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A Deep Feedforward Neural Network and Shallow Architectures Effectiveness Comparison: Flight Delays Classification Perspective
Flight delays have negatively impacted the socio-economics state of passengers, airlines and airports, resulting in huge economic losses. Hence, it has become necessary to correctly predict their occurrences in decision-making because it is important ...
Dynamic Guarantee Network Model and Risk Spill-over Effect
We propose an empirical model framework named dynamic guarantee network model for real data analysis and numerical simulation. Firstly, stock prices’ stochastic process and liquidation mechanism with fire-sale are involved in this model. Secondly, by ...
Prediction and Sensitivity Analysis of Shear Strength of Reinforced Concrete Beams with Deformed Hook Steel Fiber using Backpropagation Neural Network coupled with Garson's Algorithm
Recent studies have brought developments and researches in various ways of reinforcing concrete beams. Famous in the present era is steel fibers which has been used as reinforcement to increase shear resistance of beams and reduced crack widths. Using ...
On Large-Batch Training of Residual Networks with SignSGD
- Alex Xavier,
- Dumindu Tissera,
- Rukshan Wijesinghe,
- Kasun Vithanage,
- Ranga Rodrigo,
- Subha Fernando,
- Sanath Jayasena
Large-batch training of deep neural networks (DNN) has recently been widely studied, since traversing the optimization landscape is faster with large batches and the emergence of parallel computing has made large-batch training feasible. However, its ...
Towards Quantification of Explainability Algorithms
Despite the proliferation in the use cases and the escalation in accuracy of Deep Neural Networks, the fact that such networks are black box models hamper our reliability in these models. Explainable Artificial Intelligence (XAI) algorithms work on ...
AdaFed: Performance-based Adaptive Federated Learning
Federated Learning is a distributed and privacy-preserving machine learning technique that allows local clients to learn a model without sharing their own data by coordinating with a global server. In this work, we present the Adaptive Federated ...
Predictive Modeling and Simulation to Identify the Prenatal, Natal, and Postnatal Risk Factors of Autism Spectrum Disorder: A Case Study from the Philippines
Perhaps the most crucial life skill is the ability to communicate effectively. Social interaction also shows positive feedback in our life. However, not everyone is capable of doing effective communication and social engagement. People have autism ...
Deep Learning-based EEG Detection of Mental Alertness States from Drivers under Ethical Aspects
- Tihomir Rohlinger,
- Le Ping Peng,
- Tobias Gerlach,
- Paul Pasler,
- Bo Zhang,
- Ralf Seepold,
- Natividad Martinez Madrid,
- Matthias Raetsch
One of the most critical factors for a successful road trip is a high degree of alertness while driving. Even a split second of inattention or sleepiness in a crucial moment, will make the difference between life and death. Several prestigious car ...
Efficient Fruit and Vegetable Classification and Counting for Retail Applications Using Deep Learning
The process of manual classification and counting of fruits and vegetables, from the moment the customer places items on the conveyor belt to their weighing by the cashier on the checkout scale is time consuming and may be burdensome for cashiers, who ...
Stochastic Neural Variational Learning of Noisy-OR Bayesian Networks for Images
Bayesian networks are not only useful as causal probabilistic models but also promising as models of the cerebral cortex. This paper addresses the problem of unsupervised learning in Bayesian networks with noisy-OR conditional probability tables. We ...
ACU-Net: Adaptive Context Network Based on U-Net for Retinal Vessel Segmentation
The accurate segmentation of retinal vessels is essential for the diagnosis of various ophthalmic diseases. However, the manual segmentation approaches are time-consuming and seriously affected by individual subjective factors. In addition, retinal ...
An interactive system to improve cognitive abilities using electromyographic signals
- Marco Enrique Benalcázar Palacios,
- Xavier Aguas,
- Ángel Leonardo Valdivieso Caraguay,
- Lorena Isabel Barona López,
- Rubén Nogales,
- Jaime Guilcapi,
- Freddy Benalcázar
This article presents a system for improving people’s cognitive abilities using electromyography (EMG) signals. This system was created under the serious game mode with a new way of interaction with the user. The sensor Myo Armband was used to measure ...
Factors Affecting Student Engagement in Online Learning during Covid-19: A Case Study of Students’ Perceptions
During the lockdown time of the novel coronavirus illness 2019 (COVID-19), the entire educational system, from basic to tertiary level, has collapsed not just in Vietnam but around the world. This transition has brought both pros and cons to students ...
Applying Exploratory Search for Self-Paced Learning using Tagging
This research proposes an exploratory system to support self-paced learning. The system applied principles of exploratory search and tagging. An empirical study was conducted as a proof of concept. The exploratory system included the web pages of the ...
The Implementation of Project-based Learning Approach in Technical Courses: An Investigation into Students’ Perceptions
Project-based learning is widely regarded as a viable strategy for enhancing student learning in higher education. Project-based learning effectively bridges the theoretical and practical education gaps by encouraging true knowledge, initiative, and a ...
Data Mining for Discovering Cognitive Models of Learning
A cognitive model is a descriptive account or computational representation of human thinking about a given concept, skill, or domain. A cognitive model of learning, includes both a way of organizing knowledge within a subject area and an account of how ...
Analysis on the Human Development Path of Vocational Education in the Era of Artificial Intelligence
At present, under the background of multiple national policies, the demand for intelligent development talents in the manufacturing industry is particularly tight based on the company's own cost-driven and the demand-driven technology in related fields; ...
Analysis of the Difficulties When Applying Positive Teaching Methods in Credit Training at Public Universities in Vietnam
The form of credit training is not too unfamiliar to the education of developed countries but is still quite new in Vietnam. The positive results that it brings about have encouraged this model to be replicated in many universities in general and public ...
Vietnamese Students' Perspectives towards Using Graphic Organizers on Reading Comprehension Skills
Numerous educators and scholars have cited graphic organizers (hereafter GOs) as instructional tools that are highly recommended for use in contemporary classrooms. A graphic organizer is a visual and graphical representation of the relationships ...
Exploration and Practice of Hierarchical Graduation Project under the Background of Science Collaborative Education and Engineering Education Accreditation
Graduation project is an important integrated practice segment for undergraduate education, since the quality of undergraduate education can be directly evaluated by the quality of graduation project. Under the background of science collaborative ...
Comparison of Tree-based Feature Selection Algorithms on Biological Omics Dataset
Feature selection is of great significance in processing high-dimensional data, which can save cost of computation and improve the performance of analysis. Tree based classifiers have been gaining their popularity due to their great performance and ...
A Simple and Effective Sound-based Five-Class Classifier for Induction Motor Overload
Overloading can shorten operating life of induction motors. It is also a primary cause of some faults, such as excessive temperatures or tooth breakage. Detecting and classifying overload levels are very essential to ensure durable and stable operations ...
Deep Learning-Based Detection for Traffic Control
Often urban intersections have a problem with long queues, but the traffic flow during the green light is relatively small. In this paper, we propose an integrated, machine-vision control mode process for controlling traffic lights. The method proposed ...
A Study on Applying Decentralized Constraint Optimization to Mobile Sensor Teams with Range Sensors
Observation systems using autonomous mobile sensor agents have been studied for application in emergency response and surveillance of hazardous areas. Several major types of sensor agents have range sensors and one of their tasks is to observe an ...
Design of a semi-automatic system that projects UV-C rays for the sterilization of household pantry products
- Helder Alexis Mayta Leon,
- Jean Pierre Arce Misajel,
- Sario Angel Chamorro Quijano,
- Frank William Zarate Pena
This research presents the design and control of a machine for use in homes, using mechatronic systems. In this work, control is defined for the correct use of UV light, thus being the most efficient. The development of the project shows that the ...
iMobilAkou: The Role of Machine Listening to Detect Vehicle using Sound Acoustics
Machine Learning can work very well with image recognition, but it is used to recognize audio patterns. Machine listening identifies audio patterns of different entities like the car engine, human speaking, nature sounds, etc. The environmental sound ...
Index Terms
- Proceedings of the 5th International Conference on Advances in Artificial Intelligence