Does AHP help us make a choice? - An experimental evaluation

In this paper, we use experimental economics methods to test how well Analytic Hierarchy Process (AHP) fares as a choice support system in a real decision problem. AHP provides a ranking that we statistically compare with three additional rankings given by the subjects in the experiment: one at the beginning, one after providing AHP with the necessary pair-wise comparisons and one after learning the ranking provided by AHP. While the rankings vary widely across subjects, we observe that for each individual all four rankings are similar. Hence, subjects are consistent and AHP is, for the most part, able to replicate their rankings. Furthermore, while the rankings are similar, we do find that the AHP ranking helps the decision-makers reformulate their choices by taking into account suggestions made by AHP.Decision analysis, Multiple Criteria Decision Aid, Analytic Hierarchy Process (AHP)

Modeling Vocal Fold Motion with a New Hydrodynamic Semi-Continuum Model

Vocal fold (VF) motion is a fundamental process in voice production, and is also a challenging problem for direct numerical computation because the VF dynamics depend on nonlinear coupling of air flow with the response of elastic channels (VF), which undergo opening and closing, and induce internal flow separation. A traditional modeling approach makes use of steady flow approximation or Bernoulli's law which is known to be invalid during VF opening. We present a new hydrodynamic semi-continuum system for VF motion. The airflow is modeled by a quasi-one dimensional continuum aerodynamic system, and the VF by a classical lumped two mass system. The reduced flow system contains the Bernoulli's law as a special case, and is derivable from the two dimensional compressible Navier-Stokes equations. Since we do not make steady flow approximation, we are able to capture transients and rapid changes of solutions, e.g. the double pressure peaks at opening and closing stages of VF motion consistent with experimental data. We demonstrate numerically that our system is robust, and models in-vivo VF oscillation more physically. It is also much simpler than a full two-dimensional Navier-Stokes system.Comment: 27 pages,6 figure

The Low Adhesion Problem due to Leaf Contamination in the Wheel/Rail Contact: Bonding and Low Adhesion Mechanisms

Autumn leaves often cause low adhesion problems for train operations, leading to station overruns and signals passed at danger (SPADS). The aim of this paper was to review operational data and research methods to assess the current understanding of the problem and formulate hypotheses for the causes. Incident analysis showed the relatively high possibility of incidents between the hours of 05:00 – 10:00 and 20:00 – 24:00, suggesting the dew effect was important. This result corresponds to the knowledge that wet leaves in the contact area produce very low friction coefficients, below 0.1. Current mitigation methods, such as sanding, seem inadequate to remove the leaf films completely. To explain the bonding mechanism between the leaf film and the rail, a laboratory-based model and a field-based model were developed based on previous studies. Moreover, key parameters for a strong bond formation were identified, which are iron oxide, temperature, pressure and leaf material. The research gaps were identified by a paper grading method, and several hypotheses for bonding mechanisms and low adhesion mechanisms were proposed, such as sub- or super critical water and pectin gel

Does AHP help us make a choice? - An experimental evaluation

Author's pre-print version dated 2. August 2010 deposited in Munich Personal RePEc Archive. Final version published by Palgrave Macmillan; available online at http:// www.palgrave-journals.com/In this paper, we use experimental economics methods to test how well Analytic Hierarchy Process (AHP) fares as a choice support system in a real decision problem. AHP provides a ranking that we statistically compare with three additional rankings given by the subjects in the experiment: one at the beginning, one after providing AHP with the necessary pair-wise comparisons and one after learning the ranking provided by AHP. While the rankings vary widely across subjects, we observe that for each individual all four rankings are similar. Hence, subjects are consistent and AHP is, for the most part,able to replicate their rankings. Furthermore, while the rankings are similar, we do find that the AHP ranking helps the decision makers reformulate their choices by taking into account suggestions made by AHP

Development of the Shinshu University Online System of General Academic Resources (SOAR)

This paper discusses the development of the Shinshu University Online System of General Academic Resources (SOAR). As a participant in the 2006-2007 Cyber Science Infrastructure (CSI) development project of the National Institute of Informatics (NII), Shinshu University is seeking to develop SOAR as an integrated academic resource system. In addition to developing an environment for providing accesstothe latest academic resources within the university, SOAR is intended to promulgate university research results and research activities, both within Japan and around the world, to a broad audience. Specifically, this system achieves mutual coordination by linking e-journals and the Web of Science to the researcher directory and the institutional repository—two system cornerstones. SOAR can be regarded as a potential model for future academic-resource systems. Although the Institutional Repository (SOAR-IR) was developed using existing software, the Researcher Directory (SOARRD) is a new system based on XML technology.ArticleProgress in Informatics. 5:137-151 (2008)journal articl

Use of a novel coaxial guide needle-wire (GNW) combination system for computed tomography guided radiofrequency tumor ablation

We developed a novel coaxial system using a fine guide needle wire (GNW) to safely and easily place the radiofrequency needle under CT-guidance. The GNW consists of a fine needle (diameter, 21-gauge; length, 150 mm) and a wire (0.018 inch, 250 mm). An exclusive radiofrequency cannula (14-gauge; 160 mm) was also used. This system was used for the treatment of six hepatocellular carcinomas in six patients. All lesions were located deeper than 10 cm from the needle entry site. This system was useful in performing CT-guided RF ablation for deeply or precariously located liver lesions particularly in patients who are unable to hold their breath

Pseudogap of metallic layered nickelate R2-xSrxNiO4 (R=Nd, Eu) crystals measured using angle-resolved photoemission spectroscopy

We have investigated charge dynamics and electronic structures for single crystals of metallic layered nickelates, R2-xSrxNiO4 (R=Nd, Eu), isostructural to La2-xSrxCuO4. Angle-resolved photoemission spectroscopy on the barely-metallic Eu0.9Sr1.1NiO4 (R=Eu, x=1.1) has revealed a large hole surface of x2-y2 character with a high-energy pseudogap of the same symmetry and comparable magnitude with those of underdoped (x<0.1) cuprates, although the antiferromagnetic interactions are one order of magnitude smaller. This finding strongly indicates that the momentum-dependent pseudogap feature in the layered nickelate arises from the real-space charge correlation.Comment: 4 pages, 4 figures. Accepted in Physical Review Letter

Machine learning for multi-criteria inventory classification applied to intermittent demand

Multi-criteria inventory classification groups inventory items into classes, each of which is managed by a specific re-order policy according to its priority. However, the tasks of inventory classification and control are not carried out jointly if the classification criteria and the classification approach are not robustly established from an inventory-cost perspective. Exhaustive simulations at the single item level of the inventory system would directly solve this issue by searching for the best re-order policy per item, thus achieving the subsequent optimal classification without resorting to any multi-criteria classification method. However, this would be very time-consuming in real settings, where a large number of items need to be managed simultaneously. In this article, a reduction in simulation effort is achieved by extracting from the population of items a sample on which to perform an exhaustive search of best re-order policies per item; the lowest cost classification of in-sample items is, therefore, achieved. Then, in line with the increasing need for ICT tools in the production management of Industry 4.0 systems, supervised classifiers from the machine learning research field (i.e. support vector machines with a Gaussian kernel and deep neural networks) are trained on these in-sample items to learn to classify the out-of-sample items solely based on the values they show on the features (i.e. classification criteria). The inventory system adopted here is suitable for intermittent demands, but it may also suit non-intermittent demands, thus providing great flexibility. The experimental analysis of two large datasets showed an excellent accuracy, which suggests that machine learning classifiers could be implemented in advanced inventory classification systems

Maximally entangled mixed states of two qubits

We consider mixed states of two qubits and show under which global unitary operations their entanglement is maximized. This leads to a class of states that is a generalization of the Bell states. Three measures of entanglement are considered: entanglement of formation, negativity and relative entropy of entanglement. Surprisingly all states that maximize one measure also maximize the others. We will give a complete characterization of these generalized Bell states and prove that these states for fixed eigenvalues are all equivalent under local unitary transformations. We will furthermore characterize all nearly entangled states closest to the maximally mixed state and derive a new lower bound on the volume of separable mixed states