13,954 research outputs found
Energy Market Integration and Economic Convergence: Implications for East Asia
Energy Market Integration (EMI) has been pursued by East Asian countries in recent years, but how it could play a role in facilitating economic growth of countries in the region remains to be an empirical question. This paper uses the economic convergence analysis (including both the σ-convergence and β-convergence approaches) to examine the impact of EMI - measured by two newly constructed indexes (namely, the energy trade index and the energy market competition index) - at the country level, on dynamic economic growth path across countries, with a special interest to inform policy makings related to promoting EMI among East Asian countries. The result shows that a more integrated energy market may significantly reduce income disparity across countries and thus help poor countries to catch up with rich countries in economic development. Moreover, a comparison among the three regions including EU, NAFTA and EAS shows that EAS countries are more likely to achieve economic convergence along with the construction of EMI process. An important policy implication is that less developed countries in the EAS region can increase benefits from actively participating into the EMI process.
Nanonewton force generation and detection based on a sensitive torsion pendulum
In this paper, we introduce the experiment based on a sensitive torsion
pendulum for measuring and calibrating small forces at nanonewton scale. The
force standard for calibration is the universal gravitation between four masses
separated by known distances. It is realized by two test masses suspended as
the part of torsion pendulum and two source masses on a rotation table. Two
force generation mechanisms, optical force from radiation pressure and
electrostatic force by capacitive actuation unit, are designed and will be
calibrated by the gravitation force. We present our recent results of radiation
pressure measurements, and describe the design of capacitive displacement
sensing/actuating unit.Comment: This work has been presented on Conference on Precision
Electromagnetic Measurements, 8-13 June 2008, Broomfield, Colorad
Question Type Guided Attention in Visual Question Answering
Visual Question Answering (VQA) requires integration of feature maps with
drastically different structures and focus of the correct regions. Image
descriptors have structures at multiple spatial scales, while lexical inputs
inherently follow a temporal sequence and naturally cluster into semantically
different question types. A lot of previous works use complex models to extract
feature representations but neglect to use high-level information summary such
as question types in learning. In this work, we propose Question Type-guided
Attention (QTA). It utilizes the information of question type to dynamically
balance between bottom-up and top-down visual features, respectively extracted
from ResNet and Faster R-CNN networks. We experiment with multiple VQA
architectures with extensive input ablation studies over the TDIUC dataset and
show that QTA systematically improves the performance by more than 5% across
multiple question type categories such as "Activity Recognition", "Utility" and
"Counting" on TDIUC dataset. By adding QTA on the state-of-art model MCB, we
achieve 3% improvement for overall accuracy. Finally, we propose a multi-task
extension to predict question types which generalizes QTA to applications that
lack of question type, with minimal performance loss
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