Random Time Research Articles

Модель оценки функциональной устойчивости элементов информационной инфраструктуры для условий воздействия множества компьютерных атак

Information is given about a new approach to the application of methods of the theory of semi-Markov processes to solve the applied problem of assessing the functional stability of elements that make up the information infrastructure, functioning under the influence of multiple computer attacks. The task of assessing functional stability is reduced to the task of finding the survivability function of the element under study and determining its extreme values. The relevance of the study is substantiated. The rationale is based on the assumption that quantitative methods of studying the stability of technical systems, which operate on the theory of reliability, cannot always be used to assess survivability. The concepts of «stability» and «computer attack» are being clarified. Verbal and formal statements of research tasks are formulated. The novelty of the results obtained lies in the application of well-known methods to solve a practically significant problem in a new formulation, taking into account the limitations on the resource allocated to maintain the survivability of the element under study, provided that arbitrary distribution laws are adopted for the random times of the implementation of computer attacks and the recovery times of the functional element. Recommendations on the formation of initial data, the content of the enlarged stages of modeling and a test case to demonstrate the performance of the model are given. The results of the test simulation are presented in the form of graphs of the survivability function. The resulting application can be used in practice to construct a survivability function when implementing up to three computer attacks, as well as a tool for evaluating the reliability of analogous statistical models. The limitation is explained by a progressive increase in the dimension of the analytical model and a decrease in the possibility of its meaningful interpretation.

Optimal and heuristic policies for production and inventory controls in dual supply chains with fluctuating demands

AbstractIn the context of fast‐fashion business, we study the joint control of production, inventory, and unilateral transshipment in dual supply chains in which one supply chain is a responsive supply chain for fashion products and the other is an efficient supply chain for basic products in a fluctuating demand environment (FDE). Our research focuses on: (1) formulating an appropriate model for this complex problem; (2) characterizing the structured optimal policy, which can be used to develop effective heuristic policies; and (3) generalizing our studies for more applications. To address these issues, we formulate a discrete‐time finite‐horizon stochastic dynamic program model in which FDE is represented by a world state evolving in accordance with the discrete‐time Markov chain. The supply chain for the fashion product is modeled by a two‐stage tandem production system with a make‐to‐stock (MTS) stage for the fabric and a subsequent MTS stage for finished fashions. In parallel, the supply chain for the basic products is also modeled by a two‐stage tandem production system with a MTS stage for the fabric and a subsequent make‐to‐order (MTO) stage for finished basics. Further, the two supply chains are coupled via the unilateral transshipment of fabric with random transshipment time. By value iteration, we characterize the optimal policy for the single‐product problem with a set of monotone switching surfaces. The results are extended to the multi‐product multi‐supplier case. Further, based on the structure of the optimal policy, we develop a heuristic policy for the multi‐dimensional dynamic program model. From a practice perspective, we demonstrate the value of transshipment and controlled transshipment, analytically and numerically, and therefore justify the establishment of two separate local manufacturing bases in dual supply chains. Additionally, to achieve both quick response and efficiency, we show that the total cost can be reduced significantly if sufficient fabric is prepared just in time (JIT) for in‐season production at the beginning of a season.

Baseline modern medical management in the BEST-CLI trial

ObjectivesThe use of optimal medical therapy (OMT) in patients with chronic limb-threatening ischemia (CLTI) has not been well-studied. The Best Endovascular vs Best Surgical Therapy in Patients with CLTI study (BEST-CLI) is a multicenter, randomized, controlled trial sponsored by the National Institutes of Health comparing revascularization strategies in patients with CLTI. We evaluated the use of guideline-based OMT among patients with CLTI at the time of their enrollment into the trial. MethodsA multidisciplinary committee defined OMT criteria related to blood pressure and diabetic management, lipid-lowering and antiplatelet medication use, and smoking status for patients enrolled in BEST-CLI. Status reports indicating adherence to OMT were provided to participating sites at regular intervals. Baseline demographic characteristics, comorbid medical conditions, and use of OMT at trial entry were evaluated for all randomized patients. A linear regression model was used to identify the relationship of predictors to the use of OMT. ResultsAt the time of randomization (n = 1830 total enrolled), 87% of patients in BEST-CLI had hypertension, 69% had diabetes, 73% had hyperlipidemia, and 35% were currently smoking. Adherence to four OMT components (controlled blood pressure, not currently smoking, use of one lipid-lowering medication, and use of an antiplatelet agent) was modest. Only 25% of patients met all four OMT criteria; 38% met three, 24% met two, 11% met only one, and 2% met none. Age ≥80 years, coronary artery disease, diabetes, and Hispanic ethnicity were positively associated, whereas Black race was negatively associated, with the use of OMT. ConclusionsA significant proportion of patients in BEST-CLI did not meet OMT guideline-based recommendations at time of entry. These data suggest a persistent major gap in the medical management of patients with advanced peripheral atherosclerosis and CLTI. Changes in OMT adherence over the course of the trial and their impact on clinical outcomes and quality of life will be assessed in future analyses.

Thermalization and Dephasing in Collisional Reservoirs.

We introduce a wide class of quantum maps that arise in collisional reservoirs and are able to thermalize a system if they operate in conjunction with an additional dephasing mechanism. These maps describe the effect of collisions and induce transitions between populations that obey detailed balance, but also create coherences that prevent the system from thermalizing. We combine these maps with a unitary evolution acting during random Poissonian times between collisions and causing dephasing. We find that, at a low collision rate, the nontrivial combination of these two effects causes thermalization in the system. This scenario is suitable for modeling collisional reservoirs at equilibrium. We justify this claim by identifying the conditions for such maps to arise within a scattering theory approach and provide a thorough characterization of the resulting thermalization process.

Material flow control in Remanufacturing Systems with random failures and variable processing times

Material flow control in remanufacturing is an important issue in the field of disassembly. This paper deals with the potential of autonomous material release decisions for remanufacturing systems to balance the uncertainties related to changing bottlenecks, to maximise throughput (TH) and to minimise work-in-process (WIP). The goal is to achieve the highest possible throughput rate using real-time data while keeping costs to a minimum. Unlike traditional production systems, remanufacturing must consider and handle high uncertainties in the process. Up to now, classical methods such as CONWIP, Material Requirement Planning (MRP) and Kanban have been used for material flow control. However, these methods do not perform well in a system with high variation and uncertainties such as remanufacturing as they aim to find solutions for static environments. Crucial for optimal production in stochastic environments is finding the optimum pull or release rate which can vary over time in terms of maximising TH and minimising WIP. We propose a deep reinforcement learning approach that acts on the environment and can adapt to changing conditions. This ensures that changing bottlenecks are taken care of and that there is a minimum WIP in the system.

Random Time Division Multiplexing Based MIMO Radar Processing with Tensor Completion Approach

Automotive radar pursues low cost and high performance, and especially hopes to improve the angular resolution under the condition of a limited number of multiple-input–multiple-output (MIMO) radar channels. Conventional time division multiplexing (TDM) MIMO technology has a limited ability to improve the angular resolution without increasing the number of channels. In this paper, a random time division multiplexing MIMO radar is proposed. First, the non-uniform linear array (NULA) and random time division transmission mechanism are combined in the MIMO system, and then a three-order sparse receiving tensor of a range-virtual aperture-pulse sequence is obtained during echo receiving. Next, this sparse three-order receiving tensor is recovered by using tensor completion technology. Finally, the range, velocity and angle measurements are completed for the recovered three-order receiving tensor signals. The effectiveness of this method is verified via simulations.

The Trial within Cohorts (TwiCs) study design in oncology: experience and methodological reflections

A Trial within Cohorts (TwiCs) study design is a trial design that uses the infrastructure of an observational cohort study to initiate a randomized trial. Upon cohort enrollment, the participants provide consent for being randomized in future studies without being informed. Once a new treatment is available, eligible cohort participants are randomly assigned to the treatment or standard of care. Patients randomized to the treatment arm are offered the new treatment, which they can choose to refuse. Patients who refuse will receive standard of care instead. Patients randomized to the standard of care arm receive no information about the trial and continue receiving standard of care as part of the cohort study. Standard cohort measures are used for outcome comparisons. The TwiCs study design aims to overcome some issues encountered in standard Randomized Controlled Trials (RCTs). An example of an issue in standard RCTs is the slow patient accrual. A TwiCs study aims to improve this by selecting patients using a cohort and only offering the intervention to patients in the intervention arm. In oncology, the TwiCs study design has gained increasing interest during the last decade. Despite its potential advantages over RCTs, the TwiCs study design has several methodological challenges that need careful consideration when planning a TwiCs study. In this article, we focus on these challenges and reflect on them using experiences from TwiCs studies initiated in oncology. Important methodological challenges that are discussed are the timing of randomization, the issue of non-compliance (refusal) after randomization in the intervention arm, and the definition of the intention-to-treat effect in a TwiCs study and how this effect is related to its counterpart in standard RCTs.

The long-run analysis of COVID-19 dynamic using random evolution, peak detection and time series.

It is now almost three years that COVID-19 has been the cause of misery for millions of people around the world. Many countries are in process of vaccination. Due to the social complexity of the problem, the future of decisions is not clear. As such, there is a need for the mathematical modeling to predict the long-run behavior of the COVID-19 dynamic for the decision-making with regard to the result of the pandemic on the economy, health, and others. In this paper, we have studied the short and long-run behavior of COVID-19. In a novel way, random evolution (Trichotomous and Dichotomous Markov Noise) is used to model and analyze the long-run behavior of the pandemic in different phases of the pandemic in different countries. On the given conditions, the random evolution model can help us establish the long-run asymptotic behaviour of the pandemic. This allows us to consider different phases of the pandemic as well as the effect of vaccination and other measures taken. The simplicity of the model makes it a practical tool for decision-making based on the long-run behavior of the pandemic. As such, we have established a criterion for the comparison of different regions and countries in different phases. In this regard, we have used real pandemic data from different countries to validate our results.

Random-time quantum measurements

The analysis of a continuous measurement record $z(t)$ poses a fundamental challenge in quantum measurement theory. Different approaches were used in the past as records can, e.g., exhibit predominantly Gaussian noise, telegraph noise, or clicks at random times. The last case may appear as photon clicks in an optical spin-noise measurement at very low probe laser power. Here we show that such random-time quantum measurements can, similarly to the first two cases, be analyzed in terms of higher-order temporal correlations of the detector output $z(t)$ and be related to the Liouvillian of the measured quantum system. Our analysis in terms of up to fourth-order spectra (quantum polyspectra) shows that this type of spectra reveals the same valuable information as previously studied higher-order spectra in the case of the usual continuous quantum measurements. Surprisingly, broadband system dynamics is revealed even for deliberately low average measurement rates. Many applications are envisioned in high-resolution spectroscopy, single-photon microscopy, circuit quantum electrodynamics, quantum sensing, and quantum measurements, in general.

On a New Characterization of Harris Recurrence for Markov Chains and Processes

This paper shows that Harris recurrent Markov chains and processes can be characterized as the class of Markov chains and processes for which there exists a random time T at which the distribution of the chain or process does not depend on its initial condition. In particular, no independence assumptions concerning the post-T process or T play a role in the characterization. Since Harris chains and processes are known to contain infinite sequences of regeneration times exhibiting various independence properties, it follows that the existence of this single T implies the existence of infinitely many times at which regeneration occurs.

Hysteroscopic resection vs ultrasound-guided dilation and evacuation for treatment of cesarean scar ectopic pregnancy: a randomized clinical trial

Cesarean scar ectopic pregnancy is a type of ectopic pregnancy in which the fertilized egg is implanted in the muscle or fibrous tissue of the scar after a previous cesarean delivery. The condition can be catastrophic if not managed on time and can lead to significant morbidity and mortality. Several approaches have been studied for the management of cesarean scar ectopic pregnancy in women who opted for termination of pregnancy with no consensus on the best treatment modality reached so far. This study aimed to compare the success rate of hysteroscopic resection vs ultrasound-guided dilation and evacuation for the treatment of cesarean scar ectopic pregnancy. This was a parallel group, nonblinded, randomized clinical trial conducted at a single center in Italy. Women with singleton gestations at <8 weeks and 6 days of gestation were included in the study. Inclusion criteria were women with a cesarean scar ectopic pregnancy with positive embryonic heart activity who opted for termination of pregnancy. Patients were randomized 1:1 to receive either hysteroscopic resection (ie, intervention group) or ultrasound-guided dilation and evacuation (ie, control group). Both groups received 50 mg/m2 of methotrexate intramuscularly at the time of randomization (day 1) and another dose at day 3. A third dose of methotrexate was planned in case of persistence of positive fetal heart activity at day 5. Participants received either ultrasound-guided dilation and evacuation or hysteroscopic resection from 1 to 5 days after the last dose of methotrexate. Hysteroscopic resection was performed under spinal anesthesia using a 15 Fr bipolar mini-resectoscope. Dilation and evacuation were performed by vacuum aspiration with a Karman cannula, followed by sharp curettage, if necessary, under ultrasound guidance. The primary outcome was the success rate of the treatment protocol, defined as no further treatment required until the complete resolution of the cesarean scar ectopic pregnancy. Resolution of the cesarean scar ectopic pregnancy was evaluated based on decline of beta-hCG and the absence of residual gestational material in the endometrial cavity. Treatment failure was defined as the necessity for further treatment required until the complete resolution of the cesarean scar ectopic pregnancy. A sample size calculation indicated that 54 participants were required to test the hypothesis RESULTS: A total of 54 women were enrolled and randomized. Number of previous cesarean deliveries ranged from 1 to 3. Overall, 10 women received a third dose of methotrexate with 7 of 27 (25.9%) participants in the hysteroscopic resection group and 3 of 27 (11.1%) in the dilation and evacuation group. The success rate was 100% (27/27) in the hysteroscopic resection group and 81.5% (22/27) in the dilation and evacuation group (relative risk, 1.22; 95% confidence interval, 1.01-1.48). Additional procedures were required in 5 cases of the control group, namely 3 hysterectomies, 1 laparotomic uterine segmental resection, and 1 hysteroscopic resection. The length of stay in the hospital was 9.0±2.9 days in the intervention group and 10.0±3.5 days in the control group (mean difference,-1.00 days; 95% confidence interval,-2.71 to 0.71). No cases of admission to intensive care unit or maternal death were reported. Hysteroscopic resection was associated with an increased success rate in the treatment of cesarean scar ectopic pregnancy when compared with ultrasound-guided dilation and evacuation.

Order-Optimal Correlated Rounding for Fulfilling Multi-Item E-Commerce Orders

Problem definition: We study the dynamic fulfillment problem in e-commerce, in which incoming (multi-item) customer orders must be immediately dispatched to (a combination of) fulfillment centers that have the required inventory. Methodology/results: A prevailing approach to this problem, pioneered by Jasin and Sinha in 2015 , has been to write a “deterministic” linear program that dictates, for each item in an incoming multi-item order from a particular region, how frequently it should be dispatched to each fulfillment center (FC). However, dispatching items in a way that satisfies these frequency constraints, without splitting the order across too many FCs, is challenging. Jasin and Sinha in 2015 identified this as a correlated rounding problem and proposed an intricate rounding scheme that they proved was suboptimal by a factor of at most [Formula: see text] on a q-item order. This paper provides, to our knowledge, the first substantially improved scheme for this correlated rounding problem, which is suboptimal by a factor of at most [Formula: see text]. We provide another scheme for sparse networks, which is suboptimal by a factor of at most d if each item is stored in at most d FCs. We show both of these guarantees to be tight in terms of the dependence on q or d. Our schemes are simple and fast, based on an intuitive idea; items wait for FCs to “open” at random times but observe them on “dilated” time scales. This also implies a new randomized rounding method for the classical Set Cover problem, which could be of general interest. Managerial implications: We numerically test our new rounding schemes under the same realistic setups as Jasin and Sinha and find that they improve runtimes, shorten code, and robustly improve performance. Our code is made publicly available online. History: This paper was selected for Fast Track in the M&amp;SOM Journal from the 2022 MSOM Supply Chain Management SIG Conference. Funding: This research was partially funded by a grant from Amazon.com Inc., which was awarded through collaboration with the Columbia Center of AI Technology (CAIT).

PO-02-011 SHORT TERM OUTCOME OF DIFFERENT LOWER PACING RATES IN PATIENTS WITH RECENTLY IMPLANTED CRT

CRT is a well-established treatment for patients with congestive heart failure, impaired ejection fraction and QRS duration more than 130 msec. Around one third of patients remains to be non-responders. We aim at comparing the effect of two bi-ventricularly base pacing rates (DDD 60 Bpm vs DDD 80 Bpm) on the composite endpoint of mortality and hospitalization due to heart failure. We included patients with recently implanted CRT, all patients had LBBB, QRS duration more than 130 msec and ejection fraction less than 35%. Patients who had more than 80% of their heart rate at the 6th week follow up visit less than 80 beats/minute as evidenced by the heart rate histograms of the implanted device were randomized using randomization table into two groups (DDD 60 bpm and DDD 80 bpm). Patients with atrial fibrillation or active coronary artery disease . Patients were followed 3 months after randomization and then every 6 months thereafter. `Fifty-one patients were enrolled, 45 patients were included in the final analysis (one died before the randomization, two patients were excluded due to average heart more than 80 beats/min at the time of randomization and three were lost to follow up). Mean age was 51.67 ± 11.1 years, 23 patients (51.1%) were females. Thirty-seven patients (82.2%) had dilated Cardiomyopathy, 16 patients (35.6%) had New York heart association (NYHA) functional class (FC) III heart failure (HF) and 29 patients (64.4%) had NYHA class IV (ambulant) HF. At baseline, Minnesota living with heart failure questionnaire score was (52.56 ± 14.3), six minutes-walk distance was 242 ± 95.9 meters and EF was 24.6± 7.4%. Patients were followed for mean duration of 23.2 ± 11.5 months. More patients reached the primary endpoint of death or hospitalization due to heart failure in the DDD 80 bpm group [ 3 (13.6%) vs 13 (56.5%), P=0.003]. This was driven mainly by hospitalization due to heart failure. Death was numerically higher in the DDD 80 group but this was not statistically significant [1 (4.5%) vs 4 (17.4%), P=0.18]. Patients in DDD 60 group had significant improvement in the 6MWD, NYHA functional class, EF % and Minnesota living with heart failure score compared to non-significant improvement in the DDD 80 group. In CRT recipients, Base pacing rate 60 beats/min shows less incidence of the composite endpoint of mortality and hospitalization due to heart failure and base pacing rate 80 beats/min could potentially be harmful.Tabled 1DDD- 60 (22 patients)DDD-80 (23 patients)P ValueΔ Minnesota living with heart failure score-19 ± 1-4 ± 30.01Δ Six minutes Walking distance (meters)185±7410 ± 630.001Δ EF%6 ± 42 ± 30.01NYHA class improvement20 (90%)14 (60%)0.001 Open table in a new tab

Optimal aborting policy for shock exposed missions with random rescue time

Optimal aborting policy for shock exposed missions with random rescue time

Asynchronous Control of Stochastic Switched Boolean Control Networks With Piecewise-Homogeneous Dwell Time.

In this article, the l₁-induced performance of the stochastic switched Boolean control network (BCN) is investigated. The switched signal is considered to follow a time-varying probability distribution, the switching of which is considered to have a random dwell time. The asynchronous state feedback control (SFC) is studied to achieve the control objective. This kind of control can avoid the failure of the control due to the inconsistency between the system mode and the control mode, so the results obtained are more general. Using the semitensor product of matrices, the algebraic form of the considered BCN is represented. Under this framework, sufficient conditions are obtained to ensure that the closed-loop system is stochastic stabilized with a prescribed l₁-induced performance level ɣ. Parameters can be solved by inequalities. In addition, when the dwell time converges to infinity, the probability distribution of the switched signal becomes fixed. Necessary and sufficient conditions are presented to ensure the stabilization of the closed system under asynchronous SFC as well as the design of the asynchronous SFC. Then, sufficient condition is obtained for the prescribed l₁-induced performance level. Examples are presented to show the effectiveness of the obtained results.

Optimal Information Usage in Binary Sequential Hypothesis Testing

An interesting question is whether an information theoretic interpretation can be given of optimal algorithms in sequential hypothesis testing. We prove that for the binary sequential probability ratio test of a continuous observation process, the mutual information between the observation process up to the decision time and the actual hypothesis conditioned on the decision variable is equal to zero. This result can be interpreted as an optimal usage of the information on the hypothesis available in the observations by the sequential probability ratio test. As a consequence, the mutual information between the random decision time of the sequential probability ratio test and the actual hypothesis conditioned on the decision variable is also equal to zero.

Resilient Load Frequency Control of Power Systems to Compensate Random Time Delays and Time-Delay Attacks

Load frequency control (LFC) of modern power systems tends to employ open communication networks to transmit measurement/control signals, which makes the LFC scheme more vulnerable to random time delays and time delay attacks. In this paper, a resilient and active time-delay-compensation-based LFC scheme is proposed to compensate the random time delays and time delay attacks. At first, a state observer is employed to estimate the state of the LFC system. Then a networked predictive control method is used to predict the control signals of the system at the future moments. Next, an evaluation and compensation scheme for random time delays and time delay attacks is constructed in the actuator side of the LFC scheme based on the updating period of the actuator and the timestamp technique. Due to the stochastic characteristics of the random time delays or TDAs, the stability condition of the proposed scheme is developed with the aid of the mean square stability theory. Moreover, a dual-loop open communication is employed in the proposed scheme to improve the reliability and resilience. At last, simulation and experiment tests are undertaken to demonstrate the effectiveness of the proposed scheme.

Optimal Investment and Financing Decisions Under Cost Uncertainty

In this paper, we employ the real options approach to study the impact of cost uncertainty on a firm’s optimal investment and financing decisions. The firm owns a perpetual right to an irreversible investment project, and the firm’s goal is to determine the optimal investment timing and level of coupon payments when the investment cost jumps upward at a random time. We find that the optimal investment threshold and level of coupon payments decrease with the jump intensity and the magnitude of the jump. The cost uncertainty gives the firm a stronger incentive to accept projects with risky cash flows. Furthermore, we examine the conflict of interests between the share- and bond-holders. We show that the debt overhang distortion and the asset substitution incentive decrease with the cost uncertainty. However, the effect of cost uncertainty on the incentive of asset substitution reverses in the region of low operating profits

Poisson points, resetting, universality and the role of the last item

For a stochastic process reset at random times, we discuss to what extent the probabilities of some orderings of observables associated with the intervals of time between resetting events are universal, i.e. independent of the choice of the observables, and in particular, to what extent universality depends on the choice of the distribution of these intervals. For Poissonian resetting, universality relies only on a combinatorial argument and on the statistical properties of Poisson points. For a generic distribution of time intervals between resets, universality no longer holds in general.

An anti-collusion attack defense method for physical layer key generation scheme based on transmission delay.

Physical layer security (PLS) is considered one of the most promising solutions to solve the security problems of massive Internet of Things (IoTs) devices because of its lightweight and high efficiency. Significantly, the recent physical layer key generation (PLKG) scheme based on transmission delay proposed by Huang et al. (2021) does not have any restrictions on communication methods and can extend the traditional physical layer security based on wireless channels to the whole Internet scene. However, the secret-sharing strategy adopted in this scheme has hidden dangers of collusion attack, which may lead to security problems such as information tampering and privacy disclosure. By establishing a probability model, this article quantitatively analyzes the relationship between the number of malicious collusion nodes and the probability of key exposure, which proves the existence of this security problem. In order to solve the problem of collusion attack in Huang et al.'s scheme, this article proposes an anti-collusion attack defense method, which minimizes the influence of collusion attack on key security by optimizing parameters including the number of the middle forwarding nodes, the random forwarding times, the time delay measurement times and the out-of-control rate of forwarding nodes. Finally, based on the game model, we prove that the defense method proposed in this article can reduce the risk of key leakage to zero under the scenario of the "Careless Defender" and "Cautious Defender" respectively.