教学课程资源库 更多>>

关键词： Learning algorithms  

摘要： Construction accidents are the most significant contributor to occupational disasters among all industries worldwide. This is due to both the open and dynamic characteristics of construction sites as well as the insufficient quantity and quality of site safety management personnel. The advancement of Artificial Intelligence (AI) deep learning techniques in dynamically identifying the moving objects on-site offers a promising opportunity to improve construction safety. This paper presents the application of the most state-of-the-art AI techniques to identify on-site construction safety hazards in order to prevent risk events for construction workers. The proposed method has been implemented in a real construction project and achieved satisfactory performance with 95% of Recall, 93% of Precision for lab testing, 90% of Correctness and 80% of Cleanness for in-situ testing. It has been concluded that the proposed method has promising potential to assist construction safety management personnel in improving the safety management practices. © 2020, National Taiwan University of Science and Technology. All rights reserved.

关键词： Fuzzy sets   Interpolation   Cognition   Force   Systematics   Benchmark testing   Computer science   Active set-based solution   adaptive network-based fuzzy inference system (ANFIS)   closest rule selection   fuzzy rule interpolation (FRI)  

摘要： Fuzzy rule interpolation (FRI) is of particular significance for reasoning in the presence of insufficient knowledge or sparse rule bases. As one of the most popular FRI methods, transformation-based fuzzy rule interpolation (TFRI) works by constructing an intermediate fuzzy rule, followed by running scale and move transformations. The process of intermediate rule construction selects a user-defined number of rules closest to an observation that does not match any existing rule, using a distance metric. It relies upon heuristically computed weights to assess the contribution of individual selected rules. This process requires a move operation in an effort to force the intermediate rule to overlap with an unmatched observation, regardless of what rules are selected and how much contribution they may each make. It is, therefore, desirable to avoid this problem and also to improve the automation of rule interpolation without resorting to the user's intervention for fixing the number of closest rules. This article proposes such a novel approach to selecting a subset of rules from the sparse rule base with an embedded rule weighting scheme for the automatic assembling of the intermediate rule. Systematic comparative experimental results are provided on a range of benchmark datasets to demonstrate statistically significant improvement in the performance achieved by the proposed approach over that obtainable using conventional TFRI.

摘要： Incorporating equity and inclusion in the effort toward access for everyone.

关键词： Consciousness   Gamma band   Temporal lobe epilepsy   Mutual information   Synchronization   Mathematics   Computer science   Engineering   Biological sciences   Health sciences  

摘要： Background: Epileptic seizures are characterized by aberrant synchronization. We hypothesized that higher synchronization across the seizure onset zone (SOZ) channels during a temporal lobe seizure contributes to impaired consciousness. New method: All symmetric bivariate synchronization measures were extended to multivariate measure by a principal component analysis (PCA) based technique. A novel nonparametric method has been proposed to test the statistical significance between increased synchronization across the seizure onset zone (SOZ) channels and reduced consciousness. Results: Increased synchronization in the gamma band towards seizure termination significantly contributes to impaired consciousness (p < 0.1). Synchronization reaches its peak in the extratemporal region (frontal lobe) ahead of the temporal region (p < 0.05). Synchronization is prominent in beta and gamma bands by most methods and it is more in the second half of seizure duration than in the first (p < 0.05). Conclusions: Mutual information is the only synchronization measure out of the six that we studied, whose increase can be associated with the loss of consciousness in a statistically significant way.

关键词： Computer science   EEG   Alcoholism   Correlation distance   Distance metrics   Classification  

摘要： The basic function of the brain is severely affected by alcoholism. For the easy depiction and assessment of the mental condition of a human brain, Electroencephalography (EEG) signals are highly useful as it can record and measure the electrical activities of the brain much to the satisfaction of doctors and researchers. Utilizing the standard conventional techniques is quite hectic to derive the useful information as these signals are highly non-linear and non-stationary in nature. While recording the EEG signals, the activities of the neurons are recorded from various scalp regions which has varied characteristics and has a very low magnitude. Therefore, human interpretation of such signals is very difficult and consumes a lot of time. Hence, with the advent of Computer Aided Diagnosis (CAD) Techniques, identifying the normal versus alcoholic EEG signals has been of great utility in the medical field. In this work,we perform the initial clustering of the alcoholic EEG signals by means of using Correlation Dimension (CD) for easy feature extraction and then the suitable features are selected in it by means of employing various distance metrics like correlation distance, city block distance, cosine distance and chebyshev distance. Proceeding in such a methodology aids and assures that a good discrimination could be achieved between normal and alcoholic EEG signals using non-linear features. Finally, classification is then carried out with the suitable classifiers chosen such as *** classifier, the proposed Modified *** classifier by means of introducing Ridge and Lasso based soft thresholding technique, Random Forest with bootstrap resampling technique, Artificial Neural Networks (ANN) such as Radial Basis Functions (RBF) and Multi-Layer Perceptron (MLP), Support Vector Machine (SVM) with Linear, Polynomial and RBIF Kernel, Naive Bayesian Classifier (NBC), K-means and classifier, and K Nearest Neighbor (KNN) Classifier and the results are analyzed.

关键词： Computer science   Magnetic resonance image   Computer aided diagnosis   Convolutional neural network   Randomized neural networks   Extreme learning machine   Random vector functional link   Schmidt neural network   Chaotic bat algorithm  

摘要： Brain disease is one of the leading causes of death nowadays. Medical imaging is the most effective method for brain disease diagnosis, which provides a clear view of the interior brain. However, manual interpretation requires too much time and effort because medical images contain a large volume of information. Computer aided diagnosis is playing a more and more significant role in the clinic, which can help doctors and physicians to analyze medical images automatically. In this study, a novel pathological brain detection system was proposed for brain magnetic resonance images based on ResNet and randomized neural networks. Firstly, a ResNet was employed as the feature extractor, which was a famous convolutional neural network structure. Then, we used three randomized neural networks, i.e., the Schmidt neural network, the random vector functional-link net, and the extreme learning machine. The weights and biases in the three networks were trained by the chaotic bat algorithm. The three proposed methods achieved similar results based on five runs, and they yielded comparable performance in comparison with state-of-the-art approaches.

关键词： Service robots   Robot acceptance   Robot etiquette   Non-interactive tasks   Socially acceptable behaviour  

摘要： Some applications of service robots within domestic and working environments are envisaged to be a significant part of our lives in the not too distant future. They are developed to autonomously accomplish different tasks either on behalf of or in collaboration with a human being. Robots can perceive and interpret data from the external environment, so they also collect personal information and habits;they can plan, navigate, and manipulate objects, eventually intruding in our personal space and disturbing us in the current activities. Indeed, such capabilities need to be socially enhanced to ensure their effective deployment and to favour a significant social impact. The modelling and evaluation of a service robot's behaviour, while not interacting with a human, have only been marginally considered in the last few years. But these can be expected to play a key role in developing socially acceptable robotic applications that can be used widely. To explore this research direction, we present research objectives related to the effective development of socially-aware service robots that are not involved in tasks that require explicit interaction with a person. Such discussion aims at highlighting some of the future challenges that will be posed for the social robotics community in the next years.

关键词： Approximation algorithms   Optimization   Decision making   Computer science   Electronic mail   Zirconium   Linear programming   Decision-making   evolutionary multiobjective optimization (EMO)   preference incorporation   reference point  

摘要： The ultimate goal of multiobjective optimization is to help a decision maker (DM) identify solution(s) of interest (SOI) achieving satisfactory tradeoffs among multiple conflicting criteria. This can be realized by leveraging DM's preference information in evolutionary multiobjective optimization (EMO). No consensus has been reached on the effectiveness brought by incorporating preference in EMO (either a priori or interactively) versus a posteriori decision making after a complete run of an EMO algorithm. Bearing this consideration in mind, this article: 1) provides a pragmatic overview of the existing developments of preference-based EMO (PBEMO) and 2) conducts a series of experiments to investigate the effectiveness brought by preference incorporation in EMO for approximating various SOI. In particular, the DM's preference information is elicited as a reference point, which represents her/his aspirations for different objectives. The experimental results demonstrate that preference incorporation in EMO does not always lead to a desirable approximation of SOI if the DM's preference information is not well utilized, nor does the DM elicit invalid preference information, which is not uncommon when encountering a black-box system. To a certain extent, this issue can be remedied through an interactive preference elicitation. Last but not the least, we find that a PBEMO algorithm is able to be generalized to approximate the whole PF given an appropriate setup of preference information.