2,397 research outputs found
Spatial Dynamic Modeling and Urban Land Use Transformation:
Assessing the economic impacts of urban land use transformation has become complex and acrimonious. Although community planners are beginning to comprehend the economic trade-offs inherent in transforming the urban fringe, they find it increasingly difficult to analyze and assess the trade-offs expediently and in ways that can influence local decisionmaking. New and sophisticated spatial modeling techniques are now being applied to urban systems that can quickly assess the probable spatial outcomes of given communal policies. Applying an economic impact assessment to the probable spatial patterns can provide to planners the tools needed to quickly assess scenarios for policy formation that will ultimately help inform decision makers. This paper focuses on the theoretical underpinnings and practical application of an economic impact analysis submodel developed within the Land use Evolution and Impact Assessment Modeling (LEAM) environment. The conceptual framework of LEAM is described, followed by an application of the model to the assessment of the cost of urban sprawl in Kane County, Illinois. The results show the effectiveness of spatially explicit modeling from a theoretical and a practical point of view. The agent-based approach of spatial dynamic modeling with a high spatial resolution allows for discerning the macro-level implications of micro-level behaviors. These phenomena are highlighted in the economic submodel in the discussion of the implications of land use change decisions on individual and communal costs; low-density development patterns favoring individual behaviors at the expense of the broader community.
Feasibility of Warehouse Drone Adoption and Implementation
While aerial delivery drones capture headlines, the pace of adoption of drones in warehouses has shown the greatest acceleration. Warehousing constitutes 30% of the cost of logistics in the US. The rise of e-commerce, greater customer service demands of retail stores, and a shortage of skilled labor have intensified competition for efficient warehouse operations. This takes place during an era of shortening technology life cycles. This paper integrates several theoretical perspectives on technology diffusion and adoption to propose a framework to inform supply chain decision-makers on when to invest in new robotics technology
Contract Aware Components, 10 years after
The notion of contract aware components has been published roughly ten years
ago and is now becoming mainstream in several fields where the usage of
software components is seen as critical. The goal of this paper is to survey
domains such as Embedded Systems or Service Oriented Architecture where the
notion of contract aware components has been influential. For each of these
domains we briefly describe what has been done with this idea and we discuss
the remaining challenges.Comment: In Proceedings WCSI 2010, arXiv:1010.233
A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)
In the 1990s, Agent-Based Modeling (ABM) began gaining popularity and represents a departure from the more classical simulation approaches. This departure, its recent development and its increasing application by non-traditional simulation disciplines indicates the need to continuously assess the current state of ABM and identify opportunities for improvement. To begin to satisfy this need, we surveyed and collected data from 279 articles from 92 unique publication outlets in which the authors had constructed and analyzed an agent-based model. From this large data set we establish the current practice of ABM in terms of year of publication, field of study, simulation software used, purpose of the simulation, acceptable validation criteria, validation techniques and complete description of the simulation. Based on the current practice we discuss six improvements needed to advance ABM as an analysis tool. These improvements include the development of ABM specific tools that are independent of software, the development of ABM as an independent discipline with a common language that extends across domains, the establishment of expectations for ABM that match their intended purposes, the requirement of complete descriptions of the simulation so others can independently replicate the results, the requirement that all models be completely validated and the development and application of statistical and non-statistical validation techniques specifically for ABM.Agent-Based Modeling, Survey, Current Practices, Simulation Validation, Simulation Purpose
Spatial dynamic modeling and urban land use transformation : an ecological simulation approach to assessing the costs of urban sprawl
Assessing the economic impacts of urban land use transformation has become complex and acrimonious. Although community planners are beginning to comprehend the economic trade-offs inherent in transforming the urban fringe, they find it increasingly difficult to analyze and assess the trade-offs expediently and in ways that can influence local decisionmaking. New and sophisticated spatial modeling techniques are now being applied to urban systems that can quickly assess the probable spatial outcomes of given communal policies. Applying an economic impact assessment to the probable spatial patterns can provide to planners the tools needed to quickly assess scenarios for policy formation that will ultimately help inform decision makers. This paper focuses on the theoretical underpinnings and practical application of an economic impact analysis submodel developed within the Land use Evolution and Impact Assessment Modeling (LEAM) environment. The conceptual framework of LEAM is described, followed by an application of the model to the assessment of the cost of urban sprawl in Kane County, Illinois. The results show the effectiveness of spatially explicit modeling from a theoretical and a practical point of view. The agent-based approach of spatial dynamic modeling with a high spatial resolution allows for discerning the macro-level implications of micro-level behaviors. These phenomena are highlighted in the economic submodel in the discussion of the implications of land use change decisions on individual and communal costs; low-density development patterns favoring individual behaviors at the expense of the broader community
Conformance Checking Based on Multi-Perspective Declarative Process Models
Process mining is a family of techniques that aim at analyzing business
process execution data recorded in event logs. Conformance checking is a branch
of this discipline embracing approaches for verifying whether the behavior of a
process, as recorded in a log, is in line with some expected behaviors provided
in the form of a process model. The majority of these approaches require the
input process model to be procedural (e.g., a Petri net). However, in turbulent
environments, characterized by high variability, the process behavior is less
stable and predictable. In these environments, procedural process models are
less suitable to describe a business process. Declarative specifications,
working in an open world assumption, allow the modeler to express several
possible execution paths as a compact set of constraints. Any process execution
that does not contradict these constraints is allowed. One of the open
challenges in the context of conformance checking with declarative models is
the capability of supporting multi-perspective specifications. In this paper,
we close this gap by providing a framework for conformance checking based on
MP-Declare, a multi-perspective version of the declarative process modeling
language Declare. The approach has been implemented in the process mining tool
ProM and has been experimented in three real life case studies
Stylistic Creativity in the Utilization of Management Tools
We analyze the role of management instruments in the development of collective activity and in the dynamics of organization, recurring to pragmatic and semiotic theories. In dualist representation-based theories (rationalism, cognitivism), instruments are seen as symbolic reflections of situations, which enable actors to translate their complex concrete activities into computable models. In interpretation-based theories (pragmatism, theory of activity, situated cognition), instruments are viewed as signs interpreted by actors to make sense of their collective activity, in an ongoing and situated manner. Instruments combine objective artefacts and interpretive schemes of utilization. They constrain interpretation and utilization, but do not completely determine them: they define genus (generic classes) of collective activity, but they leave space for individual or local interpretive schemes and stylistic creation in using them. A major part of organizational dynamics takes place in the permanent interplay between instrumental genus and styles. Whereas representation-based theories can be acceptable approximations in stable and reasonably simple organizational settings, interpretation-based theories make uncertain and complex situations more intelligible. They view emotions and creativity as a key part of the interpretive process, rather than as external biases of a rational modelling process. For future research, we wish to study how interpretation-based theories should impact managerial practices and improve, not only intelligibility, but also actionability of instruments and situations.Collective Activity; Genus; Instruments; Interpretation; Management Instruments; Performance Management; Pragmatism; Semiotics; Style
Multilateral Transparency for Security Markets Through DLT
For decades, changing technology and policy choices have worked to fragment securities markets, rendering them so dark that neither ownership nor real-time price of securities are generally visible to all parties multilaterally. The policies in the U.S. National Market System and the EU Market in Financial Instruments Directiveâ together with universal adoption of the indirect holding systemâ have pushed Western securities markets into a corner from which escape to full transparency has seemed either impossible or prohibitively expensive. Although the reader has a right to skepticism given the exaggerated promises surrounding blockchain in recent years, we demonstrate in this paper that distributed ledger technology (DLT) contains the potential to convert fragmented securities markets back to multilateral transparency.
Leading markets generally lack transparency in two ways that derive from their basic structure: (1) multiple platforms on which trades in the same security are matched have separate bid/ask queues and are not consolidated in real time (fragmented pricing), and (2) highspeed transfers of securities are enabled by placing ownership of the securities in financial institutions, thus preventing transparent ownership (depository or street name ownership). The distributed nature of DLT allows multiple copies of the same pricing queue to be held simultaneously by a large number of order-matching platforms, curing the problem of fragmented pricing. This same distributed nature of DLT would allow the issuers of securities to be nodes in a DLT network, returning control over securities ownership and transfer to those issuers and thus, restoring transparent ownership through direct holding with the issuer.
A serious objection to DLT is that its latency is very highâwith each Bitcoin blockchain transaction taking up to ten minutes. To remedy this, we first propose a private network without cumbersome proof-of-work cryptography. Second, we introduce into our model the quickly evolving technology of âlightning networks,â which are advanced two-layer off-chain networks conducting high-speed transacting with only periodic memorialization in the permanent DLT network. Against the background of existing securities trading and settlement, this Article demonstrates that a DLT network could bring multilateral transparency and thus represent the next step in evolution for markets in their current configuration
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