Hasil untuk "Regional planning"

Andrea Tiranti, Francesco Wanderlingh, Enrico Simetti et al.

Accurate tracking of underwater acoustic sources is critical for a variety of marine applications, yet remains a challenging task due to communication constraints and environmental uncertainties. In this regard, this paper addresses the problem of underwater acoustic source tracking using a team of autonomous underwater vehicles (AUVs). The core idea is to optimize the guidance of each agent to achieve coordinated motion planning that leads to optimal geometric configurations with respect to the target, thereby enhancing tracking performance. To tackle this, we propose a Distributed Model Predictive Control (DMPC) framework to improve performance and robustness. The control problem is formulated as a multi-objective optimization task, incorporating geometric observability, proximity to the target, and communication connectivity. A Receding Horizon Control (RHC) approach, coupled with an Unscented Transform (UT)-based prediction scheme, is employed to ensure longterm tracking accuracy while accounting for uncertainties. The optimization is distributed using the sequential multi-agent decision-making framework, combined with the Time-Division Multiple Access (TDMA) communication protocol. The proposed methodology is implemented in a simulation environment that accounts for the constraints of acoustic communication. The approach is compared with existing methods such as decentralized MPC and Particle Swarm Optimization (PSO).

Flora Roumpani, Joel Dearden, Alan Wilson

The two-tier Lowry model brings dynamic simulations of population and employment directly into the planning process. By linking regional modelling with neighbourhood design, the framework enables planners to explore how alternative planning scenarios may evolve over time. The upper tier captures regional flows of people, jobs, and services, while the lower tier allocates these to fine-grain zones such as neighbourhoods or parcels. Implemented in CityEngine, the approach allows interactive visualisation and evaluation of multi-scale scenarios. A case study in South Yorkshire (UK) illustrates how regional forecasts can be translated into local design responses, connecting quantitative modelling with 3D spatial planning.

Akshay Jaitly, Jon Arrizabalaga, Guanrui Li

Planning collision free trajectories in complex environments remains a core challenge in robotics. Existing corridor based planners which rely on decomposition of the free space into collision free subsets scale poorly with environmental complexity and require explicit allocations of time windows to trajectory segments. We introduce a new trajectory parameterization that represents trajectories in a nonconvex collision free corridor as being in a convex cartesian product of balls. This parameterization allows us to decouple problem size from geometric complexity of the solution and naturally avoids explicit time allocation by allowing trajectories to evolve continuously inside ellipsoidal corridors. Building on this representation, we formulate the Orthogonal Trust Region Problem (Orth-TRP), a specialized convex program with separable block constraints, and develop a solver that exploits this parallel structure and the unique structure of each parallel subproblem for efficient optimization. Experiments on a quadrotor trajectory planning benchmark show that our approach produces smoother trajectories and lower runtimes than state-of-the-art corridor based planners, especially in highly complicated environments.

Mekardi Ham Charles, Dewi Prasinta, Salim Lily et al.

Disasters expose small islands to heightened risks, which their unique natural conditions and limited economic capabilities further amplify. Malaka Village, located on Lombok Island in West Nusa Tenggara Province, Indonesia, experienced several destructive sequential earthquakes in 2018, providing valuable lessons four years later. A community-based quantitative household survey measures the local community's perceptions of resilience and their correlation with recovery efforts. Local volunteers participated in measuring their community using the local language based on a designed stratified sampling quantitative study employing a five-component framework. This framework assessed access to basic services, regulations and policies in disaster management, prevention and mitigation, emergency preparedness, and recovery readiness. The study finds that Malaka Village is more resilient four years after the 2018 earthquakes, despite a perceived hamlet resilience of 69.9% and a perceived local government resilience of 59.3%. Perceived family or household resilience is higher at 75.6%, which is also concerning, as a quarter of people do not think they are ready to face another disaster. This study recommends ten actions to improve community resilience and identifies the key lessons to enhance community resilience, including access to basic services, understanding disaster risk, and housing recovery capacity.

Junyoung Kim, Soyeon Kim, Sunghwa Hong et al.

BackgroundCeruminous gland adenocarcinoma is the most common malignant tumor of the feline external ear canal. These tumors are often locally invasive and may extend into adjacent musculature and lymph nodes, limiting the feasibility of surgical excision. When surgery is not an option, radiation therapy can provide palliative benefit. Advanced imaging modalities, including computed tomography (CT) and magnetic resonance imaging (MRI), play a crucial role in treatment planning and therapeutic monitoring.Case descriptionA 14-year-old spayed female Persian cat with a confirmed diagnosis of ceruminous gland adenocarcinoma presented with a progressively enlarging mass in the left external ear canal. Due to extensive local invasion into the adjacent parotid and salivary regions, surgical resection was not feasible. The cat was treated with palliative-intent radiation therapy (36 Gy in 6 weekly fractions). Serial CT and MRI, including diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping, were performed on days 0 (radiotherapy completion), 30, 90, and 180 to monitor treatment response. During the initial follow-up period, imaging demonstrated sustained tumor size reduction, symptomatic improvement, and minimal adverse effects. Functional MRI delineated residual lesions more clearly than conventional sequences, supporting its role in post-treatment assessment. However, on day 180, imaging revealed suspected local recurrence and regional lymph node metastases, suggesting disease progression. Despite this, the treatment successfully achieved the intended palliative goals, including temporary tumor control and clinical stabilization.ConclusionThis report described a rare case of feline ceruminous gland adenocarcinoma characterized by local invasiveness that precluded surgical resection. Palliative radiotherapy was administered, and sequential imaging using computed tomography and diffusion-weighted magnetic resonance imaging, including ADC mapping, enabled detailed monitoring of the tumor response. Although conventional imaging confirmed size reduction, DWI-MRI better delineated residual lesions, suggesting its complementary role in radiotherapy assessment. This case underscores the value of combining anatomic and functional imaging for evaluating radiotherapy outcomes and guiding clinical decision-making in feline oncology.

Wang Peng, Yu Xiaoyuan, Nuzul Azam Haron

The rapid expansion of transport infrastructure during economic development has led to significant increases in carbon emissions, particularly in developing countries. However, the relationship between different transport modes and carbon emissions across development stages remains unclear. This study examines the relationship between the relative improvement of railways to roads (RPR), economic growth, and transport carbon emissions, aiming to verify the Environmental Kuznets Curve (EKC) hypothesis in China's transport sector. Using an ARDL model and bounds testing approach, we analyze Chinese data from 1978 to 2021. The bounds test confirms a long-term cointegration relationship among RPR, GDP per capita, and transport carbon emissions. Both long-term and short-term analyses support the EKC hypothesis, indicating an inverted U-shaped relationship between economic growth and per capita transport carbon emissions. The impact of RPR on per capita transport carbon emissions is significantly positive in both the long and short term. The error correction term shows that approximately 41 % of short-term disequilibrium is corrected within a year, further confirming the long-term relationship between variables. Diagnostic tests and stability analysis ensure the reliability of the model results. The study reveals that the impacts of transport demand, infrastructure investment, and technological progress on carbon emissions vary across different stages of economic development. These findings suggest that developing economies should adopt a dynamic approach to transport infrastructure planning, with early preparation for railway development to avoid carbon emission lock-in effects. For sustainable development, policymakers should align infrastructure investment priorities with economic development stages while promoting cross-regional coordination in transport planning.

Mhd. Habib Ansyahri Siregar, Efi Brata Madya

This research aims to analyze the Planning of the Muhammadiyah Regional Leadership of North Sumatra in Educating Teenagers about the Dangers of Online Gambling. The method used is qualitative research that analyzes facts in the field that produce data in the form of words and information from informants.  The data collection techniques used in this research are observation, interview and documentation. The results of this study indicate that the North Sumatra Muhammadiyah Regional Leadership Planning has planned an educational program on the dangers of online gambling to teenagers. The planning includes collaborating with legal institutions, socialization, seminars, program development, khatib jum'at and youth coaching.  Challenges faced such as the resistance of the parties to the practice of online gambling, the number of online gambling sites that have not been blocked and the limitations of PWM in reaching remote areas.

Shadman Tajwar Shahid, Shah Md. Ahasan Siddique, Md. Mahidul Alam

This article addresses the challenge of UAV survey coverage path planning for areas that are complex concave polygons, containing exclusion zones or obstacles. While standard drone path planners typically generate coverage paths for simple convex polygons, this study proposes a method to manage more intricate regions, including boundary splits, merges, and interior holes. To achieve this, polygonal decomposition techniques are used to partition the target area into convex sub-regions. The sub-polygons are then merged using a depth-first search algorithm, followed by the generation of continuous Boustrophedon paths based on connected components. Polygonal offset by the straight skeleton method was used to ensure a constant safe distance from the exclusion zones. This approach allows UAV path planning in environments with complex geometric constraints.

Muhammad Akhtar Munir, Fahad Shahbaz Khan, Salman Khan

Accurate weather and climate modeling is critical for both scientific advancement and safeguarding communities against environmental risks. Traditional approaches rely heavily on Numerical Weather Prediction (NWP) models, which simulate energy and matter flow across Earth's systems. However, heavy computational requirements and low efficiency restrict the suitability of NWP, leading to a pressing need for enhanced modeling techniques. Neural network-based models have emerged as promising alternatives, leveraging data-driven approaches to forecast atmospheric variables. In this work, we focus on limited-area modeling and train our model specifically for localized region-level downstream tasks. As a case study, we consider the MENA region due to its unique climatic challenges, where accurate localized weather forecasting is crucial for managing water resources, agriculture and mitigating the impacts of extreme weather events. This targeted approach allows us to tailor the model's capabilities to the unique conditions of the region of interest. Our study aims to validate the effectiveness of integrating parameter-efficient fine-tuning (PEFT) methodologies, specifically Low-Rank Adaptation (LoRA) and its variants, to enhance forecast accuracy, as well as training speed, computational resource utilization, and memory efficiency in weather and climate modeling for specific regions.

Olivier Lamarre, Shantanu Malhotra, Jonathan Kelly

Exploration of the lunar south pole with a solar-powered rover is challenging due to the highly dynamic solar illumination conditions and the presence of permanently shadowed regions (PSRs). In turn, careful planning in space and time is essential. Mission-level path planning is a global, spatiotemporal paradigm that addresses this challenge, taking into account rover resources and mission requirements. However, existing approaches do not proactively account for random disturbances, such as recurring faults, that may temporarily delay rover traverse progress. In this paper, we formulate a chance-constrained mission-level planning problem for the exploration of PSRs by a solar-powered rover affected by random faults. The objective is to find a policy that visits as many waypoints of scientific interest as possible while respecting an upper bound on the probability of mission failure. Our approach assumes that faults occur randomly, but at a known, constant average rate. Each fault is resolved within a fixed time, simulating the recovery period of an autonomous system or the time required for a team of human operators to intervene. Unlike solutions based upon dynamic programming alone, our method breaks the chance-constrained optimization problem into smaller offline and online subtasks to make the problem computationally tractable. Specifically, our solution combines existing mission-level path planning techniques with a stochastic reachability analysis component. We find mission plans that remain within reach of safety throughout large state spaces. To empirically validate our algorithm, we simulate mission scenarios using orbital terrain and illumination maps of Cabeus Crater. Results from simulations of multi-day, long-range drives in the LCROSS impact region are also presented.

Cristian Ramirez-Atencia, Javier Del Ser, David Camacho

Management and mission planning over a swarm of unmanned aerial vehicle (UAV) remains to date as a challenging research trend in what regards to this particular type of aircrafts. These vehicles are controlled by a number of ground control station (GCS), from which they are commanded to cooperatively perform different tasks in specific geographic areas of interest. Mathematically the problem of coordinating and assigning tasks to a swarm of UAV can be modeled as a constraint satisfaction problem, whose complexity and multiple conflicting criteria has hitherto motivated the adoption of multi-objective solvers such as multi-objective evolutionary algorithm (MOEA). The encoding approach consists of different alleles representing the decision variables, whereas the fitness function checks that all constraints are fulfilled, minimizing the optimization criteria of the problem. In problems of high complexity involving several tasks, UAV and GCS, where the space of search is huge compared to the space of valid solutions, the convergence rate of the algorithm increases significantly. To overcome this issue, this work proposes a weighted random generator for the creation and mutation of new individuals. The main objective of this work is to reduce the convergence rate of the MOEA solver for multi-UAV mission planning using weighted random strategies that focus the search on potentially better regions of the solution space. Extensive experimental results over a diverse range of scenarios evince the benefits of the proposed approach, which notably improves this convergence rate with respect to a naïve MOEA approach.

Mustafa F Abdelwahed, Joan Espasa, Alice Toniolo et al.

Diverse planning approaches are utilised in real-world applications like risk management, automated streamed data analysis, and malware detection. The current diverse planning formulations encode the diversity model as a distance function, which is computational inexpensive when comparing two plans. However, such modelling approach limits what can be encoded as measure of diversity, as well as the ability to explain why two plans are different. This paper introduces a novel approach to the diverse planning problem, allowing for more expressive modelling of diversity using a n-dimensional grid representation, where each dimension corresponds to a user-defined feature. Furthermore, we present a novel toolkit that generates diverse plans based on such customisable diversity models, called \emph{Behaviour Planning}. We provide an implementation for behaviour planning using planning-as-satisfiability. An empirical evaluation of our implementation shows that behaviour planning significantly outperforms the current diverse planning method in generating diverse plans measured on our new customisable diversity models. Our implementation is the first diverse planning approach to support planning categories beyond classical planning, such as over-subscription and numerical planning.

Hankz Hankui Zhuo, Xin Chen, Rong Pan

Plan synthesis aims to generate a course of actions or policies to transit given initial states to goal states, provided domain models that could be designed by experts or learnt from training data or interactions with the world. Intrigued by the claims of emergent planning capabilities in large language models (LLMs), works have been proposed to investigate the planning effectiveness of LLMs, without considering any utilization of off-the-shelf planning techniques in LLMs. In this paper, we aim to further study the insight of the planning capability of LLMs by investigating the roles of LLMs in off-the-shelf planning frameworks. To do this, we investigate the effectiveness of embedding LLMs into one of the well-known planning frameworks, graph-based planning, proposing a novel LLMs-based planning framework with LLMs embedded in two levels of planning graphs, i.e., mutual constraints generation level and constraints solving level. We empirically exhibit the effectiveness of our proposed framework in various planning domains.

Abrar Ghaith

Background: The potential health advantages of functional food products have increased their appeal. Their reception and implementation are greatly influenced by consumer attitudes and purchasing intentions. The Theory of Planned Behavior (TPB) is used in this study to examine how attitudes toward and intentions to buy functional food products in Hungary are influenced by health consciousness (HC) and nutritional knowledge (KN). Methods: From March to May 2023, 396 adult Hungarian volunteers took part in an online survey. The poll measured respondents' intentions to buy functional food products as well as their health consciousness, nutritional knowledge, attitudes, and subjective norms (SN). Through pilot research, the questionnaire's reliability and validity were determined. Multiple regression analyses, one-sample t-tests, and Cronbach's alpha were all included in the statistical analysis. Results: The majority of participants were female, working students. In support of hypotheses H1 and H2, health consciousness significantly influenced attitudes and purchase intentions. H3 and H4 are supported by the findings that nutritional knowledge strongly influenced attitudes and purchase intentions. Both perceived behavioral control and subjective standards had a beneficial impact on purchase intentions supporting H5 and H6. Conclusion: This study provides important insights into Hungarian consumers' preferences for functional food items. It highlights the beneficial effects of health awareness, information, attitudes, arbitrary standards, and perceived behavioral control on buying intentions. It was discovered that attitudes play an important role in mediating the link between nutritional knowledge, health consciousness, and purchase intentions. It was discovered that attitudes play an important role in mediating the link between nutritional knowledge, health consciousness, and purchasing intentions. The dynamic functional food market's marketers and legislators should take these findings seriously. The subtleties of these attitudes and their implications for promotional tactics can be explored in greater detail in future research. Promoting healthier food options and informing policy and marketing decisions require an understanding of consumer perceptions and behaviors.

Giulio Vegliante, Valerio Baiocchi, Luca Maria Falconi et al.

Shallow landslides pose a widely growing hazard and risk, globally and particularly in Mediterranean areas. The implementation of adequate adaptation and mitigation measures necessarily requires the development of practical and affordable methodologies and technologies for assessing the shallow landslides hazard and its territorial impact. The assessment of shallow landslide hazard maps involves two different and sequential steps: the susceptibility and the runout analysis, respectively, aimed at the identification of the initiation and the propagation areas. This paper describes the application in the Giampilieri and Briga Villages area (Sicily, Italy) of a shallow landslide risk process at a basin scale with an innovative approach in the runout assessment segment. The runout analysis was conducted using specific GIS tools employing an empirical–geometric approach at a basin scale. The exposure and vulnerability values of the elements at risk were assigned using a qualitative and semi-quantitative approach, respectively. The results highlight the effectiveness of the procedure in producing consistent runout hazard and risk assessments in the valley areas where the more important and vulnerable exposed elements are located. This study contributes to addressing the public administration demand for valuable and user-friendly tools to manage and drive regional planning.

Faisal Faisal

The Jeneberang River has enormous potential to be developed as a green tourism destination in the city of Makassar. The potential it has consists of the natural base potential as one of the largest rivers in South Sulawesi province in the form of water and all the biota that form a single river ecosystem, panoramic views of the area located at the estuary, which is directly connected to the sea in the Makassar Strait, richness of land vegetation along the banks, rivers in river border areas, and beaches. This research is descriptive research with a normative approach to determine the objectives, implementation, and impact of tourism development policies on the existence of the Jeneberang River as a green tourism destination in the city of Makassar. The research respondents were 17 people from representatives of each element of Makassar city tourism stakeholders. Data was collected through in-depth interviews and searching for documents relevant to the policy for developing the Jeneberang River as a green tourism destination. The research results found that the development of the Jeneberang river has been stipulated in several regional policies in the form of regional regulations, namely Makassar City Regional Regulation Number 4 of 2015 concerning Makassar City Regional Spatial Plan for 2015-2034 and Makassar City Regional Regulation Number 5 of 2023 concerning Development Master Plan Makassar City Regional Tourism 2023-2025. Operationally, this policy has not been supported by technocratic planning in the form of the Jeneberang River Development Masterplan as a Green Tourism Destination

Hengdong Feng, Xiaoguang Zhang, Ying Nan et al.

Ecological sensitivity is one of the important indicators of regional ecological fragility, which can represent the sensitivity of ecosystems to natural environmental conditions and human activity disturbances in the region. In this study, the ecological sensitivity of land resources in the Tumen River Basin of China was quantitatively evaluated by taking 3 ecologically sensitive impact types, including the natural environment, human disturbance, and soil erosion, as evaluation criteria, and 11 ecologically sensitive factors were selected to build an evaluation system using the analytic hierarchy process (AHP) method, to determine the weights of the evaluation factors, combined with geographic information system (GIS) technology. The results show that: (1) Among the three types of ecological sensitivity factors, the influence of human disturbance is the most obvious, and the two factors of land use type and distance from construction land have the highest weights in the comprehensive ecological sensitivity evaluation. (2) There are no extremely sensitive areas or insensitive areas in the Tumen River Basin in China. Highly sensitive areas account for only 0.59% of the total area and are mainly concentrated in the lakes, rivers, and reservoirs in the study area. Moderately sensitive areas account for 54.12%, which are concentrated in the central part of the Tumen River Basin Slightly sensitive areas are mainly located in the mountainous areas in the north and south of the study area. (3) Among the various land resource types, the proportion of slightly sensitive areas and moderately sensitive areas of woodland is close (about 50%), while cultivated land, grassland, construction land, and bare land are mainly moderately sensitive areas (73.95%, 82.07%, 96.59%, and 78.78%), and water bodies are mostly distributed within highly sensitive areas (60.97%), and all wetlands with the smallest area are moderately sensitive. The results of the study can provide data support and a scientific basis for regional ecological protection and development planning.

Taquan Ma, Rui Liu, Zheng Li et al.

In the context of promoting high-quality development of mountainous urban areas, it is of great significance to explore the evolutionary trajectory of habitat quality in the future based on policy-driven backgrounds, particularly for the protection of the Western mountainous ecosystem. This study takes the Chongqing metropolitan area, a typical southwestern mountainous city, as the study area. Based on land use data from 1990 to 2020, the study combines the InVEST and PLUS models, considering the constraints imposed by urban construction planning and ecological control policies, to investigate the spatiotemporal variations of habitat quality from 1990 to 2030. The findings are as follows: (1) From 1990 to 2020, there was a significant decrease in cultivated land area in the study area, while forestland and unused land showed a declining trend. Conversely, built-up land, grassland, and water bodies exhibited an increasing trend. In the land use simulation for 2030, under the scenarios of natural growth and ecological protection, the cultivated land area further decreased, while forestland and grassland received a certain degree of protection. In the scenario of development, a large amount of cultivated land was converted into built-up land. (2) From 1990 to 2030, significant overall habitat quality changes were observed among different regions within the study area. Except for Nanchuan District and Qijiang District, other administrative regions experienced a certain degree of decline in habitat quality. The distribution of habitat quality exhibited significant spatial heterogeneity. The low-value habitat areas were centered in the middle of the metropolitan area and gradually expanded outward. The high-value habitat areas were concentrated in the study area, including the Huaying Mountain range and other mountainous ecological corridor regions. (3) Habitat quality in the study area showed a decreasing trend with an increasing slope gradient. With the development of urbanization, habitat quality degradation gradually spread to high-altitude and steep-slope areas. (4) The expansion of built-up land is the main cause of habitat degradation in the study area. From 1990 to 2030, against the background of development strategies in the study area, the expansion of built-up land encroached upon cultivated land and forestland. In the habitat quality prediction for 2030, habitat degradation in the region will continue to intensify. This study provides scientific references and the basis for promoting regional sustainable land use and ecological conservation.

Yogesh Wadadekar, Dipankar Bhattacharya, Abhirup Datta et al.

In order to deliver the full science potential of the Square Kilometer Array (SKA) telescope, several SKA Regional Centres (SRCs) will be required to be constructed in different SKA member countries around the world. These SRCs will provide high performance compute and storage for the generation of advanced science data products from the basic data streams generated by the SKA Science Data Handling and Processing system, critically necessary to the success of the key science projects to be carried out by the SKA user community. They will also provide support to astronomers to enable them to carry out analysis on very large SKA datasets. Construction of such large data centres is a technical challenge for all SKA member nations. In such a situation, each country plans to construct a smaller SRC over the next few years (2022 onwards), known as a proto-SRC. In India, we propose to construct a proto-SRC which will be used for the analysis of data from SKA pathfinders and precursors with strong Indian involvement such as uGMRT, Meerkat and MWA. We describe our thinking on some aspects of the the storage, compute and network of the proto-SRC and how it will be used for data analysis as well as for carrying out various simulations related to SKA key science projects led by Indian astronomers. We also present our thoughts on how the proto-SRC plans to evaluate emerging hardware and software technologies and to also begin software development in areas of relevance to SKA data processing and analysis such as algorithm implementation, pipeline development and data visualisation software.

Attila Máté Kovács

Ransomware threats and incidents have exponentially increased causing both financial and reputational losses to organizations of all sizes and sectors. Ransomware attacks became the talk of the news when the world was hit by COVID 19 pandemic and people shifted to remote work in large numbers (Brynjolfsson et al., 2020, p. 13-14). Cybercriminals and threat groups are using various types of social engineering techniques such as email phishing, smishing, spear phishing attacks to spread ransomware infections in systems and networks. To protect organizations, users, and IT infrastructures it is important to understand how ransomware works, and how various threat actors use it to exfiltrate confidential data and information. Hence a critical approach toward ransomware infection and its mitigation by using different techniques is discussed and analyzed in this research paper concerning other scholarly articles and papers.