Embedded filter bank-based algorithm for ECG compression

In this work, two ECG compression schemes are presented using two types of filter banks to decompose the incoming signal: wavelet packets (WP) and nearly-perfect reconstruction cosine modulated filter banks. The conventional embedded zerotree wavelet (EZW) algorithm takes advantage of the hierarchical relationship among subband coefficients of the pyramidal wavelet decomposition. Nevertheless, it performs worse when used with WP as the hierarchy becomes more complex. In order to address this problem, we propose a new technique that considers no relationship among coefficients, and is therefore suitable for use with WP. Furthermore, this new approximation makes it possible to apply the quantization method toM-channel maximally decimated filter banks. In this fashion, the proposed algorithm provides two efficient and effective ECG compressors that show better ECG compression performance than the conventional EZW algorithm

Semi-automatic liquid filling system using NodeMCU as an integrated Iot Learning tool

Computer programming and IoT are the key skills required in Industrial Revolution 4.0 (IR4.0). The industry demand is very high and therefore related students in this field should grasp adequate knowledge and skill in college or university prior to employment. However, learning technology related subject without applying it to an actual hardware can pose difficulty to relate the theoretical knowledge to problems in real application. It is proven that learning through hands-on activities is more effective and promotes deeper understanding of the subject matter (He et al. in Integrating Internet of Things (IoT) into STEM undergraduate education: Case study of a modern technology infused courseware for embedded system course. Erie, PA, USA, pp 1–9 (2016)). Thus, to fulfill the learning requirement, an integrated learning tool that combines learning of computer programming and IoT control for an industrial liquid filling system model is developed and tested. The integrated learning tool uses NodeMCU, Blynk app and smartphone to enable the IoT application. The system set-up is pre-designed for semi-automation liquid filling process to enhance hands-on learning experience but can be easily programmed for full automation. Overall, it is a user and cost friendly learning tool that can be developed by academic staff to aid learning of IoT and computer programming in related education levels and field

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen