Hierarchical Programming Research Articles

A Hierarchical Planning Method for AUV Search Tasks Based on the Snake Optimization Algorithm.

In a complex and dynamic battlefield environment, enabling autonomous underwater vehicles (AUVs) to reach dynamic targets in the shortest possible time using global autonomous planning is a key issue affecting the completion of search tasks. In this study, ahierarchicalAUV task planning method that uses a combination of hierarchical programming and a snake optimization algorithm is proposed for two typical cases where the platform can provide initial target information. This method decomposes the search task problem into a three-level programming problem, with the outer task planning goal of achieving the shortest encounter time between AUV and dynamic targets; the goal of task planning in the middle layer is to achieve the shortest actual navigation time for AUVs under different operating conditions; and the internal task planning is responsible for considering the comprehensive trajectory optimization under navigation constraints such as threat zone, path length, and path smoothness. The snake optimization algorithm was used for solving each layer of task planning. The feasibility of the proposed method was verified through simulation experiments of AUV search tasks under two types of initial target information conditions. The simulation results show that this method can achieve task planning for AUV searching for dynamic targets under various constraint conditions, optimize the encounter time between AUV and dynamic targets, and have strong engineering practical value. It has certain reference significance for task planning problems similar to underwater unmanned equipment.

Sprayable biomimetic double mask with rapid autophasing and hierarchical programming for scarless wound healing.

Current sprayable hydrogel masks lack the stepwise protection, cleansing, and nourishment of extensive wounds, leading to delayed healing with scarring. Here, we develop a sprayable biomimetic double wound mask (BDM) with rapid autophasing and hierarchical programming for scarless wound healing. The BDMs comprise hydrophobic poly (lactide-co-propylene glycol-co-lactide) dimethacrylate (PLD) as top layer and hydrophilic gelatin methacrylate (GelMA) hydrogel as bottom layer, enabling swift autophasing into bilayered structure. After photocrosslinking, BDMs rapidly solidify with strong interfacial bonding, robust tissue adhesion, and excellent joint adaptiveness. Upon implementation, the bottom GelMA layer could immediately release calcium ion for rapid hemostasis, while the top PLD layer could maintain a moist, breathable, and sterile environment. These traits synergistically suppress the inflammatory tumor necrosis factor-α pathway while coordinating the cyclic guanosine monophosphate/protein kinase G-Wnt/calcium ion signaling pathways to nourish angiogenesis. Collectively, our BDMs with self-regulated construction of bilayered structure could hierarchically program the healing progression with transformative potential for scarless wound healing.

Reexamination of the relationships among neurocognition, self-defeatist beliefs, experiential negative symptoms, and social functioning in a sample of patients diagnosed with chronic schizophrenia and schizoaffective disorder

PurposeThis study proposed and evaluated a theoretical model for exploring the relationships between neurocognition, self-defeatist beliefs, experiential negative symptoms, and social functioning in individuals with chronic schizophrenia.MethodThe study recruited 229 individuals given a diagnosis of schizophrenia and schizoaffective disorders from outpatient clinics and the day ward of a mental health hospital. After informed consent was obtained, the participants underwent assessments using the backward digit span, the digit symbol, and measures of self-defeatist beliefs, experiential negative symptoms, and social functioning. A structural equation model was applied to assess the fitness of the hypothesized model, with indices such as the goodness-of-fit index, comparative fit index, root mean square error of approximation, and standardized root mean square residual being used for model evaluation.ResultsThe hypothesized model had an adequate fit. The study findings indicated that neurocognition might indirectly influence self-defeatist beliefs through its effect on experiential negative symptoms. Contrary to expectations, the study did not observe a direct influence of neurocognition, self-defeatist beliefs, or negative symptoms on social functioning. The revised model revealed the role of experiential negative symptoms in mediating the association between neurocognition and social functioning. However, self-defeatist beliefs did not significantly affect social functioning.DiscussionBefore modifying negative thoughts, enhancement of self-awareness ability can help improve negative symptoms and thereby improve the performance of social functions. Future research should develop a hierarchical program of negative symptoms, from cognition rehabilitation to enhancement of self-awareness, and end with modifying maladaptive beliefs.

Scheme of Operation for Multi-Robot Systems with Decision-Making Based on Markov Chains for Manipulation by Caged Objects

This paper presents the design of a new control scheme for a group of omnidirectional robots in a multi-robot system operating in an environment with obstacles. The control scheme uses a decision agent based on discrete-time Markov chains and takes into account the state of the system, obstacle positions, and geometries to manipulate targets, providing robustness against measurement uncertainties. The decision process is dynamic, with state information updating at each time step and tasks being executed based on the hierarchy determined by quadratic hierarchical programming. The system’s stability in the mean-square sense is analyzed through the study of a closed-loop stochastic system, and the effectiveness of the proposed control scheme is demonstrated through numerical simulations, including a comparative analysis with a finite-state machine decision agent.

Complexity guarantees for an implicit smoothing-enabled method for stochastic MPECs

Mathematical programs with equilibrium constraints (MPECs) represent a class of hierarchical programs that allow for modeling problems in engineering, economics, finance, and statistics. While stochastic generalizations have been assuming increasing relevance, there is a pronounced absence of efficient first/zeroth-order schemes with non-asymptotic rate guarantees for resolving even deterministic variants of such problems. We consider a subclass of stochastic MPECs (SMPECs) where the parametrized lower-level equilibrium problem is given by a deterministic/stochastic variational inequality problem whose mapping is strongly monotone, uniformly in upper-level decisions. Under suitable assumptions, this paves the way for resolving the implicit problem with a Lipschitz continuous objective via a gradient-free zeroth-order method by leveraging a locally randomized spherical smoothing framework. Efficient algorithms for resolving the implicit problem allow for leveraging any convexity property possessed by the implicit problem, which in turn facilitates the computation of approximate global minimizers. In this setting, we present schemes for single-stage and two-stage stochastic MPECs when the upper-level problem is either convex or nonconvex in an implicit sense. (I). Single-stage SMPECs. In single-stage SMPECs, in convex regimes, our proposed inexact schemes are characterized by a complexity in upper-level projections, upper-level samples, and lower-level projections of $${\mathcal {O}}(\tfrac{1}{\epsilon ^2})$$ , $${\mathcal {O}}(\tfrac{1}{\epsilon ^2})$$ , and $${\mathcal {O}}(\tfrac{1}{\epsilon ^2}\ln (\tfrac{1}{\epsilon }))$$ , respectively. Analogous bounds for the nonconvex regime are $${\mathcal {O}}(\tfrac{1}{\epsilon })$$ , $${\mathcal {O}}(\tfrac{1}{\epsilon ^2})$$ , and $${\mathcal {O}}(\tfrac{1}{\epsilon ^3})$$ , respectively. (II). Two-stage SMPECs. In two-stage SMPECs, in convex regimes, our proposed inexact schemes have a complexity in upper-level projections, upper-level samples, and lower-level projections of $${\mathcal {O}}(\tfrac{1}{\epsilon ^2})$$ , $${\mathcal {O}}(\tfrac{1}{\epsilon ^2})$$ , and $${\mathcal {O}}(\tfrac{1}{\epsilon ^2}\ln (\tfrac{1}{\epsilon }))$$ while the corresponding bounds in the nonconvex regime are $${\mathcal {O}}(\tfrac{1}{\epsilon })$$ , $${\mathcal {O}}(\tfrac{1}{\epsilon ^2})$$ , and $${\mathcal {O}}(\tfrac{1}{\epsilon ^2}\ln (\tfrac{1}{\epsilon }))$$ , respectively. In addition, we derive statements for accelerated schemes in settings where the exact solution of the lower-level problem is available. Preliminary numerics suggest that the schemes scale with problem size, are relatively robust to modification of algorithm parameters, show distinct benefits in obtaining near-global minimizers for convex implicit problems in contrast with competing solvers, and provide solutions of similar accuracy in a fraction of the time taken by sample-average approximation (SAA).

Blending the Popular and the Profound: Organ Concerts at the 1893 World's Columbian Exposition

AbstractThe 1893 World's Columbian Exposition in Chicago was a watershed moment in U.S. organ culture. Over the course of four months, twenty-one of the finest organists in the country, along with Alexandre Guilmant of Paris, performed sixty-two solo organ recitals on a large new organ built by Farrand and Votey, paving the way for the rise of the solo organ concert in the United States. Although this was a seminal event in the organ world, it has largely been overlooked in modern musicological scholarship. This article contextualizes the series within the wider program of the fair's Bureau of Music and compares the programming strategies between Bureau of Music director Theodore Thomas and organ series director Clarence Eddy. Thomas chose to promote a hierarchical programming model that ultimately failed, but the organists endeavored to offer programs that appealed to both the uninitiated and the connoisseur. A detailed analysis of organ concert programs at the fair using a new database reveals the way in which organists embraced a mixture of “popular” and “profound” elements in their programming that was later disseminated in magazines, pamphlets, and performing editions after the event.

A novel combined Fuzzy-M5P model tree control applied to grid-tied PV system with power quality consideration

ABSTRACT A novel control strategy based on an effective combination of the fuzzy logic controller and the M5P decision tree algorithm (Fuzzy-M5P) for a grid-interfaced solar energy system is proposed in this paper. The aim is to benefit from fuzzy logic advantages using its resulting datasets along with the fast model tree functionality. This mixed control has the ability to cope effectively with the large computation time and complexity of fuzzy logic controllers especially when embedded systems or real-time implementation are considered. Using a photovoltaic (PV) inverter with active filtering capability, the primary objective is to provide a grid-solar topology with a maximum PV energy extraction and power quality enhancement. For the inverter control, the M5P model was tested in the indirect current technique. This harmonic generation method is very efficient and its performances are entirely dependent on the chosen dc-link controller. Moreover, a novel maximum power point tracking technique (MPPT) based on the M5P model tree is performed in which data inputs are collected from fuzzy logic-based MPPT. WEKA and MATLAB software are used to translate the model by formulating a simple hierarchical program structure. To validate the effectiveness of the proposed control, simulation, and experimental tests are done under steady and dynamic conditions. The final developed algorithm based on simple IF-ELSE rules shows promising results, it can reduce harmonic distortions to 2.77%, perfectly compensates reactive power with almost unity power factor, and enhances dynamic performances with fast transient response.

AHP-goal programming as the optimization method for management model in oil palm empty bunches waste

PurposeThis study aims to determine the optimum model of oil palm empty bunches (OPEB) management, to determine the optimal number of OPEB in waste management, which is then recommended to the company, and to know the achievement of various goals/targets with limited availability of resources.Design/methodology/approachThis research uses quantitative and qualitative approaches. Quantitative approach is done by processing the data for financing and profit analysis in OPEB waste management which is then used for resource approach. A qualitative approach is undertaken for weighing purposes in the analytic hierarchical program (AHP) analysis. The research location was determined purposively in the crude palm oil mill of PT. Pundi Lahan Khatulistiwa in Ambawang, Kubu Raya Regency.FindingsIn order that the optimal settlement can achieve the goal/target of minimal environmental pollution, low cost and profit gain, the amount of OPEB that must be managed by the company is 311 tons prioritized for productive plants compost of 66.67 tons, organic fertilizer of 11 tons and mushroom growing media of 233.33 tons. Consequently, the company's cost of IDR 4.000.000.000 still spares IDR 2.004.694.000. The OPEB management as oyster mushroom promises a relatively high profit compared to other OPEB managements even though the cost is not the least.Originality/valueThis research is one of the few studies that examines the waste management model of palm oil empty bunches, mainly located in West Kalimantan, Indonesia. Originality is seen from the use of optimization analysis tools with integration of AHP with goal programming.

Exploring the effects of status demotion in hierarchical loyalty programs

ABSTRACT Service industries practice hierarchical loyalty programs (HLP) to enhance the relationship with customers. However, little is known about the negative effects of HLP status demotion and under what condition such effects vary among the demoted customers. This study thus aims to examine the effects of HLP status demotion on customers’ satisfaction, word-of-mouth, and share-of-wallet. This study further explores the moderating role of the cause of demotion (spending-based vs. policy-based) of such effects. Two studies were conducted in the context of hotel and airlines industries in Bangladesh. PROCESS Macro was used to test the moderated mediation model, and the results of both studies show that status demotion significantly influences customers’ satisfaction, word-of-mouth, and share-of-wallet. Further, customers who perceive firms’ policy changes as the cause of their status demotion show lower level of satisfaction, word-of-mouth, and share-of-wallet.

A Hierarchical Restoration Mechanism for Distribution Networks Considering Multiple Faults

Service restoration of distribution networks in contingency situations is one of the highly investigated and challenging problems. In the conventional service restoration method, utilities reconfigure the topological structure of the distribution networks to supply the consumer load demands. However, the advancements in renewable distributed generations define a new dimension for developing service restoration methodologies. This paper proposes a hierarchical service restoration mechanism for distribution networks in the presence of distributed generations and multiple faults. The service restoration problem is modeled as a complicated and hierarchical program. The objectives are to achieve the maximization of loads restored with minimization of switch operations while simultaneously satisfying grid operational constraints and ensuring a radial operation configuration. We present the service restoration mechanism, which includes the dynamic topology analysis, matching isolated islands with renewable distributed generations, network reconfiguration, and network optimization. A new code scheme that avoids feasible solutions is applied to generate candidate solutions to reduce the computational burden. We evaluate the proposed mechanism on the IEEE 33 and 69 systems and report on the collected results under multitype fault cases. The results demonstrate the importance of the available renewable distributed generations in the proposed mechanism. Moreover, simulation results verify that the proposed mechanism can obtain reasonable service restoration plans to achieve the maximization of loads restored and minimization of switching operations under different faults.

Establishment of the Program for Hierarchical Prevention and Control of Sudden Infectious Diseases Based on the Coronavirus Disease 2019: Experience of Peking Union Medical College Hospital

In the current situation of Corona virus disease 2019， “to prevent import from abroad and to defend internal rebound” is the general principle. Facing the changes in the epidemic situation， especially the winter and spring epidemics， it is a huge challenge to carry out a scientific, precise and flexible program for the prevention and control of healthcare-associated infections so that to ensure the safety of healthcare workers and patients. After more than a year of anti-epidemic work， Peking Union Medical College Hospital has summarized and formulated a four-level retractable and releasable hierarchical program of prevention and control. It is dynamically adjusted according to the responsive level of public health emergencies in Beijing and the relevant regulations of epidemic prevention and control. Various departments can also respond quickly to ensure the resumption of work. This program provides reference for the prevention and control of coronavirus disease 2019 and other sudden infectious diseases.

Collision Risk Assessment by using Hierarchical Clustering Method and Real-time Data

The identification of regional collision risks in water areas is significant for the safety of navigation. This paper introduces a new method of collision risk assessment that incorporates a clustering method based on the distance factor - hierarchical clustering - and uses real-time data in case of several surrounding vessels, group methodology and preliminary assessment to classify vessels and evaluate the basis of collision risk evaluation (called HCAAP processing). The vessels are clustered using the hierarchical program to obtain clusters of encounter vessels and are combined with the preliminary assessment to filter relatively safe vessels. Subsequently, the distance at the closest point of approach (DCPA) and time to the closest point of approach (TCPA) between encounter vessels within each cluster are calculated to obtain the relation and comparison with the collision risk index (CRI). The mathematical relationship of CRI for each cluster of encounter vessels with DCPA and TCPA is constructed using a negative exponential function. Operators can easily evaluate the safety of all vessels navigating in the defined area using the calculated CRI. Therefore, this framework can improve the safety and security of vessel traffic transportation and reduce the loss of life and property. To illustrate the effectiveness of the framework proposed, an experimental case study was conducted within the coastal waters of Mokpo, Korea. The results demonstrated that the framework was effective and efficient in detecting and ranking collision risk indexes between encounter vessels within each cluster, which allowed an automatic risk prioritization of encounter vessels for further investigation by operators.

Combining approximation and exact penalty in hierarchical programming

We address the minimization of an objective function over the solution set of a (non-parametric) lower-level variational inequality. This problem is a special instance of semi-infinite programs and encompasses, as particular cases, simple (smooth) bilevel and equilibrium selection problems. We resort to a suitable approximated version of the hierarchical problem. We show that this, on the one hand, does not perturb the original (exact) program ‘too much’, on the other hand, allows one to rely on some suitable exact penalty approaches whose convergence properties are established.

Learning hierarchical probabilistic logic programs

Probabilistic logic programming (PLP) combines logic programs and probabilities. Due to its expressiveness and simplicity, it has been considered as a powerful tool for learning and reasoning in relational domains characterized by uncertainty. Still, learning the parameter and the structure of general PLP is computationally expensive due to the inference cost. We have recently proposed a restriction of the general PLP language called hierarchical PLP (HPLP) in which clauses and predicates are hierarchically organized. HPLPs can be converted into arithmetic circuits or deep neural networks and inference is much cheaper than for general PLP. In this paper we present algorithms for learning both the parameters and the structure of HPLPs from data. We first present an algorithm, called parameter learning for hierarchical probabilistic logic programs (PHIL) which performs parameter estimation of HPLPs using gradient descent and expectation maximization. We also propose structure learning of hierarchical probabilistic logic programming (SLEAHP), that learns both the structure and the parameters of HPLPs from data. Experiments were performed comparing PHIL and SLEAHP with PLP and Markov Logic Networks state-of-the art systems for parameter and structure learning respectively. PHIL was compared with EMBLEM, ProbLog2 and Tuffy and SLEAHP with SLIPCOVER, PROBFOIL+, MLB-BC, MLN-BT and RDN-B. The experiments on five well known datasets show that our algorithms achieve similar and often better accuracies but in a shorter time.

A bi-objective hierarchical program scheduling problem and its solution based on NSGA-III

A bi-objective hierarchical program scheduling problem and its solution based on NSGA-III

Energy-Water-Carbon Nexus Optimization for the Path of Achieving Carbon Emission Peak in China Considering Multiple Uncertainties: A Case Study in Inner Mongolia

The Chinese government has launched a guideline for carbon emissions up to the peak (CEUP) in the 2030 target. The electric power sector has to make its own contributions to the national CO2 emissions mitigation target. In this study, a patron–client interactive optimized (PCIO) model is proposed to investigate the regional energy–water–carbon nexus optimization under the policy background of the CEUP target. Inner Mongolia, the largest energy base in China, which is also facing the prominent contradiction including the energy production and serious environmental problems, is chosen as a case study. Multiple uncertainties, including the fuel price uncertainty and output of the wind and solar power, are considered to make the optimization process more realistic. Results show that coal-fired power will gradually be substituted by the gas, wind, and solar power in Inner Mongolia to reach the CEUP target. The CO2 capture and storage technology and air-cooling systems will play important roles, especially under the strict water policy scenario. However, the achievement of the CEUP and water-saving target will be at the expense of high system costs. The PCIO model makes it possible for the decision-maker to make flexible strategies to balance the CEUP target and saving system costs. The results have demonstrated the validity of the PCIO model in addressing the hierarchical programming problems.

Maṇḍala within the Rock: The Visualization of the Mahāmāyūrī-vidyārājñī and its Altar in Southwestern China, 9th–13th Centuries

Abstract This paper considers visualizations in Chinese medieval esoteric Buddhism in seven sculptural tableaux of the Mahāmāyūrī-vidyārājñī (Peacock Wisdom King 孔雀明王) from rock carving sites in the Sichuan Basin, Southwestern China. Early scholars highlighted the authority of Amoghavajra’s ritual manual for the Mahāmāyūrī images in this area, yet divergences between text and image hold them back from further interpretation. This paper reinvestigates these Mahāmāyūrī shrines “dialectically” by considering the text-image relationship. While keeping Amoghavajra’s ritual manual as a reference, it attempts to decode the meaning of the images and sites based on their own content, and to extrapolate from the text-image divergences how artistic productions and esoteric practices could lead to the presence of such divergences. This involves discussing artistic forms and decorative elements appropriated from exoteric Buddhism, as well as adjustments to the central icon and adjacent narrative scenes weaved within the temporal and spatial transitions. It also includes observations on the grouping between the Mahāmāyūrī and other deities in the larger iconographic program in their affiliated rock-cut sites, which reflects the interaction between this esoteric teaching and other popular beliefs. At least four out of seven examples share the same hierarchical iconographic programs or signature spatial structures similar to the Mahāmāyūrī altar prescribed in Amoghavajra’s ritual manual. It takes these visual or spatial similarities as concrete evidences that the construction of these shrines intended to make altars/maṇḍalas, although in two different ways to represent the esoteric altar and to create a space to conduct such a ritual.

Origami spring-inspired metamaterials and robots: An attempt at fully programmable robotics.

Recent advances in three-dimensional printing technologies provide one way not only to speed up freeform fabrication but also to exert programmable control over mechanical properties. Besides, origami-inspired structures, origami-inspired metamaterials, and even origami-inspired robotics primarily demonstrate the promising potential for innovative inspirations of engineering solutions. The motivation of this work is to explore a fully programmable robotic perspective with a fusion of programmable metamaterials, programmable mechanics, and programmable fabrication. First, we proposed an illustrative roadmap for transforming an origami model into a fully programmable robotic system. Then, we introduced an origami spring model and revealed its shape-shifting geometry and intrinsic metamaterial mechanisms, especially the rarely switchable behavior from transverse compression to longitudinal stretchability, and the curvilinear deployment. Furthermore, we addressed the fabrication challenges of three-dimensional printable origami sheets considering three-dimensional printability, foldability with high elasticity, and good damage tolerance. Finally, we developed a fully soft manipulator in terms of the highly reversible compressibility of origami spring metamaterials. And we also devised a peristaltic crawling robot with undulatory movements induced by inclination deployment effect of origami spring metamaterials. Conceivably, the proposed fully programmable robotic system was demonstrated starting from programmable metamaterials, programmable mechanics, and programmable fabrication to programmable robotic behaviors. The contribution of this work also suggested that robotic morphing could be tunable by hierarchical programming from modeling and fabrication to actions.

The impact of clean development mechanism on energy-water-carbon nexus optimization in Hebei, China: A hierarchical model based discussion

Clean development mechanism (CDM) is an important principle in CO2 emissions mitigation since it was proposed. However, there will be a long way for the large-scale application of CDM in China, for thermal power is still in the dominant position, while renewable power is far from being competitive. In this study, a mix integer bi-level hierarchical programming model (MIBLHP) is developed to investigate the potential impact of the CDM application on the regional energy-water-carbon nexus optimization in electric power system in China. The model integrates the advantages of bi-level programming and mix integer liner programming in dealing with conflicting objectives with hierarchical and sequential decision making process and help to achieve the optimized strategies with the highest overall system satisfaction degree. Results show that CDM will play an important role in the regional energy-water-carbon nexus optimization, the MIBLHP is able to stabilize the increasing trend of system cost and make better tradeoffs between the economic and environmental goals. Optimal strategies including power generation and capacity expansion path, system cost control, CO2 emissions abatement strategies, water consumption and waste water discharge are presented. The system would reach the supreme satisfaction degrees (λ = 0.934) when the CO2 reduction level is 40%, which means that every part of the system has achieved the best condition. The proposed model has great potential in dealing with similar regional planning problems in energy-water-carbon nexus optimization.

위계적 로열티 프로그램과 소비자 등급: 지각된 부러움과 공정성이 기업 태도에 미치는 영향

위계적 로열티 프로그램과 소비자 등급: 지각된 부러움과 공정성이 기업 태도에 미치는 영향