arXiv subjects

Jinli Zhang

Publications and source records attributed to Jinli Zhang.

4 recordsLinked to original sources

arXiv2024

Advancing Aspect-Based Sentiment Analysis through Deep Learning Models

Aspect-based sentiment analysis predicts sentiment polarity with fine granularity. While graph convolutional networks (GCNs) are widely utilized for sentimental feature extraction, their naive application for syntactic feature extraction can compromise information preservation. This study introduces an innovative edge-enhanced GCN, named SentiSys, to navigate the syntactic graph while preserving intact feature information, leading to enhanced performance. Specifically,we first integrate a bidirectional long short-term memory (Bi-LSTM) network and a self-attention-based transformer. This combination facilitates effective text encoding, preventing the loss of information and predicting long dependency text. A bidirectional GCN (Bi-GCN) with message passing is then employed to encode relationships between entities. Additionally, unnecessary information is filtered out using an aspect-specific masking technique. To validate the effectiveness of our proposed model, we conduct extensive evaluation experiments on four benchmark datasets. The experimental results demonstrate enhanced performance in aspect-based sentiment analysis with the use of SentiSys.

cs.CL↗

arXiv2024

Mining Area Skyline Objects from Map-based Big Data using Apache Spark Framework

The computation of the skyline provides a mechanism for utilizing multiple location-based criteria to identify optimal data points. However, the efficiency of these computations diminishes and becomes more challenging as the input data expands. This study presents a novel algorithm aimed at mitigating this challenge by harnessing the capabilities of Apache Spark, a distributed processing platform, for conducting area skyline computations. The proposed algorithm enhances processing speed and scalability. In particular, our algorithm encompasses three key phases: the computation of distances between data points, the generation of distance tuples, and the execution of the skyline operators. Notably, the second phase employs a local partial skyline extraction technique to minimize the volume of data transmitted from each executor (a parallel processing procedure) to the driver (a central processing procedure). Afterwards, the driver processes the received data to determine the final skyline and creates filters to exclude irrelevant points. Extensive experimentation on eight datasets reveals that our algorithm significantly reduces both data size and computation time required for area skyline computation.

cs.DC↗

arXiv2021

A low-noise on-chip coherent microwave source

The scaleup of quantum computers operating in the microwave domain requires advanced control electronics, and the use of integrated components that operate at the temperature of the quantum devices is potentially beneficial. However, such an approach requires ultra-low power dissipation and high signal quality in order to ensure quantum-coherent operations. Here, we report an on-chip device that is based on a Josephson junction coupled to a spiral resonator and is capable of coherent continuous-wave microwave emission. We show that characteristics of the device accurately follow a theory based on a perturbative treatment of the capacitively shunted Josephson junction as a gain element. The infidelity of typical quantum gate operations due to the phase noise of this cryogenic 25-pW microwave source is less than 0.1% up to 10-ms evolution times, which is below the infidelity caused by dephasing in state-of-the-art superconducting qubits. Together with future cryogenic amplitude and phase modulation techniques, our approach may lead to scalable cryogenic control systems for quantum processors.

quant-ph↗

arXiv2020

Broadband Tunable Phase Shifter For Microwaves

We implement a broadly tunable phase shifter for microwaves based on superconducting quantum interference devices (SQUIDs) and study it both experimentally and theoretically. At different frequencies, a unit transmission coefficient, $|S_{21}|=1$, can be theoretically achieved along a curve where the phase shift is controllable by magnetic flux. The fabricated device consists of three equidistant SQUIDs interrupting a transmission line. We model each SQUID embedded at different positions along the transmission line with two parameters, capacitance and inductance, the values of which we extract from the experiments. In our experiments, the tunability of the phase shift varies from from $0.07\timesπ$ to $0.14\timesπ$ radians along the full-transmission curve with the input frequency ranging from 6.00 to 6.28~GHz. The reported measurements are in good agreement with simulations, which is promising for future design work of phase shifters for different applications.

physics.app-ph↗