Rough Set Theory for Real Estate Appraisal: An Application to Directional District of Naples

This paper proposes an application of Rough Set Theory (RST) to the real estate field, in order to highlight its operational potentialities for mass appraisal purposes. RST allows one to solve the appraisal of real estate units regardless of the deterministic relationship between characteristics that contribute to the formation of the property market price and the same real estate prices. RST was applied to a real estate sample (office units located in Directional District of Naples) and was also integrated with a functional extension so-called Valued Tolerance Relation (VTR) in order to improve its flexibility. A multiple regression analysis (MRA) was developed on the same real estate sample with the aim to compare RST and MRA results. The case study is followed by a brief discussion on basic theoretical connotations of this methodology

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

From ERP to advanced resource planning: Improving the operational performance by getting the inputs right.

In this paper, we show that the planning and decision support capabilities of the MPC (Manufacturing Planning and Control) system, which forms the core of any ERP package, may be greatly enhanced by including an Advanced Resource Planning (ARP) module as an add-on at the midterm planning level. This ARP module enables to estimate the impact of variability, complexity and dynamic system behavior on key planning parameters. As such, it yields realistic information both for short-term planning purposes and for reliable lead time quotations. We show how dynamic behavior impacts the operational performance of a manufacturing system, and discuss the framework for incorporating the ARP module into the ERP system.Planning; Operational performance; Performance; International; Science;

Knowledge Management Activities and Strategic Planning Capability Development

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.While the strategic management literature extols the virtues of engaging in strategic planning for superior performance, how a dynamic strategic planning capability can be developed remains underexplored; a knowledge void addressed by the paper through applying knowledge-based theory. A mail survey was sent to high technology firms randomly sampled from the Kompass Directory of UK businesses. Firms were sampled at the SBU level, given the focus on strategic planning capability. An organization’s strategic planning capability derives from extensive information distribution and organizational memory. While learning values is non-significant, symbolic information use degrades the development of a strategic planning capability. By investigating the contributory activities that lead to strategic planning capability development, the findings establish how strategic planning materializes in organizations. Further, the differential effects found for knowledge management activities on strategic planning capability development extends empirical studies that suggest knowledge is always a central tenet of strategic planning. A set of key knowledge activities are identified that managers must address for strategic planning capability development: strategic planning routines and values of search, analysis, and assessment should be appropriately informed by investments in knowledge dissemination and memory on a continual basis. Meanwhile, information misuse compromises strategic planning capabilities and managers must protect against out-of-context or manipulated information from infiltrating into organizational memory. Despite the advent of the Knowledge-Based Theory and its core premise that capabilities derive from knowledge management activities, little research has been conducted into demonstrating the knowledge-based antecedents of a strategic planning capability

Characteristics of developed flexible polyurethane foams reinforced with coconut coir fibres and recycled tyres

Flexible Polyurethane (PU) foam is generally used in seat cushions of automotive seating for comfort and supporting the occupants. However, due to the demand for more comfortable compartment; seat cushions are now designed for better riding comfort and acoustic absorption which linked to the damping of foam. Incorporated treated coir fibres (F) and tyre particles (P) into polymeric material had improved the damping and strength of the material. In this research, flexible PU foams were reinforced with two fillers for the purpose of higher damping property and improve the mechanical strength. Five samples with 2.5wt% of filler loading were developed. The damping of samples was measured on sound absorption and vibration transmissibility test that generated at 1mm, 1.5mm, 0.1g, and 0.15g base excitation while their mechanical properties were examined through compression, tear resistance, and compression set. The morphology of samples was also observed by SEM in this research. The results showed that the foam composites produced have smaller cell size, in which the smallest was 840µm compared to 1290µm obtained in pure PU foam. The mechanical properties revealed that the strength of flexible PU foam increased with added treated coir fibres and recycled tyres. The best properties were shown in PU+2.5wt%(50F50P) which increased by 10.78% on the compressive modulus, 9.33% on the compressive strength, 14.49% on the static energy absorption, and 3.76% on the tear strength compared to pure PU foam. The sound absorption and vibration damping of the developed foams showed that more energy were absorbed and dissipated by these foams after fillers added. The PU+2.5wt%(80P20F) and PU+2.5wt%F presented an excellent sound absorption characteristics at 20mm and 40mm thickness, respectively, whereas PU+2.5wt%P, PU+2.5wt%(80P20F), and PU+2.5wt%(80F20P) showed higher vibration damping from the transmissibility test

Motion Planning of Uncertain Ordinary Differential Equation Systems

This work presents a novel motion planning framework, rooted in nonlinear programming theory, that treats uncertain fully and under-actuated dynamical systems described by ordinary differential equations. Uncertainty in multibody dynamical systems comes from various sources, such as: system parameters, initial conditions, sensor and actuator noise, and external forcing. Treatment of uncertainty in design is of paramount practical importance because all real-life systems are affected by it, and poor robustness and suboptimal performance result if it’s not accounted for in a given design. In this work uncertainties are modeled using Generalized Polynomial Chaos and are solved quantitatively using a least-square collocation method. The computational efficiency of this approach enables the inclusion of uncertainty statistics in the nonlinear programming optimization process. As such, the proposed framework allows the user to pose, and answer, new design questions related to uncertain dynamical systems. Specifically, the new framework is explained in the context of forward, inverse, and hybrid dynamics formulations. The forward dynamics formulation, applicable to both fully and under-actuated systems, prescribes deterministic actuator inputs which yield uncertain state trajectories. The inverse dynamics formulation is the dual to the forward dynamic, and is only applicable to fully-actuated systems; deterministic state trajectories are prescribed and yield uncertain actuator inputs. The inverse dynamics formulation is more computationally efficient as it requires only algebraic evaluations and completely avoids numerical integration. Finally, the hybrid dynamics formulation is applicable to under-actuated systems where it leverages the benefits of inverse dynamics for actuated joints and forward dynamics for unactuated joints; it prescribes actuated state and unactuated input trajectories which yield uncertain unactuated states and actuated inputs. The benefits of the ability to quantify uncertainty when planning the motion of multibody dynamic systems are illustrated through several case-studies. The resulting designs determine optimal motion plans—subject to deterministic and statistical constraints—for all possible systems within the probability space

Real-time Tactical and Strategic Sales Management for Intelligent Agents Guided By Economic Regimes

Many enterprises that participate in dynamic markets need to make product pricing and inventory resource utilization decisions in real-time. We describe a family of statistical models that address these needs by combining characterization of the economic environment with the ability to predict future economic conditions to make tactical (short-term) decisions, such as product pricing, and strategic (long-term) decisions, such as level of finished goods inventories. Our models characterize economic conditions, called economic regimes, in the form of recurrent statistical patterns that have clear qualitative interpretations. We show how these models can be used to predict prices, price trends, and the probability of receiving a customer order at a given price. These “regime†models are developed using statistical analysis of historical data, and are used in real-time to characterize observed market conditions and predict the evolution of market conditions over multiple time scales. We evaluate our models using a testbed derived from the Trading Agent Competition for Supply Chain Management (TAC SCM), a supply chain environment characterized by competitive procurement and sales markets, and dynamic pricing. We show how regime models can be used to inform both short-term pricing decisions and longterm resource allocation decisions. Results show that our method outperforms more traditional shortand long-term predictive modeling approaches.dynamic pricing;trading agent competition;agent-mediated electronic commerce;dynamic markets;economic regimes;enabling technologies;price forecasting;supply-chain

The developmental dynamics of terrorist organizations

We identify robust statistical patterns in the frequency and severity of violent attacks by terrorist organizations as they grow and age. Using group-level static and dynamic analyses of terrorist events worldwide from 1968-2008 and a simulation model of organizational dynamics, we show that the production of violent events tends to accelerate with increasing size and experience. This coupling of frequency, experience and size arises from a fundamental positive feedback loop in which attacks lead to growth which leads to increased production of new attacks. In contrast, event severity is independent of both size and experience. Thus larger, more experienced organizations are more deadly because they attack more frequently, not because their attacks are more deadly, and large events are equally likely to come from large and small organizations. These results hold across political ideologies and time, suggesting that the frequency and severity of terrorism may be constrained by fundamental processes.Comment: 28 pages, 8 figures, 4 tables, supplementary materia