Parallel Planning Research Articles

Study on UAV Parallel Planning System for Transmission Line Project Acceptance Under the Background of Industry 5.0

In the context of Industry 5.0, in this article, we study the cyber–physical–social systems in unmanned aerial vehicles (UAVs) based on the task background of transmission line project acceptance. First, based on the idea of a parallel system, a parallel UAV planning system for transmission line project acceptance tasks is developed. The mathematical model based on swarm intelligence is then constructed from the multidimensional perspective of improving the acceptance efficiency, shortening the acceptance time, and reducing the energy consumption. This is done based on the physical system data while considering the constraints of UAVs in performing acceptance tasks. Experiments are simulated based on the actual environment data of the quality supervision and acceptance of a 500 kV transmission line project in a plateau area before it is put into production. The obtained results are compared with those of other similar cutting-edge algorithms. The efficiency and practicality of the proposed artificial parallel planning system are finally verified.

PENINGKATAN HASIL BELAJAR PRAKTIKUM FISIKA ‎DENGAN MODEL PEMBELAJARAN KOOPERATIF TIPE TEAM ‎ASSISTED INDIVIDUALIZATION (TAI)‎

This classroom action research was conducted with the aim of knowing the improvement of students' physics practicum learning outcomes on light wave material using the Team Assisted Individualization (TAI) type of cooperative learning model. The research subjects were students of class XI IPA.6 MAN 2 Kota Padang in the 2020/2021 academic year. The research was carried out in two cycles, each cycle consisting of planning, implementation, observation, and reflection stages. Cycle I was carried out on the practical material of parallel plan glass refraction and the second cycle on the practical material of the diffraction grating. Students' practicum activity data is extracted with Student Activity Observation Sheets, teacher practicum learning management data is extracted with Learning Management Observation Sheets, while students' practicum learning outcomes data are excavated using Formative Tests in the form of practice. The results showed that: (1) Cycle I involving students with high initial abilities obtained an average learning outcome of 78.56 and a percentage of completeness 41%; (2) Cycle II involving students with high initial abilities and being given material and skill reinforcement obtained an average learning outcome of 87.78 and a 95% completeness percentage; (3) The learning outcomes of students' physics practicum in the second cycle have increased from the first cycle, both on average and the percentage of completeness. In conclusion, the Team Assisted Individualization (TAI) learning model can improve students' physics practicum learning outcomes.

Parallel Disassembly Sequence Planning of Retired Lithium-ion-battery Pack based on Heuristic Algorithm

With the explosive growth of the electric vehicle market, the recycling work of retired lithium-ion-battery packs, modules and cells is facing great challenges. Dismantling process is the primary step of the electronic waste recycling. In order to achieve rapid, efficient and safe disassembly of battery packs, and improve resource utilization efficiency, reduce environmental pollution, it is necessary to set battery pack disassembly production line. Based on the above targets, four optimization objectives are set, which are idle time, safety factor, disassembly cost and number of workstations. The solving part applies five heuristic algorithms, which can not only expand the solution range, but also discuss the performance of these algorithms. By comparing the value of objective functions, fitness and other indicators, NSGA-II is considered to have better convergence, and the optimal disassembly scheme is given.

PIPS: A Parallel Planning Model of Sentence Production.

Subject-verb agreement errors are common in sentence production. Many studies have used experimental paradigms targeting the production of subject-verb agreement from a sentence preamble (The key to the cabinets) and eliciting verb errors (… *were shiny). Through reanalysis of previous data (50 experiments; 102,369 observations), we show that this paradigm also results in many errors in preamble repetition, particularly of local noun number (The key to the *cabinet). We explore the mechanisms of both errors in parallelism in producing syntax (PIPS), a model in the Gradient Symbolic Computation framework. PIPS models sentence production using a continuous-state stochastic dynamical system that optimizes grammatical constraints (shaped by previous experience) over vector representations of symbolic structures. At intermediate stages in the computation, grammatical constraints allow multiple competing parses to be partially activated, resulting in stable but transient conjunctive blend states. In the context of the preamble completion task, memory constraints reduce the strength of the target structure, allowing for co-activation of non-target parses where the local noun controls the verb (notional agreement and locally agreeing relative clauses) and non-target parses that include structural constituents with contrasting number specifications (e.g., plural instead of singular local noun). Simulations of the preamble completion task reveal that these partially activated non-target parses, as well the need to balance accurate encoding of lexical and syntactic aspects of the prompt, result in errors. In other words: Because sentence processing is embedded in a processor with finite memory and prior experience with production, interference from non-target production plans causes errors.

Applying Improved Particle Swarm Optimization to Asynchronous Parallel Disassembly Planning

Disassembly Planning (DP) refers to an optimization method to find the most cost-effective disassembly sequence for products based on the disassembly properties of parts. In traditional sequential disassembly planning, only a single part or component is removed. To effectively improve the product disassembly efficiency, this study explores the problem of Asynchronous Parallel Disassembly Planning (aPDP) with multiple manipulators. In the aPDP situation where multiple manipulators are used, the optimization method of arranging the manipulators needs to be considered in addition to the limitation of the priority order of parts. This study proposes an improved particle swarm optimization to discuss the aPDP combination optimization problem. The minimum Make Span is the objective, and the solution status and convergence speed are compared with the results of other particle swarm optimization methods, a Genetic Algorithm and Ant Colony Optimization. The results show that the proposed improved version of the particle swarm optimization algorithm has better solution quality and execution time.

The opportunity to develop strategic spatial planning with the impulse of integrated territorial investments in Croatia

Regional development and spatial planning in Croatia are organised as parallel planning systems regulated by different legislations and coordinated by two ministries, the development of which has been strongly influenced by the European Union (EU). In the last two decades, the intensive development of strategic documentation on a local, regional, and national level regarding diverse territorial governance aspects has had extensive analytical scope but little potential for implementation due to the overlapping of responsibilities and disconnected budget and implementation instruments. The Integrated Territorial Investments (ITI) mechanism of implementation contributed to the understanding of multifaceted territorial governance beyond strategic document drafting. This paper analyses the first phase of ITI implementation in Croatia, i.e. the processes which unified functional urban areas, creating the possibility to develop joint management structures and strategies, integrated projects, and common participative planning models.

Toward a Paradigm Shift in Urban Planning in Tehran: Neighborhood Development Plans

Establishment of facilitation offices in deteriorated neighborhoods of Tehran for more than a decade has led to a significant transition from top-down and authoritative intervention into a bottom-up and participatory-based renewal; one of the important parts of this transition is the adoption of a distinct approach to provide neighborhood development plans (NDPs). This approach is based on the identification of the main problems of neighborhoods, attention to all dimensions, adaptation with parallel and upstream plans, and activation of the participation of local communities and collaboration of stakeholders in public, private, and third sectors. In this paper, the neighborhood development planning approach to the problem of deterioration and obsolescence in Tehran is defined; the most important parts are the content, features, process of provision, executive framework, and assessment phases of the plan. Despite the necessity of urban renewal-regeneration integrated and systematic planning, the challenge of ignoring the unique characteristics of neighborhoods will be addressed by NDPs Scaling and Framing. Actually by defining a new level in medium and short-term plans, Tehran Municipality changed the approach of urban planning. Developing a dynamic, flexible, partnership-driven and scalable framework for dealing with the urban decay to correctly identify the neighborhoods key issues and the point solutions has been the new approach's main objective.

Optimal partitioning of unbalanced active distribution systems for supply‐sufficient micro‐ grids considering uncertainty

Partitioning large-scale smart distribution systems into multiple microgrids (MG) are considered an effective solution to maintain system reliability and to improve the power system restoration under emergency conditions. The partitioning planning process faces many challenges especially if the uncertain nature of both renewable energy resources (RERs) and loads, and the unbalanced operation of the distribution systems are considered. In this paper, the active distribution system partitioning is handled through a proposed three stages method. The proposed method presents a parallel planning for both energy sources integration process and partitioning process, taking into consideration all the circumstances that the system is exposed to, with determining the optimal specification of the devices that will be added to the system to reach the required efficiency of the system during system partitioning and system unification. The proposed three-stage method considers the uncertainty of PV modules and wind turbines. A new criterion for modeling RERs uncertainty is developed. Four phases for uncertainty reduction are applied based on the main sources of uncertainty involving solar irradiation, temperature, wind speed for the loading ratio. Moreover, the load uncertainty and system unbalance have been considered. The proposed reduction strategy leads to 92% reduction of the uncertainty cases for 1 year is sufficient for effective modeling with an acceptable level of accuracy. The proposed method is tested on the IEEE 123-node as a large-scale unbalanced test feeder. The obtained results verify the effectiveness of the proposed method in partitioning the tested distribution system into five micro-grids with self-dependence exceeded 85%.

Clothoid curve optimization for parallel parking path planning and tracking control

In order to solve the problem of abrupt curvature change at the connection between arcs and straight lines in circle-line-circle (C-L-C) combined parallel parking paths, curvature optimization was carried out by using a cycloid curve, and the trajectory curvature and heading Angle were made to meet the pose requirements of parallel parking. By establishing the kinematics model state equation and taking the optimized C-L-C trajectory as the reference trajectory, the error model was obtained. The model predictive controller based on the error model was designed, and the effectiveness of the path planning and model predictive controller was verified on Carsim and Matlab/Simulink co-simulation platform.

Integration of Algal Biofuels With Bioremediation Coupled Industrial Commodities Towards Cost-Effectiveness

Microalgae offer a great potential to contribute significantly as renewable fuels and documented as a promising platform for algae-based bio refineries. They provide solutions to mitigate the environmental concerns posed by conventional fuel sources; however, the production of microalgal biofuels in large scale production system encounters few technical challenges. High quantity of nutrients requirements and water cost constrain the scaling up microalgal biomass to large scale commercial production. Crop protection against biomass losses due to grazers or pathogens is another stumbling block in microalgal field cultivation. With our existing technologies, unless coupled with high-value or mid-value products, algal biofuel cannot reach the economic target. Many microalgal industries that started targeting biofuel in the last decade had now adopted parallel business plans focusing on algae by-products application as cosmetic supplements, nutraceuticals, oils, natural color, and animal feed. This review provides the current status and proposes a framework for key supply demand, challenges for cost-effective and sustainable use of water and nutrient. Emphasis is placed on the future industrial market status of value added by products of microalgal biomass. The cost factor for biorefinery process development needs to be addressed before its potential to be exploited for various value-added products with algal biofuel.

Parallel best-first search algorithms for planning problems on multi-core processors

The multiplication of computing cores in modern processor units permits revisiting the design of classical algorithms to improve computational performance in complex application domains. Artificial Intelligence planning is one of those applications where large search spaces require intelligent and more exhaustive search control. In this paper, parallel planning algorithms, derived from best-first search, are proposed for shared memory architectures. The parallel algorithms, based on the asynchronous work pool paradigm, maintain good thread occupancy in multi-core CPUs. All algorithms use one ordered global list of states stored in shared memory from where they select nodes for expansion. A parallel best-first search algorithm that develops new states with depth equal to one is proposed first. Then, we propose an extension of this parallel algorithm that features a diversification strategy in order to escape local minima. We study and analyse a set of computational experiments for problems that come from the International Planning Competition and real-world industry applications. The empirical evaluation shows that the parallel algorithms solve most of the domains efficiently without incurring higher solutions costs. In those problems with partial results, we highlight the potential shortcomings of the proposed approaches for promising future directions.

A branch-and-price algorithm for parallel machine campaign planning under sequence dependent family setups and co-production

We investigate a tactical level production planning problem in process industries under costly sequence dependent family setups, which drives the need for manufacturing of product families in campaigns. The motivation of our work is float glass manufacturing, which has some unique properties such as co-production and uninterruptible production. To solve the problem, we develop a branch-and-price algorithm based on a novel formulation of the problem. Our algorithm is capable of providing consistent performance in different problem sizes. We compare our proposed algorithm with previous work on the same problem by running computational experiments.

Transition from child and adolescent MHS to adult MHS: what happens to young people with personality disorder?

AimsHypothesis: Personality Disorder (PD) adolescents, compared to non-PD case, have a worse experience at transition.Aims: To describe the outcomes of referrals of adolescents for transition to adult services and compare PD and non-PD populations to identify potential improvements to allow for better transition experience of the PD patients.BackgroundBorderline PD is prevalent in adolescents - although there is a reluctance to make the diagnosis. When patients reach graduation from CAMHS, many fall through the ‘gap’ in services during the transition. Consequently, adding the paucity in research about the transition experience of PD patients, it is important to evaluate what happens to these patients during the transition process to help better understand their experience, and how it can be improved.MethodPatient's clinical records from Tower Hamlet CAMHS, East London NHS Foundation Trust, were reviewed retrospectively from July 2018 to November 2019, assessing whether optimal transition standards were met. A total of 41 cases that transitioned from CAMHS to AMHS were identified. Transition standards compared were: information sharing – case and risk, parallel care, transition planning and continuity. PD diagnosis was identified based on the recording of this diagnosis or meeting DSM5 criteria from the notes. PD and non-PD transition experience was compared.Result36 were given a diagnosis by the CAMHS clinician at transition and 5 had no diagnosis assigned. No cases had a PD diagnosis made by the CAMHS clinician, however 1 case mentioned ‘PD traits’, 1 mentioned ‘EUPD’ as a possible differential and 2 cases were labelled as ‘emotional dysregulation’. The research team found 17 cases that met DSM5 criteria for PD diagnosis.Comparing transition experience of PD vs non-PD patients, the PD patients had a less optimal transition process. Statistical analysis using Chi Square Tests, showed significantly less optimal transition planning (X2 = 5.103, p < 0.05) and continuity (Fisher's exact test p = 0.049). Cohens W indicated a medium effect for transition planning and continuity.ConclusionAdolescents with a diagnosis of PD transition less well to Adult MHS than those without the PD diagnosis. Implications of our findings point to 1) the importance of considering a diagnosis of PD 2) if the diagnosis of PD is made, to anticipate greater difficulties in transition 3) the need to identify specific reasons for transition difficulties related to patient, clinician and system factors and their interrelation.

Practical Considerations in Providing End-of-Life Care for Dying Patients and Their Family in the Era of COVID-19.

In the era of coronavirus disease 2019 (COVID-19), social distancing and strict visitation policies at hospitals have made it difficult for medical staff to provide high-quality end-of-life (EOL) care to dying patients and their families. There are various issues related to EOL care, including psychological problems of patients and their families, difficulties in EOL decision-making, the complicated grief of the bereaved family, moral distress, and exhaustion of medical staff. In relation to these issues, we aimed to discuss practical considerations in providing high-quality EOL care in the COVID-19 pandemic. First, medical staff should discuss advance care planning as early as possible and use the parallel planning strategy. Second, medical staff should play a role in facilitating patient-family communication. Third, medical staff should actively and proactively evaluate and alleviate dying patients' symptoms using non-verbal communication. Lastly, medical staff should provide care for family members of the dying patient, who may be particularly vulnerable to post-bereavement problems in the COVID-19 era. Establishing a system of screening high-risk individuals for complicated grief and connecting them to bereavement support services might be considered. Despite the challenging and limited environment, providing EOL care is essential for patients to die with dignity in peace and for the remaining family to return to life after the loved one's death. Efforts considering the practical issues faced by all medical staff and healthcare institutions caring for dying patients should be made.

Compilation-Based Approaches to Parallel Planning: An Empirical Comparison

Automated planning deals with finding a sequence of actions, a plan, to reach a goal. One of the possible approaches to automated planning is a compilation of a planning problem to a Boolean satisfiability problem or to a constraint satisfaction problem, which takes direct advantage of the advancements of satisfiability and constraint satisfaction solvers. This paper provides a comparison of three encodings proposed for the compilation of planning problems: Transition constraints for parallel planning (TCPP), Relaxed relaxed exist-Step encoding and Reinforced Encoding. We implemented the encodings using the programming language Picat 2.8, we suggested certain modifications, and we compared the performance of the encodings on benchmarks from international planning competitions.

Parallel collaborative planning for the coupled system of underground heavy-load robot

At present, designing and planning of robots are mainly based on path planning. This mode cannot meet requirements of real-time and precise planning for robots, especially under complex working conditions. Therefore, a parallel collaborative planning strategy is proposed in this paper, which parallel collaborates optimal task allocation planning and optimal local path planning. That is, according to real-time dynamic working environment of robots, the dynamic optimal task allocation planning strategy for coupled system of robot in low coupling state is adopted, to improve real-time working efficiency of underground heavy-load robot. Meanwhile, the parallel elite particle swarm optimization algorithm is adopted to improve accuracy of path tracking and controlling. Finally, the two planning strategies are collaborated parallel to realize intelligent and efficient planning of whole complex coupled system for underground heavy-load robot. The simulation and experiment results show that the parallel collaborative planning algorithm proposed in this paper has perfect controlling effects: Total flow of overall system is saved by 11.03 L, execution time saved by 16.8 s and implementation efficiency has been improved by 10 times. Therefore, the parallel collaborative planning strategy proposed in this paper can not only meet requirements of high efficiency and precision of intelligent robot under complex working conditions, but also greatly improve real-time working effectiveness and robustness of robots, so as to provide a reference for dynamic planning of complex intelligent engineering machinery, and also supply design basis for development of multi-robot collaborative system.

A Parallel Approach to Water Stewardship Planning

The professional practice of planning and the state-controlled mechanisms under which western-science planning operate offer little to improve the lives of Indigenous people and their communities. Arguably, western-science planning along with its many legal tools, collectively reproduce existing colonial relations in the interest of state domination over, and suppression of, Indigenous people. In this paper, we describe a different planning model, one that Viswanathan (2019) refers to as “parallel planning”, wherein Indigenous planning principles are practiced in parallel to western-science planning, with each approach informing, and complementing, the other. Our case example is from the Saskatchewan River Delta wherein Indigenous values nested in traditional knowledge in the land and water are the centrepiece of a planning process supported by the western-science planning framework. Challenges facing this approach will be discussed alongside suggestions on how these challenges may be overcome.

A hybrid method for optimizing selective disassembly sequence planning in adaptive reuse of buildings

PurposeA successful adaptive reuse process relies heavily on the strong performance of disassembly sequence planning (DSP), yet the studies in the field are limited to sequential disassembly planning (SDP). Since in sequential disassembly, one component or subassembly is removed with only one manipulator at a time, it can be a relatively inefficient and lengthy process for large or complex assemblies and cannot fully utilize the DSP benefits for adaptive reuse of buildings. This study aims to present a new hybrid method for the single-target selective DSP that supports both sequential and parallel approaches.Design/methodology/approachThis study uses asynchronous parallel selective disassembly planning (aPDP) method, one of the newest and most effective parallel approaches in the manufacturing industry, to develop a parallel approach toward DSP in adaptive reuse of buildings. In the proposed method, three objectives (i.e. disassembly sequence time, cost and environmental impacts) are optimized using the Non-dominated Sorting Genetic Algorithm (NSGA-II).FindingsThe proposed method can generate feasible sequential solutions for multi-objective DSP problems as the sequence disassembly planning for buildings (SDPB) method, and parallel solutions lead to 17.6–23.4% time reduction for understudy examples. Moreover, in disassembly planning problems with more complex relations, the parallel approach generates more effective and time-efficient sequences.Originality/valueThis study introduces the parallel approach for the first time in this field. In addition, it supports both sequential and parallel approaches as a novel strategy that enables the decision-makers to select the optimum approach (i.e. either the parallel or the sequential approach) for DSP. Moreover, a metaheuristic method (i.e. NSGA-II) is adopted as the optimization tool with robust results in the field in which those heuristic methods have only been employed in the past.

Inverted Meckel's diverticulum associated with heterotopic pancreatic tissue causing intestinal obstruction: a case report

BackgroundMeckel’s diverticulum is the most frequent congenital anomaly of the gastrointestinal tract. It can invert or invaginate into the small intestine lumen. It is usually associated with heterotopic tissue elements.Case presentationWe present a case of inverted Meckel's diverticulum, clinically and radiologically diagnosed as intestinal obstruction due to intussusceptions. The diagnosis was suspected due to target sign shown on radiological examination. Pathologically, it was inverted Meckel's diverticulum obstructing the lumen in parallel plan mimicking the telescoping appearance, with heterotopic pancreatic tissue formed of exocrine and ductal components only.ConclusionsInverted Meckel’s diverticulum may present by vague symptoms and may simulate other causes of intestinal obstruction.

Parallel Planning of Marine Observation Tasks based on Threading Building Blocks

Parallel Planning of Marine Observation Tasks based on Threading Building Blocks