Asset Location Research Articles

Robust, multi-objective optimization for the military medical evacuation location-allocation problem

Determining where to locate mobile aeromedical staging facilities (MASFs) as well as identifying how many aeromedical helicopters to allocate to each MASF, commonly referred to as the medical evacuation (MEDEVAC) location-allocation problem, is vital to the success of a deployed MEDEVAC system. Within this research, we develop an integer mathematical programming formulation to determine the location and allocation of MEDEVAC assets over the phases of a military deployment to support operations ranging from peacekeeping through combat to post-combat resolution. Our model seeks to address the multi-objective problem of maximizing the expected demand coverage as a measure of solution effectiveness, minimizing the maximum number of located MASFs in any deployment phase as a measure of solution efficiency, and minimizing the total number of MASF relocations throughout the deployment as a measure of solution robustness. This research makes two contributions. First, it formulates a representative mathematical programming formulation and identifies an accompanying solution methodology (i.e., the ε-constraint Method) to assess and recommend improvements to deployed military MEDEVAC systems designed to provide large-scale emergency medical response for contingency operations that range in casualty-inducing intensity (i.e., demand) over the phases of a deployment. Second, the research illustrates the application of the model for a realistic, synthetically generated medical planning scenario in southern Azerbaijan. Comparisons are made between the model’s (multi-phase) optimal solution and the phase-specific optimal solutions that disregard concerns of transitions between phases. The results highlight the conflicting nature between the objectives and illustrate the trade-offs between objectives as restrictions applied to the second and third objectives are respectively tightened or relaxed.

Using a statistical model of past wildfire spread to quantify and map the likelihood of fire reaching assets and prioritise fuel treatments

We present a method to quantify and map the probability of fires reaching the vicinity of assets in a wildfire-prone region, by extending a statistical fire spread model developed on historical fire patterns in the Sydney region, Australia. It calculates the mean probability of fire spreading along sample lines around assets, weights the probability according to ignition probability and also estimates the change in spread probability that fuel reduction in treatment blocks would achieve. We have developed an R package WildfireRisk to implement the analysis and demonstrate it with two case studies in forested eastern Australia. The probability of a fire reaching the vicinity of an asset was highest in the heavily forested parts of each case study, but when weighted for ignition probability, the high probability shifted to the wildland–urban interface. Further, when weighted by asset location, high-priority areas for treatment were in blocks next to the wildland–urban interface. This method is objective, fast and based on the behaviour of real historical fires. We recommend its use in wildfire risk planning, as an adjunct to heuristic methods and simulations. Additional functionality can be incorporated into our method, for instance via a function for building impact.

The Geography of Real Property Information and Investment: Firm Location, Asset Location and Institutional Ownership

AbstractUsing a sample of Real Estate Investment Trusts (REITs), we show that institutional investors exploit location‐based information asymmetries by overweighting firms headquartered locally and those with greater economic interests in the investor's home metropolitan statistical area (MSA). This asset allocation strategy is associated with superior portfolio performance. In a difference‐in‐difference‐in‐differences analysis of investor headquarters relocations, we find that investors tend to increase their ownership of REITs that have property holdings in the market to which the investor relocates. Our findings highlight the importance of understanding the relation between information advantages and the geography of firm's operations, as well as the implications on ownership patterns and portfolio construction.

'Back-Loaded' Tax Subsidies for Saving, Asset Location and Crowd-Out: Evidence from Tax-Free Savings Accounts

This paper presents estimates of the causal effect of Canadian Tax-Free Savings Accounts (TFSAs) balances on household saving and portfolio asset location choices. Contributions to TFSAs are not tax-deductible but capital income earned in the account accrues tax-free and withdrawals are not taxed. Using a difference-in-differences research design that exploits the sharp change in a family’s cumulative TFSA contribution room that arises when a family member turns 18 years old, I find that a 10 percent increase in TFSA balances reduces taxable financial asset holdings by 2.5 percent with no statistically significant effect on holdings in traditional tax-deferred accounts. I also find that the crowd-out in taxable asset holdings is driven by families reducing the share of their taxable financial assets held in fixed income securities.

INTRODUCING A FRAMEWORK FOR CONFLATING ROAD NETWORK DATA WITH SEMANTIC WEB TECHNOLOGIES

Abstract. Road network asset management is a challenging task as many data sources with different road asset location accuracies are available. In Australia and New Zealand transport agencies are investigating into harmonisation of road asset data, whereby two or more data sets are merged to create a new data set. Currently, identifying relations between road assets of the same meaning is not always possible, as road authorities of these countries use their own data structures and standards. This paper employs SemanticWeb Technologies, such as RDF/Turtle ontologies and semantic rules to enable road network conflation (merge multiple data sets without creating a new data set) as a first step towards data harmonisation by means of information exchange, and shifts road network data from intersections and road nodes to data sets considering the accuracy of the data sets in the selected area. The data integration from GeoJSON into RDF/Turtle files is processed with Python. A geographic coordinates shifting algorithm reads unique data entries that have been extracted from RDF/Turtle into JSON-LD and saves the processed data in their origin file format, so that a closed data flow can be approached.

A multi-objective, bilevel sensor relocation problem for border security

Consider a set of sensors having varying capabilities and respectively located to maximize an intruder’s minimal expected exposure to traverse a defended border region. Given two subsets of the sensors that have been respectively incapacitated or degraded, we formulate a multi-objective, bilevel optimization model to relocate surviving sensors to maximize an intruder’s minimal expected exposure to traverse a defended border region, minimize the maximum sensor relocation time, and minimize the total number of sensors requiring relocation. Our formulation also allows the defender to specify minimum preferential coverage requirements for high-value asset locations and emplaced sensors. Adopting the ε-constraint method for multi-objective optimization, we subsequently develop a single-level reformulation that enables the identification of non-inferior solutions on the Pareto frontier and, consequently, identifies trade-offs between the competing objectives. We demonstrate the aforementioned model and solution procedure for a scenario in which a defender is relocating surviving air defense assets to inhibit intrusion by a fixed-wing aircraft.

Investing in the Homeland: cross-border investments and immigrant wealth in the U.S.

ABSTRACT The ties that immigrants maintain across national borders are important indicators of both patterns of global interconnectedness and the incorporation of immigrants in their host countries. Scholars acknowledge that cross-border ties are extensive but debate the persistence of these ties following migration. We propose that simultaneously studying the home and host country financial investments of three large immigrant groups in the United States may provide unique insight into these important questions. Specifically, we study the home and host country investments of Mexican, Chinese, and Indian immigrants to the United States. We propose that home country financial ties are likely to decline over time but that host country financial ties will become stronger. However, significant and meaningful differences in these patterns are likely across the three groups we study. Using data from the New Immigrant Survey – a nationally representative multicohort longitudinal study of adult immigrants who are U.S. legal permanent residents – we find that cross-border investments are considerably less enduring than previous literature has found. However, portfolio composition and the location of critical assets vary in significant and informative ways by country of origin.

Historical Trajectories of Disaster Risk in Dominica

The calamitous consequences of 2017 Hurricane Maria for the Caribbean island of Dominica highlighted the acute and increasing susceptibility of the region to disasters. Despite increasing international attention to disaster risk reduction, recovery from hazard events can be especially lengthy and difficult for small island developing states. In this article, we build on existing understandings of disaster risk as a physical and social condition, showing that historical processes are fundamental to understanding how conditions of risk emerge and persist over time. We take an integrated approach to analyzing the drivers of risk accumulation, using the example of Dominica, where processes set in motion during the colonial period have shaped the location of people and assets, the degree to which they might be harmed, the societal repercussions of that harm and the prospects for recovery. We focus on the underlying economic vulnerabilities and physical exposure to hazards created by agricultural, economic, and social practices, and successive disaster responses that have constrained recovery. Uncovering these historical drivers and persistent issues, elucidates lessons for pursuing a more resilient development trajectory, including through the promotion of economic restructuring and diversification, and land reform.

Three location referencing method families: a new theoretical framework

This conceptual paper provides a new theoretical framework for location necessary to enable integration of current road asset management systems with digital designs based on IFC standards. Three important concepts are proposed. The first is redefining the meaning of location data taking into account three different types of model view: linear/network location referencing methods, spatial earth coordinates, and digital design modelling. The creation of new families for location referencing methods takes into account these model views. The new families proposed are: Topological (Logical Linear and Network Referencing), Geospatial (Real World Coordinates), and Geometric (Model Coordinates). By expanding the definitions of each of these families, a more complex, and thus, more inclusive concept of location data can be utilised to support the storage and retrieval of both heritage and future road asset location information.

PEMANFAATAN GOOGLE MAP API GUNA OPTIMALISASI IDENTIFIKASI ASET PEMERINTAH KOTA SEMARANG DENGAN METODE PASSING MULTIPLE PARAMETERS

The Law on Regional Autonomy has the impact of the Regional Government having the authority to manage the assets and regional income independently. Semarang City is an area in the Central Java Province managed by the local government of Semarang city that is required to be able to carry out autonomy well. One of the things done is the management of land and building assets owned by Semarang city government that functioned for the public interest and the implementation of city government semarang. data of government assets owned by Semarang city government recorded in Identity Card belonging to the Regional Finance and Asset Management Agency (DPKAD) there are 3,092 plots of asset managed by Regional Secretariat, Institution under Semarang City Government and management by sub-district and kelurahan area.Land assets managed by the municipal government of Semarang are currently not considered optimal. The application of the management information system for the location of the city government's land assets is planned to use the Google Maps Application Programming Interface (API), can be viewed as a solution to help the implementing officer recognize the location of the asset land and provide competitive advantages and advantages in an effort to transparency of the city government semarang on assets owned and the achievement of Semarang city to semarang be smart city.With the support of management information system application of land asset location of Semarang city government which can represent referring to location of location of real asset with remote sensing (sensing) is expected to be used effectively to manage, control and control the land asset.

Intelligent Asset Tracking System for Logistics Industry using IoT and Big Data

The logistics industry is a complex and dynamic ecosystem that requires efficient and reliable asset tracking systems (IATS) to optimize operations and reduce costs. To address these challenges, an IATS is proposed in this paper that leverages the power of IoT and big data technologies to collect real-time data on the location, condition, and status of assets such as trucks, containers, and shipments. The system is designed to provide end-to-end visibility and control of assets throughout the logistics value chain. It uses a combination of RFID, GPS, and other tracking technologies to collect data on asset location, temperature, humidity, vibration, and other relevant parameters. The data is then transmitted to a cloud-based platform for storage, processing, and analysis using big data analytics and machine learning algorithms. The platform enables logistics companies to monitor and manage their assets in real-time, optimize routes and schedules, and improve delivery times. It also provides machine learning tools for predictive modeling of asset price movement, enabling companies to identify potential price changes before they occur and minimize loss. The efficiency and effectiveness of our system were shown through simulation studies using data from real-world assets; as a result, it is an attractive option for the tracking and management of assets in real-world logistic businesses.

Analysis of Mutual Couple Effect of UHF RFID Antenna for the Internet of Things Environment

Asset management was a common RFID-based Internet-of-Things (IoT) application scene. RFID tags in the equipment warehouse were usually large, and the communication between the reader and the tag was prone to data collision problems, which affected the recognition efficiency of the device. In practical applications, due to the structural characteristics of the micro-strip UHF RFID tag antenna, the traditional inter-coupling impedance expression had large errors and insufficient accuracy in predicting the mutual coupling effect, such as system frequency shift. In this paper, the 3D initialization model of the tag was used to indirectly extract the electrical parameter values by the ANSYS HFSS software. At the same time, the dual-tag was taken as an example to derive the transimpedance expression between the dense tags to extract the corresponding coupling parameters. Finally, various tag-intensive scenarios in the actual environment were tested and the derivation formula was verified, and the dual-tag UHF RFID near-field frequency shift affected by the environmental factors, such as relative position, attachment, and the stacking method, was discussed. The mutual coupling effect on the minimum transmit power of the reader antenna was also studied. The experimental results showed that the average error of the formula calculated by this method was significantly smaller than that of the traditional formula. When the tag spacing was less than 30 mm, the derived mutual impedance expression was applied to the frequency shift calculation error range (1.6-7.3 MHz). For dense tag systems, the error was less than 9.8% when the number of tags was greater than 7, and the prediction accuracy was higher than the superposition method. The research results provided a theoretical and practical basis for the rapid identification and location of power assets during the dense RFID tag environment.

Internationalization of the oil and gas complex in Latin American countries

This article discusses the participation of foreign companies in the oil and gas complex of key Latin American countries. Special attention is paid to their origin and location of production assets in the host countries. Despite the participation of foreign capital in the oil and gas complexes of each of the countries considered, the degree of their internationalization is different and defies general trends. The main reasons for this are the presence of local state-owned companies and the foreign investment policy of economies. At the same time, the activities of foreign companies in Latin American countries are concentrated in the hydrocarbon production sector rather than their processing.

Enhancing access to industrial iot measurements by means of location based services

Location based services (LBS) have emerged as an active area of research aimed to filter and organize the information present on the internet. This work deals with LBS applied to industrial Internet of Things (IoT) applications, ranging from distributed measurement systems (DMS) to distributed human -machine interface (HMI). The goal is to investigate the available techniques to determine the location of assets (e.g., sensors and actuators) and then to characterize some application scenarios. In detail, the use cases have been implemented exploiting the eLUX Living Laboratory in Brescia, Italy, which resembles a smart grid, smart living and Industry 4.0 real scenario thanks to the numerous installed plants (including renewable sources, indoor sensory systems and electric vehicles). The ranging performance of beacon based and ultrawide band -based localization principles have been experimentally assessed.

Welfare measures and the composition of the bottom decile: The example of gender and extreme poverty in South Africa

ABSTRACTWe examine the composition of the bottom decile in South Africa using three alternative measures of socio-economic status (SES): an asset index, household income per capita and household expenditure per capita. We show that the gender composition of the bottom decile is sensitive to the measure used. We discuss possible reasons for these discrepancies, highlighting gender differences in asset ownership and location. This has implications for the use of asset indices for identifying the poorest members of society.

Zoom in, zoom out: Geographic scale and multinational activity

IB scholars have long studied the multinational enterprise (MNE) and now recognize that its ability to capture value stems from its control of bottleneck assets. In contrast, economic geographers and regional scientists have largely focused their attention on the locations within which economic and business systems operate. In this article, we draw on both these literatures. We emphasize that the MNE’s integration of upstream and downstream strategic considerations to maximize its control of bottleneck assets implies an optimal geographic footprint. This optimal footprint is typically asymmetric, with a spatial scale that varies dramatically across the different activities of the value chain. Upstream innovation processes are likely to be based on highly local considerations like the availability of specialized resources and collocation advantages. In contrast, downstream sales and marketing processes are likely to driven by imperatives of high volume and global reach. Further, in the current fast clockspeed business environment, the location and nature of bottleneck assets are likely to change rapidly and unpredictably, making organizational flexibility a crucial MNE capability.

Real-time location systems in nursing homes: state of the art and future applications

PurposeIn the domain of healthcare, both process efficiency and the quality of care can be improved through the use of dedicated pervasive technologies. Among these applications are so-called real-time location systems (RTLS). Such systems are designed to determine and monitor the location of assets and people in real time through the use of wireless sensor networks. Numerous commercially available RTLS are used in hospital settings. The nursing home is a relatively unexplored context for the application of RTLS and offers opportunities and challenges for future applications. The paper aims to discuss these issues.Design/methodology/approachThis paper sets out to provide an overview of general applications and technologies of RTLS. Thereafter, it describes the specific healthcare applications of RTLS, including asset tracking, patient tracking and personnel tracking. These overviews are followed by a forecast of the implementation of RTLS in nursing homes in terms of opportunities and challenges.FindingsBy comparing the nursing home to the hospital, the RTLS applications for the nursing home context that are most promising are asset tracking of expensive goods owned by the nursing home in order to facilitate workflow and maximise financial resources, and asset tracking of personal belongings that may get lost due to dementia.Originality/valueThis paper is the first to provide an overview of potential application of RTLS technologies for nursing homes. The paper described a number of potential problem areas that can be addressed by RTLS.

A bilevel exposure-oriented sensor location problem for border security

We propose a bilevel math programming model for locating a heterogeneous set of sensors to maximize the minimum exposure of an intruder’s penetration path through a defended region. Our formulation also allows a defender to specify minimum probabilities of coverage for a subset of the located sensors (e.g., the most valuable sensors) and for high-value asset locations in the defended region. We reformulate the bilevel program to a single-level optimization problem for which instances can be readily solved using a commercial solver. Given the locations of a defender’s sensors, we additionally formulate three alternative path identification models corresponding to conceptually-motivated intrusion-path metrics. We examine a test instance for the air defense of a border region against intrusion by an enemy aircraft; upon identifying the optimal, respective defender asset location and intruder routing solutions, we examine the intruder-optimal solutions corresponding to each of three alternative metric-specific paths, illustrating the relative impact of an intruder choosing an inappropriate metric. Sensitivity analyses are conducted to examine the effect of several model parameters on solution quality and required computational effort.

Vulnerability assessment and seismic mitigation intervention for artistic assets: from theory to practice

This paper deals with the vulnerability assessment of artistic assets, aiming at exploiting the potential of specifically designed seismic-isolation strategy to mitigate their seismic risk. In detail, starting from a review of the multidisciplinary procedure proposed by some of the authors for evaluating the safety level of art objects, this paper focuses on the required steps necessary to effectively design proper seismic mitigation intervention. For this purpose, the case study of the bust of Francesco I d’Este is investigated. This sculpture is housed at the second floor of Palazzo dei Musei in Modena, one of the cities hit by the seismic events occurred in May 2012 in Italy, which brought up to date the need of preserving this valuable object from seismic risk. After a preliminary vulnerability analysis carried out to assess the safety of the bust, a specific intervention of seismic isolation is conceived and realized by adopting Double Concave Curved Surface Sliders (DCCSS), which combine a strong flexibility to different museum contexts, with the possibility of standardizing the production process. To this aim, some operative charts are proposed as useful tool for the design phase of the seismic devices. Then special attention is devoted to an accurate evaluation of the seismic action, considering the location of the artistic asset at upper floors, also by means of different strategies for numerical modeling of the host masonry building. Finally, a series of non linear dynamic analyses are carried out to assess the effectiveness of the whole isolated system.

A “New” Asset Location: The Family Corporation

Recent tax legislation has opened up a new avenue for analysis when deciding where an asset may best be held to be most tax efficient: the tax-paying C type corporation. The new law lowered the tax on these entities to 21% from 35%. With the corporate rate now considerably below the individual rate, families need to consider what assets, if any, would be better held in a C corp.