Period disambiguation with MaxEnt model

Abstract. This paper presents our recent work on period disambiguation, the kernel problem in sentence boundary identification, with the maximum entropy (Maxent) model. A number of experiments are conducted on PTB-II WSJ corpus for the investigation of how context window, feature space and lexical information such as abbreviated and sentence-initial words affect the learning performance. Such lexical information can be automatically acquired from a training corpus by a learner. Our experimental results show that extending the feature space to integrate these two kinds of lexical information can eliminate 93.52% of the remaining errors from the baseline Maxent model, achieving an F-score of 99.8227%.

An Improved Corpus Comparison Approach to Domain Specific Term Recognition

PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20-22, 200

A GRP-basedHesitant Fuzzy Multiple Attribute Decision MakingMethod and Its Application to E-Commerce Risk Assessment

With respect to multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant fuzzy elements, the traditional grey relational projection (GRP) method is extended to solve multiple attribute decision making problems under hesitant fuzzy environment. Based on the hesitant fuzzy decision matrix provided by decision makers, all feasible alternatives are ranked according to the descending order of relative grey relational projections, and the most desirable alternative(s) should have the largest grey relational projection on positive ideal solution and the smallest grey relational projection on negative ideal solution. Finally, a numerical example of e-commerce risk assessment is given to illustrate the application of the proposed method

Fall Risk Assessments Based on Postural and Dynamic Stability Using Inertial Measurement Unit

Objectives: Slip and fall accidents in the workplace are one of the top causes of work related fatalities and injuries. Previous studies have indicated that fall risk was related to postural and dynamic stability. However, the usage of this theoretical relationship was limited by laboratory based measuring instruments. The current study proposed a new method for stability assessment by use of inertial measurement units (IMUs). Methods: Accelerations at different body parts were recorded by the IMUs. Postural and local dynamic stability was assessed from these measures and compared with that computed from the traditional method. Results: The results demonstrated: 1) significant differences between fall prone and healthy groups in IMU assessed dynamic stability; and 2) better power of discrimination with multi stability index assessed by IMUs. Conclusion: The findings can be utilized in the design of a portable screening or monitoring tool for fall risk assessment in various industrial settings

Analytical modeling of Lamb wave propagation in composite laminate bonded with piezoelectric actuator based on Mindlin plate theory

Dynamic analysis of plate structures based on the Mindlin plate theory has become one of the usual modeling methods for the structural health monitoring (SHM) of composite structures in recent years. Compared to the classical plate theory (CPT) based on Kirchhoff hypothesis, the Mindlin plate theory considers the influence of transverse shear deformation and moment of inertia on displacements. Thus it is more suitable for dynamic analysis of composite laminate with low transverse shear stiffness and large transverse shear deformation. Combining the adhesive layer coupling model of the piezoelectric actuator with the Mindlin plate theory, the dispersion curve of Lamb wave in any direction and mechanical parameters of any point in the composite are obtained, and thus after the substitution of boundary condition, the modeling of piezoelectric wafer excited Lamb wave propagating in composite laminate is realized. The validation experiment is performed on a carbon fiber composite laminate. It proves that the analytical modeling effectively reflects the propagation characteristics of Lamb wave in composite laminate and promotes the engineering application of SHM

Data Files: Bi-Objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity

This data supports the research project Bi-objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity and a final report published on NITC’s website. Dataset collected through multiple sources and organized into different formats including CSV format, JSON format, shapefile and code repository. Context: The research project develops a bi-objective model that aims to help transit agencies to optimally deploy BEB while considering both capital investment and environmental equity. The unique spatio-temporal characteristic of BEB system, charging limitations (on-route and in-depot charging), and operational constraints are also considered and incorporated into the model

Measuring the Quality of Service for High Occupancy Toll Lanes Operations

AbstractHigh Occupancy Toll (HOT) lane systems have been proposed as one of the most applicable countermeasures against freeway congestion. Under HOT lane operational scheme, a Single Occupancy Vehicle (SOV) can pay to access HOT lanes in exchange of travel time saving or enhanced trip reliability when excess HOT lane capacity is available. Compared with regular freeway facilities, HOT lane systems demonstrate unique characteristics in facility capacity, driver behavior, travel pattern, demand modeling, and trip reliability. This study aims at conducting a comprehensive performance analysis on two representative HOT lane systems of State Route 167 in Washington and I-394 MnPass in Minnesota based on the field data collected from traffic sensors and transponder toll tags. Performance measurements are proposed to quantify the quality of service for HOT lane operations. Three critical issues are addressed in this study: 1) the speed-flow relationships in HOT lane systems, 2) quantified system-wide travel time savings and travel time reliability achieved, 3) SOVs tolling incentives. Based on the empirical analysis and evaluation results for the SR 167 and I-394 MnPass HOT lane systems, operational problems and challenges are also identified. Although the HOT lane system preserves favorable travel reliability, under-utilized HOT lane capacities were observed. The existing tolling strategies may be modified for better SOV allocation for HOT lane usages and further optimize the overall HOT system operations. The research findings greatly advance our understanding on HOT lane system operation mechanisms and are complementary to the freeway facility performance analysis provided by Highway Capacity Manual 2000

Evidence for Dirac Fermions in a honeycomb lattice based on silicon

Silicene, a sheet of silicon atoms in a honeycomb lattice, was proposed to be a new Dirac-type electron system similar as graphene. We performed scanning tunneling microscopy and spectroscopy studies on the atomic and electronic properties of silicene on Ag(111). An unexpected $\sqrt{3}\times \sqrt{3}$ reconstruction was found, which is explained by an extra-buckling model. Pronounced quasi-particle interferences (QPI) patterns, originating from both the intervalley and intravalley scattering, were observed. From the QPI patterns we derived a linear energy-momentum dispersion and a large Fermi velocity, which prove the existence of Dirac Fermions in silicene.Comment: 6 pages, 4 figure

BioNMT: A Biomedical Neural Machine Translation System

To solve the problem of translation of professional vocabulary in the biomedical field and help biological researchers to translate and understand foreign language documents, we proposed a semantic disambiguation model and external dictionaries to build a novel translation model for biomedical texts based on the transformer model. The proposed biomedical neural machine translation system (BioNMT) adopts the sequence-to-sequence translation framework, which is based on deep neural networks. To construct the specialized vocabulary of biology and medicine, a hybrid corpus was obtained using a crawler system extracting from universal corpus and biomedical corpus. The experimental results showed that BioNMT which composed by professional biological dictionary and Transformer model increased the bilingual evaluation understudy (BLEU) value by 14.14%, and the perplexity was reduced by 40%. And compared with Google Translation System and Baidu Translation System, BioNMT achieved better translations about paragraphs and resolve the ambiguity of biomedical name entities to greatly improved

Enabling Decision-Making in Battery Electric Bus Deployment through Interactive Visualization

The transit industry is rapidly transitioning to battery-electric fleets because of the direct environmental and financial benefits they could offer, such as zero emissions, less noise, and lower maintenance costs. Yet the unique spatiotemporal characteristics associated with transit system charging requirements, as well as various objectives when prioritizing the fleet electrification, requires the system operators and/or decision-makers to fully understand the status of the transit system and energy/power system in order to make informed deployment decisions. A recently completed NITC project, No. 1222 titled An Electric Bus Deployment Framework for Improved Air Quality and Transit Operational Efficiency, developed a bi-objective spatiotemporal optimization model for the strategic deployment of the Battery Electric Bus (BEB) to minimize the cost of purchasing BEBs, on-route and in-depot charging stations, and to maximize environmental equity for disadvantaged populations. As agencies such as the Utah Transit Authority (UTA) adopt the model and results, they desire to have a tool that could enable detailed spatiotemporal monitoring of components for the BEB system (e.g., locations of BEBs, the state-of-charge of batteries, charging station energy consumption at each specific timestamp), so that the integration of BEBs into the power/grid system as well as its operating condition could be better understood. To this end, this Translate Research to Practice grant will support the development of a visualization tool that allows transit operators/planners as well as decision-makers to explore the interdependency of the BEB transit system and energy infrastructure in both spatial and temporal dimensions with high resolution. The tool will be built on the scenario-based optimization modeling effort in NITC Project No. 1222, and allow agencies to make phase-wise (short-, mid-, or long-term) decisions based on investment resources and strategic goals. This project will also develop a guidebook to provide step-by-step guidance on data compilation for BEB analysis, model input, model implementation, and results interpretation. It will further detail how the developed visualization tool is structured and designed to ensure results exploration across transit operation and energy consumption. Both the guidebook and the tool will be directly useful to practitioners to easily implement our optimization model for their own transit network, and allow them to build interactive visualizations to assist with decision-making