bison are rare and only occur in a small number of locations throughout Canada and the United States. We examined management guidelines for maintenance of genetic health and population persistence for a small and isolated population of plains bison that occupy the interface between a protected national park and private agricultural lands. To address genetic health concerns, we measured genetic diversity relative to other populations and assessed the potential effects of genetic augmentation. We then used individual-based population viability analyses (PVA) to determine the minimum abundance likely to prevent genetic diversity declines. We assessed this minimum relative to a proposed maximum social carrying capacity related to bison use of human agricultural lands. We also used the PVA to assess the probability of population persistence given the limiting factors of predation, hunting, and disease. Our results indicate that genetic augmentation will likely be required to achieve genetic diversity similar to that of other plains bison populations. We also found that a minimum population of 420 bison yields low probability of additional genetic loss while staying within society-based maxima. Population estimates based on aerial surveys indicated that the population has been below this minimum since 2007. Our PVA simulations indicate that current hunting practices will result in undesirable levels of population extinction risk and further declines in genetic variability. Our study demonstrates that PVA can be used to evaluate potential management scenarios as they relate to long-term genetic conservation and population persistence for rare species.

Popularity-Aware Multi-Failure Resilient and Cost-Effective Replication for High Data Durability in Cloud Storage

Large-scale data stores are an increasingly important component of cloud datacenter services. However, cloud storage system usually experiences data loss, hindering data durability. Three-way random replication is commonly used to lead better data durability in cloud storage systems. However, three-way random replication cannot effectively handle correlated machine failures to prevent data loss. Although Copyset Replication and Tiered Replication can reduce data loss in correlated and independent failures, and enhance data durability, they fail to leverage different data popularities to substantially reduce the storage cost and bandwidth cost caused by replication. To address these issues, we present a popularity-aware multi-failure resilient and cost-effective replication (PMCR) scheme for high data durability in cloud storage. PMCR splits the cloud storage system into primary tier and backup tier, and classifies data into hot data, warm data and cold data based on data popularities. To handle both correlated and independent failures, PMCR stores the three replicas of the same data into one Copyset formed by two servers in the primary tier and one server in the backup tier. For the third replicas of warm data and cold data in the backup tier, PMCR uses the compression methods to reduce storage cost and bandwidth cost. Extensive numerical results based on trace parameters and experimental results from real-world Amazon S3 show that PMCR achieves high data durability, low probability of data loss, and low storage cost and bandwidth cost compared to previous replication schemes.

Comparative analysis of cumulative distribution function for TCP congestion window size and triple‐duplicate period

SummaryVarious version of Transmission Control Protocol (TCP) congestion window model are available in the literature. TCP congestion control is handled in two phases: (a) slow start and (b) congestion avoidance. This paper deals with congestion avoidance phase that is based on additive increase multiplicative decrease (AIMD) mechanism in which window size either increase by one or cuts to half of the previous window size. For distribution of window sizes, a model developed by Yan et al has been presented for two loss indications: (a) triple duplicate (TD) and (b) time‐outs (TOs) only while it does not deal with the window size limitation. It does not allow to cap over the TCP congestion window size if the buffer size is restricted to a fixed value though window size could not move beyond that. The unconstrained window size moves on in the presence of low loss probability. In this paper, we propose a model for the case where the window size is bounded by a maximum value that makes applicable to window size limitation as well. Further, the work has been extended to develop a new model that obtains a cumulative distribution function for TD periods (TDPs). The proposed model is validated on ns‐2, and we conclude that observed results for distribution function are very closed to our proposed model.

Option Portfolio Management in a Risk-Neutral World

The most commonly used strategy of the speculative investments in options is a statistical arbitrage between the objective underlying price distribution which the price is following and the risk-neutral distribution on the basis of which options were priced. This article investigates an alternative approach which does not demand these two distributions to be different. Instead, it uses a periodical roll-over of an investment horizon with including options of the next expirations in the portfolio. We consider a risk-neutral world where the real distribution coincides with the risk-neutral distribution as a model of the market. In such a market, the expected return from investments in any option portfolio corresponds with the risk-free rate. However, it is possible to construct and manage the portfolio dynamically in such a way that it provides higher return with a probability close to unity or lower return (possibly a large negative return) with a given very low probability. To optimize the portfolio a stochastic program with the approximative safety-first criterion for option portfolio was developed along with the corresponding multinomial scenario tree. The results of the Monte-Carlo simulation of the portfolio management are presented. The very low probability of loss during option portfolio management is provided by the strategy with periodical rolling horizon of the optimization. The developed portfolio management strategy can be used as a basis for constructing trading strategies for the real option markets.

Decentralized polynomial trajectory generation for flight formation of quadrotors

This paper deals with the decentralized polynomial trajectory generation for the formation flight of a leader–follower network of quadrotors. The proposed decentralized trajectory planning method guarantees stability of the formation in missions with aggressive trajectories or low information exchange frequencies or data loss. Moreover, designed formation protocol ensures robustness of the formation against variations of the network communication topology. First, quadrotor translational dynamics is represented as a quadruple integrator by linearizing and differentiating its equations of translational motion. Then, a formation control law for a leader–follower network of the quadruple integrators is designed by implementing robustness properties of linear quadratic regulator design method and special characteristics of the network graph. Moreover, sufficient condition for the robustness of the formation against possible variations of the communication topology is addressed. According to the represented trajectory generation algorithm, once a follower receives information from its neighbors (e.g. coefficients of their intended polynomial trajectories), it plans a polynomial trajectory. To generate proper trajectories, integral of squared magnitude of error between the snap of the trajectory and its determined value by the formation control law over a finite horizon time should be minimized. The optimization problem can be formulated as a quadratic problem, which can be solved in real time. Furthermore, actuators limits can be imposed on the optimization problem as inequality constraints. As it is validated in the simulations, this predictive model of the trajectory generation provides stability of the formation in operations with aggressive trajectories or low information update frequencies or probability of data packets loss. Additionally, the quadrotors track the planned trajectories via implementing a hierarchical nonlinear trajectory tracking controller including a position controller and a geometrical attitude controller. Stability of the tracking error dynamics is proven by Lyapunov stability theorem. Expected capabilities of the formation control law, trajectory generation method and nonlinear trajectory tracking controller are examined in numerical simulations. In all of the simulations, an experimentally verified full model of a specific quadrotor taken from literatures is used.

Probabilistic private cost-benefit analysis for green roof installation: A Monte Carlo simulation approach

Green roofs are known as one of the environmentally-friendly applications and also as a sustainable approach in developing countries. Although many researchers have proven the environmental benefits of installing green roofs all around the world, they have not been used widely in many countries due to the lack of knowledge about cost-benefit issues. This paper places an emphasis on all the private factors affecting cost-benefit analysis. Installation, operation and maintenance costs are compared with the benefits such as energy saving, the increase in property value, and the acoustic effect in order to determine two indicators namely “net present value” and “pay-back period,” using the Monte Carlo simulation. Two scenarios are considered in the analyses: using the property, and selling the property after construction. Moreover, correlation and regression sensitivity analyses are also conducted. The capital of Malaysia, Kuala Lumpur, is selected for the case study due to the lack of cost-benefit analysis in developing countries. The results show that there is low probability of loss in the installation of both types of green roofs during their lifespans. Moreover, net present value for intensive green roofs is found to be higher than extensive ones, whereas the payback period for installing extensive green roofs is lower than intensive green roofs. It is concluded that the probability of loss for the owner is higher than that of benefit in the scenario of selling the property after construction resulting from the installation of both types of green roofs.

The effects of spinal anesthesia on auditory function in pediatric patients

ObjectivesPersistent or transient hearing loss (HL) is a less-recognized complication of spinal anesthesia (SA) in the pediatric population, although it has been previously reported in adults. The primary aim of this study was to investigate the effects of SA on auditory function in the pediatric population. MethodsAfter gaining institutional approval and parental consent, 30 American Society of Anesthesiologists physical status I-II children between 4 and 15 years undergoing lower extremity orthopedic surgery were enrolled in this prospective study. Spinal blocks were performed in the midline with a 25G Quincke needle using 0.5% hyperbaric bupivacaine. Transient evoked otoacoustic emission (TEOAE) and distortion product otoacoustic emission (DPOAE) tests were administered before surgery and one-day postoperative. Children with detected HL were retested on postoperative day seven. Preoperative and postoperative results were compared. A Wilcoxin Signed-Ranks test (with Bonferroni correction) was used for statistical analyses. ResultsThere was no statistically significant HL in the postoperative period compared to the preoperative period. In 29 of 30 patients, no difference was detected at any frequency tested. In one patient, TEOAE and DPOAE tests were found to be decreased on postoperative day one. In this patient, control tests were found to be improved on postoperative day seven. ConclusionsAdministration of SA may results in a low probability of transient hearing loss with no clinical significance in children 4–15 years of age.

Who Obtains Greater Discounts on Automobile Insurance Premiums?

Insurance purchasers obtain varied discounts for insurance. This paper examines what drives these differences, specifically whether the loss probability and the wealth of the insured affect the size of the premium discount in automobile insurance. To describe a bargain between a client and an insurer over premiums and coverage, we first develop a sequential insurance bargaining game where the client has an outside option to bargain with another insurer. We find that the equilibrium involves full coverage and, based on the results of comparative statics, we propose hypotheses regarding the effects of the loss probability and the wealth of the insured on the size of the premium discount. We then use a unique data set of 85,806 observations of Taiwanese automobile liability insurance for property damage to empirically test the predictions. After controlling for underwriting and macroeconomic variables, we find that both (1) the insured with a lower claim probability (as a proxy for the insured with a lower loss probability) and (2) the insured with a higher salvage value car (as a proxy for the wealthier insured) receive a greater premium discount. These results support our theoretical results.

Domain-specific risk preference and cognitive ability

Kahneman and Tversky’s works on Prospect Theory compellingly demonstrate that people tend to show varying risk-attitudes for gains versus losses as well as high versus low probabilities associated with the outcomes. Although some studies have found that individuals with lower cognitive skills tend to be risk averse, the literature has not addressed yet a comprehensive understanding of domain-specific risk preference variation by cognitive ability and by gains versus losses as well as high versus low probabilities associated with the outcomes. Thus, this paper attempts to provide a comprehensive picture of domain-specific risk preference variations. The results of this paper show the following: individuals with low cognitive skills tend to be risk-averse (and more risk-averse compared to people with high cognitive ability) when facing high probability of gain or low probability of loss, however risk-seeking (although less risk-seeking compared to people with high cognitive ability) when facing low probability of gain or high probability of loss. My results are consistent with the implications of Kahneman and Tversky’s prospect theory.