International Journal of Intelligent Systems and Applications in Engineering

International Journal of Intelligent Systems and Applications in Engineering

Basic info

  • Publisher: IJISAE
  • Country of publisher: turkey
  • Date added to EuroPub: 2017/Apr/13

Subject and more

  • LCC Subject Category: Engineering, Nanotechnology
  • Publisher's keywords: engineering
  • Language of fulltext: english
  • Time from submission to publication: 4 weeks

Publication charges

  • Article Processing Charges (APCs): No
  • Submission charges: No
  • Waiver policy for charges? Yes

Open access & licensing

  • Type of License: CC BY
  • License terms
  • Open Access Statement: Yes
  • Year open access content began: 2013
  • Does the author retain unrestricted copyright? True
  • Does the author retain publishing rights? True

Best practice polices

  • Permanent article identifier: None
  • Content digitally archived in: Nopolicy
  • Deposit policy registered in: None

This journal has '83' articles

Design and Implementation of High Speed Artificial Neural Network Based Sprott 94 S System on FPGA

Design and Implementation of High Speed Artificial Neural Network Based Sprott 94 S System on FPGA

Authors: Ismail Koyuncu *| Department of Electronics and Automation, Duzce University, 81010, Duzce, Turkey
(21 downloads)
Abstract

FPGA-based embedding system designs have been preferred for industrial applications and prototyping because of the advantages of parallel processing, reconfigurability and low cost. Due to having characteristic structure of the parallel processing of Artificial Neural Networks (ANNs), these systems provide the advantage of speed and performance when they are implemented with FPGA-based hardware. The hardware implementation of transfer functions used for modeling non-linear systems is a challenging problem. Therefore, this problem creates convergence problems. In this paper, non-linear Sprott 94 S system has been modeled using ANNs running on FPGA. All related parameter values and processes are defined with IEEE-754-1985 32-bit floating point number format. ANN-based Sprott 94 S system design has been developed using VHDL synthesized using Xilinx ISE Design Tools. In test stage, ANN-based Sprott 94 S system has been tested using 3X100 data set and obtained error analysis results have been presented. The constructed design has been performed for Xilinx VIRTEX-6 family XC6VHX255T-3FF1923 FPGA chip using Place&Route process and chip usage statistics have been given. The clock frequency of ANN-based Sprott 94 S system which has pipeline processing scheme has been obtained with the value of 304.534 MHz. Accordingly, the proposed FPGA-based ANN system has produced 3X3.284 billion outputs in 1 second.

Keywords: FPGA, VHDL, Nonlinear Systems, ANN, Sprott 94 S System
Classification of Different Wheat Varieties by Using Data Mining Algorithms

Classification of Different Wheat Varieties by Using Data Mining Algorithms

Authors: Kadir Sabanci*| Karamanoglu Mehmetbey University, Faculty of Engineering Department of Electrical and Electronics Engineering, Karaman, Turkey, Mustaf...
(23 downloads)
Abstract

There are various applications using computer-aided quality controlling system. In this study, seed data set acquired from UCI machine learning database was used. The purpose of the study is to perform the operations for separation of seed species from each other in the seed data set. Three different seed whose data was acquired from the UCI machine learning database was used. Later it was classified by applying the methods of KNN, Naive Bayes, J48 and multilayer perceptron to the dataset. While wheat seed data received from the UCI machine learning database was classified, WEKA program was used. Depending on the number of neurons the highest classification success came in 7-layer neurons. Our success rate for the number of 7-layer neurons came to 97.17% When the classification success rate was calculated according to KNN for the values of different neighbour, the highest success rate for neighbour was set at 95.71% for 4. Neighbour. With this method, classification of seeds depending on their properties was provided more quickly and effectively.

Keywords: WEKA, Multilayer Perceptron, KNN, J48, Naive Bayes
Application of ANN Modelling of Fire Door Resistance

Application of ANN Modelling of Fire Door Resistance

Authors: Sakir Tasdemir| Selcuk University, Technology Faculty, Computer Engineering, Konya, Turkey, Mustafa Altin *| Selcuk University Higher School of Vocati...
(22 downloads)
Abstract

Fire doors are compulsorily used in every kind of building nowadays. The determination of fire doors’ resistance in which kind of buildings is also essential. This determination is needed to be watched through the experimental works done. Computer technologies and applications are commonly used in many fields in industry. In this study, by using the data obtained as a result of experiments made in order to determine the resistance of fire doors, artificial neural network (ANN) model was developed. With this model, it is aimed to evaluate the inner temperature of fire room having an important role in resistance of the fire door. In the developed system, temperature values belonging to thermocouples on the door (Top Left, Top Right, Middle Left, Middle Right, Bottom Left, Bottom Right (oC) and time (minute) were taken as input parameters and in-room temperature (oC) was taken as output parameters. When the results obtained from ANN and experimental data are compared, it is determined that two groups of data were coherent. It is shown that ANN can be safely used in the determination of fire door resistance.

Keywords: Artificial neural network, Fire doors, In-Room temperature, Computer modelling
Using Word Embeddings for Ontology Enrichment

Using Word Embeddings for Ontology Enrichment

Authors: İzzet Pembeci*| Muğla Sıtkı Koçman University. Department of Computer Engineering
(25 downloads)
Abstract

Word embeddings, distributed word representations in a reduced linear space, show a lot of promise for accomplishing Natural Language Processing (NLP) tasks in an unsupervised manner. In this study, we investigate if the success of word2vec, a Neural Networks based word embeddings algorithm, can be replicated in an aggluginative language like Turkish. Turkish is more challenging than languages like English for complex NLP tasks because of her rich morphology. We picked ontology enrichment, again a relatively harder NLP task, as our test application. Firstly, we show how ontological relations can be extracted automaticaly from Turkish Wikipedia to construct a gold standard. Then by running experiments we show that the word vector representations produced by word2vec are useful to detect ontological relations encoded in Wikipedia. We propose a simple but yet effective weakly supervised ontology enrichment algorithm where for a given word a few know ontologically related concepts coupled with similarity scores computed via word2vec models can result in discovery of other related concepts. We argue how our algorithm can be improved and augmented to make it a viable component of an ontoloy learning and population framework.

Keywords: Neural Language Models, Word Embeddings, Ontology Enrichment, Ontology Population
Validation of Registration for Renal Dynamic Contrast Enhanced MRI Imaging

Validation of Registration for Renal Dynamic Contrast Enhanced MRI Imaging

Authors: Seniha Esen Yuksel *| Hacettepe University, Department of Electrical and Electronics Engineering, Ankara, Turkey.
(23 downloads)
Abstract

In Dynamic Contrast Enhanced Resonance Imaging (DCE-MRI), abdomen is scanned repeatedly and rapidly after injection of a contrast agent. During data acquisition, collected images suffer from the motion induced by the patient if he/she moves or breathes heavily during the scan. Therefore, these images should be aligned accurately to correct the motion. Recently, mutual information (MI) registration has become the first tool to register renal DCE-MRI images before any further processing. However, MI registration is sensitive to initial conditions and optimization methods, and it is bound to fail under certain conditions such as extreme movement or noise in the image. Therefore, if automated image analysis for renal DCE-MRI is to enter the clinical settings, it is necessary to have validation strategies that show the limitations of registration models on known datasets. In this study, two methods are introduced for the validation of registration of renal DCE-MRI images. The first method demonstrates how to use the inverse transform to generate realistic looking DCE-MRI kidney images and use them in validation. The second method shows how to generate checkerboard images and how to evaluate the goodness of registration for real DCE-MRI images. These validation methods can be incorporated into the registration studies to quantitatively and qualitatively demonstrate the success and the limitations of registration models.

Keywords: Contrast-enhanced magnetic resonance imaging, inverse transform, mutual information, registration, validation
A highly Reliable and Fully Automated Classification System for Sleep Apnea Detection

A highly Reliable and Fully Automated Classification System for Sleep Apnea Detection

Authors: Laiali Almazaydeh| Department of Software Engineering, Al-Hussein Bin Talal University, Ma’an, Jordan, Khaled Elleithy| Department of Computer Science...
(22 downloads)
Abstract

Sleep apnea (SA) in the form of Obstructive sleep apnea (OSA) is becoming the most common respiratory disorder during sleep, which is characterized by cessations of airflow to the lungs. These cessations in breathing must last more than 10 seconds to be considered an apnea event. Apnea events may occur 5 to 30 times an hour and may occur up to four hundred times per night in those with severe SA [1]. Nowadays, polysomnography (PSG) is a standard testing procedure to diagnose OSA which includes the monitoring of the breath airflow, respiratory movement, and oxygen saturation (SpO2), body position, electroencephalography (EEG), electromyography (EMG), electrooculography (EOG), and electrocardiography (ECG). Therefore, a final diagnosis decision is obtained by means of medical examination of these recordings [2]. However, new simplified diagnostic methods and continuous screening of OSA is needed in order to have a major benefit of the treatment on OSA outcomes. In this regard, a portable monitoring system is developed to facilitate the self-administered sleep tests in familiar surroundings environment closer to the patients’ normal sleep habits. With only three data channels: tracheal breathing sounds, ECG and SpO2 signals, a patient does not need hospitalization and can be diagnosed and receive feedback at home, which eases follow-up and retesting after treatment.

Keywords: Sleep Apnea, PSG, ECG, RR interval, SpO2, VAD
An Efficient Approach for Ground Echoes Suppression Based on Textural Features and SVM

An Efficient Approach for Ground Echoes Suppression Based on Textural Features and SVM

Authors: Mehdia Hedir*| University of Science and Technology Houari Boumediene , Beb ezzouar – BP32, Algeria, Boualem Haddad| University of Science and Technol...
(26 downloads)
Abstract

The use of the Support Vector Machine (SVM) technique for the clutter identification in the context of meteorological data is presented. The clutter is due to ground echoes and anomalous propagation. The SVM is combined with textural approach which is based on the Grey Level Co-occurrence Matrix (GLCM) that is the most used in the textural analysis image. An incoherent radar site is considered for this study. The results reveal that over than 91.1% of ground echoes are identified and 90.3% of precipitations are preserved. In addition 95.99% of anomalous propagation are removed. The use of our approach is lasts than 1mn for the treatment of each image. We can then filter the radar image in real time.

Keywords: Precipitation echoes, ground echoes, anomalous propagation, textural parameters, support vector machine
Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age

Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age

Authors: Ilker Ali OZKAN*| Selcuk University, Technology Faculty, Computer Engineering, Konya, Turkey, Mustafa ALTIN| Selcuk University Higher School of Vocati...
(26 downloads)
Abstract

Compressive strength of concrete is one of the most important elements for an existing building and a new structure to be built. While obtaining the desired compressive strength of concrete with an appropriate mix and curing conditions for a new structure, with non-destructive testing methods for an existing structure or by taking core samples the concrete compressive strength are determined. One of the most important factors that affects the concrete compressive strength is age of concrete. In this study, it is attempted to estimate compressive strength, modelling Artificial Neural Networks (ANN) and using different mixture ratios and compressive strength of concrete samples at different ages. In accordance with obtained data’s in the estimation of concrete compressive strength, ANN could be used safely.

Keywords: Concrete strength, Prediction, Artificial neural networks
Long Term and Remote Health Monitoring with Smartphone

Long Term and Remote Health Monitoring with Smartphone

Authors: Pinar Kirci*| Istanbul University, Engineering Faculty, Engineering Sciences Department, Istanbul,Turkey, Gokhan Kurt| Istanbul University, Engineerin...
(24 downloads)
Abstract

The basic aim of our work is to provide solutions with monitoring the heart beat rates of disabled or old people. And also we expect to help the people who have specific heart diseases like potential cardiac arrests and cardiac pacemaker carriers. Besides in case of emergency situations, our system will produce an immediate alarm to provide urgent help for the patients. In the system, emergency situations depend on the heart beat rates. If the heart beat rates of a person decreases at lower rates compared with normal heart beat rates or if the heart beat rates of a person increases at higher rates compared with normal heart beat rates or if big heart beat rate changes occur during the predetermined time period then these situations will be evaluated as emergency situations and these situations should be announced to considered people and places like hospitals, patient’s doctor and patient’s family members. The proposed system colloborates with smartphones and includes sensors to collect data from the patient. Also the system is used to process and compare data with pre defined normal heart beat rates by patient’s doctor and to notice if there is an emergency situation. Besides, in case of an emergengy situation, to inform considered people. But if there is not an emergengy situation exists, then the system stores the collected data and sends them as daily and weekly graphics to the patient’s doctor. These graphics are collected as a result of definite daily activities like sleeping, sitting, standing, walking and jogging. The results are compared with the patient’s doctor’s stated normal heart rate intervals for every activity period. Furthermore, our proposed system structure includes heart pulse sensor, a smartphone screen, bluetooth interface and memory.

Keywords: Remote health monitoring, GPS, wireless sensor network, sensors
Process modelling and simulation of a Simple Water Treatment Plant

Process modelling and simulation of a Simple Water Treatment Plant

Authors: Vincent Anayochukwu Ani*| University of Nigeria, Department of Electronic Engineering, Nsukka, Nigeria
(24 downloads)
Abstract

Water treatment plants are likely to experience problems such as the water level both in the filter cells and in the tanks tend to fluctuate widely. These create the potential for partial drainage, overflow, and potential initial turbidity breakthrough at the beginning of the filtration cycles. This paper presents a mathematical model for studying the process behavior of a water treatment plant. A state equation was developed as a mathematical model of the process. This mathematical model was used to simulate the effects of varying the parameters of the plant (R, C, and I) representing the restriction of the connecting pipes, the capacity of the tanks and the filteration of the water filter, respectively, on the state variables (height of tank, h, and flowrate, q). The results of the simulation are presented graphically in the study. From the analyses, it was observed that varying any of the values of the parameters of the model has an effect on the water levels in the various tanks and the flow of water through the filter. The analyses of this paper on modeling a water treatment plant is a very simple way of knowing from the beginning the various sizes of pipes, tanks and filter to be used and how these will affect the flow of water in the plant before going into the physical construction of the plant.

Keywords: Water, State equation, Process Control, Modelling, Simulation, Filtration
A Low Cost Single Board Computer Based Mobile Robot Motion Planning System for Indoor Environments

A Low Cost Single Board Computer Based Mobile Robot Motion Planning System for Indoor Environments

Authors: Serdar Solak| Department of Informatics, Kocaeli University, Kocaeli – 41380, Turkey, Emine Dogru Bolat*| Dep. of Biomedical Eng., Kocaeli University,...
(22 downloads)
Abstract

In this study, a low cost, flexible and modular structure is proposed for mobile robot motion planning systems in an indoor environment with obstacles. In this system, the mobile robot has to follow the shortest path to the target avoiding obstacles. It is designed as three main modules including image processing, path planning and robot motion blocks. These modules are embedded on a single board computer. In the image processing module, the image of the indoor environment, including a mobile robot, obstacles and a target, having different colors is taken to the single board computer with a wireless IP camera. This image is processed to find the locations of the mobile robot, obstacles and the target in C programming language using OpenCV. In path planning module, the shortest and optimal path is generated for the mobile robot. Generated path is applied to the robot motion module to produce necessary angles and distances for the mobile robot to reach the target. Since the structure of the proposed system is designed as modular and flexible, similar or different hardware, software or methods can be applied to these three modules.

Keywords: Genetic Algorithms, image color analysis, mobile robots, open source software, open source hardware, path planning
Fusion of Target Detection Algorithms in Hyperspectral Images

Fusion of Target Detection Algorithms in Hyperspectral Images

Authors: Seniha Esen Yuksel*| Hacettepe University, Department of Electrical and Electronics Engineering, Ankara, Turkey, Ahmet Karakaya| Hacettepe University,...
(22 downloads)
Abstract

Target detection in hyperspectral images is important in many applications including search and rescue operations, defence systems, mineral exploration and border security. For this purpose, several target detection algorithms have been proposed over the years, however, it is not clear which of these algorithms perform best on real data and on sub-pixel targets, and moreover, which of these algorithms have complementary information and should be fused together. The goal of this study is to detect the nine arbitrarily placed sub-pixel targets, from seven different materials from a 1.4km altitude. For this purpose, eight signature-based hyperspectral target detection algorithms, namely the GLRT, ACE, SACE, CEM, MF, AMSD, OSP and HUD, and three anomaly detectors, namely RX, Maxmin and Diffdet, were tested and compared. Among the signature-based target detectors, the three best performing algorithms that have complementary information were identified. Finally these algorithms were fused together using four different fusion algorithms. Our results indicate that with a proper fusion strategy, five of the nine targets could be found with no false alarms.

Keywords: Target detection, hyperspectral imaging, fusion
Structure-Texture Decomposition of RGB-D Images

Structure-Texture Decomposition of RGB-D Images

Authors: Aykut Erdem*| Hacettepe University, Department of Computer Engineering, Ankara, Turkey.
(23 downloads)
Abstract

In this paper, we study the problem of separating texture from structure in RGB-D images. Our structure preserving image smoothing operator is based on the region covariance smoothing (RCS) method in [16] that we present a number of modifications to this framework to make it depth-aware and increase its effectiveness. In particular, we propose to incorporate three geometric depth features, namely height above ground, angle with gravity and horizontal disparity to the pool of image features used in that study. We also suggest to use a new kernel function based on KL-divergence between the distributions of extracted features. We demonstrate our approach on challenges images from NYU-Depth v2 Dataset [24], achieving more accurate decompositions than the state-of-the-art approaches which do not utilize any depth information.

Keywords: RGB-D images, structure-preserving smoothing, image decomposition, region covariances
The Usage of Artificial Neural Networks Method in the Diagnosis of Rheumatoid Arthritis

The Usage of Artificial Neural Networks Method in the Diagnosis of Rheumatoid Arthritis

Authors: Kadir Tok*| Institute of Science and Technology, University of Selcuk, Turkey, Ismail Saritas| Faculty of Technology, University of Selcuk, Turkey
(23 downloads)
Abstract

In this study, artificial neural networks (ANN) method is used for the diagnosis of rheumatoid arthritis in order to support medical diagnostics. For the diagnosis of rheumatoid arthritis, backpropagation algorithm was examined in Matlab R2015b environment in artificial neural networks. With the system, the data in a data set, which are received from the patients with rheumatoid arthritis and from the people who are not suffering from rheumatoid arthritis, are classified successfully. Also, ANN backpropagation algorithm results and the results found by Perceptron algorithm are compared in terms of performance. Whereas %82 accuracy percentage is obtained with the Backpropagation method in performance tests in the data set, the accuracy percentage is calculated %71 with Perceptron method.

Keywords: Rheumatoid arthritis, disease diagnosis, artificial neural networks
Solution for the Travelling Salesman Problem with a Microcontrollerbased Instantaneous System

Solution for the Travelling Salesman Problem with a Microcontrollerbased Instantaneous System

Authors: İlhan İlhan*| Necmettin Erbakan University, Faculty of Engineering and Architecture, Department of Mechatronic Engineering, Konya, Turkey
(32 downloads)
Abstract

The travelling salesman problem (TSP) is one of the most frequently researched combinational optimization problems. Despite its trivial definition, the problem is very difficult to solve. Therefore, it is categorized as an NP-hard problem in research literature. It is used for the solution of many real-life problems like route planning, transportation and logistics applications. In this study, a microcontroller-based system was proposed for the solution of the TSP. In the proposed system, location information was imported instantaneously via a GPS module. The Ant Colony Optimization (ACO) algorithm was coded inside the microcontroller for the solution of the TSP. Various tests were performed on two different datasets using different parameter values. Tests showed that the only difference between the results for the microcontroller-based and the computer-based systems were the run-times. Therefore, it was concluded that population-based algorithms like ACO could easily be used in current microcontrollers for various purposes in different areas.

Keywords: Ant Colony Optimization, GPS Module, Microcontroller, Travelling Salesman Problem

About Europub

EuroPub is a comprehensive, multipurpose database covering scholarly literature, with indexed records from active, authoritative journals, and indexes articles from journals all over the world. The result is an exhaustive database that assists research in every field. Easy access to a vast database at one place, reduces searching and data reviewing time considerably and helps authors in preparing new articles to a great extent. EuroPub aims at increasing the visibility of open access scholarly journals, thereby promoting their increased usage and impact.