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Noninvasive measurement of skin tissue oxygen saturation, StO2, is of interest especially in the studies of wound healing and detection of vascular diseases. This work aims to compare Partial Least Square (PLS) regression, K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN) technique in the prediction of StO2 using spectral data obtained from Monte Carlo simulations.…

In more recent times, researchers have turned their attention to link prediction and the role link inference can play in better understanding the evolutionary nature of social networking sites. The objective of this paper is to present an in-depth review, analysis, and discussion of the cutting-edge link prediction methods that can be applied to better…

Map of prediction of fishing ground that already exists in Indonesia issued by the Bali Marine Research and Observation Center (BPOL) and the National Aeronautics and Space Agency (LAPAN) of Jakarta, there are still many weaknesses including the spatial aspect of the point of forecasting far from the coast and the unclear type of fish…

In recent years, deep learning has been widely used for time series prediction. Deep learning model that is most often used for time series prediction is LSTM. LSTM is widely used because of its excellence in remembering very long sequences. However, doing training on models that use LSTM requires a long time. Trying from one…

This paper examines application of linear general model predictive control (LGMPC). The stability of the LGMPC is proven by means of a demonstration of a theorem stating a sufficient and constructive condition. Lower bounds conditions are found for one of these matrices and then a system with saturation is taken into consideration. The conditions can…

Data mining is recognized as an effective technique for extracting and retrieving valuable information or decision from the vast available data. Because of the nature of the functionality of medical centers and hospitals, their data centers contain a collection of valuable information about their patients. By properly processing these data, different applications can be developed…

Currently, one of the challenges of educational institutions is drop-out student issues. Several factors have been found and determined potentially capable to stimulate dropouts. Many researchers have been applied data mining methods to analyze, predict dropout students and also optimize finding dropout variables in advance. The main objective of this study is to find the…

This article is addressed to show the results of hybrid dynamical modeling in the form of PWA (piecewise-affine) and equivalent MLD (mixed-logical dynamical) model for multi-restricted areas avoidance of an autonomous system. It is a problem of determining the optimal moving trajectory from plant’s initial position to some desired position while avoiding some restricted areas…

This paper is proposed to build a model by applying two methods, namely support vector machine and nonnegative matrix factorization in the process of predicting stock market movement using twitter and historical data. The stock exchange is based on the LQ 45 stock with period from August 2018 – January 2019. The features consist of…

This paper is an extension of work originally presented in 2018 Global Smart Industry Conference (GloSIC). Researches are devoted to the development of Smart technology for complex objects control and prediction on the basis of a distributed Honeywell DCS control system of the TengizChevroil enterprise using the example of a technological process of medium pressure…

Location-based service has been widely used in modern life. It brings a lot of convenience to our lives. Improving the accuracy of location prediction can provide better location- based service. We propose a location prediction method based on the variable-order Markov model with time feature and user’s spatio-temporal rule. First, the user’s trajectory data needs…

Acute Myocardial Infarction (Heart Attack), a Coronary Heart Disease (CHD) is one of the major killers worldwide. Around one thousand data has been collected from AMI patients, people are at risk of maybe a heart attack and individuals with the significant features closely related to heart attack. The sophistication in mobile technology, health care applications…

Predicting the impact of suicide on incidental witnesses at an early stage helps to avert the possible side effect. When suicide is committed in public, incidental observers are left to grapple with it. In many cases, these incidental witnesses tend to experience the emotional side effect with time. In this study, we employed a Machine…

The abilities of human brain to discover solutions for many problems is a great gift that motivate the scientists to develop the revolution of the artificial intelligence and using it in many areas. This paper proposed an intelligent chessboard which works in a way that similar to the human brain that predicts the next positions…

Smoking has been proven to negatively affect health in a multitude of ways. As of 2009, smoking has been considered the leading cause of preventable morbidity and mortality in the United States, continuing to plague the country’s overall health. This study aims to investigate the viability and effectiveness of some machine learning algorithms for predicting…

Cloud computing allows users and enterprises to process their data in high performance servers, thus reducing the need for advanced hardware at the client side. Although local processing is viable in many cases, collecting data from multiple clients and processing them in a server gives the best possible performance in terms of processing rate. In…

In the current industrial development, an increasing number of sensors is applied for monitoring of any kind of appliances and machines. A predictive mathematical model allows for realistic assessment of the health state of the appliance, indication of service requirements, as well as control of the appliance, serving as so-called digital twin on a control…

A new statistical approach to predict the gain bandwidth of Phoenix-cell based reflectarrays is proposed. It combines the effects of both main factors that limit the bandwidth of reflectarrays: spatial phase delays and intrinsic bandwidth of radiating cells. As an illustration, the proposed approach is successfully applied to two reflectarrays based on new Phoenix cells.

Water quality assessment and prediction is a more and more important issue. Traditional ways either take lots of time or they can only do assessments. In this research, by applying machine learning algorithm to a long period time of water attributes’ data; we can generate a decision tree so that it can predict the future…

This paper proposes extended-range high-speed control for an IPMSM drive system. A simple real-time tuning flux-weakening control algorithm is proposed and implemented to control an IPMSM drive system in a wide variable speed range, from 3 r/min up to 2700 r/min. This flux-weakening control algorithm does not require any motor parameters and only needs simple…

Nowadays, Ischemic Heart Disease (IHD) (Heart Attack) is ubiquitous and one of the major reasons of death worldwide. Early screening of people at risk of having IHD may lead to minimize morbidity and mortality. A simple approach is proposed in this paper to predict risk of developing heart attack using smartphone and data mining. Clinical…

The SoC estimation of Li Ion batteries presents a difficult task for almost applications in order to ensure their higher energy density and their safety. Hence, there have been several methods to optimize the state of charge of the Lithium cells such as observer strategies which have been considered in this work. Kalman filter observer…

The Cognitive Radio usage has been estimated as non-emergency service with low volume traffic. Present work proposes an infrastructure based Cognitive Radio network and probability of success of CR traffic in licensed band. The Cognitive Radio nodes will form cluster. The cluster nodes will communicate on Industrial, Scientific and Medical band using IPv6 over Low-Power…

This paper is an extended version of the paper originally presented at the International Conference on Machine Learning and Applications (ICMLA 2016), which proposes the construction of classifiers, based on the application of machine learning techniques, to identify defaulting clients with credit recovery potential. The study was carried out in 3 segments of a Bank’s…

For the design of Information and Communications Technology (ICT) related products, basic level of technical expertise and simple development tools were enough in the early 1980s. As time goes by, new generation products designed by engineers are always expected to be smaller, lighter and faster, due to the increasing global competition and the application of…