Asset Model Research Articles

Reality Model-Based Facility Management Framework for Existing Building

Facility management (FM) is the most extended phase of the entire life cycle of buildings and incurs the highest expenses. However, limited quality drawings and historical data make information flow more complicated for many existing buildings and lead to inefficient FM. This research proposes a systematic and comprehensive reality point cloud model-based framework to support the FM process with feasible visual data collection. Specifically, this framework covers an end-to-end workflow of using a reality model to implement FM strategies, including visual data capture process for generating a reality model; FM information attachment in a reality model for issue queries; and information flow for issue tracking. The resulting reality model captures with critical and necessary FM data input can be used as an asset information model (AIM). We have also defined stakeholders' responsibilities in implementing FM and how the data are transferred, updated, and used within a reality point cloud-based AIM by stakeholders. The framework is evaluated by interviewing FM experts, and the results demonstrate that implementing the framework could improve the FM process's efficiency by using reality models.

The role of adaptivity in a numerical method for the Cox–Ingersoll–Ross model

We demonstrate the effectiveness of an adaptive explicit Euler method for the approximate solution of the Cox–Ingersoll–Ross model. This relies on a class of path-bounded timestepping strategies which work by reducing the stepsize as solutions approach a neighbourhood of zero. The method is hybrid in the sense that a convergent backstop method is invoked if the timestep becomes too small, or to prevent solutions from overshooting zero and becoming negative. Under parameter constraints that imply Feller’s condition, we prove that such a scheme is strongly convergent, of order at least 1/2. Control of the strong error is important for multi-level Monte Carlo techniques. Under Feller’s condition we also prove that the probability of ever needing the backstop method to prevent a negative value can be made arbitrarily small. Numerically, we compare this adaptive method to fixed step implicit and explicit schemes, and a novel semi-implicit adaptive variant. We observe that the adaptive approach leads to methods that are competitive in a domain that extends beyond Feller’s condition, indicating suitability for the modelling of stochastic volatility in Heston-type asset models.

Automanejo en personas con multimorbilidad: aportes desde la salutogénesis y el modelo de activos en salud

Different models of care in context of chronicity and multimorbidity include community, health system, clinical practice, health policies, prevention, and health promotion. Among these, the role of the health team as a facilitator of self-management is pointed out, being people the protagonists of their process. Multimorbidity approach is mostly carried out from a risk and disease focused point of view, which limits the exploration of resources of people and their environment. Incorporating a positive health approach can contribute to a greater comprehensiveness. The purpose of this article is to propose an approach from the synergy model of health, integrating salutogenesis and health assets model, to help facilitate self-management promoting people's agency capacity. Potential areas of application of these models are presented to work in the context of multimorbidity, promoting health and well-being conditions in people and their families.

The Asset Model: What Midwives Need To Support Alternative Physiological Births (Outwith Guidelines)

The Asset Model: What Midwives Need To Support Alternative Physiological Births (Outwith Guidelines) Dr Claire Feeley – Midwife, researcher and freelance consultant Instagram/Twitter @drfeeleyrm Published in The Practising Midwife Volume 25 Issue 02 February 2022 Introduction Full-scope midwifery was defined by the Lancet Midwifery Series1 which includes the optimisation of normal biological, psychological, social and […]

Endogenous fluctuations and international business cycles

AbstractWe introduce equilibrium indeterminacy into a two‐country incomplete asset model with imperfect competition to analyze the role of self‐fulfilling expectations or beliefs in explaining international business cycles. We find that, when self‐fulfilling beliefs are correlated with technology shocks, the model can account for the countercyclical behaviour observed for the terms of trade and real net exports while simultaneously generating higher volatilities relative to output, as in the data. The choice of the labour‐supply elasticity is shown to be critical for generating a negative correlation between the real exchange rate and relative consumption, thereby resolving the Backus–Smith puzzle.

Secure Integrity Auditing System for Electronic Patient Health Records using Advanced Encryption Techniques

Abstract: Cloud computing is one of evolving technology nowadays, giving versatile services. However, secure information sharing is vulnerable to cloud computing. With cloud storage services, users can remotely keep their information to the cloud and recognize the data sharing with others. Electronic wellbeing record (EHR) is a framework that gathers patients' computerized wellbeing data and offers it with other medical care suppliers in the cloud. Since EHR contains a lot of critical and delicate data about patients, it is necessitated that the framework guarantees reaction accuracy and capacity respectability. The verifiable database (VDB), where a user’s redistributes his huge data set to a cloud worker and makes questions once he needs certain information, is proposed as an effective updatable distributed storage model for asset compelled users. To improve productivity, most existing VDB plans use confirmation reuse and evidence refreshing strategy to demonstrate accuracy of the question results. Notwithstanding, it overlooks the "continuous" of confirmation age, which brings about an overhead that the user needs to perform additional cycle (for example evaluating plans) to check stockpiling trustworthiness. In this paper, we propose a publicly verifiable shared updatable EHR database scheme that supports privacy-preserving using secure encryption and batch integrity checking. Keywords: cloud storage, data integrity auditing, functional commitment, privacy-preserving auditing, sensitive information hiding, third-Party Auditor (TPA), user revocation Verifiable database.

Constructing a Real-Time Value-Chain Integration Architecture for Mass Individualized Juice Production

Mass individualized production refers to the mass production of individualized products. It becomes important for delivering a personalized customer experience in the Industrial Revolution 4.0 era. Developing seamless value chain integration between enterprises to achieve mass individualized production is challenging. Based on Reference Architecture Model Industrie 4.0 (RAMI 4.0), this paper aims to address two major challenges, which are asset modeling and integration, and data communication and brokering in a value chain data exchange ecosystem. This paper proposes a communication architecture that enables both vertical and horizontal value-chain integration. A proof-of-concept is built, which involves two stakeholders. The first is the individualized juice online ordering system, named PEC, and the second is a highly automated individualized mixed juice production manufacturing line, named OMIS. Three different tests are conducted in the experiments. The first is to test the creation of assets wrapped in the asset administration shell. The second is to test the connectivity between the Asset Brokering Manager (ABM) Connector and the ABM Portal. Last is to test the connectivity performance between two Asset Administration Systems. As a result, the experiments successfully created the asset instance data accurately, and the data were published in the ABM Portal for subscription by PEC and OMIS. The connectivity tests from OMIS to PEC, and vice versa, were successful, with the time taken of 114 and 121 ms, respectively.

Bounded rationality, adaptive behaviour, and asset prices

This paper develops a simple heterogeneous agent model (HAM) of asset prices with bounded rationality and adaptive behaviour. The model features feedback loop that amplifies shocks and leads to large price fluctuations. Our model not only retains the nonlinear interaction between prices and population in HAMs but also allows for a quantitative comparison with the data. Estimating the model to the data shows that the feedback loop helps explain the large variations in expected returns, such as return predictability and excess volatility.

Developing a two-stage multi-period stochastic model for asset and liability management: A real case study in a commercial bank of Iran

In this paper, a novel two-stage multi-period stochastic model is developed to obtain a comprehensive plan. This plan aims to manage the assets and liabilities such that all legal and budget constraints are satisfied. Assets in the model include short- and long-term loans with reasonable interest rates, investments in the stock market, varied bonds with different expirations, investments in other banks, and the legal budget in the Central Bank. However, liabilities encompass all types of sight and investment deposits with different maturities. In the model, each type of deposit's amount is considered a decision variable, while its total amount is assumed to be stochastic. The mathematical model is constructed in an innovative way such that all previous loans and bonds with possible transactions in the planning horizon could be considered initial parameters. Real data for a commercial bank in Tehran, the Islamic Republic of Iran capital, are used to construct and check the optimization model. The total revenues obtained through the mathematical model and one achieved based on the experiences of financial experts in the commercial bank for four years are compared.

Circular Economy, Sharing, and Sustainability

This study aims to analyse the predisposition of social economy agents to resource sharing. To achieve this, it was chosen to implement an exploratory qualitative approach directed to managers and an exploratory quantitative approach directed to employees. The results allowed to estimate that they do have a significant economic impact on number, paid work and business volume. It was shown the relationship between the interest demonstration on sharing and the appropriate qualification for the jobs of managers and employees. It was demonstrated the practice of informal and non-regulated sharing of own and third parties’ resources, among close partners, without the existence of a management model of knowledge, assets, time, use/reuse and exploitation. It is anticipated that the study could serve as scientific/methodological basis for a regional investment project, R&D and establishment of partnerships, reconciling interest in a smart region, as well as the application of circular economy principles.

Predictive maintenance in mining industry: grinding mill case study

The maintenance of industrial mining machines is a challenging process, especially in the case of critical assets, as it impact the hole process: for instance the grinding mills. However, many approaches have been developed by the growth of the mining industry in order to reduce the cost and optimize the time. Traditionally, machines operate until a failure occurs and then process to the maintenance (curative maintenance). However the loss of equipment and the time squandered during the maintenance procedure, rather than the stoppage of production, make this case inefficient. The second case is preventive maintenance, where the condition of the equipment is not taken into account, thus even healthy components are also susceptible to be replaced, which is a waste of time and budget. This is where predictive maintenance appears. This work aims to present a state of the art of recent works in predictive maintenance using machine learning algorithms including deep learning algorithms to end up with a synthesis of all cases that use predictive maintenance, and propose a Data Driven Model for mining industry assets for a better predictive maintenance.

Comparing the Effect of Intangible Assets and Macroeconomic Parameters on the Stock Prices in Firms Listed on the Stock Exchange of Iran, Saudi Arabia and Iraq

Comparing the Effect of Intangible Assets and Macroeconomic Parameters on the Stock Prices in Firms Listed on the Stock Exchange of Iran, Saudi Arabia and Iraq

Чутливість розв’язків при моделюванні динаміки інвестицій

The efforts of researchers for analysis of the financial investment market are largely aimed at considering multi-criteria problems with a large number of criteria, studying and solving investment management problems in static and dynamic settings, building procedures for an adequate description of random processes of market price changes, developing applied numerical methods and algorithms for solving large-scale problems. These problems as tasks of management under conditions of uncertainty refer equally to the fundamental problems of the applied theory of decision-making. The researches of R. Bellman, J. Danzig, R. Merton, and G. Markowitz are aimed at establishing the fundamental foundations and studying various meaningful interpretations of financial analysis processes. Thus, in the static case, they obtained fundamental results that had a wide practical application. The property of the distribution of the optimal portfolio into risk-free and risky components for the case of the presence of a risk-free asset on the market was established, and the fundamental properties of the equilibrium market of optimal portfolios were investigated. Dynamic models of asset and liability management have found the most successful application in the field of long-term financial planning, where the need for repeated decision-making is determined by the essence of the process.

A two-component realized exponential generalized autoregressive conditional heteroscedasticity model

This paper proposes a two-component realized exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model – an extension of the realized EGARCH model – for the joint modeling of asset returns and realized measures of volatility. The proposed model assumes that the volatility of asset returns consists of two components: a long-run component and a short-run component. The model’s unique ability to capture the long-memory property of volatility distinguishes it from the standard realized EGARCH model. The model is convenient to implement within the framework of maximum likelihood estimation. We apply the two-component realized EGARCH model and a restricted version of the model (the two-component realized EGARCH model with only short-run leverage) to four stock indexes: the Standard & Poor’s 500 index, the Hang Seng index, the Nikkei 225 index and the Deutscher Aktienindex. The empirical study suggests that the two-component realized EGARCH model and its restricted version outperform the realized GARCH model, the realized EGARCH model and the realized heterogeneous autoregressive GARCH model in terms of in-sample fit. Further, an out-of-sample predictive analysis demonstrates that the two-component realized EGARCH model and its restricted version yield more accurate volatility forecasts than the alternatives.

МОДЕЛИРОВАНИЕ СОЦИАЛЬНОЙ СИСТЕМЫ ТАДЖИКСКИХ СТУДЕНТОВ, ОБУЧАЮЩИХСЯ В РФ

Tajik students studying in the Russian Federation can be considered as a social system. Indeed, it is characterized by such universal (common to all social systems) characteristics as complex interrelation and interconitionality of internal processes, emergence, dynamics of social processes, and interconnection with outside environment. There are also a number of specific features of the social system of Tajik students studying at universities of the Russian Federation, namely as a social system. The application of a systematic approach, as well as the principles and concepts of management theory, makes it possible not only to formalize the very concept of the target asset (the social system of Tajik students studying in the Russian Federation), but also to describe its management system. Modeling of the target asset based on a set-theoretic approach was carried out for such difficult-to-formalize characteristics as personal data of Tajik students, data on their educational process, data on employment and obtaining additional professional skills, social and everyday nature data. For this purpose Boolean and linguistic variables are used in the work inter alia. The results obtained in the work of modeling the target asset (the social system of Tajik students studying in the Russian Federation) will subsequently describe not only the process of TS management, but also the specifics of monitoring the achievement of targets for the simulated management system.

The Work of Art in the Age of its Sanitized Fruition

Abstract For almost two years now the COVID-19 pandemic impacted in most different forms habits, models of organization, socio-political dynamics and economic assets. Arrangements and orders taking decades to reach stabilization have demonstrated an unsuspected precarity, demanding a profound reorganization of dynamics we had been long accustomed to. As the distant, sanitized character of interaction, transmission, fruition and creation processes has turned from a contingent measure into the unamenable norm of these days’ routine, every aspect of social interaction is changing accordingly. “Contact”, “contagion”, “proximity” and “distance” are not features of a transient period anymore: they are keywords of today’s experience. Indeed, while these concepts were already at stake in masscommunication and social media, it was not before nowadays that their precipitate on art forms could be taken into account more pristinely, for especially performative arts never had to amend their “familiar ground” in order to pursue their goals. Hence, how did artforms adjust themselves to wholly new forms of participation? What are we supposed to expect next? The main aim of this paper is to sketch out, relying on some classical loci of the history of Western aesthetics such as Plato, Aloïs Riegl, Walter Benjamin, this new, re-configured notion of aesthetic and artistic experience in the time of the COVID-19 pandemic.

Resolution and Quality Issues in 3D Analysis of Inscribed Signs: An Example from Cypro-Minoan Inscriptions

A recurrent demand in many archaeological digital documentation systems is the need for an accurate as possible registration of data. Somehow, contrary to this request, are efforts led by various computer science groups dealing with 3D documentation and focusing on developing fast and cheap solutions to record 3D models of archaeological assets. The aim of the article is to highlight the importance of aligning the 3D documentation strategy to the archaeological aims, by detailing all factors to be considered when deciding on one documentation strategy over another. The archaeological question discussed here, part of the PhD thesis of one of the co-authors (MP), relates to the Cypro-Minoan signatory and its diachronic variability. The 3D geometric characterization of signs and subsequent shape analysis is the method chosen to reach this goal. A major effort to be invested in correctly determining the shape and variability of each sign, is in assuring that the 3D captured shape is as close as possible to the archaeological reality, which is a common problem not only in palaeographical analysis but also in other fields, where features of interest are in the sub-millimetre range. The paper will illustrate how different data acquisition approaches and post-processing steps such as alignment methods and error treatment may distort the visualised result and thus have a negative impact on planned analysis. Thus, it will argue for the importance of more detailed paradata to allow an informed assessment of the reliability of 3D models and it proposes a list of values and decision-making steps that help make the 3D digitization process more robust and verifiable.

UNDERSTANDING BIG DATA-FAIR VALUE MEASUREMENT MODEL OF BIOLOGICAL ASSETS

This research establishes a Big Data-Fair Value Measurement Model of Biological Assets using a Smart Farming Approach. The aim of the study is to gather literature knowledge about the judgment of biological assets. The use of big data and innovative farming in the agricultural sector is relatively new in Malaysia, making people wonder about its effectiveness, whether positive or negative. However, determining fair value can be a daunting task due to the existence of personal biological properties and the variety of specimens (offspring), classes, and conditions. Agricultural sectors need to be more emphasised by many parties as the increases in cost production is not a trivial matter that can be ignored. There have been pressures from foreign countries such as Thailand, Vietnam, and Indonesia in the agricultural sector. Malaysia faces one major challenge: the cost of production, including wages and inputs, is relatively higher. (Rozhan 2019). Agricultural accounting is a minor standard, but it has a broad scope and a significant impact on agricultural businesses based on the accounting perspective, the MFRS141/IAS 41. The standard improves the transparency of the cost to replace capital (by allowing for depreciation and amortisation) and better reflects the productive lifespan of assets in agricultural operations. However, the application of MFRS 141 Agriculture is still relatively new in Malaysia, and a thorough examination of the literature indicates several gaps and deficiencies. This literature review is vital to support the study on Big Data-Fair Value Measurement Model of Biological Assets as the agricultural sector's involvement was recently popular. It might also offer some good ideas for handling problems involving the fair value measurement. Future studies will help the Ministry of Agriculture and Food Industries, agriculture sector workers, in terms of practical perspective. Therefore, the future result of the study suggests an improvement within the agriculture sector related to the treatment in their fair values, issues, and strategies.

Factor investing: A Bayesian hierarchical approach

This paper investigates the asset allocation problem when returns are predictable. We introduce a market-timing Bayesian hierarchical (BH) approach that adopts heterogeneous time-varying coefficients driven by lagged fundamental characteristics. Our approach estimates the conditional expected returns and residual covariance matrix jointly enables evaluating the estimation risk in the portfolio analysis. The hierarchical prior allows the modeling of different assets separately while sharing information across assets. We demonstrate the performance of the U.S. equity market, and our BH approach outperforms most alternative methods in terms of point prediction and interval coverage. In addition, the BH efficient portfolio achieves monthly returns of 0.92% and a significant Jensen’s alpha of 0.32% in sector investment over the past twenty years. We detect that technology, energy, and manufacturing are the most critical sectors in the past decade, and size, investment, and short-term reversal factors are heavily weighted in our portfolio. Furthermore, the stochastic discount factor constructed by our BH approach can explain many risk anomalies.

Blockchain-native mechanism supporting the circulation of complex physical assets

An increasing number of physical assets, such as academic certificates and credentials, are being represented in the form of digital assets. These assets always involve multiple statuses, rules, and complex associations. It is challenging to determine the transaction execution order using the existing blockchains because they lack the ability to record and execute associations between assets, which results in problems of inconsistency of assets, such as the loss of asset status changes and status conflict between transactions. This study proposes a blockchain-native mechanism supporting complex physical assets, including a novel digital asset model and transaction validity guarantee protocol. Under the premise of ensuring safety and performance, the proposed mechanism can fully describe different associations and their influence on the transaction execution order. This study builds a global deterministic transaction execution sequence that can be executed in parallel to guarantee the consistency of complex digital assets based on partial orders. Theoretical analysis of the proposed mechanism demonstrates that it can guarantee digital asset consistency and can protect against attacks such as reentrant and transaction sequence attacks. Furthermore, experiments show that the proposed mechanism can achieve a transaction execution speed of up to 10,000 transactions per second, and this speed can be further increased by increasing the number of CPU cores.