Location Selection Research Articles

Efficacy of plantar foot temperature monitoring in preventing ulcers in individuals with diabetes: An umbrella review protocol

Diabetes mellitus often leads to foot ulcers, which can result in amputations and significantly affect quality of life. Monitoring plantar foot temperature has emerged as a promising intervention for preventing these ulcers. This study aims to examine the potential benefits of plantar foot temperature monitoring in preventing ulcers in individuals with diabetes mellitus. The umbrella review protocol will follow the guidelines set forth by the Joanna Briggs Institute. Participants aged 18 years and older with a diagnosis of type 1 or type 2 diabetes mellitus, and without any active ulcers at the commencement of the study, will be included. We will consider studies that monitor plantar foot temperature using thermometry and thermography. Two independent reviewers will carry out the study location selection and data extraction, employing a modified and validated JBI extraction tool. The methodological quality of the studies included will be evaluated using both the JBI Critical Appraisal Checklist for Systematic Reviews and Research Syntheses, as well as the AMSTAR-2 tool. This systematic review is registered under PROSPERO number CRD42024509838. Data on the effectiveness of interventions for monitoring plantar foot temperature to prevent ulcers in individuals with diabetes will be collected and summarized. A citation matrix will analyze the overlap of primary studies, and meta-analysis will be performed if feasible. The certainty of evidence will be assessed using the GRADE system. This protocol ensures rigorous execution by researchers and may aid in implementing evidence-based nursing interventions for ulcer prevention in diabetes.

Household solid waste processing plant location selection: interval-valued intuitionistic fuzzy information-based gained and lost dominance score approach

Household solid waste processing plant location selection: interval-valued intuitionistic fuzzy information-based gained and lost dominance score approach

Digital Marketing Development Strategy to Increase the Number of Tourists

The increase in number of tourists is inseparable from the strategies used by tourist attractions by utilizing social media and Generation Z as a potential segmentation because they are known as digital natives. As happened to Bigstone Riverside located in Bogor, West Java, which once utilized social media by collaborating with influencers and getting an increase in visitors. Unfortunately, because the strategy used was inconsistent, there was a decline in visitors. This research aims to formulate a digital marketing development strategy for Bigstone Riverside. The selection of this research location was carried out purposively because this tourist destination has the potential to be developed and become a source of income for the surrounding community. This research uses qualitative data sourced from primary data and secondary data. The strategy formulation method used SWOT matrix by analyzing internal and external factors. The results of the strategy in this study are alternative strategies such as creating content that highlights advantages, creating promotions so that tourists share their excitement, conducting digital marketing training for administrators, collaborating with influencers and tourist information accounts, utilizing content generated by UGC users, optimizing SEO, and forming a team.

Assessment of Wind Energy Potential and Selection of Wind Park Location on the Example of the Trusina Mountain Ridge (Republic of Srpska, Bosnia and Herzegovina)

Assessment of Wind Energy Potential and Selection of Wind Park Location on the Example of the Trusina Mountain Ridge (Republic of Srpska, Bosnia and Herzegovina)

Analysis of Building Distribution and Accessibility of Kanigoro Urban Roads

The Kanigoro Settlement Area's land is mostly utilized for residential and agricultural purposes. Modifications to the city's construction and development are necessary to turn Kanigoro into a sustainable urban region, particularly in the field of urban morphological pattern development. City or area morphology may be analyzed using three primary components: building density, land use patterns, and road network patterns. This research aims to investigate the urban morphology pattern in Kanigoro Urban Area, focusing on road accessibility and building dispersion. In order to accomplish this goal, land use and building distribution were identified using satellite image data from 2011, 2015, 2019 and 2023, along with questionnaire data on residential location selection. The findings demonstrate that elongated patterns dominate settlement patterns in Kanigoro, with group patterns and the main road network following closely behind. Kinship and historical factors also play a role in this pattern. During the study, there was a notable increase in settlement growth, particularly on main transportation routes. The population density analysis shows that there is a concentration of population in the city center and some rapidly developing residential areas as a result of this rapid settlement growth. According to the road accessibility analysis, most areas are served by arterial roads, but there are still some areas with limited accessibility, especially with regard to collector roads. Based on the research results, there is a need for sustainable integrated spatial planning, adequate infrastructure, improving the quality of the collector road network and developing integrated public transportation.

A three-stage framework for optimal site selection of hybrid offshore wind-photovoltaic-wave-hydrogen energy system: A case study of China

The integration of offshore wind-photovoltaic-wave-hydrogen production is a sustainable energy development concept that could smooth the intermittency of renewable energy generation, reduce energy abandonment, and improve energy efficiency. However, the successful deployment of a hybrid offshore wind-photovoltaic-wave-hydrogen energy system is premised on the selection of an appropriate location, which necessitates a robust framework to support this decision. This study proposes a three-stage decision framework based on Geographic Information System and multi-criteria decision-making to determine the optimal location from macro and micro perspectives. To ensure the effectiveness of site selection, it develops a comprehensive criteria system, including exclusion criteria and evaluation criteria, encompassing geographical, resource, economy, risk, and sustainable potential aspects. Then, the spatial simulation of alternative sites is conducted according to exclusion criteria to rule out infeasible alternative sites. The multi-criteria decision-making in the third stage is performed in a rough-fuzzy environment to eliminate the uncertainty in decision-making. Finally, a case study is conducted on Hainan Island, China. The results show that the western sea area of Dongfang City is the optimal location to deploy the hybrid offshore wind-photovoltaic-wave-hydrogen energy system. The proposed framework offers a reference for practical offshore renewable energy project implementation.

Multi-objective model for electric vehicle charging station location selection problem for a sustainable transportation infrastructure

The transportation industry mostly depends on conventional vehicles, leading to significant adverse effects on the environment. The widespread usage of electric vehicles can be seen as a relief for this problem. However, the success of electric vehicles largely depends on the availability and proper deployment of charging station infrastructure. It is crucial for cities to strategically select suitable locations for charging stations with adequate capacity levels to promote sustainable and environmentally-friendly transportation options. Hence, in this study, a multi-objective model is proposed for the electric vehicle charging station location selection and capacity allocation problem. The model aims to maximize customer satisfaction, minimize total risk, and minimize costs as key objective functions. To manage the demand effectively, the region of interest is divided into grids. The proposed multi-objective model is applied to the European side of Istanbul and solved by using AUGMECON2 technique. Finally, computational analyses are presented based on scenarios including different demand values. These analyses provide valuable insights into the effectiveness of the proposed model and its implications for achieving sustainable transportation in Istanbul.

Preparation of A Map of Potential Areas For the Installation of A Sanitary Landfill in The Porto Murtinho/MS Region

Objective: The main objective is to prepare a map to identify areas with potential for the installation of a landfill in the region of Porto Murtinho/MS. Theoretical Framework: This study addresses the relevance of the careful selection of locations for the implementation of Sanitary Landfills, with an emphasis on environmental and social aspects, using geotechnologies as fundamental tools for a comprehensive and effective analysis. Method: The mapping was based on the acquisition and processing of geospatial and environmental data. The factors were classified as limiting or not, considering watercourses, areas subject to flooding, roads, land use and occupation, slope, soil and urban proximity. Data integration through map algebra was performed in QGIS software, and WRPLOT View was used for wind analysis. Results and Discussion: The results revealed that the majority of areas with high installation potential are located at a distance of 2 (two) to 5 (five) kilometers from the urban perimeter. The supplementary analysis of Rosa dos Ventos demonstrated that areas located to the east are more suitable for the implementation of sanitary landfills. Research Implications: The multifaceted approach, which includes environmental and operational aspects, makes it possible to identify areas suitable for the implementation of sanitary landfills. Originality/Value: This study demonstrates the relevance of geotechnologies in choosing locations for landfills, where limiting factors exclude unsuitable areas, and non-limiting factors classify the installation potential, being a methodology replicable in other locations for sustainable environmental management.

Early visual modulation and selection predict saccadic timing during visual search: An ERP study.

Saccadic eye movements, a critical aspect of real-world visual behavior, are preceded by an initial accumulation of visual information followed by the selection of a single location to move one's eyes. However, it is currently unclear how each of these stages uniquely affects saccadic timing. In this study, participants searched for a contour integration target while EEG was used to measure posterior cortical activity between search display onset and first saccade initiation. The goal was to determine whether saccade timing could be attributed to differences in early ERP amplitudes, with the P1 reflecting the magnitude of early perceptual information accumulation and the N1 reflecting the strength of selection leading to the saccadic decision. EOG was used to measure saccade timing, and trials were divided into fast, middle, and slow bins. The N1 response was smallest in the slow saccade tertile, relative to both the fast and middle tertiles, suggesting weak selection. In contrast, the P1 response was largest for this same slow saccadic tertile relative to the middle saccadic tertile, suggesting vigorous information accumulation. Therefore, delays in saccadic behavior may occur when the visual system is overwhelmed with visual input, thus increasing the time to reach a saccadic decision. These findings reconcile models of eye movement behavior which often prioritize either the impact of information accrual or selection, rather than regarding both as an integrated whole.

Reshoring concepts: definitions and a structured bibliometric review

PurposeThe aim of this paper is to clearly mark the clusters in the related literature using bibliometric analysis and draw useful implications for the academic research purposes especially in the stream of Supply Chain Management (SCM).Design/methodology/approachBy employing rigorous selection criteria, sample articles were selected for synthesizing and conducting a bibliometric analysis. This paper tries to identify the significance of the concept of reshoring with the aspect of SCM, operations, logistics etc. Starting from sample selection, systematic selection criteria has been used to generate the database, using Scopus. The sample size was 184. Using VOSViewer, statistical and graphical representations were generated for clusters in the literature that will be useful for judging the trends of research under shoring concepts.FindingsFindings show that unclear difference compared to other supply chain concepts obstructs further theory development within reshoring concepts. To address this challenge, the review categorizes themes and defines boundaries. Based on the analysis findings, this paper advocates for additional research in areas that are crucial but have received limited or no attention. Specifically, there is a need for action research on motivations, governance modes, and location selection concerning reshoring decisions.Research limitations/implicationsThis review has a few limitations. The absence of publications in other language, than English, may result in a significant loss of knowledge. This research paper cited a few relevant publications in the form of conference papers, industry reports, books, and book chapters. Nonetheless, they were excluded from the organized bibliometric audit. To further advance the knowledge in this field, exploratory longitudinal case studies will bring to focus the changes on manufacturing strategies using the shoring and reshoring stages.Practical implicationsA current example of this is a French company named Stil (Terzian, 2020) which brought its glass thermometer production back to its home after the unexpected closure of its suppliers from China. Another Italian firm has restarted production of disposal bio-degradable face masks after 15 years to compete with low-cost alternatives from China (Greco, 2020). Reshoring concepts are now under consideration of organizations including Boeing, Bosch, Phillips and more.Originality/valueTo the best of our knowledge, this represents one of the earliest efforts to conceptualize and define reshoring concepts, aiming to distinguish them from one another appropriately. To accomplish this, the earlier demarcated clusters precede this section’s classification of reshoring concepts illustrated in Table 8. Based on the synthesis of definitions and thematic clusters above, we have concluded the literature review in this emerging field. It is intended to contribute to theory development and practitioner support in reshoring decisions by clarifying the dimensions.

Wind Power Plant Location Selection with Fuzzy Logic and Multi-Criteria Decision-Making Methods

This study aims to examine the effectiveness of the fuzzy multi-criteria decision-making methods, especially Fuzzy Weight by Envelope and Slope (F-WENSLO) and Fuzzy Ranking Alternatives with Weights of Criterion (F-RAWEC) for evaluating the potential locations for wind power plants. The study's objective is to provide a solid framework for deciding which locations are most suitable for wind energy projects, taking into account various criteria and expert opinion. The study includes the evaluation of five potential places including Gürün, Kangal, Divriği, Ulaş and Zara in Sivas province of Turkey. The evaluation criteria include wind speed and direction, altitude, land use, environmental impacts, infrastructure proximity, social acceptance, economic costs, security and risk factors, climatic conditions and legal and permit requirements. Scores from experts from various fields and weights of criteria were determined. The analysis revealed that Ulaş and Kangal got the highest point for the wind power plant installation. As Ulaş gets the highest point due to favorable wind conditions, favorable altitude and advantageous land use; Kangal stood out as a strong candidate because of its acceptable wind speed, positive social acceptance and low economic costs. The study highlights the importance of integrating multiple criteria and expert assessments in the decision-making process. The findings suggest that fuzzy multi-criteria decision-making methods can be effectively supportive of wind power plant site selection. The study provides valuable information for project managers and policy makers, emphasizing the importance of criteria such as security in the choice of location, legal requirements and social acceptance. Future research may expand these findings to examine the integration of additional criteria, alternative locations, and other multi-criteria decision-making techniques.

MANGROVE HEALTH INDEX IN MARTAJASAH MANGROVE ECOTOURISM, BANGKALAN REGENCY, EAST JAVA, INDONESIA

Mangrove areas need to be considered from the condition of distribution and density of mangrove forests for future mangrove forest management planning, especially on Madura Island, especially Martajasah mangrove ecotourism. The purpose of this study is to determine the type of mangrove, canopy cover, and mangrove health index. The method used in this study is observation, which is to know the general overview of the research to be carried out. The selection of the research location was determined by the stratified random sampling method. The canopy cover on the mangrove was measured using the Hemispherical Photography method using the front camera of the OPPO Reno 6 phone with a camera resolution of 8 megapixels with a 180° angle of view at the point of taking the photo. The results of this study found 7 types of mangroves, including Sonneratia alba, Sonneratia caseolaris, Rhizophora apiculata, Rhizophora mucronata, Avicennia alba, Avicennia marina, and Lumnitzera racemosa. The percentage of canopy cover obtained an average score of 63.44% or in the solid category. This indicates that the mangrove ecosystem found in Martajasah mangrove ecotourism is in a good category. The Mangrove Health Index in Martajasah Mangrove Ecotourism is included in normal (33-66%).

Application of multi-criteria decision making (MCDM) model for solar plant location selection

This study aims to systematically evaluate and identify the most suitable locations for establishing solar farms in the United Kingdom. It employs a comprehensive Multi-Criteria Decision-Making (MCDM) model that incorporates the Fuzzy Analytic Hierarchy Process (FAHP) method. Eight potential locations have been identified and selected for their climatic conditions and other pertinent parameters. These potential locations underwent additional assessment considering several factors including temperature, annual hours of sunshine, absolute humidity, proximity to major roads, distance from the power network, and potential demand. The data was normalized to eliminate scale effects and improve comparability. A MATLAB program has been developed with universality and user-friendliness in mind. Its purpose is to establish location selection factors graphs according to application-specific criteria and generate the matrix representation of these graphs for each potential candidate location. The permanent matrix, a composite metric synthesizing six criteria, identifies Torquay as the optimal location with a permanent value of 18.16. This quantitative approach, intersected with qualitative assessments, presents a clear hierarchy of site suitability. The model's simplicity, scalability, and proven accuracy make it a valuable tool for assessing renewable energy project viability in diverse regions.

Towards advanced sustainable criteria for choosing the best site for collecting solar energy in cities using multi-criteria GIS

Solar energy has become a prominent and crucial source of clean energy due to the increasing global demand for electricity. There is a prevailing global trend towards the construction of solar farms as a means of energy generation. This study aims to assess multiple criteria encompassing urban, environmental, and social aspects in order to ascertain the optimal site for constructing solar farms. The evaluation primarily focuses on characteristics such as topography, solar radiation, accessibility, land use, and proximity to roads and power stations. In order to acquire the necessary spatial fit model, the data was evaluated utilizing a Geographic Information System (GIS) program, and the criteria were subsequently consolidated into an integrated geographic information system. A comprehensive review of the existing body of literature reveals that environmental factors, specifically solar radiation and aspect, play a crucial role in determining the suitable places for the establishment of solar energy collection projects (Merrouni et al. in Energy Procedia 49:2270-2279, 2013; McKinney in J Student Res Environ Sci Appalac 4:1-14, 2014). Furthermore, other analysis factors such as proximity to built-up regions, closeness to power lines, and proximity to roadways are taken into account (Hott et al. in GIS-based Spatial Analysis For LargeScale Solar Power And Transmission Line Issues: Case Study of Wyoming, U.S. In: Proceedings of the 41st American Solar Energy Society Meeting, 2012; Effat in Int J Adv Remote Sens GIS 2:205-220, 2013). These criteria have an impact on the cost of solar farms. The objective of this study was to assess several aspects influencing the selection of an optimal location for a solar energy farm, taking into consideration the aforementioned criteria. The study was carried out in New Aswan city, utilizing data obtained from the Urban Planning Authority within the Ministry of Housing and Urban Development, as well as the New Aswan City AuthorityI generated cartographic representations and compiled quantitative data, which informed our selection of places that met the established criteria through the utilization of a Geographic Information System (GIS) software. Upon the conclusion of the study, numerous locations that satisfied the established criteria were selected. The present study focuses on regions with high capacity, and the findings are depicted in the form of spatial and objective maps. One of the primary benefits associated with the utilization of this methodology lies in its versatility, as it can be implemented across several domains. Furthermore, a straightforward adjustment of the criteria facilitates its application in the selection of optimal locations for wind farms.

Utilizing Fuzzy TOPSIS for Sustainable Development: A Case Study in Selection of Airport Location

In recent years, most countries have seen an increased focus on the concept of sustainable development in decisions regarding transportation infrastructure where environmental and social criteria are considered on par with economic criteria. This is particularly important in decisions to build new airports or expand their capacity with long-term implications for economic growth, welfare and regional development processes.The fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) method is distinguished from the other methods of the multi-criteria decision making (MCDM) in that it arranges the available alternatives according to their proximity to the optimal solution. In real life, alternatives are observed in relation to the criteria and the weights of the criteria with fuzzy numbers. In such a case, the crisp traditional methods that solve the problems of multi-criteria decision-making are considered to be of weak effectiveness. The aim of this paper is to solve the problem of choosing a new hub airport for a hypothetical European Union airline, by applying the fuzzy TOPSIS method based on alpha level sets as it was applied to a selected data set from the available alternatives (candidate airports). The criteria for expressing the performance of these airports are defined and evaluated by the decision maker. The objective of the practical application of the studied problem is to show the usefulness of the method used as a tool that helps the decision maker to determine which of the alternatives represents the best solution in an environment with fuzzy data.

COMPANIONSHIP ON EDUCATION AND INTRODUCTION TO BAT SPECIES IN BRAJA HARJOSARI AND LABUHAN RATU VII, EAST LAMPUNG

Under the HETI Project Program of Universitas Lampung 2023/2024, education and introduction to bats have been conducted in Braja Harjosari and Labuhan Ratu VII, East Lampung. Knowledge about bats and their ecological roles is essential as a conservation effort, particularly in residential areas adjacent to natural bat habitats. Information on bats, including their natural habitats, behaviors, and roles in supporting human life, as well as general species identification, was provided. The selection of locations, mist net installation, capture, handling, and release were demonstrated, including oral swab sample collection. The community’s response and enthusiasm were very positive in understanding bats as wildlife and their roles in human life.

Determination of hydrogen fuel production from GIS-based selected ponds using hybrid renewable energy systems in Kayseri

This study offers the feasibility study of large-scale hydrogen production to establish environmentally friendly hybrid energy facilities based on wind and solar energy resources in the vicinity of lakes and rivers within the Kayseri region of Türkiye. The ultimate objective is to enable hydrogen production from lakes and rivers and identify optimal locations for the installation of hydrogen fuel stations. The precise selection of locations for the designated province is based on geographical, environmental, and infrastructural considerations by utilizing GIS technology which allows spatial analysis and superimposition of various layers. The methodology also involves the utilization of the HOMER software to facilitate the integration of wind and solar power, along with hydrogen production, providing a platform for environmentally friendly energy system design and optimization. A comprehensive evaluation has been conducted for the sizing and placement of renewable energy systems based on microgrid analysis, the design of hydrogen production facilities, and the establishment of hydrogen refueling infrastructure. The study also incorporates a financial analysis to assess the economic viability of the project over its lifecycle. Among the five water sources considered, the highest annual hydrogen production is 830 tons in Zamantı River, while Kızılırmak River has the lowest value according to LCOE and LCOH values, 0.030 $/kWh and 3.85 $/kgH2, respectively.

Use of UAVs in Earthquakes and UAV Base Location Selection for a Possible Marmara Earthquake

UAV’s are widely used in many fields today, and one of the most important of these fields is disaster management. The most significant disaster that comes to mind when mentioning disasters is undoubtedly earthquakes. UAV’s are used to support search and rescue operations before and especially after an earthquake. As Türkiye is located in an earthquake zone, earthquakes have affected and will continue to affect us from past to present. The Marmara earthquake, which is predicted to occur in the coming years, will cause great destruction considering the population density of the region. In this study, the use of UAV’s in earthquakes and the selection of the most suitable UAV base location for quick intervention without being affected by a potential Marmara earthquake was conducted using the TOPSIS method, which is one of the multi-criteria decision-making methods with criteria weights. As for the UAV class, MALE class UAV’s, which are produced by Türkiye and classified by NATO, were preferred due to their mission duration and payload capacity. While determining the alternatives, seven airports close to the Marmara region but not on the fault line were selected. The criteria and their weights were determined based on the opinions of five UAV pilots, and a total of six criteria were chosen. As a result of applying the TOPSIS method, Sivrihisar Aviation Center was determined to be the most suitable UAV base for intervention in a potential Marmara earthquake, being the closest to the ideal solution among the selected alternatives.

Corporate farming model for sustainable supply chain crude palm oil of independent smallholder farmers

Independent oil palm smallholders in Indonesia contributed significantly to the sustainable of Crude Palm Oil (CPO) supply chain. On the other hand, sustainability in the process of implementing the supply chain system for independent smallholders is an issue that is extremely important for the success of the supply chain system for the CPO company. This study’s objective is to develop an alternative business model with the goal of strengthening the interaction that already exists between independent farmers and cooperatives in ensuring the existence of a supply chain for raw materials and having access to financial resources, knowledge, and technology. The selection of the research location considered several factors, including the size of the area’s oil palm plantations, the number of oil palm farmers who are self-sufficient, and the possibility of locating CPO plant. Study findings that, the new model by business canvas analysis as the upgraded model of existing model business recommended that it should be built based on the cooperative palm oil family which provides farmers with access to financial, replanting, intensification, and extensification and infrastructure by APKASINDO, BPDPKS, Bank, and other stakeholders to sustain the FFB supply chain in cooperation through a partnership program in a long-term scheme. This whole system was developed by corporate farming system based on the cooperative as the off taker of FFB farmers and develop mini plant CPO to produce cooking oil and biofuels and by product as the waste management system as the value added for farmers.

Machine Learning Approach for Spatiotemporal Multivariate Optimization of Environmental Monitoring Sensor Locations

Abstract Long-term environmental monitoring is critical for managing the soil and groundwater at contaminated sites. Recent improvements in state-of-the-art sensor technology, communication networks, and artificial intelligence have created opportunities to modernize this monitoring activity for automated, fast, robust, and predictive monitoring. In such modernization, it is required that sensor locations be optimized to capture the spatiotemporal dynamics of all monitoring variables as well as to make it cost-effective. The legacy monitoring datasets of the target area are important to perform this optimization. In this study, we have developed a machine-learning approach to optimize sensor locations for soil and groundwater monitoring based on ensemble supervised learning and majority voting. For spatial optimization, Gaussian process regression (GPR) is used for spatial interpolation, while the majority voting is applied to accommodate the multivariate temporal dimension. Results show that the algorithms significantly outperform the random selection of the sensor locations for predictive spatiotemporal interpolation. While the method has been applied to a four-dimensional dataset (with two-dimensional space, time, and multiple contaminants), we anticipate that it can be generalizable to higher-dimensional datasets for environmental monitoring sensor location optimization.