Planning Approach Research Articles

Automatic base-dose planning for a robust field junction in total marrow irradiation.

Total marrow (lymph-node) irradiation (TMI/TMLI) is a radiotherapy technique irradiating the whole body of a patient. The limited couch travel range in modern linacs (130-150cm) forces to split the TMI/TMLI delivery into two plans with opposite orientation. A dedicated field junction is necessary to achieve satisfactory target coverage in the overlapping region of the two plans. In a recent study, we implemented an automatic tool (AT) using the Eclipse Scripting API for the creation of a field junction and optimization of TMI/TMLI. In this work, we improved the AT by developing an automatic base-dose planning approach. Ten patients were selected to compare the manual procedure, original automatic planning approach, and new base-dose approach. Treatment plans were evaluated with the D98%, Dmean, and D2% for the planning target volume at the junction (PTV_J), while Dmean and D2% were considered for the PTV without the junction (PTVNoJ) and healthy tissues. Base-dose planning significantly improved the PTV_J coverage compared with the manual approach, with unaltered Dmean, consistently lower D2% (2.24Gy vs. 2.30Gy) and higher D98% (1.98Gy vs. 1.89Gy). Moreover, it significantly reduced the hotspots in healthy tissues (2.02Gy vs. 2.15Gy). No significant differences for PTVNoJ dose statistics were observed among the procedures, demonstrating that the automatic approaches produced a target coverage similar to the one obtained manually. Base-dose planning improved the field junction optimization of TMI/TMLI. Automatic planning tools can incrementally improve procedures that would be challenging or error-prone to achieve manually.

PENDEKATAN SISTEMATIS DALAM PERENCANAAN DAN PENGEMBANGAN KARIER: TANTANGAN SERTA FAKTOR PENENTU

Effective career planning and development is essential in the context of today's competitive and dynamic job market. A systematic approach is crucial to helping individuals and organizations identify and achieve their career goals. This research aims to analyze the importance of a systematic approach in career planning and development, the challenges faced, and the determining factors for success that need to be considered. The method used in this research is literature study, which includes analysis of related literature and best practices in career development. The research results show that self-assessment, setting clear goals, developing skills, as well as mentorship and technology support play an important role in achieving career success. Apart from that, organizations must also play an active role in providing structured development programs to increase employee engagement. The conclusion of this research emphasizes the need for synergy between individuals and organizations in creating a mutually beneficial career development ecosystem.

Kids Just Wanna Get Fun: A Children-Centric Participatory Research Methodology for Sustainable Cities and Communities

Introduction: Urban planning and design have traditionally been adult-centric, driven by professionals and decision-makers focusing on space efficiency, economic development, and urban performance. This approach has resulted in cities becoming increasingly hostile environments for younger populations. Cuenca, Ecuador, an intermediate-sized city, exemplifies this trend, with children no longer walking or cycling to school due to decades of car-centric planning. They now rely on private cars, school buses, or public transport. Despite growing interest in integrating the perspectives of vulnerable groups into urban design, there is limited information on participatory planning and co-design approaches focused on school-age children. Objective: The objective of this study is to propose and evaluate a participatory research methodology to incorporate the perspectives of children aged 10 to 12 regarding their school environments and their visions for safer, more engaging routes to school in Cuenca in the context of more sustainable cities and communities Method: The methodology includes several participatory techniques organized within an interactive fictional narrative in which children assume the role of urban environment researchers. The method employs various instruments: mapping, route-to-school evaluation, place awareness, activity journals, and co-design activities. Results and Discussion: The results offer vital insights for planning and designing safer routes to schools that meet children's specific needs and aspirations. These insights sometimes contradict adult-centric views that prioritize efficiency. For instance, solutions deemed safer by adults can impede efforts to promote active commuting among children. Findings: The findings highlight the importance of using tailored methods to gain deep insights into children's preferences and perceptions. These insights call for fundamentally reevaluating urban planning paradigms in Latin American cities to better accommodate children's needs and perspectives. Research Implications: Governments, Urban Planners and Decision Makers should include the perspectives and voices of children by using participatory planning and a co-design approach to create more friendly cities. Originality/Value: This study contributes to the literature by proposing and evaluating a participatory design approach to a better understanding of children needs in urban planning specifically in developing safe routes to schools.

Public Vitality-Driven Optimization of Urban Public Space Networks—A Case Study from Nanjing, China

Spontaneous recreational activities in public spaces are a vital source of public vitality. Given the similarity between the walking patterns of recreational crowds in public spaces and the movement of electrons on a two-dimensional circuit surface, this study combines big data from various sources to create an “electrical conductivity surface” that attracts and aggregates recreational crowds. Using current flow simulation, we generate the path selection preferences of people as they move across public spaces. The results reveal an uneven distribution of public spaces in Nanjing’s main urban area, with high-vitality areas mostly concentrated in the urban center. The core demand for enhancing public vitality lies is improving connectivity between multiple spaces. Based on this, the public space plan for Nanjing’s main urban area emphasizes overall connectivity by aligning with the natural landscape, thus linking the city’s green and gray infrastructure. In this study, we have assessed current public space services and their development potential from a number of different angles, developing a digital approach for optimizing the urban layout. We aim to provide a human-centric, bottom-up perspective to complement the top-down city planning and management approach. This will enable urban planners to make informed decisions for creating and managing more vibrant cities.

Shaping Cities and Housing Environments for People

Since the 1960s, urban landscapes and housing environments have been profoundly shaped by industrial and technological advancements, alongside globalization. However, despite increasing environmental consciousness, urban planning has often neglected human-centered and neighborhood-scale approaches, resulting in urban environments and housing complexes lacking essential physical and social qualities. Modernist urban planning, while addressing certain urban challenges, has inadvertently given rise to issues such as urban sprawl, lack of diversity, and social alienation, as exemplified by the failure of developments like the Pruitt-Igoe housing complex. This article explores human-centered approaches in urban planning and design, championed by influential figures like Constantinos A. Doxiadis, Jacqueline Tyrwhitt, N. John Habraken, Amos Rapoport, Christopher Alexander, and others. Their theories emphasize integrating human needs, behaviors, and cultural contexts into planning, focusing on fostering vibrant communities, adaptable environments, and responsive design principles. Inspired by traditional Mediterranean and Middle Eastern settlements, the neighborhood emerges as a pivotal unit for fostering social cohesion, well-being, and belonging through the integration of private, semi-private, and public spaces to create meaningful connections. Addressing the deficiencies of contemporary car-centric and fragmented urban environments requires strategies that prioritize pedestrian-friendly spaces, community participation, and responsive design tailored to local contexts. Ultimately, achieving socially and environmentally sustainable urban environments depends on cohesive planning, innovative policymaking, and active community involvement. This vision requires a commitment to addressing both social and environmental dimensions of urban life, ensuring livable, inclusive, and resilient cities for future generations.

Urban Informality and the New Urban Agenda: Looking for the New Transformative Development Agenda in Masvingo City, Zimbabwe

While urban informality has played a critical role in the creation of inclusive and resilient cities, agents of informality, otherwise known as ‘the poor’, are typically excluded from the development of cities. As the New Urban Agenda calls for inclusive urbanism to create resilient cities, new planning systems which are inclusive of urban informality should be adopted. In addition, typically exclusive traditional planning methods have proven to be largely responsible for widespread poverty in urban areas. In the context of the New Urban Agenda, this research examined urban informality in the city of Masvingo, Zimbabwe. A qualitative approach using a combination of in-depth interviews and textual sources was employed. The findings revealed that, despite the principles of New Urban Agenda being widely agreed upon, very little is actually being done to include urban informality; demonstrating that the call for new planning approaches to face the realities of cities and plan for their future challenges has not been heeded in the city of Masvingo, where urban informality remains outside the planning system. This paper discussed the implications of this lack of inclusion, and makes recommendations that will enable cities to recognize the livelihoods of the poor and their role in the developing resilient cities.

Hierarchical Planning Applied to the Preliminary Design of CubeSats: Nanospace Study

ABSTRACTCubeSat design has been already studied and formalized but knowledge representation remains a challenge. The management of human‐learnt knowledge during the process is not an aspect that is often spoken about. This paper discusses the proposal of integrating a hierarchical planning approach with a model‐based one to the open‐source Nanospace framework, a web‐based application for concurrent engineering during the preliminary design phase of CubeSats. Hierarchical planning aids to introduce commonly tacit human expertise, an aspect that the preliminary design of CubeSats can benefit from. The proposed integration could allow a faster design convergence and faster inspection of candidate architectures The Nanospace framework itself may benefit from an approach bringing in model‐based efforts and hierarchical planning facilitate knowledge representation and reuse. A use case on the CREME CubeSat project is detailed, emphasizing how to impregnate the design iterations with experts' knowledge.

Adaptive Planning Approaches for Coastal Climate Adaptation: Process and Key-elements.

The paradigm of Adaptive Planning and Management provides several methodological approaches for designing robust adaptive plans to cope with uncertain future changes, namely the Adaptation Pathways' method (APs). These approaches, particularly those containing APs, have captured increasing interest in the field of coastal climate adaptation as useful for guiding its planning and management. While these approaches have been tested in several research cases, there are still few real cases of application into coastal spatial planning instruments. Furthermore, the lack of implementation of coastal adaptation actions in urbanized coasts worldwide, so-called adaptation gaps, points to the need of investigating to what extent these Adaptive Planning approaches containing APs are being applied in coastal plans. A deeper analysis of cases of application of these approaches in coastal plans is required to understand how adaptive plans are being crafted. This article focusses on the two major cases of application of APs-based Adaptive Planning and Management approaches into planning and management instruments - the Thames Estuary 2100 Plan and the Delta Programme - to identify what elements were essential to design an adaptive plan and operationalize an Adaptive Planning and Management approach, including ingredients that the plan had to meet to be robust and adaptive. Our results suggest that at least five elements are required to craft and deliver a robust adaptive plan and accomplish a real Adaptive Planning and Management.

Review On Layout Optimization For Rollingstock Maintenance Depot

This review paper discusses the importance of having an optimal layout for rollingstock maintenance depots to optimize rollingstock maintenance in improving maintenance efficiency and reducing maintenance costs while maintaining the availability and reliability of railway vehicles. The current problems in rollingstock maintenance depots faced by railway industry are limited land availability, limited storage space, material handling issues, and the lack of standards for train maintenance depot layouts. The paper also presents classification criteria and categories on layout planning and maintenance optimization approach for rollingstock maintenance depots based on various recent studies including the methods used and the results obtained. Finally, this review paper proposes guidelines for future research on rollingstock maintenance depots in Indonesia as decision-making that considers the economic factors of layout optimization and the implications for safety and the environment of maintenance activities. This could also help improve the company's reputation as well as prepare for future expansion

Advanced Path Planning for UAV Swarms in Smart City Disaster Scenarios Using Hybrid Metaheuristic Algorithms

In disaster-stricken areas, rapid restoration of communication infrastructure is critical to ensuring effective emergency response and recovery. Swarm UAVs, operating as mobile aerial base stations (MABS), offer a transformative solution for bridging connectivity gaps in environments where the traditional infrastructure has been compromised. This paper presents a novel hybrid path planning approach combining affinity propagation clustering (APC) with genetic algorithms (GA), aimed at maximizing coverage, and ensuring quality of service (QoS) compliance across diverse environmental conditions. Comprehensive simulations conducted in suburban, urban, dense urban, and high-rise urban environments demonstrated the efficacy of the APC-GA approach. The proposed method achieved up to 100% coverage in suburban settings with only eight unmanned aerial vehicle (UAV) swarms, and maintained superior performance in dense and high-rise urban environments, achieving 97% and 93% coverage, respectively, with 10 UAV swarms. The QoS compliance reached 98%, outperforming benchmarks such as GA (94%), PSO (90%), and ACO (88%). The solution exhibited significant stability, maintaining consistently high performance, highlighting its robustness under dynamic disaster scenarios. Mobility model analysis further underscores the adaptability of the proposed approach. The reference point group mobility (RPGM) model consistently achieved higher coverage rates (95%) than the random waypoint model (RWPM) (90%), thereby demonstrating the importance of group-based mobility patterns in enhancing UAV deployment efficiency. The findings reveal that the APC-GA adaptive clustering and path planning mechanisms effectively navigate propagation challenges, interference, and non-line-of-sight (NLOS) conditions, ensuring reliable connectivity in the most demanding environments. This research establishes the APC-GA hybrid as a scalable and QoS-compliant solution for UAV deployment in disaster response scenarios. By dynamically adapting to environmental complexities and user mobility patterns, it advances state-of-the-art emergency communication systems, offering a robust framework for real-world applications in disaster resilience and recovery.

Psychotherapy boosting future risk research: the role of radical masculinities in social polarisation from a trauma-informed perspective

This paper examines the potential integration of trauma-informed practices and Critical Studies on Men and Masculinities (CSMM) into global and European risk research, with a focus on foresight methodologies. It explores how the complex interplay between untreated trauma, rapid resource loss, radicalisation, and rigid masculine norms can potentially escalate societal risks. The study argues for the adoption of a more holistic approach in risk assessment and future planning, incorporating insights from trauma studies, masculinity research, and psychotherapy. The paper discusses the value of participatory foresight methods in capturing diverse perspectives and lived experiences, particularly those affected by toxic masculinity and radicalisation. We highlight the importance of considering intersectionality and the compounded traumas that may arise from the interaction of extremist masculine norms with other social factors. Current findings suggest that including psychotherapy scientists and practitioners in risk research could provide valuable insights into the psychological mechanisms underlying trauma, meaning-making, and identity formation. By adopting this interdisciplinary approach, the paper proposes that risk researchers may develop more comprehensive and nuanced understandings of societal risks, leading to more effective strategies for addressing the complex challenges posed by radicalisation, radical masculinity/ies, and the associated traumas in an increasingly uncertain world.

Anesthetic Management of Renal Tumor with Level 3 Inferior Vena Cava Extension at a University Hospital in Vietnam: A Case Report

Background: Renal tumors with inferior vena cava (IVC) invasion pose significant challenges for surgical and anesthetic management. This report presents the anesthetic management of a patient with a level 3 IVC-invading renal tumor, emphasizing the complexity and multidisciplinary approach required. Case Presentation: A 55-year-old woman with a large left renal tumor causing complete obstruction of the left renal vein and near-total obstruction of the IVC was admitted for surgery. Multidisciplinary planning included a nephrectomy with removal of tumor from the IVC. The patient underwent general anesthesia with extensive hemodynamic monitoring and fluid management to mitigate potential blood loss and cardiovascular instability. The surgery, lasting 5 h, involved successful radical nephrectomy, tumor removal from the IVC, and resection of liver metastases. Postoperative recovery was without complications, and the patient was discharged 7 days. Conclusion: Managing anesthesia for renal tumors with IVC invasion requires careful preoperative planning, invasive monitoring, and multidisciplinary approach.

Placemaking for inclusive public spaces in South African townships: a community-led approach

ABSTRACT Scholarly engagement on Southern Urban Theory offers an opportunity to analyze and deliberate case studies from cities in the South where planning practices provide useful evidence to support alternative approaches. The practice of placemaking presents a promising methodology for democratic planning in the form of a collaborative, process-orientated practice that reimagines public spaces through participatory design and community engagement. By making use of a case study example in South Africa (Cape Town), this paper positions placemaking within the discourse of southern urban theory and critically examines a community-led placemaking initiative and how participatory design processes effectively enhance local public spaces. The research challenged traditional ideologies of power and top-down planning approaches where change and action are initiated by authorities. It concluded that bottom-up initiatives to transform living environments not only capitalize on community buy-in but yield transformative processes possessing more longevity.

Global path planning on uneven terrain at construction sites for robots based on an improved A* Algorithm

With the increasing application of construction robots on construction sites, autonomous path planning in unstructured and uneven construction sites has become an urgent challenge. Current path planning approaches face several issues, including prolonged computation times, low efficiency, and redundant nodes, often resulting in impractical paths for robots. Addressing these concerns, this study introduces a global path planning method based on an enhanced A* algorithm to ensure safe and robust navigation of construction robots in such challenging environments. The Improved A* algorithm initially incorporates a bidirectional alternating search strategy to expedite computational speed. Subsequently, it employs path node filtering to mitigate issues associated with bidirectional search and reduce the number of critical nodes, thereby enhancing search efficiency. Furthermore, the introduction of slope constraints decreases the robot's climbing and tilting angles, augmenting the safety of the planned paths. Finally, the paths are smoothed using Bézier curve fitting, facilitating better motion control for the robots. The efficacy of the improved algorithm was validated through experiments on elevation maps with varying terrain and obstacle densities. Simulation results indicate that, compared to the traditional A* algorithm, the Improved A* algorithm reduced computation time by 71.05% to 82.90% and the number of critical nodes by 51.94% to 70.53%, while only increasing the path length by 14.6% to 37.84%. Additionally, there was a significant reduction in climbing and tilting angles, and the paths have become smoother. Therefore, this method not only improves efficiency while generating safe and reliable paths in unstructured and uneven construction sites, but also enables robots to adapt to complex environments, and promotes automation and intelligent construction processes.

Space Syntax Analysis of Gated Communities in Jordan: Examining Urban Connectivity and Social Impact

The trend of gated communities is becoming the new alternative housing for the high-end residents of Jordan, reflecting global patterns of urbanisation. However, their emergence on the outskirts of Amman on vacant lands requires an early proactive planning approach to ensure their development in response to the growth of the surrounding areas, fostering an integrated urban fabric. This article examines whether gated communities contribute to urban discontinuity and lead to social segregation. The study employs a space syntax analysis on two cases in Amman to assess their integration, accessibility, and navigability to address the study’s key questions related to its integration, design implications, and spatial layout. Findings reveal significant spatial segregation, with low levels of integration and high step depth values, indicating potential challenges in navigation, connectivity, residents’ mobility, accessibility, and safety. The article suggests the importance of re-evaluating the design and planning approaches for these developments to promote organic townscape growth to ensure smooth integration with the surroundings.

CLUSTERING DISTRICTS/CITIES IN EAST JAVA PROVINCE BASED ON HIV CASES USING K-MEANS, AGNES, AND ENSEMBLE

Cluster analysis is a method of grouping data into certain groups based on similar characteristics. This research aims to group districts/cities in East Java Province in 2021 based on HIV cases using hierarchical cluster analysis (AGNES), non-hierarchical cluster analysis (K-means), and ensemble clustering. The study found that the ensemble clustering solution forms four clusters, consistent with the results of AGNES clustering. This suggests that ensemble clustering improves the quality of cluster solutions by leveraging both hierarchical and non-hierarchical methods. The grouping of districts/cities based on HIV cases provides a clear distribution pattern for more targeted interventions. The study is limited to HIV cases in East Java Province and may not be generalizable to other regions with different epidemic characteristics. Additionally, the study focuses on clustering methods without investigating temporal changes in HIV case distribution. This research is one of the few studies that applies ensemble clustering to HIV cases in East Java Province. It combines hierarchical and non-hierarchical methods to improve the clustering process and provides a practical approach for regional HIV control planning.

Evaluating the effectiveness of cost-minimal planning of decarbonized electricity systems in reducing life cycle greenhouse gas emissions

Abstract The decarbonization of regional electricity systems is a critical enabler of broader economy-wide decarbonization strategies and has motivated robust research on how to decarbonize electricity systems at minimum monetary cost. Since these efforts often focus on the operation of electricity systems, however, they do not account for emissions of the full life cycle associated with different resources. Different resource mixes can achieve a similar level of decarbonization apparent decarbonization through operational emissions, while achieving very different levels of life cycle greenhouse gas (GHG) emissions reductions. To explore these differences, we model the expansion of the California electricity system from 2030 to 2045 using a simplified electricity dispatch model to investigate how the planning of future electricity systems may differ between prioritizing minimum cost versus minimum life cycle GHG emissions under a common target for operational GHG reductions. We find that explicitly planning for minimum life cycle GHG emissions yields an additional 1.6-2.0% reduction in annual life cycle GHG emissions at a cost penalty of 3.2–9.6% and that electricity resource mixes that minimize life cycle GHG emissions tend to favor high capacity factor zero-carbon resources and long-duration storage compared to a minimum cost approach. Comparatively, we find that aggressive supply chain decarbonization of generation and storage technologies reduces life cycle GHG emissions of electricity supplies by 3.0% to 14% and combining both increases these reductions to 5.0% to 16%. Further, we find that applying a carbon tax to minimum cost-based capacity expansion can incentivize planning to account for life cycle GHG emissions. Our results indicate that a planning approach focused on minimizing life cycle GHG emissions may not be palatable, but significant reductions in life cycle emissions can be realized through conventional mechanisms like carbon taxes, import standards, and targeted supply chain decarbonization.

A study on delay of Local Government Development Projects Completion and Its Impact in Bangladesh

Successful project outcomes rely on various well-coordinated actions from start to finish. This study aims to identify the issues affecting local government projects in Bangladesh and their significant impacts. Delays in projects are often caused by the conventional administrative system and poor coordination among stakeholders. Ministries and departments Develop Project Proposals (DPPs) without thorough feasibility studies or appropriate measures, leading to delays in approval and project execution. Although the Local Government Division undertakes numerous projects with substantial funding, several issues prevent timely completion, including insufficient funds, untrained personnel, inadequate planning, flawed feasibility studies, lack of modern technology, frequent natural disasters, and fluctuating project material costs. Additionally, the protracted administrative process and top-down planning approach do not align with optimal outcomes. This outdated planning system complicates project implementation, whereas a bottom-up approach could be more effective. It is noted that although Local Government Division undertake many projects, gaps in execution often lead to deteriorated project quality, time and cost overruns, and eventual project failure. In addition to assessing corrective measures like structured planning, thorough feasibility studies, compliance enforcement, project prioritization, efficient monitoring, and land acquisition challenges, this study will look into delays that result in misappropriation of public funds and setbacks in ADP progress. This research seeks to address these issues by analyzing all available information, including primary and secondary data, respondents' opinions, and other evidence through a qualitative approach.

Simulation of Autonomous Tractor using ROS

Farmers encounter a multitude of obstacles in agriculture, such as operating in challenging weather conditions and unpredictable surroundings, which can have a significant impact on sustainability and productivity. To tackle these hurdles, autonomous agricultural vehicles are indispensable. This paper introduces the digital modelling and testing of a self-driving tractor system tailored for agricultural tasks. By utilizing the Robot Operating System (ROS) and Gazebo simulator, the study delves into the incorporation of cutting-edge navigation algorithms, including the GMapping algorithm for Simultaneous Localization and Mapping (SLAM), Dijkstra algorithm, and the Dynamic Window Approach (DWA) for efficient path planning. The tractor prototype, developed using Fusion 360, undergoes thorough assessments to evaluate its mapping accuracy, localization precision, path planning effectiveness, and obstacle avoidance capabilities. The outcomes showcase successful mapping and localization, precise trajectory planning, adept obstacle avoidance, and visualization through RViz and Gazebo co-simulation. The study aims to propel the realm of autonomous agriculture by offering insights into the design, enhancement, and virtual implementation of autonomous tractor systems, ultimately enhancing the efficiency and sustainability of agricultural practices. Keywords: Autonomous Vehicles, Autonomous Tractors, Path Planning, GMapping, AMCL, ROS, Gazebo, RViz, Dijkstra’s Algorithm, DWA Path Planning, PID Controller, Simulation

Adaptive Robot Motion Planning for Smart Manufacturing Based on Digital Twin and Bayesian Optimization-Enhanced Reinforcement Learning

Abstract Advanced motion planning is crucial for safe and efficient robotic operations in various scenarios of smart manufacturing, such as assembling, packaging and palletizing. Compared to traditional motion planning methods, Reinforcement Learning (RL) shows better adaptability to complex and dynamic working environments. However, the training of RL models is often time-consuming and the determination of well-behaved reward function parameters is challenging. To tackle these issues, we propose an adaptive robot motion planning approach based on digital twin and reinforcement learning. The core idea is to adaptively select geometry-based or RL-based method for robot motion planning through a real-time distance detection mechanism, which can reduce the complexity of RL model training and accelerate the training process. In addition, we integrate Bayesian Optimization within RL training to refine the reward function parameters. We validate the approach with a Digital Twin enabled robot system through five kinds of tasks (Pick and Place, Drawer Open, Light Switch, Button Press, Cube Push) in dynamic environments. Experiment results show that our approach outperforms traditional RL-based method with improved training speed and guaranteed task performance. This work contributes to the practical deployment of adaptive robot motion planning in smart manufacturing.