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Ming-Hua Hsieh

dblp:64/436 · DBLP profile ↗
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13ranked-venue papers
3as first author
4since 2021 · last 2026
0000-0001-7130-6742ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 8 · 1 first-author · 3 since 2021Databases, data management, data science and information retrieval · 3 · 1 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1Security and privacy · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Mathematical optimization · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
primer design
0.012003
An efficient algorithm for minimal primer set selection · Bioinform. 2003
Mathematical optimization › discrete optimization
binary integer programming
0.012003
An efficient algorithm for minimal primer set selection · Bioinform. 2003
Mathematical optimization
discrete optimization
0.012003
An efficient algorithm for minimal primer set selection · Bioinform. 2003

Methods — techniques the papers use, named apart from their topics

variable fixing · 0.1redundant constraint elimination · 0.1
YearPublicationVenuePosition
2026 Can Social Sentiment Improve Bitcoin Dollar-Cost Averaging? Evidence from VADER and CryptoBERT
Hsiu Yuan Liang, Jyh-Shing Roger Jang, Ming-Hua Hsieh, Chien-Ping Chung
ICBC3
2025 Turning Point Prediction Under Multi-Objective Genetic Algorithm
Chi-Fang Chao, Mu-En Wu, Hsin-Hung Li, Ming-Hua Hsieh
IEEE Big Data4
2024 An intelligent option trading system based on heatmap analysis via PON/POD yields
Min-Kuan Chen, Dong-Yuh Yang, Ming-Hua Hsieh, Mu-En Wu
Expert Syst. Appl.3
2023 Fuzzy-Based Factor Evaluation System for Momentum Overweight Trading Strategy
Chi-Fang Chao, Mu-En Wu, Ming-Hua Hsieh
ACIIDS (1)3
2013 A hybrid scheme for energy-efficient object tracking in sensor networks
Ming-Hua Hsieh, Kawuu Weicheng Lin, Vincent S. Tseng
Knowl. Inf. Syst.1
2011 Photosense: Make sense of your photos with enriched harmonic music via emotion association
abstract
This paper proposes a novel audiovisual presentation system, called PhotoSense, to enrich photo navigation experience by associating emotionally harmonic music with a given photo collection. Different from many conventional photo visualization systems which predominantly focus on the visual elements for presentation, we explore both visual and aural perspectives which can enhance the browsing experience from each other. This is achieved by building an emotion space shared by visual and aural domains, and a set of emotion classifiers which can associate each visual and aural element with this space. Furthermore, we design a sequence matching algorithm to associate a set of music with a photo collection by maximizing similarity in the emotion space. Photo-Sense represents one of the first mash-up applications which build a natural connection between the ever increasing personal photo collections on the Web and music-sharing sites. Experiments show that PhotoSense provides better browsing experience for photo collections.
Ja-Hwung Su, Ming-Hua Hsieh, Tao Mei 0001, Vincent S. Tseng
ICME2
2011 A systematic design for coping with model risk
Yu-Hsiang Yang, Rua-Huan Tsaih, Ming-Hua Hsieh
Expert Syst. Appl.3
2010 A novel prediction-based strategy for object tracking in sensor networks by mining seamless temporal movement patterns
Kawuu Weicheng Lin, Ming-Hua Hsieh, Vincent S. Tseng
Expert Syst. Appl.2
2009 Level Converting Scan Flip-flops
abstract
Power consumption is an important issue in nanoscale circuits. The multiple supply voltages (MSV) technique, where non-critical parts are supplied with the lower supply voltage, can be used to balance power and performance, as both dynamic and leakage power are reduced with the lower supply voltage. However, level converting circuits must be inserted between different voltage domains to avoid leakage current. In this paper, we present three scan flip-flop designs that support a low-power mechanism, including level converting and sleep mode operation. The designs provide tradeoff between power and speed, and thus provide a simple and efficient way to design low-power high-testability circuits.
Katherine Shu-Min Li, Ming-Hua Hsieh, Sying-Jyan Wang
ISCAS2
2009 An efficient hybrid Taguchi-genetic algorithm for protein folding simulation
Cheng-Jian Lin, Ming-Hua Hsieh
Expert Syst. Appl.2
2009 Classification of mental task from EEG data using neural networks based on particle swarm optimization
Cheng-Jian Lin, Ming-Hua Hsieh
Neurocomputing2
2006 An intelligent primer design system for multiplex reverse transcription polymerase chain reaction and complementary DNA microarray
Ming-Hua Hsieh, Rua-Huan Tsaih, Chiung-Yu Huang
Expert Syst. Appl.1
2003 An efficient algorithm for minimal primer set selection
abstract
SUMMARY: We have developed U-PRIMER, a primer design program, to compute a minimal primer set (MPS) for any given set of DNA sequences. The U-PRIMER algorithm, which uses automatic variable fixing and automatic redundant constraint elimination to tackle the binary integer programming problem associated with the MPS selection problem. The program has been tested successfully with 32 adipocyte development-related genes and 9 TB-specific genes to obtain their respective MPSs. AVAILABILITY: A free copy of U-PRIMER implemented in C++ programming language is available from http://www.u-vision-biotech.com
Ming-Hua Hsieh, Wei-Che Hsu, Sung-Kay Chiu, Chi-Meng Tzeng
Bioinform.1