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Chapter and Conference Paper
LANCMDA: Predicting MiRNA-Disease Associations via LightGBM with Attributed Network Construction
Since the abnormal expressions of microRNAs (miRNAs) were likely to induce human diseases and traditional biological methods for predicting miRNA-disease associations (MDAs) are costly and time-consuming, it i...
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Article
Heterogeneous selective ensemble learning model for mill load parameters forecasting by using multiscale mechanical frequency spectrum
A ball mill is a heavy mechanical device and its safe operation affects the entire grinding process. Mill load is a key index in the optimum operation of the grinding process, but it cannot be measured directl...
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Article
Complex Valued Deep Neural Networks for Nonlinear System Modeling
Deep learning models, such as convolutional neural networks (CNN), have been successfully applied in pattern recognition and system identification recent years. But for the cases of missing data and big noises...
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Chapter and Conference Paper
A Study on Online Reservation Behavior of Hotel Catering Industry
With the development of new media on the Internet, more and more consumers can obtain various information and reservation locations of restaurants through integrated booking platforms. This paper studies the i...
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Chapter and Conference Paper
The Impact of Online Comments on Consumers’ Purchase Decision
With the rise of online travel reservation and hotel reservation, the transaction mode has gradually developed from the traditional offline mode to the online mode. Before making a purchase decision, consumers...
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Article
Bayesian inference for data-driven training with application to seismic parameter prediction
Bayesian inference shows that the distribution of the future event not only depends on the past events (prior), but also depends on the relation between the past and the future events (likelihood). However, th...
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Article
New Results for Prediction of Chaotic Systems Using Deep Recurrent Neural Networks
Prediction of nonlinear and dynamic systems is a challenging task, however with the aid of machine learning techniques, particularly neural networks, is now possible to accomplish this objective. Most common n...
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Chapter and Conference Paper
Evaluation of the Effectiveness of an Interpretive Nutrition Label Format in Improving Healthy Food Discrimination Using Signal Detection Theory
This paper presents the results of a pilot study examining the effectiveness of an interpretive nutrition label as an information nudge in the context of Human-Computer Interaction (HCI) with a mobile Health ...
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Article
Multi-agent reinforcement learning for redundant robot control in task-space
Task-space control needs the inverse kinematics solution or Jacobian matrix for the transformation from task space to joint space. However, they are not always available for redundant robots because there are ...
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Article
Frequency domain CNN and dissipated energy approach for damage detection in building structures
Recent developments tools and techniques for structural health monitoring allow the design of early warning systems for the damage diagnosis and structural assessment. Most methods to damage detection involve ...
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Article
Two-stage three-machine assembly scheduling problem with sum-of-processing-times-based learning effect
Researchers claim that the processing of most products can be formulated as a two-stage assembly scheduling model. The literature states that cumulative learning experience is neglected in solving two-stage as...
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Chapter and Conference Paper
Fuzzy Control of Uncertain Nonlinear Systems with Numerical Techniques: A Survey
This paper provides an overview of numerical methods in order to so...
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Chapter and Conference Paper
Genetic Algorithm Modeling for Photocatalytic Elimination of Impurity in Wastewater
The existence of C.I. Acid Yellow 23 (AY23) in water causes a great...
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Article
Deep Boltzmann machine for nonlinear system modelling
Deep Boltzmann machine (DBM) has been successfully applied in classification, regression and time series modeling. For nonlinear system modelling, DBM should also have many advantages over the other neural net...
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Chapter and Conference Paper
The Selection of DNA Aptamers Against the Fc Region of Human IgG
Aptamers can bind with various kinds of target molecules and therefore they have highly potential for using in the therapeutic, diagnostic, biosensing, purification applications, etc. The aptamer that could sp...
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Chapter and Conference Paper
A Study on the Binding Ability of Truncated Aptamers for the Prostate Specific Antigen Using Both Computational and Experimental Approaches
Prostate-specific antigen (PSA) test is a commonly used clinical examination to evaluate the risk of prostate cancer, with the antibodies used normally as the recognition molecules for measuring PSA levels in ...
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Chapter and Conference Paper
Reachable Domain of Adults’ Right Leg in Sitting Posture
The reachable domain of the bending and stretching of male and female adults’ right leg in standard sitting posture was investigated. Twenty-seven healthy subjects with no movement impairing disorders were rec...
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Chapter and Conference Paper
A Novel Matching Technique for Two-Sided Paper Fragments Reassembly
Paper fragments reassembly has been playing an important role in many places such as public security and even archaeology. Combined with the travelling salesman problem, a novel approach based on the matching ...
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Chapter and Conference Paper
A New Elderly Clothing Design Reduces Nurse Aides’ Occupational Injury in Nursing Homes
Nurse aids assist the elderly to dress for a long time, they always get work-related musculoskeletal disorders (WMSDs) owing to inappropriate application of force. The purpose of this study is to design a new ...
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Chapter and Conference Paper
User Experience Design Based on Eye-Tracking Technology: A Case Study on Smartphone APPs
With the rapid development of mobile technology, smartphone has been becoming a part of our daily life. There are amounts of applications (APPs) developed for smartphone in the market, in order to meet the var...