Hierarchical Multilevel Research Articles

Synthesis of MAPbBr3 -Polymer Composite Films by Photolysis of DMF: Toward Transparent and Flexible Optical Physical Unclonable Functions (PUFs) with Hierarchical Multilevel Complexity.

Physical entities with inherent randomness have been investigated as anti-counterfeiting labels based on physical unclonable functions (PUFs). Herein, a transparent and flexible optical PUF label associated with multilevel complexity is demonstrated by taking advantage of the optical properties of hierarchical morphologies of the composite film composed of metal halide perovskite nanoparticles (MAPbBr3 NPs) and the intrinsic spinodal-decomposition-like phase separation of polymer blend (PMMA/PS blend). Due to the combinatorial effects of the photolysis synthesis of MAPbBr3 and the thermodynamic instability of the PMMA/PS blend, randomized patterns emerge at two-level scales. These patterns are intrinsically non-deterministic, and therefore, the PUF labels from the multilevel random patterns are challenging to replicate. This is mainly attributed to random spot patterns (higher-level patterns) confined within intricate bicontinuous patterns (lower-level patterns).

Label Metric for Multi-Class Multi-Target Tracking under Hierarchical Multilevel Classification.

Aiming at multiple quantities and types of targets, multi-class multi-target tracking usually faces not only cardinality errors, but also mis-classification problems. Considering its performance evaluation, the traditional optimal subpattern assignment (OSPA) method tends to calculate a separate metric for each class of targets, or introduce other indexes such as the classification error rate, which decreases the value of OSPA as a comprehensive single metric. This paper proposed a hierarchical multi-level class label for multi-class multi-target tracking under hierarchical multilevel classification, which can synthetically measure the state errors, cardinality error, and mis-classification. The hierarchical multi-level class label is introduced as an attached label to finite sets based on the hierarchical tree-structured categorization. A Wasserstein distance type metric then can be defined among the distribution represented by any two labels. The proposed label metric is a mathematic metric, and its advantages are illustrated by examples in several cases.

Hierarchical Multilevel Surrogate Model Based on POD Combined With RBF Interpolation of Nonlinear Magnetostatic FE Model

From solutions of finite element (FE) simulations depending on parameters, a surrogate model of the FE solution can be built based on the proper orthogonal decomposition (POD) combined with the radial basis functions (RBFs) interpolation. Then, a fast approximation of an FE solution can be computed for any parameter set. In order to optimize the number of FE solutions required for the construction of the surrogate model and to control the error between the FE and surrogate models, a hierarchical multilevel approach based on an iterative algorithm is investigated. In this article, a hierarchical multilevel (H-POD-RBF) approach is developed for a nonlinear magnetostatic problem. In terms of application, a 3-D three-phase inductance is considered. The results obtained from the surrogate model are compared with those given from the FE model for a current or voltage supply.

Analysis of the Correlation between Cross‐Border E‐Commerce and Economic Growth Based on Hierarchical Multilevel Gray Evaluation Model

Cross‐border e‐commerce is a new form of global trade development under the background of “Internet+,” and it is also a new engine driving economic development. Cross‐border e‐commerce is growing rapidly and has broad development prospects. As a pioneering pilot zone for comprehensive cross‐border e‐commerce, it has played a leading role in the development of the country’s cross‐border e‐commerce industry. This paper takes China’s 35 cross‐border e‐commerce comprehensive pilot areas as the research object, selects the annual data of 31 provinces across the country, and conducts an empirical research based on the gray‐related Internet development level and economic growth. It analyzes the influencing factors of cross‐border e‐commerce development, constructs a cross‐border e‐commerce development influencing factor model, and applies gray theory to conduct an empirical analysis of the correlation between cross‐border e‐commerce development influencing factors and cross‐border e‐commerce. The research results show that foreign direct investment has the greatest correlation with the number of websites and webpages; the number of patent applications has the greatest correlation with the number of domains and websites; the total fixed assets have the greatest correlation with the number of Internet users and the number of mobile phones at the end of the year; the total amount of foreign investment enterprises in and out. It has the greatest correlation with the number of URLs and Webpages; GDP has the greatest correlation with the number of Internet users and the number of mobile phones at the end of the year. The Internet infrastructure and popularity have a close relationship with economic growth, and the relationship between foreign investment and patent applications and the level of Internet development is more significant.

Fear of childbirth, nonurgent obstetric interventions, and newborn outcomes: A randomized controlled trial comparing mindfulness-based childbirth and parenting with enhanced care as usual.

ObjectiveTo investigate whether mindfulness‐based childbirth and parenting (MBCP) or enhanced care as usual (ECAU) for expectant couples decreases fear of childbirth (FOC) and nonurgent obstetric interventions during labor and improves newborn outcomes.DesignRandomized controlled trial.SettingMidwifery settings, the Netherlands, April 2014‐July 2017.PopulationPregnant women with high FOC (n = 141) and partners.MethodsAllocation to MBCP or ECAU. Hierarchical multilevel and intention‐to‐treat (ITT) and per‐protocol (PP) analyses.Main outcome measuresPrimary: pre‐/postintervention FOC, labor anxiety disorder, labor pain (catastrophizing and acceptance), and preferences for nonurgent obstetric interventions. Secondary: rates of epidural analgesia (EA), self‐requested cesarean birth (sCB), unmedicated childbirth, and 1‐ and 5‐minute newborn's Apgar scores.ResultsMBCP was significantly superior to ECAU in decreasing FOC, catastrophizing of labor pain, preference for nonurgent obstetric interventions, and increasing acceptance of labor pain. MBCP participants were 36% less likely to undergo EA (RR 0.64, 95% CI [0.43‐0.96]), 51% less likely to undergo sCB (RR 0.49, 95% CI [0.36‐0.67]), and twice as likely to have unmedicated childbirth relative to ECAU (RR 2.00, 95% CI [1.23‐3.20]). Newborn's 1‐minute Apgar scores were higher in MBCP (DM −0.39, 95% CI [−0.74 to −0.03]). After correction for multiple testing, results remained significant in ITT and PP analyses, except EA in ITT analyses and 1‐minute Apgar.ConclusionsMBCP for pregnant couples reduces mothers’ fear of childbirth, nonurgent obstetric interventions during childbirth and may improve childbirth outcomes. MBCP adapted for pregnant women with high FOC and their partners appears an acceptable and effective intervention for midwifery care.

ERRATUM: A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow

ERRATUM: A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow

Network Public Opinion Data Mining Model of Hierarchical Multi Level

Network Public Opinion Data Mining Model of Hierarchical Multi Level

Hierarchical Architecture for Integration of Rooftop PV in Smart Distribution Systems

This paper presents a novel hierarchical multilevel decentralized optimal power flow (OPF) for power loss minimization in three-phase unbalanced large-scale distribution systems via optimal reactive power scheduling of rooftop photovoltaics generators. The system is decomposed into three levels corresponding to: 1) the primary; 2) the lateral; and 3) the secondary feeder subnetworks of distribution systems. A distributed sequential coordination scheme based on analytical target cascading method is developed to minimize power losses while considering the operational constraints. Results based on the proposed method are compared with centralized OPF for validation. Control based on the proposed method is compared with no reactive power control and local reactive power control to identify its effectiveness. Further, a virtual feeder is introduced to separate the coupled subnetworks into decomposed layers, which enables parallel processing of the optimization problems to reduce computational complexity and provide faster solution. A 559-node large-scale distribution network built based on the IEEE 37 node test system is used to demonstrate performance of the proposed algorithm.

A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow

In this paper we address the problem of the prohibitively large computational cost of existing Markov chain Monte Carlo methods for large--scale applications with high dimensional parameter spaces, e.g. in uncertainty quantification in porous media flow. We propose a new multilevel Metropolis-Hastings algorithm, and give an abstract, problem dependent theorem on the cost of the new multilevel estimator based on a set of simple, verifiable assumptions. For a typical model problem in subsurface flow, we then provide a detailed analysis of these assumptions and show significant gains over the standard Metropolis-Hastings estimator. Numerical experiments confirm the analysis and demonstrate the effectiveness of the method with consistent reductions of more than an order of magnitude in the cost of the multilevel estimator over the standard Metropolis-Hastings algorithm for tolerances $\varepsilon < 10^{-2}$.

Hierarchical Multilevel on/off Source Traffic Modeling for a Warship Combat System

For successful migration to network-centric warfare (NCW), it is necessary to control and manage sensor, weapons, and communication systems. Each of these systems must be incorporated in a combat management (CM) system through connection via the combat system databus (CSDB). This synergy between critical features is termed a warship combat system (WCS). For optimization of WCS, performance evaluation before real war should be conducted to measure the reliability of the system. This is accomplished through traffic modeling according to specific scenarios of warships. In practice, the traffic of each system within the WCS exhibits self-similar behavior. This is different from the behavior of short-range dependence (SRD) processes. In this paper, we propose a traffic model called the hierarchical multilevel on/off source (HMLOS) model, which aggregates a number of on/off sources in accordance with the hierarchical structure of the WCS after taking into account the individual characteristics of traffic in each system. The duration of time for the on state of each module is described using the Pareto distribution with a different Pareto index. For two different scenarios, including general navigation and training (GNT) and combat and emergency (CE), the proposed model demonstrates characteristics of self-similarity that are closer to the original characteristics of traffic than conventional traffic modeling.

Modeling the Competitiveness of Indonesian Palm Oil Industry: A Conceptual Model Using Hierarchical Multi-Level System Approach

Indonesian Palm Oil Industry has the largest market share in the world, but still faces problems in order to strengthen the level of competitiveness. Those problems are in the industry chains, government regulation and policy as meso environment, and macro economic condition. Therefore these three elements should be considered when analyzing the improvement of competitiveness. Here, the governmental element is hoped to create a conducive environment. This paper presents the industry competitiveness conceptual model, using hierarchical multilevel system approach. The Hierarchical multilevel system approach is used to accommodate the complexity of the industrial relation and the government position as the meso environment. The step to develop the model firstly is to define the relevant system. Secondly, is to formulate the output of the model that is competitiveness in the form of indicator. Then, the relevant system with competitiveness as the output is built into a conceptual model using hierarchical multilevel system. The conceptual model is then discussed to see if it can explain the relevant system, and the potential of it to be developed into mathematical model.

Hierarchical Multilevel Space-Shift Keying for Unequal Error Protection under Rician Fading

Hierarchical Multilevel Space-Shift Keying Modulation is proposed for Unequal Error Protection under Line-Of Sight conditions in Rician fading channels. The High Priority (HP) information is conveyed via the number of active antennas employed to transmit a codeword. The Low Priority (LP) information is transmitted employing Generalized Space Shift Keying (GSSK) in the codeword subsets corresponding to the transmission of the HP symbols. Hierarchical modulation is accomplished by associating phase shifts with every transmit antenna and adjusting these phase shifts to achieve different levels of Unequal Error Protection. The simulations demonstrate the performance and design options offered by the proposed scheme.

A Novel Energy Efficient Hierarchical Multi Level Cluster Routing Protocol based on LEACH

As the use of Wireless sensor networks (WSNs) has grown enormously in the past few decades, the need of scalable & energy efficient routing and data aggregation protocol for large scale deployment has also risen. LEACH is a hierarchical clustering protocol that provides an elegant solution for such protocols. One deficiency that affects the performance of the protocol is existence of very large and very small clusters in the network at the same time. This leads to decrease in lifetime of WSNs. Sensors operate on battery of limited power, so it is a great challenging aim to design an energy efficient routing protocol, which can minimize the delay while offering highenergy efficiency and long span of network lifetime. In this paper, a new protocol is proposed. The proposed protocol is energy efficient multi level cluster-based routing protocol for continuous stream queries in WSN for large network areas. We incorporate multi hop concept into LEACH [3] by dividing clusters into levels as in TL-LEACH [8] and consider a set of cluster heads, head-set, for cluster-based routing. The head-set members are responsible for control and management of the network. On rotation basis, a head-set member receives data from the neighboring nodes and from previous level, then aggregated data is transmitted to node of next level and so on, until it reaches the distant base station. For a given number of data collecting sensor nodes, the number of control and management nodes can be systematically adjusted to reduce the energy consumption, which increases network life and multi hop transmission reduces energy consumption as distance between transmitting nodes is reduced.

A New Method for Achieving Flexibility in Hierarchical Multilevel System Design

Analytical target cascading (ATC) method has been widely applied to solve multilevel decomposed system design optimization problems. In the ATC method, concurrent design is achieved by target cascading. However, due to the complexity and the presence of uncertainty, it is a challenging task to set proper targets. In this article, instead of using point value targets, interval targets are analyzed and propagated through the multilevel system with the goal of reducing the effects of uncertainty while providing more flexibility to a design process. In the proposed method, the design of a hierarchical system at each level is taken as a single-objective optimization problem, by minimizing the degree of deviation between the target response interval and the achievable response interval. Not only the optimal design performance is considered in this method, but also the acceptable variation range of the performance is analyzed. When the present target for a lower level system and the achievable response from a lower level system are not point values, but rather intervals, their probability distributions are not available. Therefore, these variables are treated as interval variables. When the random and interval variables are present, the most probable point-based first-order reliability and the interval analysis methods are used to calculate the reliability bounds. The proposed method for flexibility under uncertainty provides more degree of freedom to the design of lower level systems, while also keeping the performance of the upper systems stable within a tolerable range. The accuracy of the proposed method is demonstrated via comparing results from both the proposed and traditional methods.

Motion tracking using fuzzy logic and consistent labeling for multiple objects in multiple cameras vision

In this work we address the issue of tracking multiple objects in an environment covered by multiple cameras having overlapped fields of view (FOV); we use FOV lines to achieve consistent labeling. The proposed method results advantageous in video-surveillance of indoor and outdoor environments (e.g., airports, metropolitan areas, banks, etc.) or in cinematic and television field for the optimal camera shooting management, suggesting the camera that offers the best view of the objects in the scene. We propose a system infrastructure and a new approach based on a Hierarchical Multilevel Clusterized Architecture (HMC) applied to image tracking. The areas that two or more fields of view have in common are the core for our approach: thanks to FOV lines detection, a Consistent Labeling mechanism is achieved with the use of projective invariants. The user has the chance to indicate one or more Interest Areas. Object Tracking is performed with the application of two tracking algorithms in parallel, ensuring efficient solutions even in scenarios with noised images. The system is time continuous: the temporal distance between two consecutive DAQ frames is much smaller than the one between two consecutive tracking frames. The Human Behaviour Analysis (HBA) Module avails itself of a Decision Support System (DSS) to guide the user in those critical situations that can occur while observing the scene. The anomaly detection is executed with the use of optional ribbons; collisions are managed through the use of the color histograms of the ribbons representing the object. The black areas management (i.e., uncovered areas) is performed by the Fuzzy Prediction System (FPS), structured on two levels and capable to predict the position of the tracked object in the instants immediately subsequent to its entrance in a black area, by means of fuzzy inference rules. The system results particularly efficient thanks to the implementation of a Consistent Labeling mechanism, united with a FPS that contributes to more and more accurate tracking. The use of a DSS and a HBA module simplifies the usage of the system, preserving its security issues.

Modeling, Simulation and Control of Large Scale Cryogenic Systems

This paper presents a dynamic simulator for large scale cryogenic systems using helium refrigerators and controlled by Programmable Logic Controllers (PLC) for the European Organization for Nuclear Research (CERN). The process is modeled by a set of linear differential and algebraic equations and the control policy is based on a hierarchical multilevel and multilayer framework control. First simulation results carried out on the refrigerator used in the Compact Muon Solenoid (CMS) experiment are presented. It is worth to mention that CMS is a particle detector used in the future CERN accelerator (the LHC) where a superconducting magnet of 225 tons, the largest ever built, must be maintained at 4.5K (-268.7°C). The model of this cryogenic plant is composed of 4126 equations whereof 287 differential-algebraic equations. The work objectives of this simulator are threefold: first, to provide a tool to train the operators, second to validate new control strategies before their implementation and, third, to improve our knowledge about large scale complex cryogenic systems. In order to respect the real system architecture, the simulator is composed of different modules sharing data.

Transient Radiation and Conduction Heat Transfer in a Gray Absorbing-Emitting Medium Applied on Two-Dimensional Complex-Shaped Domains

This article is devoted to transient radiation and conduction heat transfer in a gray absorbing-emitting medium in a two-dimensional complex-shaped domain using unstructured triangular meshes. The radiative transfer equation (RTE) is solved by using a new finite-volume method (FVM) based on a cell vertex scheme and associated to a modified exponential scheme. The PHAML (Parallel Hierarchical Adaptive MultiLevel) code is used to solve the energy balance equation using low- or high-order finite elements. Several benchmark cases including steady and transient states and applied to different geometries are used to validate the developed code. Results show very good agreement.

A Hierarchical Multilevel Flow Modeling for Power Substation Control and Restoration

The intelligent system proposed in this paper has been implemented for helping the Piratininga Power and Light's technicians in the system operational occurrences. It allows the operator to go through the ways for problem solving. The use of hybrid systems with artificial intelligence techniques, together with correctional numeric techniques, make possible to solve non-systematic problems and to show to the user the reasoning path used for the problem solving. This last factor is very important in a learning process, one of the aims of this system, once it make possible for the operator to understand the way the specialist in the area uses for solving one problem.

Coordination of Hierarchical Multiobjective Systems: Theory and Methodology

A static deterministic hierarchical system consisting of subsystems with multiple objectives is considered here; this system's overall multiple objectives are functions of its subsystems' objectives. Two powerful and well-developed approaches-the hierarchical multilevel and the multiobjective multiattribute approaches-are integrated into a unified hierarchical multiobjective framework. Theoretical and methodological grounding for this framework are developed. Two basic schemes-the feasible and the nonfeasible-are derived. The feasible scheme extends existing algorithms with respect to the possibility of several objectives in each subsystem. The nonfeasible scheme constitutes a new contribution to the hierarchical multiobjective framework. Lower dimensional multiobjective subproblems are formulated in terms of trade-offs. Algorithms for coordinating the subproblems are derived. Mainly systems having a single decisionmaker are considered. Thus the first-hand benefit of decomposition accrues to the analyst dealing with lower dimensional subsystems; a possible benefit for the decisionmaker lies in the decreased number of interactions. The presence of multiple decisionmakers is dealt with briefly, using the Stackelberg strategy and negotiations about trade-offs. A numerical example illustrating the basic concepts is presented.

A Hierarchical Strategy for Traffic Control in Urban Networks

The paper presents an application of hierarchical multi level system theory in network traffic control problem solving. Street network is represented by a directed graph. Nodes represent signalized intersections, and arcs represent street sections between adjacent signal ized intersections. Traffic process is described by delay-difference-of-offset functions. Loop constraints on offsets are incorporated in the model. The problem is to minimize loses (delay) in the network. Two-level hierarchical system structure is used in solving the problem. For subproblems coordination interaction balance principle is applied. It is shown that tasks performed by first and second level subsystems are quite simple, and suitable for real time control.