Non-homogeneous Information Research Articles

A Novel Early Warning Method for Handling Non-Homogeneous Information

Early warnings are an indispensable part of emergency management, which is a powerful way to eliminate or reduce the negative impacts caused by emergencies in advance. Early warning problems have been discussed from different perspectives and have obtained fruitful results. Information plays a critical role in all kinds of decision problems, with no exception for the early warning problem. There are various information types related to emergencies in real-world situations; however, existing early warning studies only considered a single information type, which might not describe the problem properly and comprehensively. To enrich existing early warning studies, a novel early warning method considering non-homogeneous information together with experts’ hesitation is proposed, in which numerical values, interval values, linguistic terms, and hesitant fuzzy linguistic terms are considered. To facilitate the computations with non-homogeneous information, a transformation process needs to be conducted. On such a basis, a fuzzy TOPSIS method based on alpha-level sets is employed to handle the transformed fuzzy information due to its superiority in obtaining information and its capacity to contain as much information as possible during the early warning process. Additionally, two different options are provided to analyze the status and tendency of early warning objects. Finally, an illustrative example about early warnings about landslides and a related comparison are conducted to demonstrate the novelty, superiority, and feasibility and validity of the proposed method.

Accounting Disclosure Practices – An Over View

The accounting principles consist of both concepts and conventions. Among different conventions, the disclosure convention is the most important one. The information should be presented in such a manner that it can be easily understood by a person of average knowledge and prudence. The Company Act 1956 not only requires that Income Statement and Balance Sheet of a company must give prescribed forms in which these statements are to be prepared. In recent years, many business enterprises have broadened the scope of their activities to different industries foreign counties and market. Due to the growth of diversified business and expansion of firms into foreign market, consolidated information becomes non-homogeneous information. The problems of disclosure can be resolved in the light of the objectives of financing reporting. The methods of disclosure include Income Statement, balance Sheet, Statement of Retained earnings, and Funds Flow statement.

103P - Contrast-enhanced CT-based textural parameters as potential prognostic factors of survival for colorectal cancer patients receiving targeted therapy

BackgroundTexture analysis is used to assess the homogeneous or nonhomogenous information of the selected regions, and provides many quantitative and semiquantitative parameters that are able to closely reflect the characteristics of cancer lesions. This study was designed to estimate the clinical significance of the contrast-enhanced computed tomograpgy (CT) textural features for prediction of survival in colorectal cancer (CRC) patients receiving targeted therapy (bevacizumab and cetuximab). MethodsThe LifeX software was used to extract the textural parameters of the tumor lesions in the contrast-enhanced CT. Univariate and multivariate analyses using the Cox proportional hazards model were performed to assess the prognostic value of textural parameters. ResultsEighty CRC patients receiving targeted therapy (bevacizumab 42; cetuximab 38) were included. In the multivariate analysis, 8 textural parameters were revealed to be independent predictors (p < 0.05) of progression-free survival (PFS) and overall survival (OS), including Skewness, Kurtosis, Homogeneity, Energy and Entropy of Gray-level co-occurrence matrix (GLCM), Long-run emphasis (LRE), Long-run high gray-level emphasis (LRHGE), and Contrast. Furthermore, Sphericity, Compacity, Long-run low gray-level emphasis (LRLGE), Low gray-level zone emphasis (LGZE) and Short-zone low gray-level emphasis (SZLGE) were show to be significantly associated with PFS, while Entropy-Histogram and Energy-Histogram, Dissimilarty, Short-run emphasis (SRE), Short-run low gray-level emphasis (SRLGE), Run percentage (RP), Long-zone emphasis (LZE), Long-zone low gray-level emphasis (LZLGE) and Long-zone high gray-level emphasis (LZHGE) were significantly associated with OS. ConclusionsIn conclusion, our study provides preliminary evidences that several radiomic parameters of tumor lesions derived from CT images were prognostic factors and predictive markers for CRC patients who are candidates for targeted therapy (bevacizumab and cetuximab). Legal entity responsible for the studyThe authors. FundingHas not received any funding. DisclosureAll authors have declared no conflicts of interest.

Industrial applications of big data in disruptive innovations supporting environmental reporting

Abstract Disruptive innovations are usually identified as ideas that are created ‘outside the box’. They are expected to fundamentally change existing business models and processes founded on technological applications. Disruptive innovations can be challenging to define. Information technology (IT) solutions focus on collecting, processing, and reporting different types of data. Commonly, is the solutions are expected (in cybernetics or self-regulating processes) to provide feedback to original processes and to steer them based on the data. To achieve continuous improvement with regard to environmental responsibility and profitability, new thinking and, in particular, accurate and reliable data are needed for decision-making. Very large data storages, known as big data, contain an increasing mass of different types of homogenous and non-homogenous information, as well as extensive time-series. New, innovative algorithms are required to reveal relevant information and opportunities hidden in these data storages. Global environmental challenges and zero-emission responsible production issues can only be solved using relevant and reliable continuous data as the basis. The final goal should be the creation of scalable environmental solutions based on disruptive innovations and accurate data. The aim of this paper is to determine the explicit steps for replacing silo-based reporting with company-wide, refined information, which enables decision-makers in all industries the chance to make responsible choices.

A Multi-Criteria 2-Tuple Linguistic Group Decision-Making Method Based on TODIM for Cholecystitis Treatments Selection

Cholecystitis is a common disease with a high incidence, and attracts much attention. It not only harms human health, but also affects quality of work and life. Therefore, the choice of a suitable treatment is badly important for patients. In this paper, a novel selection model of treatments for cholecystitis based on hybrid multiple-criteria group decision-making (MCGDM), which is helpful to choose the most suitable treatment in the case of asymmetric information between doctors and patients. Subsequently, subjective and objective criteria are comprehensively taken into account in the index system of the selection model for cholecystitis, and combines 2-tuple linguistic with quantitative data analysis. Besides, the evaluation information obtained from the patient's conditions, the treatment and the hospital's medical status, etc., including real numbers, interval numbers, and linguistic labels with multi-granularity, is more complete and real. And the 2-tuple linguistic model is used to unify the non-homogeneous information, so the treatment selection is accurate and reliable. Simultaneously, for the unknown index and criteria weight, the improved entropy weight method and the BWM (best-worst-method) are utilized to figure out the index weight and criteria weight, respectively. Further, TODIM (an acronym in Portuguese for interactive and multi-criteria decision-making model) method based on the prospect theory is applied to solve the prioritization of cholecystitis treatments, and give full consideration to the decision maker of risk aversion. Eventually, an empirical study of treatment selection for cholecystitis is conducted. Sensitivity analysis and comparative analysis indicate that the proposed selection model of treatments for cholecystitis patients is reliable and effective.

Fuzzy Techniques for Decision Making

This book contains the successful invited submissions [1–21] to a Special Issue of Symmetry on the subject area of “Fuzzy Techniques for Decision Making”.[...]

Managing Non-Homogeneous Information and Experts’ Psychological Behavior in Group Emergency Decision Making

After an emergency event (EE) happens, emergency decision making (EDM) is a common and effective way to deal with the emergency situation, which plays an important role in mitigating its level of harm. In the real world, it is a big challenge for an individual emergency manager (EM) to make a proper and comprehensive decision for coping with an EE. Consequently, many practical EDM problems drive group emergency decision making (GEDM) problems whose main limitations are related to the lack of flexibility in knowledge elicitation, disagreements in the group and the consideration of experts’ psychological behavior in the decision process. Hence, this paper proposes a novel GEDM approach that allows more flexibility for preference elicitation under uncertainty, provides a consensus process to avoid disagreements and considers experts’ psychological behavior by using the fuzzy TODIM method based on prospect theory. Eventually, a group decision support system (GDSS) is developed to support the whole GEDM process defined in the proposed method demonstrating its novelty, validity and feasibility.

An integrated fuzzy MCDM approach for supplier evaluation and selection

A fuzzy multi-criteria group decision making approach that makes use of quality function deployment (QFD), fusion of fuzzy information and 2-tuple linguistic representation model is developed for supplier selection. The proposed methodology seeks to establish the relevant supplier assessment criteria while also considering the impacts of inner dependence among them. Two interrelated house of quality matrices are constructed, and fusion of fuzzy information and 2-tuple linguistic representation model are employed to compute the weights of supplier selection criteria and subsequently the ratings of suppliers. The proposed method is apt to manage non-homogeneous information in a decision setting with multiple information sources. The decision framework presented in this paper employs ordered weighted averaging (OWA) operator, and the aggregation process is based on combining information by means of fuzzy sets on a basic linguistic term set. The proposed framework is illustrated through a case study conducted in a private hospital in Istanbul.

An extension of MACBETH method for a fuzzy environment to analyze alternatives in reverse logistics for automobile tire wastes

Waste tire related environmental problems and its recycling alternatives have been a major issue nowadays because of their complex combination of very different materials, which include several rubbers, carbon blacks, steel cord and other organic and inorganic minor components. The most important problem in the scrap tire recycling program is the type of product recovery option because there are few specific data available. Multi-criteria decision analysis (MCDA) was used to assess options in reverse logistics for waste tire. MCDA is a widely used decision methodology that considers conflicting systems of criteria. However, many real-world decision problems involve ambiguity and imprecise information. In this study, the analysis has been undertaken using an extended version of MACBETH methodology to take into account the imprecise and linguistic assessments provided by a decision-maker by integrating the 2-tuple model dealing with non-homogeneous information data. The proposed fuzzy MACBETH method has been applied to a real case related to the automobile tire waste to elucidate its details.

The Central Limit Theorem for th-Order Nonhomogeneous Markov Information Source

We prove a central limit theorem for th-order nonhomogeneous Markov information source by using the martingale central limit theorem under the condition of convergence of transition probability matrices for nonhomogeneous Markov chain in Cesaro sense.

A new multi-criteria approach dealing with dependent and heterogeneous criteria for end-of-life product strategy

Abstract Strict regulations, technological growth and environmental impacts are influent factors in the choice of the best strategy for end-of-life (EOL) product. In fact, EOL is one stage of the life cycle having gained the attention of the market. This study proposes an integrated methodology that relies on multi-criteria analysis and takes into account both quantitative and qualitative criteria while respecting mutual interactions between them. This has been performed by introducing, on the one hand, the 2-tuple linguistic representation model dealing with non-homogeneous information data, and on the other hand, the Choquet integral interaction modeling between criteria into the PROMETHEE method. Although it has been developed for EOL selection problems, the proposed method fits to all kinds of decision-making problems with heterogeneous information. As this work demonstrates, this multi-criteria analysis approach can offer a technical-scientific decision making support tool in the EOL product sector. We also perform a sensitivity to reveal the effect of the subjective parameter variations on the originally resulted ranking.

A new methodology for fuzzy multi-attribute group decision making with multi-granularity and non-homogeneous information

The aim of this paper is to develop a new methodology for solving fuzzy multi-attribute group decision making problems with non-homogeneous information, including multi-granular linguistic term sets, fuzzy numbers, interval values and real numbers. In this methodology, different distances are defined to measure differences between alternatives and the ideal solution as well as the negative ideal solution. A relative closeness method is developed by introducing the multi-attribute ranking index based on the particular measure of closeness to the IS. The proposed method determines a compromise solution for the group, providing a maximum "group utility" for the "majority" and a minimum of an individual regret for the "opponent". The implementation process, effectiveness and feasibility of the method proposed in this paper are illustrated with a real example of the missile weapon system design project selection.

Some Research on Shannon–McMillan Theorem for mth-Order Nonhomogeneous Markov Information Source

In this article, a class of strong limit theorems for relative entropy density of arbitrary stochastic sequence, expressed by inequalities, are obtained by comparing arbitrary dependent distribution with and the mth-order Markov distribution on probability space. As corollaries, some Shannon–McMillan theorems of mth-order nonhomogeneous Markov information source are obtained. Some results of nonhomogeneous Markov information source obtained are generalized.

A group decision-making aggregation process

Within the frame of decision aid literature, decision making problems with multiple sources of information have drawn the attention of researchers from a wide spectrum of disciplines. In decision situations with multiple individuals, each one has his own knowledge of the decision problem alternatives. The use of information assessed in different domains is not a seldom situation. This non-homogeneous information can be represented by values belonging to domains with different nature as linguistic, numerical and interval valued or can be values assessed in label sets with different granularity and multigranular linguistic information. Decision processes for solving these problems are composed by two steps: aggregation and exploitation. The main problem to deal with non-homogeneous contexts is the aggregation manner of the information assessed in these contexts. The purpose of this paper is to address this problem and establish a procedure to aggregate individual opinions into a common decision to deal with non-homogeneous contexts. This process combines at the same time numerical, interval valued and linguistic information. Since subjectivity, vagueness and imprecision enter into the assessments of experts, the 2-tuple fuzzy linguistic representation model is used to deal with the fuzziness of human judgment.

Managing non-homogeneous information in group decision making

Within the frame of decision aid literature, decision making problems with multiple sources of information have drawn the attention of researchers from a wide spectrum of disciplines. In decision situations with multiple individuals, each one has his own knowledge on the alternatives of the decision problem. The use of information assessed in different domains is not a seldom situation. This non-homogeneous information can be represented as values belonging to domains with different nature as linguistic, numerical and interval valued or can be values assessed in label sets with different granularity, multi-granular linguistic information. Decision processes for solving these problems are composed by two phases: aggregation and exploitation. The main problem to deal with non-homogeneous contexts is how to aggregate the information assessed in these contexts? In this paper, taking as base the 2-tuple fuzzy linguistic representation model we shall develop an aggregation process for dealing with non-homogeneous contexts. In first place, we shall develop an aggregation process for combining numerical, interval valued and linguistic information, afterwards we shall propose different extensions of this process to deal with contexts in which can appear other type of information as intuitionistic fuzzy sets or multi-granular linguistic information.

Modelling change in state of complex ecological systems in space and time: An application to sustainable grazing management

Meeting the challenge of sustainable development requires substantial advances in understanding of the interaction of natural and human systems. The emerging ecosystem management paradigm of multiple stable states, non-linear systems behaviour, discontinuous change, self-organisation and multiple development pathways has major implications for when and how change in complex systems occurs and how it can be managed. It also poses considerable challenges for modelling the structure and function of natural and human management systems, including fundamental constraints relating to: scaling mismatches, synthesis of non-homogeneous information, multiscaled system interactions, complex management systems, uncertainty in causal relationships, assessment of trade-offs, and validation. This paper examines how a decision support system (DSS) for sustainable grazing management, called Landassess DSS, attempts to deal with some of these issues through an integrated systems approach to DSS development. This approach utilises object-oriented techniques, knowledge-based systems, geographical information systems (GIS), and a state-and-transition model framework to model the critical change processes. It provides for the identification of the major driving factors and constraints to change in complex resource management systems, as well as the assessment of the likely trade-offs between resource sustainability and economic production at a scale relevant to management decision-making (i.e., paddock or property).

13. Applications of the theory of blown‐ups to weather forecasting

The nonhomogeneous information is applied to the study of sudden and severe weather processes in this paper, based on the theory of blown‐ups (OuYang, 1994). Severe weather processes, such as torrential rain and severe convection, are clarified first by using the nonhomogeneous parameters in the spring in Hubei Province, and second by combining with the severe convection forecasting criteria. We can distinguish the severe convective weather processes and forecast the short‐range severe convective weather by using this theory in the spring in Hubei province. After practical applications from March 15 to May 15 in 1995, it showed that the forecast accuracy was satisfactory.

Nonhomogeneous Expectations and Information in the Capital Asset Market

Nonhomogeneous Expectations and Information in the Capital Asset Market