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Keyword: AROvercome Discrimination: A Logistic Regression with 10-year Longitudinal Investigation of Emo Kids’ Facebook Posts
This study primarily aims to identify the factors that helped emo kids in 2010 move through the emo-identity discrimination and be able to obtain a certain level of achievement. Facebook is the social network that allows users to track friends’ posts back over 10 years. Content analysis was conducted by using two coders to rate…
Read MoreThe Design Process in the Improvement of The Experience Between a Brand and its Target Audience Through a Digital Product: The Lexus Portugal’s used Car Website Case Study
The study aims to demonstrate how the use of the design process can align a brand’s strategy with the interests of its target audience through a digital product based on a case study. Currently, Lexus internal studies show that there is a possibility to meet the needs of new audiences, beyond the traditional ones (men,…
Read MoreCNN-LSTM Based Model for ECG Arrhythmias and Myocardial Infarction Classification
ECG analysis is commonly used by medical practitioners and cardiologists for monitoring cardiac health. A high-performance automatic ECG classification system is a challenging area because there is difficulty in detecting and clustering various waveforms in the signal, especially in the manual analysis of electrocardiogram (ECG) signals. In this paper, an accurate (ECG) classification and monitoring…
Read MoreNumerical Study of Gas Microflow within a Triangular Lid-driven Cavity
A rarefied gas flow is modeled inside two cases of triangular lid-driven microcavity using single (SRT) and multi-relaxation time (MRT) lattice Boltzmann approaches. In the first one, the right angle is in the top-left corner and the upper wall moves with positive horizontal velocity. However, in the second case, the right angle is in the…
Read MoreAdvances in Optimisation Algorithms and Techniques for Deep Learning
In the last decade, deep learning(DL) has witnessed excellent performances on a variety of problems, including speech recognition, object recognition, detection, and natural language processing (NLP) among many others. Of these applications, one common challenge is to obtain ideal parameters during the training of the deep neural networks (DNN). These typical parameters are obtained by…
Read MoreWideband and High-Gain Aperture Coupled Feed Patch Array Antenna for Millimeter-Wave Application
Millimeter-wave (mmW) antenna is one of the most important parts of the fifth-generation (5G) systems because of its advanced characteristics, for example, wideband and high transmission rate. In this paper, an mmW 4×1 array antenna with high gain and wideband based on an aperture coupled feeding patch (ACFP) antenna is presented. The proposed array antenna…
Read MoreMalware Classification Using XGboost-Gradient Boosted Decision Tree
In this industry 4.0 and digital era, we are more dependent on the use of communication and various transaction such as financial, exchange of information by various means. These transaction needs to be secure. Differentiation between the use of benign and malware is one way to make these transactions secure. We propose in this work…
Read MoreContextual Word Representation and Deep Neural Networks-based Method for Arabic Question Classification
Contextual continuous word representation showed promising performances in different natural language processing tasks. It stems from the fact that these word representations consider the context in which a word appears. But until recently, very little attention was paid to the contextual representations in Arabic question classification task. In the present study, we employed a contextual…
Read MoreInterpretation of Machine Learning Models for Medical Diagnosis
Machine learning has been dramatically advanced over several decades, from theory context to a general business and technology implementation. Especially in healthcare research, it is obvious to perceive the scrutinizing implementation of machine learning to warranty the rewarded benefits in early disease detection and service recommendation. Many practitioners and researchers have eventually recognized no absolute…
Read MoreBayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis.…
Read MoreComparative Study of Cryptocurrency Algorithms: Coronavirus Towards Bitcoin’s Expansion
The widespread presence of Coronavirus (COVID-19) is causing organizations and individuals major economics downsizing. The way this virus is transmitted from one individual to another is the real cause of the problem. For that, researchers in different fields started seriously looking for touch-less and contact-less exchange. Particularly in the finance world, cash transactions and keypad…
Read MoreNew Algorithm for the Development of a Musical Words Descriptor for the Artificial Composition of Oriental Music
The Music Composition Library of the great composers constitutes an intellectual heritage. This article introduces an algorithm of artificial Oriental composing music based on the descriptors determined on a large learning base to automatically write Oriental music as the logic identical to any composer. Musical words are called a grammatical alphabet. Each word derived is…
Read MoreShape Optimization of Planar Inductors for RF Circuits using a Metaheuristic Technique based on Evolutionary Approach
In this article, we concentrate on the use of a metaheuristic technique based on an Evolutionary Algorithm (EA) for determining the optimal geometrical parameters of spiral inductors for RF circuits. For this purpose, we have opted for an optimization procedure through an enhanced Differential Evolution (DE) algorithm. The proposed tool allows the design of optimized…
Read MoreA Hybrid Mod
The ability to verify the critical risk factors related to an effective diagnosis is very crucial for improving accuracy on coronary heart disease prediction. The objective of this research is to find the best predictive model for coronary heart disease diagnosis. Three approaches are set up to achieve the goals (1) investigating the classifier algorithms…
Read MoreMulti-Objective Optimization when Surface Grinding the 3X13 Steel by Combining the General Reduced Gradient Algorithm and Harmonic Mean Method
In this paper, the multi-objective optimization process was applied for the surface grinding process of 3X13 steel using an aluminum oxide grinding wheel (WA46J7V1A). For each experiment, three cutting parameters, including the workpiece velocity, feed rate, and the depth of cut, were controlled to change according to the experimental matrix. At each experiment, surface roughness…
Read MoreUsing Envelope Analysis and Compressive Sensing Method for Intelligent Fault Diagnosis of Ball Bearing
Bearings are the key components of many rotating machines, in which serious failure or even major breakdown may occur due to their abnormal operation and defects. Thus, accurate fault diagnoses of bearing elements are essential for proactive predictive maintenance. However, the using of multiple sensors with high sampling rate reveal considerable shortages in the analysis…
Read MoreModelling and Simulation of Reduce Harmonic Distortion in Non-linear Loads
Harmonic distortion is a problem that can be caused by the use of power electronic devices. The effect of harmonics has an impact on changes in the input voltage source waveform which is referred to as wave defects. This incident has an impact on electronic faults and overheating of the power transformer coil as a…
Read MoreWater Availability for a Self-Sufficient Water Supply: A Case Study of the Pesanggrahan River, DKI Jakarta, Indonesia
The research will explore the challenges of using local water sources inside the city for a self-sufficient urban water supply by developed a system dynamics model. This study aims to evaluate and understand the Pesanggrahan River appropriateness as a raw drinking water source through a conceptual model that can accurately represent the interactions between the…
Read MoreISR Data Processing in Military Operations
This paper provides an overview of Intelligence, Surveillance, and Reconnaissance (ISR) data with respect on NATO standards and recommendations; further presents methods, tools, and experiences in ISR data processing in military operations. The steps of the Intelligence cycle and disciplines Business Intelligence (BI), Data Warehousing, Data Mining, and Big Data are presented in the introduction.…
Read MoreArduino-Compatible Modular Kit Design and Implementation for Programming Education
To cultivate creative talent, ways to learn creative problem-solving skills is needed, and one of them is programming. Arduino is a well-known tool used for programming education and the usefulness has been demonstrated in various case studies. However, there are several problems in existing Arduino-compatible kits as education tools, including the need for understanding hardware…
Read MoreBISINDO (Bahasa Isyarat Indonesia) Sign Language Recognition Using CNN and LSTM
Sign language is one of the languages which are used to communicate with deaf people. By using it, they can communicate and understand each other. In Indonesia, there are two standards of sign language which are SIBI (Sistem Bahasa Isyarat) and BISINDO (Bahasa Isyarat Indonesia). Deep learning is a model that is used to apply…
Read MoreSupervised Machine Learning Based Medical Diagnosis Support System for Prediction of Patients with Heart Disease
Application in the field of medical development has always been one of the most important research areas. One of these medical applications is the early prediction system for heart diseases especially; coronary artery disease (CAD) also called atherosclerosis. The need for a medical diagnosis support system is to detect atherosclerosis at the earlier stages to…
Read MoreDifferential Evolution based Hyperparameters Tuned Deep Learning Models for Disease Diagnosis and Classification
With recent advancements in medical filed, the quantity of healthcare care data is increasing at a faster rate. Medical data classification is considered as a major research topic and numerous research works have been already existed in the literature. Presently, deep learning (DL) models offers an efficient method for developing a dedicated model to determine…
Read MoreAssessing Heutagogical Elements in Learning of Engineering Education: Instrument Validation
Practically level of design element (i.e., explore, sharing, connect) is an essential of heutagogical approach. The self-determined learning process can be at ease with the implementation of these elements, and the critical step is reliability to measure teaching and learning feedback. Although various instruments were proposed in the literature to assess heutagogy elements, the specific…
Read MoreFPGA Acceleration of Tree-based Learning Algorithms
Machine learning classifiers provide many promising solutions for data classification in different disciplines. However, data classification at run time is still a very challenging task for real-time applications. Acceleration of machine-learning hardware solutions is needed to meet the requirements of real-time applications. This paper proposes a new implementation of a machine learning classifier on Field…
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