1,599 research outputs found

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

    Get PDF
    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    Innovation in Energy Security and Long-Term Energy Efficiency Ⅱ

    Get PDF
    The sustainable development of our planet depends on the use of energy. The increasing world population inevitably causes an increase in the demand for energy, which, on the one hand, threatens us with the potential to encounter a shortage of energy supply, and, on the other hand, causes the deterioration of the environment. Therefore, our task is to reduce this demand through different innovative solutions (i.e., both technological and social). Social marketing and economic policies can also play their role by affecting the behavior of households and companies and by causing behavioral change oriented to energy stewardship, with an overall switch to renewable energy resources. This reprint provides a platform for the exchange of a wide range of ideas, which, ultimately, would facilitate driving societies toward long-term energy efficiency

    Tradition and Innovation in Construction Project Management

    Get PDF
    This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings

    Current issues of the management of socio-economic systems in terms of globalization challenges

    Get PDF
    The authors of the scientific monograph have come to the conclusion that the management of socio-economic systems in the terms of global challenges requires the use of mechanisms to ensure security, optimise the use of resource potential, increase competitiveness, and provide state support to economic entities. Basic research focuses on assessment of economic entities in the terms of global challenges, analysis of the financial system, migration flows, logistics and product exports, territorial development. The research results have been implemented in the different decision-making models in the context of global challenges, strategic planning, financial and food security, education management, information technology and innovation. The results of the study can be used in the developing of directions, programmes and strategies for sustainable development of economic entities and regions, increasing the competitiveness of products and services, decision-making at the level of ministries and agencies that regulate the processes of managing socio-economic systems. The results can also be used by students and young scientists in the educational process and conducting scientific research on the management of socio-economic systems in the terms of global challenges

    Systems of State-Owned Enterprises: from Public Entrepreneurship to State Shareholding

    Get PDF
    This thesis outlines a new analytical perspective on state ownership through the original concept of systems of state-owned enterprises (SOSOEs). It is argued that the SOSOEs concept adequately captures the evolution of state-owned enterprises (SOEs) in modern capitalist economies, challenging and enriching existing economic theories as well as contributing to reinstate the policy instrumentality of state ownership. The concept is defined from a comparative case study analysis of two distinct SOSOEs, operating within the same national context in different time periods. The first case concerns the Istituto per la Ricostruzione Industriale (IRI), Italy’s former and most relevant state holding company, that played a central role in the Country’s post-WWII economic development. This thesis advances an interpretation of IRI’s economic function based on an original empirical investigation of its archival and documentary sources, focusing on its main public policy missions and on its display of industrial entrepreneurship features. The second case examines the current Italian system of SOEs, assessing the still relevant presence of SOEs in the Italian national context and evaluating the overall governance of the system through a set of interviews with leading executives. Despite the similarity in size and sectoral diversification, the two SOSOEs differ significantly in terms of their operating configurations. In fact, they could be assimilated to two dichotomous ideal types: the IRI SOSOEs represents a template for the policy-oriented and dynamic ‘public entrepreneurship’ model, while the current Italian SOSOEs resembles the policy-neutral and passive ‘state shareholding’ variant. Implicit in these results is the opportunity for current SOSOEs to embrace a public entrepreneurship configuration, in order to exploit the full policy potential of state ownership in driving economic change. The thesis concludes with a proposal for reforming Italy’s current SOSOEs via the creation of a state holding company

    Concurrent Product and Supply Chain Architecture Design Considering Modularity and Sustainability

    Full text link
    Since sustainability is a growing concern, businesses aim to integrate sustainability principles and practices into product and supply chain (SC) architecture (SCA) design. Modular product architecture (MPA) is essential for meeting sustainability demands, as it defines detachable modules by selecting appropriate components from various potential combinations. However, the prevailing practice of MPA emphasizes architectural aspects over interface complexity and design production processes for the structural dimension, potentially impending manufacturing, assembly/disassembly, and recovery efficiency. Most MPA has been developed assuming equal and/or fixed relations among modules rather than configuring for SC effectiveness. Therefore, such methods cannot offer guidance on modular granularity and its impact on product and SCA sustainability. Additionally, there is no comparative assessment of MPA to determine whether the components within the configured modules could share multiple facilities to achieve economic benefits and be effective for modular manufacture and upgrade. Therefore, existing modular configuration fails to link modularization drivers and metrics with SCA, hampering economic design, modular recycling, and efficient assembly/disassembly for enhancing sustainability. This study focuses on the study of design fundamentals and implementation of sustainable modular drivers in coordination with SCA by developing a mathematical model. Here, the architectural and interface relations between components are quantified and captured in a decision structure matrix which acts as the foundation of modular clustering for MPA. Again, unlike previous design approaches focused only on cost, the proposed work considers facility sharing through a competitive analysis of commonality and cost. It also evaluates MPA's ease of disassembly and upgradeability by a comparative assessment of different MPA to enhance SCA sustainability. The primary focus is concurrently managing the interdependency between MPA and SCA by developing mathematical models. Consistent with the mathematical model, this thesis also proposes better solution approaches. In summary, the proposed methods provide a foundation for modeling the link between product design and SC to 1) demonstrate how sustainable modular drivers affect the sustainability performance, 2) evaluate the contribution of modularity to the reduction of assembly/disassembly complexity and cost, 3) develop MPA in coordination with SC modularity by trading off modular granularity, commonality, and cost, and 4) identify a sustainable product family for combined modularity considering the similarity of operations, ease of disassembly and upgradability in SCA. Using metaheuristic algorithms, case studies on refrigerators showed that MPA and its methodology profoundly impact SCA sustainability. It reveals that interactions between components with levels based on sustainable modular drivers should be linked with modular granularity for SCA sustainability. Another key takeaway is that instead of solely focusing on cost, facility sharing and ensuring ease of disassembly and upgradeability can help to reap sustainability benefits

    Development and Application of Suspect and Nontarget Screening to Characterize Organic Micropollutants in Aquatic Environments of New York State

    Get PDF
    Organic micropollutants (OMPs) have presented a global challenge to water resources management due to concerns over their adverse impacts on aquatic biota and human health at low exposure concentrations (e.g., at ng/L to μg/L levels in aquatic systems). OMPs encompass an extensive array of synthetic organic compounds (e.g., pharmaceuticals, pesticides, personal care products, household chemicals, industrial additives) and their transformation products. My research has been centered around establishing analytical methods based on liquid chromatography-high-resolution mass spectrometry (LC-HRMS), with a focus on the development and application of suspect and nontarget screening workflows for the identification and prioritization of OMPs in inland lakes, streams, and urban wastewater in New York State. In Chapter 1, I collaborated with volunteers from the Citizens Statewide Lake Assessment Program and scientists at the Upstate Freshwater Institute to conduct the first statewide investigation of OMP occurrence in New York inland lakes. Through this project, I developed a suspect screening method based on LC-HRMS to identify and quantify 65 OMPs in 314 lake water samples collected by volunteers from 111 lakes, ponds, and reservoirs across the state. I also performed partial least squares regression and multiple linear regression analyses to prioritize total dissolved nitrogen, specific conductance, and a wastewater-derived fluorescent organic matter component as the best combination of explanatory predictors for the inter-lake variability in OMP occurrence patterns. I further applied the exposure-activity ratio approach to estimate the potential for biological effects associated with OMPs. My work demonstrated that engaging an established network of citizen volunteers offers a viable approach to increasing the spatiotemporal coverage of OMP monitoring while raising public awareness of their prevalence. In Chapter 2, I collaborated with Drs. Christa Kelleher and Rebecca Schewe to investigate the occurrence patterns of OMPs in streams draining mixed-use watersheds in central New York. I combined the use of polar organic chemical integrative samplers (POCIS) with suspect screening and nontarget screening based on LC-HRMS to identify and quantify 133 OMPs in samples collected from 20 stream sites over two sampling seasons. I also performed hierarchical clustering to establish the co-occurrence profiles of OMPs in connection with watershed attributes indicative of anthropogenic influences. I further evaluated the feasibility of deploying POCIS for estimating daily average loads of OMPs and their potential for biological effects in streams via screening-level risk assessments. My work supported the prospect of combining passive sampling with high-resolution accurate mass screening for the multi-watershed characterization of OMP contamination status in streams. In Chapter 3, I collaborated with colleagues from the School of Public Health to pursue one of the earliest wastewater-based epidemiology studies on population-level substance use during the COVID-19 pandemic. I developed and validated an online solid-phase extraction method for sample preconcentration before LC-HRMS analyses to achieve rapid screening of health and lifestyle-related substances in urban wastewater. I applied this method to quantify the levels of 26 pharmaceuticals and lifestyle chemicals in wastewater influent samples collected from six sewersheds in central New York over a period spanning the rising and falling of COVID-19 prevalence. I back-calculated the population-level consumption rates of antidepressants, antiepileptics, antihistamines, antihypertensives, and central nervous system stimulants and further identified their co-variation with disparities in household income, marital status, and/or age of the contributing populations as well as the detection frequency of SARS-CoV-2 RNA in wastewater and the COVID-19 test positivity within the sewersheds. My work highlighted the utility of high-throughput wastewater analysis for assessing substance use patterns during a public health crisis such as COVID-19
    corecore